#But she can easily predict things due to data she collects
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Thinking about the UTDP scene where Junko does fortune telling for a festival
Thinking about Ult Titles
Hm..
#Junko's not clairvoyant#But she can easily predict things due to data she collects#And very rarely does she ever make a miscalculation#Atleast one she did not see or purposely ignored just to have an obstacle later on#That's her whole thing with makoto#She knew she couldn't predict his luck but let him run loose bc it would make things more interesting#But what makes the title of Ult Clairvoyant?#She has no spiritual connection#But she has a high success rate for predictions#So if she did become a 'clairvoyant' she would be very successful#What does talent mean when you're the ult analyst#It's the same for her title of Ult fashionista#She predicts trends and is the first to ride them#Did izuru only need to be the Ultimate Analysts to become the Ultimate hope?#Is that why his eyes are red?#scarposts
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Quarantine Reviews - The Social Dilemma
The Social Dilemma is the most important documentary of our times.
Unless you live under a Wi-Fi disabled rock, you have likely heard of this new documentary offering by Netflix. In India, it’s already trending at #5.The Social Dilemma follows the journeys and opinions of industry insiders who believe that social media platforms have turned into a Frankenstein’s Monster that none of its creators intended it to be. For the purpose of this review, I will not be focusing on what the documentary is about but rather the narrative style, film-making, video editing, art direction and other aspects of the documentary. In other words, this review focuses on how the documentary has been structured rather than what it says.
[Of course I will summarize the essence of the documentary, but judging by the trending list, this might be one documentary on everyone’s must-watch.]
Right off the bat, this documentary wins for the mere fact that it pooled in experts from Silicon Valley who worked to create, design and monetize Facebook, Twitter, Pinterest and other platforms. They also interviewed Dr.Anna Lembke who is the Medical Director of Addiction Medicine at Stanford University. This goes to show that when they talk about social media addiction, it isn’t hyperbole. She talks about the biological aspect of why people get easily addicted to social media.
The story is told in two worlds, the “interview world”, where these experts are talking to viewers directly. And a “fictional family world”, where a family on a steady social media diet is used as an example of its dire consequences. They are interwoven mostly through cross-cuts (also called as parallel editing).
The opening sequence of the documentary establishes the talking heads- experienced high-level insiders from Facebook,Google etc. However, the interviewers still seem a bit “off-the-record”. They’re not yet in the “formal structured interview space” of talking to the camera. Many of them are holding the clapperboard. The documentary continues this style of “rehearsal” bytes later on as Tristan Harris is on a stage, seeming to be rehearsing a presentation about Ethics in Social Media.
In parallel to the interviews runs a fictional story of an American family of five and their normal lives intertwined with social media.The youngest daughter is a social media addict .The oldest daughter is the conscience of the family who knows that social media is bad. And the middle child, the son named Ben, is an average Joe who later gets hooked on to political propaganda due to social media.
Back in the “interview world” ,Tristan Harris recants his time as a Design Ethicist (Yes that is the job title) at Google for Gmail. As he talks about his journey of questioning the moral responsibility of Google towards the users of Gmail, the video shifts to an animation style that is generally used in animated explainer videos. Nowhere else is this animation style used. My guess is maybe they weren’t allowed to use footage of the actual Google HQ.
The ficitional family is used to as an example to drive home the points that the interviewees are making. All the interviewees speak in a very factual fashion, which does not ignite much emotion. However, if the audience is shown a narrative of an ordinary family who’ve become sad, irritated or happy because social media is altering their behavior, it becomes easier for the audience to relate to.There is a sequence about how the personal data collection is used to alter or predict behavior. For example, in one scene, we see the teenager, Ben, scrolling through his phone at school. The video moves to a personification of the AI tracking Ben’s every move. In the office where his holographic body floats and a team of predictive AI decide what would be the best thing to show the kid next. This part kind of makes your stomach turn to be honest.
To push in the point of “addiction” to social media, the filmmakers combine interviewees talking about how they themselves are addicted to social media with cut-away shots of a dilated pupil and the ka-ching sound of a slot machine.
As the story goes on, the interviewees gets to the heart of the problem- disinformation.
This is the nefarious part of the documentary where they point out how the “truth” for one person is completely based on the algorithm shown to them. This goes for “silly” conspiracies about the world being flat, to real-world violence and chaos due to political polarization being fed to users. This saddening truth is no longer a conspiracy or a what if, but a reality.
As the documentary concludes, the audience is shown that the interviewers aren’t a bunch of alarmists at all. In fact they view this as a problem to be fixed. They want to make social media humane. They stand by the fact that social media can only become better with stricter regulations.There is a lot of hopeful “all-is-not-lost” background music played toward the end as the interviewees talk about this.
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Year in Review
I don’t know what’s in the air these days, but it’s like everyone has a stick up their ass about something. I get the idea of proving a point by exemplifying bad behavior, and professing to be holier-than-thou. I think we all do it to some degree. It’s like a tendency to look at a small minutia of data, extrapolate from it, and then apply it to a larger whole. I would even go so far as to guess that this is a natural phenomenon of the human mind, since it would allow us to remain alert for any possible danger based on experiencing a small example of it. It’s just getting real irritating hearing but the Real Problem is...! The Patriarchy, or it’s Systemic Racism, or it’s Heteronormativity, or Western Colonization, or Capitalism. These accusations are calcifying our ability to relate to each other, since they roam about on invisible threads and needles, toying with our emotions and making everyone suspect to one another. I find myself oscillating between absolutely not making sweeping claims that [1] every bad thing is a result of some amorphous superstructure of perfectly coordinated individuals, and, [2] there is never an example of any one of these accusations that has lead to bad results. It’s like there is an arms race for the strongest mythos to make sense of things. There is a force behind the proponents of these phrases that wishes to subjugate people based on outcries of vague guilt: ‘You may have done nothing wrong, but you’re guilty by association! Repent now or be ostracized.’ The Soviets would be proud. And the blowback from these claims, made by people on the outside of the mainstream camp, can be just as annoying too, but not nearly as smarmy and self-unaware as the accusers.
You can find ways to dismiss these claims as pure falsehoods, or better yet, whittle the arguments down to ad hominems and red herrings, or any other rhetorical ploy, which reveals their pure psychological motivation/s. Here is something Jung wrote about concerning women and Animus Possession:
[335] “The animus [psychological imago] does not appear as one person, but as a plurality of persons. In H. G. Wells’ novel Christina Alberta’s Father, the heroine, in all that she does or does not do, is constantly under the surveillance of a supreme moral authority, which tells her with remorseless precision and dry matter-of-factness what she is doing and for what motives. Wells calls this authority a 'Court of Conscience.' This collection of condemnatory judges, a sort of College of Preceptors, corresponds to a personification of the animus. The animus is rather like an assembly of fathers or dignitaries of some kind who lay down incontestable, 'rational,' ex cathedra judgments. On closer examination these exacting judgments turn out to be largely sayings and opinions scraped together more or less unconsciously from childhood on, and compressed into a canon of average truth, justice, and reasonableness, a compendium of preconceptions which, whenever a conscious and competent judgment is lacking (as not infrequently happens), instantly obliges with an opinion.”
[337] “A woman possessed by the animus is always in danger of losing her femininity, her adapted feminine persona, just as a man in like circumstances [anima possession] runs the risk of effeminacy. These psychic changes of sex are due entirely to the fact that a function which belongs inside has been turned outside. The reason for this perversion is clearly the failure to give adequate recognition to an inner world which stands autonomously opposed to the outer world, and makes just as serious demands on our capacity for adaptation.” -Anima and Animus, The Relations Between the Ego and the Unconscious, Pt. II
I would argue Jung accurately predicted and revealed the inner motivations for what our contemporary lingo dubs The Patriarchy. And this is coming from a novice, recreational reader, located on some distant planet with nothing to go on except my own intuition. I just cannot take as fact that the flag waving behind calls to End the Patriarchy! points to anything truly physical; it only reveals a synthesis of projection and a lack of self-examination. But what would it take for people to seriously consider the sources of their aggression, their animosity? If everywhere you look, you see masculinity as a problem, maybe it’s your axis of assumption that needs assessment. This isn’t to say that men do not need to mature within their lifetime. But there has to be a recognition between expectations and reality. Parenting and socialization leads people to grow up to a certain point, but past that cultivation period, folks can easily slip through the cracks. The animosity towards masculinity is perhaps a recognition: people who fall through the cracks do not learn to play the game as we expect them to. Who’s fault is that?
That is just one attempt at clarifying the fervor in some of these sweeping movements. They run rampant, treading over anything they wish to subsume into the muck and mire of nothingness. And it’s very tiring. You have to see the line of logic being applied that aims to undermine something as foundational as the scientific method. How do you defend against this charlatanism, when the mere act of calling it out as “false” leads you, the rebutter, down the road of Colonial Tyranny? At least find it in yourself to not follow those who would make that argument.
Maybe we’re all an expression of something beyond just our single identity. But if that is the case, find the locus of your intentions. Harness it before it harnesses you.
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Laziness Does Not Exist
But unseen barriers do.
[This article was posted on Medium, written by Erika Price]
I’ve been a psychology professor since 2012. In the past six years, I’ve witnessed students of all ages procrastinate on papers, skip presentation days, miss assignments, and let due dates fly by. I’ve seen promising prospective grad students fail to get applications in on time; I’ve watched PhD candidates take months or years revising a single dissertation draft; I once had a student who enrolled in the same class of mine two semesters in a row, and never turned in anything either time.
I don’t think laziness was ever at fault.
Ever.
In fact, I don’t believe that laziness exists.
I’m a social psychologist, so I’m interested primarily in the situational and contextual factors that drive human behavior. When you’re seeking to predict or explain a person’s actions, looking at the social norms, and the person’s context, is usually a pretty safe bet. Situational constraints typically predict behavior far better than personality, intelligence, or other individual-level traits.
So when I see a student failing to complete assignments, missing deadlines, or not delivering results in other aspects of their life, I’m moved to ask: what are the situational factors holding this student back? What needs are currently not being met? And, when it comes to behavioral “laziness”, I’m especially moved to ask: what are the barriers to action that I can’t see?
There are always barriers. Recognizing those barriers— and viewing them as legitimate — is often the first step to breaking “lazy” behavior patterns.
…
It’s really helpful to respond to a person’s ineffective behavior with curiosity rather than judgment. I learned this from a friend of mine, the writer and activist Kimberly Longhofer (who publishes under Mik Everett). Kim is passionate about the acceptance and accommodation of disabled people and homeless people. Their writing about both subjects is some of the most illuminating, bias-busting work I’ve ever encountered. Part of that is because Kim is brilliant, but it’s also because at various points in their life, Kim has been both disabled and homeless.
Kim is the person who taught me that judging a homeless person for wanting to buy alcohol or cigarettes is utter folly. When you’re homeless, the nights are cold, the world is unfriendly, and everything is painfully uncomfortable. Whether you’re sleeping under a bridge, in a tent, or at a shelter, it’s hard to rest easy. You are likely to have injuries or chronic conditions that bother you persistently, and little access to medical care to deal with it. You probably don’t have much healthy food.
In that chronically uncomfortable, over-stimulating context, needing a drink or some cigarettes makes fucking sense. As Kim explained to me, if you’re laying out in the freezing cold, drinking some alcohol may be the only way to warm up and get to sleep. If you’re under-nourished, a few smokes may be the only thing that kills the hunger pangs. And if you’re dealing with all this while also fighting an addiction, then yes, sometimes you just need to score whatever will make the withdrawal symptoms go away, so you can survive.
Few people who haven’t been homeless think this way. They want to moralize the decisions of poor people, perhaps to comfort themselves about the injustices of the world. For many, it’s easier to think homeless people are, in part, responsible for their suffering than it is to acknowledge the situational factors.
And when you don’t fully understand a person’s context — what it feels like to be them every day, all the small annoyances and major traumas that define their life — it’s easy to impose abstract, rigid expectations on a person’s behavior. All homeless people should put down the bottle and get to work. Never mind that most of them have mental health symptoms and physical ailments, and are fighting constantly to be recognized as human. Never mind that they are unable to get a good night’s rest or a nourishing meal for weeks or months on end. Never mind that even in my comfortable, easy life, I can’t go a few days without craving a drink or making an irresponsible purchase. They have to do better.
But they’re already doing the best they can. I’ve known homeless people who worked full-time jobs, and who devoted themselves to the care of other people in their communities. A lot of homeless people have to navigate bureaucracies constantly, interfacing with social workers, case workers, police officers, shelter staff, Medicaid staff, and a slew of charities both well-meaning and condescending. It’s a lot of fucking work to be homeless. And when a homeless or poor person runs out of steam and makes a “bad decision”, there’s a damn good reason for it.
If a person’s behavior doesn’t make sense to you, it is because you are missing a part of their context. It’s that simple. I’m so grateful to Kim and their writing for making me aware of this fact. No psychology class, at any level, taught me that. But now that it is a lens that I have, I find myself applying it to all kinds of behaviors that are mistaken for signs of moral failure — and I’ve yet to find one that can’t be explained and empathized with.
…
Let’s look at a sign of academic “laziness” that I believe is anything but: procrastination.
People love to blame procrastinators for their behavior. Putting off work sure looks lazy, to an untrained eye. Even the people who are actively doing the procrastinating can mistake their behavior for laziness. You’re supposed to be doing something, and you’re not doing it — that’s a moral failure right? That means you’re weak-willed, unmotivated, and lazy, doesn’t it?
For decades, psychological research has been able to explain procrastination as a functioning problem, not a consequence of laziness. When a person fails to begin a project that they care about, it’s typically due to either a) anxiety about their attempts not being “good enough” or b) confusion about what the first steps of the task are. Not laziness. In fact, procrastination is more likely when the task is meaningful and the individual cares about doing it well.
When you’re paralyzed with fear of failure, or you don’t even know how to begin a massive, complicated undertaking, it’s damn hard to get shit done. It has nothing to do with desire, motivation, or moral upstandingness. Procastinators can will themselves to work for hours; they can sit in front of a blank word document, doing nothing else, and torture themselves; they can pile on the guilt again and again — none of it makes initiating the task any easier. In fact, their desire to get the damn thing done may worsen their stress and make starting the task harder.
The solution, instead, is to look for what is holding the procrastinator back. If anxiety is the major barrier, the procrastinator actually needs to walk away from the computer/book/word document and engage in a relaxing activity. Being branded “lazy” by other people is likely to lead to the exact opposite behavior.
Often, though, the barrier is that procrastinators have executive functioning challenges — they struggle to divide a large responsibility into a series of discrete, specific, and ordered tasks. Here’s an example of executive functioning in action: I completed my dissertation (from proposal to data collection to final defense) in a little over a year. I was able to write my dissertation pretty easily and quickly because I knew that I had to a) compile research on the topic, b) outline the paper, c) schedule regular writing periods, and d) chip away at the paper, section by section, day by day, according to a schedule I had pre-determined.
Nobody had to teach me to slice up tasks like that. And nobody had to force me to adhere to my schedule. Accomplishing tasks like this is consistent with how my analytical, hyper-focused, Autistic little brain works. Most people don’t have that ease. They need an external structure to keep them writing — regular writing group meetings with friends, for example — and deadlines set by someone else. When faced with a major, massive project, most people want advice for how to divide it into smaller tasks, and a timeline for completion. In order to track progress, most people require organizational tools, such as a to-do list, calendar, datebook, or syllabus.
Needing or benefiting from such things doesn’t make a person lazy. It just means they have needs. The more we embrace that, the more we can help people thrive.
…
I had a student who was skipping class. Sometimes I’d see her lingering near the building, right before class was about to start, looking tired. Class would start, and she wouldn’t show up. When she was present in class, she was a bit withdrawn; she sat in the back of the room, eyes down, energy low. She contributed during small group work, but never talked during larger class discussions.
A lot of my colleagues would look at this student and think she was lazy, disorganized, or apathetic. I know this because I’ve heard how they talk about under-performing students. There’s often rage and resentment in their words and tone — why won’t this student take my class seriously? Why won’t they make me feel important, interesting, smart?
But my class had a unit on mental health stigma. It’s a passion of mine, because I’m a neuroatypical psychologist. I know how unfair my field is to people like me. The class & I talked about the unfair judgments people levy against those with mental illness; how depression is interpreted as laziness, how mood swings are framed as manipulative, how people with “severe” mental illnesses are assumed incompetent or dangerous.
The quiet, occasionally-class-skipping student watched this discussion with keen interest. After class, as people filtered out of the room, she hung back and asked to talk to me. And then she disclosed that she had a mental illness and was actively working to treat it. She was busy with therapy and switching medications, and all the side effects that entails. Sometimes, she was not able to leave the house or sit still in a classroom for hours. She didn’t dare tell her other professors that this was why she was missing classes and late, sometimes, on assignments; they’d think she was using her illness as an excuse. But she trusted me to understand.
And I did. And I was so, so angry that this student was made to feel responsible for her symptoms. She was balancing a full course load, a part-time job, and ongoing, serious mental health treatment. And she was capable of intuiting her needs and communicating them with others. She was a fucking badass, not a lazy fuck. I told her so.
She took many more classes with me after that, and I saw her slowly come out of her shell. By her Junior and Senior years, she was an active, frank contributor to class — she even decided to talk openly with her peers about her mental illness. During class discussions, she challenged me and asked excellent, probing questions. She shared tons of media and current-events examples of psychological phenomena with us. When she was having a bad day, she told me, and I let her miss class. Other professors — including ones in the psychology department — remained judgmental towards her, but in an environment where her barriers were recognized and legitimized, she thrived.
…
Over the years, at that same school, I encountered countless other students who were under-estimated because the barriers in their lives were not seen as legitimate. There was the young man with OCD who always came to class late, because his compulsions sometimes left him stuck in place for a few moments. There was the survivor of an abusive relationship, who was processing her trauma in therapy appointments right before my class each week. There was the young woman who had been assaulted by a peer — and who had to continue attending classes with that peer, while the school was investigating the case.
These students all came to me willingly, and shared what was bothering them. Because I discussed mental illness, trauma, and stigma in my class, they knew I would be understanding. And with some accommodations, they blossomed academically. They gained confidence, made attempts at assignments that intimidated them, raised their grades, started considering graduate school and internships. I always found myself admiring them. When I was a college student, I was nowhere near as self-aware. I hadn’t even begun my lifelong project of learning to ask for help.
…
Students with barriers were not always treated with such kindness by my fellow psychology professors. One colleague, in particular, was infamous for providing no make-up exams and allowing no late arrivals. No matter a student’s situation, she was unflinchingly rigid in her requirements. No barrier was insurmountable, in her mind; no limitation was acceptable. People floundered in her class. They felt shame about their sexual assault histories, their anxiety symptoms, their depressive episodes. When a student who did poorly in her classes performed well in mine, she was suspicious.
It’s morally repugnant to me that any educator would be so hostile to the people they are supposed to serve. It’s especially infuriating, that the person enacting this terror was a psychologist. The injustice and ignorance of it leaves me teary every time I discuss it. It’s a common attitude in many educational circles, but no student deserves to encounter it.
…
I know, of course, that educators are not taught to reflect on what their students’ unseen barriers are. Some universities pride themselves on refusing to accommodate disabled or mentally ill students — they mistake cruelty for intellectual rigor. And, since most professors are people who succeeded academically with ease, they have trouble taking the perspective of someone with executive functioning struggles, sensory overloads, depression, self-harm histories, addictions, or eating disorders. I can see the external factors that lead to these problems. Just as I know that “lazy” behavior is not an active choice, I know that judgmental, elitist attitudes are typically borne of out situational ignorance.
And that’s why I’m writing this piece. I’m hoping to awaken my fellow educators — of all levels — to the fact that if a student is struggling, they probably aren’t choosing to. They probably want to do well. They probably are trying. More broadly, I want all people to take a curious and empathic approach to individuals whom they initially want to judge as “lazy” or irresponsible.
If a person can’t get out of bed, something is making them exhausted. If a student isn’t writing papers, there’s some aspect of the assignment that they can’t do without help. If an employee misses deadlines constantly, something is making organization and deadline-meeting difficult. Even if a person is actively choosing to self-sabotage, there’s a reason for it — some fear they’re working through, some need not being met, a lack of self-esteem being expressed.
People do not choose to fail or disappoint. No one wants to feel incapable, apathetic, or ineffective. If you look at a person’s action (or inaction) and see only laziness, you are missing key details. There is always an explanation. There are always barriers. Just because you can’t see them, or don’t view them as legitimate, doesn’t mean they’re not there. Look harder.
Maybe you weren’t always able to look at human behavior this way. That’s okay. Now you are. Give it a try.
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Pre-Selling Properties Or Important Real Estate Products? Virtual Tours , Your Agents of Choice
Creating a real estate business needs time and effort. The more your organization develops, the more administrative responsibilities you have. A virtual assistant can get you from those late evenings behind your table and manage the responsibilities that stop you from growing your business. Several virtual company assistants are providing particular solutions particularly tailored for today's real estate professional. Whether you'll need assistance with entries or you intend to discover somebody who is able to promote your organization on the web, a virtual company assistant is the solution to your problems as-built plans .
A real estate virtual assistant is an on line team member. He or she may allow you to negotiate income more effectively and hold your customers informed. One of the major responsibilities of a real estate virtual office assistant is planning marketing products such as postcards, brochures, and flyers. Showing your visitors the method that you are working to offer their properties is a significant the main process.
The real estate business can be quite difficult, specially in a poor economy. In order to promote your solutions successfully, you'll need to produce your brand and build a strong on the web presence. The very basic promotional technique is to truly have a website that lists your companies and contact information. You are able to employ a virtual assistant to assist with your certain wants from internet style to old-fashioned telephone support services and visit scheduling.
A talented virtual company assistant will get the quickest and most affordable ways to promote your real estate organization online. She can inform you what operates and what's a spend of time and money. Virtual personnel may help you handle your results and transactions, relate to your web visitors, and design virtual tours. Some personnel concentrate searching motor optimization, list control, marketing, website development, suggestion marketing systems, and lead management.
Virtual company assistants usually takes your real estate company to another location level. An excellent assistant are designed for all of the calls that come in as a result of your marketing effort. She also can screen potential customers, make the record papers, and schedule property showings. If you're obtaining there are inadequate hours in your day to accomplish all of your tasks, then you will benefit from using the services of a virtual assistant.
The start home is slowly becoming the old style way to exhibit your property. Virtual tours are nearly necessary in the present fast moving world. With the growth, prospective buyers may have the look of each and every space of a home from their computer without the need to professionally go to the home. Real estate virtual tour application has become one of many newest marketing resources in the industry. That software allows suppliers to create eye-catching and visually interesting tour directory of their home or property which can be prepared for sale. The application therefore enhances the marketing initiatives and assists in getting possible buyers.
Online real estate business is made easy and powerful through directory. The directory features ranging from low-cost slide-show tours to extremely active tours. Extremely fun on line virtual tours can be found for industrial and residential properties. It could reach the attention of numerous potential customers round the clock time. It gives you a definite and actual view of equally the inner and outside placing of a home. It will just create a stress-free and travel-free trip to a purchase property.
The application can help home retailers and real estate agents create virtual tours of homes on the Internet or CD. You will find a company to generate and present still photos of the home on a website or CD. The companies permit to create with skilled narration, music and links. Virtual tour gives higher advertising to a property and hence it may facilitate to market the property quickly and easily. Some providers use enhanced see-through screen engineering in order to improve the property sales value and the viewer's experience. Some on line free do-it-yourself services can be found to enable you create your own personal utilizing your own digital pictures of your property.
If you're a buyer trying to find property through on line research directories will help you a lot. It offers you the complete image and facts of each room of a property from the comfort of his or her home. Ergo it preserves the precious time of potential customers without the need to privately visit the property to collect the details. Any buyers can scan the internet anytime and visit listing to have the data and location of a property without any price and touring difficulty. Through, you may get a 360-degree see of each space of a property. Once you go for on line, it is better if you consider the following tips. Prevent doing an excessive amount of visit of a certain property as they could misguide you with music and narration. View products from outlined in a directory before you choose a specific one.
Have you been so eager to create a purchase of a real estate property ? Are you seeking to find the best clients to deal with? Well, if this is the case it would really be difficult to produce a sudden sale. Come to consider it, various clients have varying needs. In all these needs, feelings are often different.
Handling the thoughts of real estate customers is just like handling your personal feelings if you are a person yourself. In this sense, additionally you develop into a therapist and a psychiatrist cum real estate retailer all folded in to one. Do not worry if you match different celebrities when making a sale. The real essential is to handle the specific situation with much confidence.
How to handle emotions of real estate consumers
Assume some feelings that choose the specific real estate transaction. The emotions really happen from the truth that home buying is very stressful. Look at this as an normal situation to many home consumers and anything else is going to be treated carefully. Moreover, you have to also contemplate the following tips:
Know why such emotions arise. Your prospects believe they cannot have total control within the process. Occasionally, they do not know how the process goes. In some instances, there's also worries of buying a new home. Once you have really recognized the sparks to the feelings, it could be simpler to handle the situation.
Talk in their mind about their expectations. Buying a dream home is something which becomes a dilemma. Ensure that you will have the ability to ask your customers about what they need and let them know that compromises may be required to generally meet these expectations. Give them market figures, impart more information about the brand new community and share your personal experiences.
Let them know that you will be together every stage of the way. Clients usually experience that they're perhaps not in control of the situation because you don't speak with them. Whenever there's something occurring along the way, you have to tell them immediately. Do not let them to worry and believe that you're not permitting them to have their own bit on the matter.
Respect begets respect. Your real estate buyers are number different with different forms of consumers in town. Make sure they are relaxed and regard them due to their views. When there is any prediction that is not even close to what is happening in the real estate industry, make sure they are understand the real situation without shouting at them or telling them that they are wrong. Make sure they are find out more about the terms applied in the market without bad them.
Most importantly these exact things, it could be best if you take your responsibilities than get things personally. Occasionally, real estate customers generalize ideas that they have noticed from other people. Effectively, show them they are improper without having to be psychological in the end. Discover ways to manage your own emotions and the rest will continue to work in accordance with your real applications - that is, to produce an outright sale of the property.
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Keep Your Business Going Even In the Lockdown Through A CRM Solution
The time that we all are going through has brought about drastic changes in our lives, both personally as well as professionally. You cannot even venture out of your home due to COVID-19, but you need to keep your business running. Work from home has become a trend in the times of stay home, stay safe. Organizations have realized that they need software, like CRM, to keep their business going from home.
If you and your team are not working anyhow because you do not have any tools or software yet, then there are chances that you may almost touch the bottom in the competition after lockdown. You may not have the idea that CRM software can be very fruitful for your business. We don’t know that till when COVID-19 is going to wreak its havoc on us, but this is for sure that we cannot just sit and wait for the good time to come.
CRM software is gaining much traction these days as many organizations are aware of its usefulness. GlobalData projects that CRM applications segment is likely to escalate at a CAGR of around 3.3% over 2023 in India. If predictions are to be believed, India will spend around $2.3 billion on CRM by 2023. These figures are enough to convey the importance of CRM for any organization, be it an SME or MNC.
Let’s find out the answer to the question that must have popped up in many minds- What is CRM?
CRM, an acronym for Customer Relationship Management, is a tool to handle the relationships and communications of a company with its prospects or customers. The basic goal of this handy tool at your disposal is to enhance your business relations quality, improve employee productivity, perk up profitability, and manage sales. You can manage the entire lifecycle of buying journey, from acquisition to post-sales support. Many CRM software providers offer a multitude of other features, like FinCRM, which is a CRM-cum-office organizer. It is highly recommendable if you are on a tight budget during this lockdown period but still wants to grow. You can try it for free here.
You are afraid of losing your business during this global COVID-19 crisis. But now, you got a ray of light to bring back your firm on track without breaking the bank. You must be thinking that how CRM software can provide you the juices that you require to sustain your business.
Let’s decipher the answer to your question and understand how CRM software can twist your fate in this lockdown season.
Good Enough For Work From Home Trend
No one is still able to figure out when COVID-19 pandemic will come to an end. Predictions also say that it may never leave us like an endemic. So this is for sure that we will have to add staying home in our lifestyles. Recently, Gartner has surveyed around 317 CFOs and Finance leaders and found that almost 74% of them are looking to shift about 5% of their on-site employees to permanently remote positions post COVID-19.
Looking at these circumstances, now or later, everyone will have to deploy CRM software in their operations. Collecting leads, contacting them, initiating marketing campaigns, managing tasks, and analyzing business reports, everything will be done using CRM from home. If you haven’t started using a CRM solution, it’s still not too late. You can still find a CRM solution or just visit (here) to access the industry-best, customizable, and budget-friendly CRM software.
Keep Your Campaign Going From Home
You can stop traveling to the office due to COVID-19, but you cannot stop your work. For campaigning from home, you need access to a CRM solution. Carry out your marketing campaigns to let people know that even in this lockdown season, you are open to business and ready to help them. CRM solutions establish your connectivity with customers across various channels from anywhere. With CRM software, you are all set to make your business survive in any pandemic or next lockdown.
Calculate the Success of Your Marketing Campaign
After effectuating any marketing campaigns, the next thing most of the marketers want to know is the results of their marketing campaign. Not everyone till now, but almost 35% of the marketers believes that measuring the ROI of a marketing campaign is very/extremely important. CRM software is of great use here because you can see in-depth campaign reports. So, it is an incentive in this lockdown that you can do campaigning and evaluation of that campaign at the same time through a single CRM solution.
Become Less Likely to Miss Any Lead Even From Home
With everyone working from home, a series of data is being transferred daily. If you are using informal methods for transmitting data, then there are chances that you may lose some or all of that data. But if you are using a CRM solution, then your leads and prospects can safely reach the right person. A good CRM can capture all the quality leads from online channels and present it on your screen without any menial work. You can hold your business in this lockdown before it takes a turn for the worse by simply putting a CRM solution at use.
Keep Your Entire Workforce Organized
Many things are likely to get overlooked without in-person meetings or face-to-face interaction. But with CRM software, you can remind the right person beforehand about sending quotes, following up, and contacting leads further. Easily assign tasks to the right employee and keep track of the sales pipeline. FinCRM allows you to automate repetitive tasks without assigning them every time. So you get a lot of work done in lesser time with a CRM solution.
Keep A Daily Record of Every Employee Turning Up to Work
Working from home can be easy for associates, but it can turn into a nightmare for a manager in the absence of office resources. As this trend is going to last for longer, then you also need a CRM solution, like FinCRM, which offers you an in-built office organizer with CRM software. By the end of the day, every employee can record their login & logout time, with their task details. It gets submitted to the manager and he/she can approve or comment on it if required. It is as easy to do as it sounds.
Look Over All the Stats When Everything is Said And Done
After everything, you can finally see how much your business has grown in this lockdown through the comprehensive sales report. You get real-time visualizations, customizable dashboards, and various filters to compare individual, team, & organizational performance. Accessibility to the entire data and deep reports at one place reduces the burden of slicing, dicing, viewing multiple spreadsheets. This all is very easy with a customizable and versatile CRM solution.
Present time is very tough for all kinds of businesses, be it a local shop or the largest organization of the country. But luckily, many of you got a job that can be done from home by simply deploying CRM software. A few more months are going to be challenging for every one of us. So don’t waste your time anymore, invest in a good CRM, and acquaint with its features to grow now and in the future.
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Neural Networks In Political Campaigning And Its Impact On Democracy
By Jasmine Emilio, University of Tampa Class of 2022
September 13, 2020
Neural networks (NN) are a rapidly expanding branch of artificial intelligence (AI). NN’s ability to predict from data has seen an explosion in capability over the last decade due to improvements in data storage, computing power, and new mathematical algorithms. As a result, political campaigns are increasingly turning to NNs to predict voting outcomes and target voters in ways that could forever change the political landscape. Data-driven campaign models are becoming the new norm in elections. But what does this mean for democracy? Some see this new technology as a threat to democracy because voters can easily be manipulated, and their privacy can be compromised. Others see the positives of AI where it can increase voter-turnout and political knowledge, strengthening democracy.
What is AI and NNs?
AI mimics human or animal intelligence. For example, AI can do many things we as humans can do, such as seeing, speaking, listening, moving, communicating, and learning. NNs are currently the most popular AI methodology used to mimic human predictive intelligence.NNs are used in political campaigns to find patterns in voter data and predict the best methods to appeal to voters. Rouhianen describes NNs as:
the ability of machines to use algorithms to learn from data and used what has been learned to make decisions like humans would. Unlike humans, though, AI-powered machines do not need to take breaks or rest and they can analyze massive volumes of information all at once. The ratio of errors is significantly lower for machines that perform the same task as their human counterparts (Rouhianen 3).
AI’s learning and decision-making capabilities will affect society in many ways. For example, AI will displace jobs previously performed by humans; legal or ethical boundaries could be crossed; more data will be collected on individuals; and workplaces will become more efficient. AI needs data to produce its algorithms. Rouhianen predicts “data will be the new oil” (Rouhianen 10). Companies with greater access to data will outperform those lacking access to data. We already see data becoming very important to political campaigns. Data can be the difference between winning and losing an election.
AI in Trump’s 2016 Presidential Campaign
After some hesitation, Trump eventually embraced the use of AI in his campaign model. Trump used microtargeting to mobilize his voters and demobilize Clinton’s voters by reminding democrats of Clinton’s controversies through targeted ads. Much of this microtargeting was done on Facebook. Trump spent forty-four million dollars on Facebook ads. In comparison, Clinton spent twenty-eight million dollars on Facebook ads. Stromer-Galley argues Trump’s Facebook ads were more effective than Clinton’s. She states, “Trump's campaign ran 5.9 million different variations of ad content, conducting rigorous A/B testing to determine which was more effective. Clinton's campaign ran sixty-six thousand different variations of ad content by comparison” (Stromer-Galley 251). A/B testing is a method campaigns use to test which messages are more effective to audiences. The Federal Elections Commission reported Trump spent 400% more than Clinton on digital advertising even though Clinton outspent Trump in her campaign all together (Stromer-Galley 251). While Trump’s campaign lacked organization, experience, and staff in comparison to Clinton’s campaign, his focus on sophisticated digital advertising may be largely responsible for his win. This suggests how effective AI-driven digital marketing and microtargeting can be.
Cambridge Analytica (CA), a data analytics firm, played a controversial role in the Trump campaign. CA provided tools that helped the Trump campaign find the most influential individuals and communities to micro-target as well as what the most effective communication strategies would be. It helped Trump find the most effective cities and towns to hold rallies. CA seemed to be cutting edge, boasting that they have “up to four thousand distinct data points on each adult in the United States” (Stromer-Galley 248). CA claimed that their ability to perform psychographic modeling separated them from other data analytics companies. Psychographic modeling uses data to predict an individual’s personality, thenuse these predictions to appeal to individuals more effectively. The Trump campaign planned to use CA’s psychographic modeling with Facebook data. A whistleblower revealed that CA never deleted the Facebook data of fifty million accounts they were contractually required to delete, creating a huge controversy for the Trump campaign (Stromer-Galley 249). Some scholars are doubtful about CA’s capabilities. Stromer-Galley argues many of the capabilities CA boasted about were ineffective to the campaign. She states, “Consultants complained that Cambridge Analytica was better at selling themselves than delivering on their technologies” (Stromer-Galley 249). While data analytics has had significant shortcomings in previous campaigns, as technology becomes more advanced, data analytics may become essential to campaigning.
Risks of AI in Political Campaigns
Jamie Barrett et al. forecasts the dangers of AI being used in political campaigns in The Future of Political Campaigning. Barrett et. al outlines five risks of AI in politics. The first risk is privacy. More diverse data is needed to maximize AI’s capabilities. Therefore, campaigns are incentivized to obtain even more personal data on citizens, raising privacy concerns. The second risk is user consent and knowledge. As AI becomes more complex it is hard for users to understand how it works and how data is being used. Barrett states, “AI led processes are typically difficult to scrutinize and explain, the principle of ‘informed consent’ will become increasingly difficult to apply” (Barrett 38). The third risk is inappropriate profiling and messaging. AI can produce automatically generated messages tailored to citizens. An issue with this is that like humans, AI can be biased, racist, and sexist in its automated messages. Inappropriate and false messages can result, leading to citizens distrusting political parties. The fourth risk is accountability. As the use of AI technology in campaigns grows, it will be increasingly hard for parties to be monitored and regulated. Barrett believes AI will soon be used by all political parties “enabling them to routinely run thousands, perhaps millions of algorithmically tuned messages” (Barrett 39). It will be challenging for the high volumes of messages to be monitored and regulated, posing major accountability concerns. The fifth risk is emotional manipulation. Emotional targeting will improve as campaigns collect more information on citizens. This will allow campaigns to find correlations between mood, personality, and psychological state and individual’s political behavior. Barret finds, “handing control to an AI based system could potentially sometimes result in political parties targeting people who are extremely depressed, anxious or suffering from particular psychological difficulties with adverts designed to appeal to them” (Barret 40). The magnitude of these risks is dependent on whether campaigns adopt the new AI technologies on the market. However, Barrett et al. is confident campaigns will purchase these AI technologies, stating “It is reasonable to assume that political campaigns will continue to evolve, and will adopt many of the state of the art techniques being developed in the marketing and advertising technology. The allocation of political campaign budgets supports this assertion” (Barrett 27).
AI is changing the way campaigns operate, but what does this mean for democracy? The use of AI can be a promise for democracy by increasing political engagement and knowledge. However, it can also be seen as a threat for democracy. For example, political parties increasingly collecting data on citizens raises privacy concerns. Only certain groups of individuals that are most influential to the campaign’s success will receive microtargeted advertisements. So, campaigns are discriminating against individuals who do not receive advertisements, limiting their political knowledge. Next, microtargeted ads can manipulate citizens into taking political action. Messages do not always have to be true and campaigns may target individuals who exhibit psychological difficulties and are easier to sway. Lastly, parties are not being transparent about their use of AI in campaigning. CA failing to delete Facebook data that they were contractually required to delete is an example of this. Campaigning rules and regulations must catch up to the speed at which AI technologies are accelerating to protect democracy. Furthermore, media sites have the power to enforce regulation as well. In 2019 Twitter banned politicians from running microtargeted advertisements. Facebook has followed, limiting microtargeting in response to Trump’s controversial digital advertising in the 2016 campaign (Timberg 2019). Yet, even with these regulations it is hard to know what AI’s capabilities will lead to in the 2020 election and what its implications will be on democracy. NN’s capabilities will forever change the political landscape; perhaps in ways that are unimaginable today.
________________________________________________________________
1. <ref name="Timberg 2019">{{cite web | last=Timberg | first=Craig | title=Critics say Facebook’s powerful ad tools may imperil democracy. But politicians love them. | website=Washington Post | date=2019-12-09 | url=https://www.washingtonpost.com/technology/2019/12/09/critics-say-facebooks-powerful-ad-tools-may-imperil-democracy-politicians-love-them/ | access-date=2020-09-07}}</ref>
2. <ref name="Demos 2019">{{cite web | title=The Future of Political Campaigning | website=Demos | date=2019-02-04 | url=https://demos.co.uk/project/the-future-of-political-campaigning/ | access-date=2020-09-07}}</ref>
3. <ref name="Rouhiainen 2018 p. ">{{cite book | last=Rouhiainen | first=Lasse | title=Artificial intelligence : 101 things you must know today about our future | publisher=Lasse Rouhiainen | publication-place=San Bernardino, CA | year=2018 | isbn=978-1-9820-4880-8 | oclc=1030308615 | page=}}</ref>
4.<ref name="Galley 2014 p. ">{{cite book | last=Galley | first=Jennifer | title=Presidential campaigning in the Internet age | publisher=Oxford University Press | publication-place=New York, NY | year=2014 | isbn=978-0-19-973194-7 | oclc=869281940 | page=}}</ref>
Photo Credit: The Opte Project
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POLITICO Playbook: Trump’s two worlds
New Post has been published on https://thebiafrastar.com/politico-playbook-trumps-two-worlds/
POLITICO Playbook: Trump’s two worlds
PRESIDENTDONALD TRUMPwill officially launch his 2020 campaign in Orlando tonight. He does so amid signs of unease in his own camp about his electoral prospects, despite what any other president would be touting as an enviable record. There are two ways to view the political climate in Trump’s Washington:
— THE PRO-TRUMP WORLD:As the president and his allies see it, a second term should be his for the taking. After all, the economy is solid — inflation is low and growth is chugging along, despite some warning signs. The United States has not entered any new wars on Trump’s watch, and America is even speaking to old adversaries. His base is with him, and tonight’s rally in Florida will draw tens of thousands of people in a critical part of a crucial 2020 state. Despite withering pressure from investigations on the Hill, at DOJ and in New York, Republicans are not abandoning the president.
— THE ANTI-TRUMP WORLD:Trump’s foes are just as certain he’s got a losing record. Trade wars with Mexico and China are hurting farmers in the Midwest and pushing up prices for everyone else. A surge of migrants from Central America has swamped the border. The United States could be dragged into a war with Iran at any moment, and talks with North Korea have stalled. Internal Trump polling shows the president trailing in key battleground states, with numbers so bad Trump fired some of his campaign’s pollsters. He’s losing to almost every single Democratic candidate. Impeachment looms on the horizon, and should that happen, some Republicans could begin abandoning him to save themselves.
AND YET,here’s the thing about Donald Trump: After he shocked the world in 2016, nobody dares predict which of the above narratives will prevail in 2020. Democrats could easily nominate a weak challenger. And unlike last time, he now has his party behind him and the trappings of incumbency on his side. With the election 16 months away, anyone who can say for sure that he’s doomed — or destined to return — is either clairvoyant … or smoking something.
THE MAIN EVENT … ORLANDO SENTINEL: “Trump supporters line up 42 hours early for Orlando campaign rally at Amway Center,”by Caroline Glenn and David Harris: “With tents, sleeping bags and coolers of water in tow, Donald Trump supporters began lining up early Monday for Tuesday’s campaign rally in Orlando, nearly two full days before the event. …
“The line had grown to about 50 as of 3 p.m. By 9:30 p.m.,the line ballooned to about 250, with people snaked around to Central Boulevard. Around the same Trump tweeted there were ‘thousands of people already lined up.’” Orlando Sentinel
Good Tuesday morning.
MOOD MUSIC …via WaPo’s Damian Paletta and Heather Long: “Trump has threatened to escalate trade conflicts with China, Mexico, the European Union and Japan, spooking business leaders and leading some to pull back investment. Similarly, budget and debt-ceiling talks with congressional leaders from both parties have sputtered, raising the possibility of another government shutdown in October.
“The uncertainty — and a cooling global economy — led JPMorgan Chaseon Monday to predict that there was a 45 percent chance the U.S. economy would enter a recession in the next year, up from 20 percent at the beginning of 2018.” WaPo
PETER BAKER SETS THE TABLEonNYT A12:“As President Trump kicks off his campaign for a second term on Tuesday with an eardrum-pounding, packed-to-the-rafters rally in Florida, no one doubts that he is the dominant force in the arena today, the one defining the national conversation as no president has done in generations.
“But the coming election is shaping up as a test— not just of the man but of his country. Was Mr. Trump’s victory the last time around a historical fluke or a genuine reflection of America in the modern age? Will the populist surge that lifted him to the White House run its course or will it further transform a nation and its capital in ways that will outlast his presidency? What kind of country do Americans really want at this point?
“Whatever voters thought about Mr. Trump in 2016,they have now had more than enough time to take their measure of him, and their judgment arguably will say more about the mood of the world’s last superpower than whatever roll-the-dice decision may have been made last time. Mr. Trump promised to blow up the system; voters will decide if more disruption is still needed.” NYT
WAPO’S NICK MIROFFandMARIA SACHETTI: “Trump vows mass immigration arrests, removals of ‘millions of illegal aliens’ starting next week”:“President Trump said in a tweet Monday night that U.S. immigration agents are planning to make mass arrests starting ‘next week,’ an apparent reference to a plan in preparation for months that aims to round up thousands of migrant parents and children in a blitz operation across major U.S. cities.
“‘Next week ICE will begin the process of removing the millionsof illegal aliens who have illicitly found their way into the United States,’ Trump wrote, referring to U.S. Immigration and Customs Enforcement. ‘They will be removed as fast as they come in.’
“Large-scale ICE enforcement operations are typicallykept secret to avoid tipping off targets. In 2018, Trump and other senior officials threatened the mayor of Oakland, Calif., with criminal prosecution for alerting city residents that immigration raids were in the works. … U.S. officials with knowledge of the preparations have said in recent days that the operation was not imminent, and ICE officials said late Monday night that they were not aware that the president planned to divulge their enforcement plans on Twitter.” WaPo
— REALITY CHECK:There’s no way ICE can deport “millions” of people in the near term. In fiscal year 2012, its peak, the agency deported 409,849 individuals. In FY 2017, the first for which we have partial data under Trump, that number was 226,119. And, as NBC’s Julia Ainsley explains, “[I]nterior removals have been down across the country for a simple reason: ICE is running out of space due to the influx of immigrants coming across the border.”
ON THE OTHER SIDE … BIDEN POOL REPORT,from WSJ’s Ken Thomas at 9:56 p.m.: “Prior to Mr. Biden’s arrival, around 6 p.m., about two dozen climate change demonstrators gathered outside the Upper East Side home of Jim Chanos, the president and founder of Kynikos Associates, a prominent short-selling investment firm. …
“The pool was escorted to the dining room of Mr. Chanos’penthouse apartment, where guests mingled, sipped wine and chatted at an adjoining outdoor terrace. Artwork lined the walls of the apartment. … He said he appreciated the donors for ‘writing a check to allow me to compete. And you are putting me in a position to be able to compete nationally.’”
NUGGET OF NEWS:Biden said he had 360,000 donors who have given an average of $55. That comes to $19.8 million in contributions for his campaign.
BTW … REPUBLICANS FOR BIDEN? …“Guests spotted by the pool included: Former Sen. Al D’Amato, R-N.Y.; Rep. Carolyn Maloney, D-N.Y.; Former Veterans Affairs Secretary David Shulkin, who served as a VA undersecretary for health during the Obama administration and as VA secretary for President Trump until 2018; billionaire businessman John Catsimatidis; Robert Wolf, founder of 32 Advisors and a top fundraiser for President Obama’s campaigns; Michael Kempner, CEO of MWWPR and a prominent Democratic fundraiser and numerous other attendees.”
A ZINGER FROM ELIZABETH WARREN (@ewarren)at 10:28 p.m.: “I don’t spend time at fancy fundraisers. Instead, I spend my time meeting voters and thanking grassroots donors who chip in what they can. Donate $3 to my campaign, and you might just get a call from me to thank you!”
LINE OF THE DAY … BURGESS EVERETTandHEATHER CAYGLE:“The [DNC] chairman is the face of presidential debate rules that will allow a meditation guru to take the stage next week while a red state Western governor watches on TV. Against that backdrop, a collection of Democratic lawmakers are still aggravated with [DNC chair Tom] Perez after he yielded to the party’s base last year and agreed to dilute their power as superdelegates — a problem Perez is still trying to defuse in private meetings with Democrats.” POLITICO
COMING ATTRACTIONS:TheSENATE FINANCE COMMITTEEhas this hearing today:“The President’s 2019 Trade Policy Agenda and the United States-Mexico-Canada Agreement.”U.S. Trade Rep. Robert Lighthizer will testify at 10:15 a.m. in 215 Dirksen.
IMPEACHMENT WATCH — FRESHMAN REP. KATIE PORTER(D-Calif.) came out for impeachment in a video she posted online. People will make a lot of this, considering she beat Mimi Walters in an R+3 seat. …
… BUT KEEP THIS IN MIND:Just two Democrats in Republican seats have called for impeachment proceedings. The other is Rep. Tom Malinowski, a former Obama State Department official who represents New Jersey’s 7th District.
FOR YOUR RADAR — “Pentagon sending 1,000 more troops as tensions with Iran grow,”by Bryan Bender: “The Pentagon is dispatching an additional 1,000 troops to the Middle East in response to recent attacks on oil tankers in the Gulf of Oman that the United States blames on Iran.
“‘The recent Iranian attacks validate the reliable,credible intelligence we have received on hostile behavior by Iranian forces and their proxy groups that threaten United States personnel and interests across the region,’ acting Defense Secretary Pat Shanahan said in a statement announcing the deployment. The additional forces are ‘for defensive purposes to address air, naval, and ground-based threats in the Middle East,’ the statement added.” POLITICO
— “Pentagon claims new photos show Iran responsible for tanker attacks,”by Wesley Morgan
THE BIG PICTURE — NAHAL TOOSI: “Iran tests Trump’s desire to actually strike a new deal”:“President Donald Trump is at a make-or-break moment with Iran. Tehran said Monday it will soon take steps that likely violate the 2015 nuclear deal Trump himself abandoned, an announcement that came just days after the U.S. accused the Islamist-led country of sabotaging international oil tankers. The Pentagon announced Monday that it is sending 1,000 more troops to the Middle East for ‘defensive purposes.’ In Europe, meanwhile, leaders are starting to acknowledge that they may have to walk away from the nuclear agreement or devise a new one.
“The confluence of events will test Trump’s weak appetitefor military action, his ability to rally allies he has frequently snubbed and his seriousness about actually striking the better deal with the Iranians that he once promised. Along the way, Trump must win over officials well-aware of his history of misstatements and uneasy about relying on U.S. intelligence when a potential new Middle East war could result.” POLITICO
KUSHNER SPLATS EGG ON TRUMP’S FACE ON THE WORLD STAGE,via Barak Ravid in Axios:“White House will not invite Israeli officials to Bahrain conference”:“The White House has decided not to invite the Israeli Minister of Finance Moshe Kahlon or other Israeli government officials to the Bahrain conference in Manama on June 25, where it plans to launch the economic part of the Trump administration’s Israeli-Palestinian peace plan, U.S. officials told me.
“Why it matters:This is a major setback for the White House’s vision for the much-anticipated Bahrain conference, which will now take place without Israeli or Palestinian officials.” Axios
THE JUICE …
— IN 2018,Texas GOP Rep.KENNY MARCHANTwon reelection by 3 percentage points — his closest margin in 14 years in Congress. Marchant’s district, which is north of Dallas and Fort Worth, is shifting, strategists in both parties say, and Democrats are newly competitive.KIM OLSON,a veteran, is running against Marchant in 2020, attempting to meld her military background with an anti-Trump message.OLSONcloses out her video — which is primarily about her military service — saying she is running because “this president is attacking everything we’ve fought for over the years.”
OLSONlost a 2018 statewide race for agriculture commissioner by 5 points, so she’s a practiced candidate. But 2020 is a presidential year, and Marchant won by nearly 17 points in 2016. This seat could be one to watch.Video
— WASHINGTON INC.: DOUG THORNELL, OREN SHURandEMILY CAMPBELLwill be the new heads ofSKDKNICKERBOCKER’Spolitical consulting department. The trio will lead an expansion of the firm’s political advertising work.
TRUMP’S TUESDAY —The president and first lady Melania Trump will leave the White House at 3:50 p.m. en route to Orlando. Trump will speak at a 2020 reception at 7:30 p.m. and campaign kickoff event at the Amway Center at 8 p.m. Afterward, they will leave for Miami to spend the night in Doral, Fla.
KNOWING KELLY KNIGHT CRAFT — “Trump’s U.N. nominee was ‘absent’ ambassador,”by Lauren Gardner: “President Trump’s nominee to be ambassador to the United Nations – current U.S. ambassador to Canada Kelly Craft – was frequently absent from her post in Ottawa, raising questions about her level of engagement with the job, according to officials in both the United States and Canada.
“State Department officials acknowledge her frequent travelsoutside of Canada, but said many of the trips were related to the new North American trade deal. Her absences from her official post are likely to be an issue in her confirmation hearing, which is now scheduled for Wednesday.
“Federal Aviation Administration recordsobtained under the Freedom of Information Act by POLITICO show that a private jet registered to Craft’s husband and used by the ambassador made 128 flights between the United States and Canada during a 15-month span of her tenure in Ottawa, the equivalent of a roundtrip once a week.
“Some of the trips correspond with dates of events Craft attendedin her home state of Kentucky – such as the Kentucky Derby and a media interview at a University of Kentucky basketball center named for her husband Joe Craft, a coal billionaire – but neither she nor he, through their spokespeople, would confirm how many of the flights involved her travel.” POLITICO
THE INVESTIGATIONS …“Paul Manafort Seemed Headed to Rikers. Then the Justice Department Intervened,”by NYT’s William Rashbaum and Katie Benner: “[L]ast week, Manhattan prosecutors were surprised to receive a letter from the second-highest law enforcement official in the country inquiring about Mr. Manafort’s case. The letter, from Jeffrey A. Rosen, Attorney General William P. Barr’s new top deputy, indicated that he was monitoring where Mr. Manafort would be held in New York.
“And then, on Monday, federal prison officials weighed in,telling the Manhattan district attorney’s office that Mr. Manafort, 70, would not be going to Rikers.
“Instead, he will await his trial at a federal lockup in Manhattan or at the Pennsylvania federal prisonwhere he is serving a seven-and-a-half-year sentence for wide-ranging financial schemes, according to people with knowledge of the matter.” NYT
IMMIGRATION FILES … WAPO’S MARIA SACCHETTIinCiudad Juárez, Mexico:“‘The American Dream has turned into hell’: In test of a deterrent, Juarez scrambles before U.S. dumps thousands of migrants”:“This gritty, industrial city on the banks of the murky Rio Grande is bracing for the Trump administration to dump thousands of migrants from Central America and other lands here under a new agreement to curb mass migration to the United States. But frantic Mexican officials say they likely cannot handle the rapid influx, as they are desperate for more shelter space, food and supplies.
“With days to prepare, a top state officialsaid he expects a fivefold increase in the number of migrants who will be sent to Juarez as a result of the expansion of the Trump administration’s Migrant Protection Protocols. The program, which is under court challenge, sends migrants who are seeking refuge in the United States back across the border into Mexico to await their asylum hearings.
“More than 200 migrants were sent backto Juarez on Thursday, double the previous day, and officials expect as many as 500 migrants each day will be returned from El Paso to Juarez in coming weeks.”
THE TRUMP ADMINISTRATION — “Number of workplace safety inspectors fall under Trump,”by Rebecca Rainey: “Despite assurances from Labor Secretary Alexander Acosta that he will boost the number of OSHA compliance officers this fiscal year, new data shows the number of inspectors has declined. According to statistics that POLITICO obtained through the Freedom of Information Act, the number of compliance safety and health officers tasked with conducting workplace inspections at the agency had fallen in April to 870. That’s down from the 875 safety inspectors that OSHA reported in January.” POLITICO
WHAT ERIC GREITENS IS READING … “Former FBI agent who investigated Greitens indicted for perjury, evidence tampering,”by the Kansas City Star’s Crystal Thomas and Bryan Lowry: “The former FBI agent chosen by the St. Louis City prosecutor to investigate former Gov. Eric Greitens has been indicted on six counts of perjury and one count of tampering with physical evidence, according to documents unsealed Monday in St. Louis City Circuit Court.
“William Don Tisaby, 66, a private investigator,was hired by St. Louis Circuit Attorney Kim Gardner to assist in a probe following allegations that Greitens took a partially nude photograph of a woman without her consent while they were having an affair in 2015. The woman was allegedly bound and blindfolded when the photo was taken, and she says he threatened to release it if she ever spoke about the affair.
“Gardner charged Greitens with invasion of privacy.But the charge was dropped when Greitens’ defense team accused Tisaby of perjury and said it planned to call Gardner at trial as a witness. …
“In the court documents made public Monday,[St. Louis Circuit Court judge Gerard] Carmody accuses Tisaby, 66, of lying multiple times during a deposition and concealing notes from Greitens’ legal team.” Kansas City Star
MEGATREND:“Africa is projected to overtake Asia in births by 2060, and will account for half of all babies being born in the world by the year 2100,” via Pew Research Center’s Tony Flores
MEDIAWATCH — Jeet Heeris joining The Nation as national affairs correspondent andJane McAleveyas strikes correspondent, covering the labor movement. This is D.D. Guttenplan’s first week as new editor at The Nation.Jeet’s first piece
PER CALIFORNIA PLAYBOOK: “SPOTTED:Polish president President Andrzej Duda dining at John’s Grill in San Francisco on Sunday – with an entourage of 30 security officers in tow. Sources said the President – on a Western swing that also included a trip to Nevada — dined on raw oysters and a porterhouse steak, downed with Anchor Steam beer.”
TRANSITIONS — NSC DEPARTURE LOUNGE:The White House’s top Russia hand,Fiona Hill,is leaving the administration at the end of August, per the NYT’s Peter Baker. She’ll be replaced by NSC arms control specialistTim Morrison,according to Baker, indicating Trump’s possible focus on replacing the Intermediate-Range Nuclear Forces treaty.
… Amy Daceywill be the inaugural executive director of AU’s Sine Institute of Policy and Politics. She is the former CEO of the DNC and former exec director of EMILY’s List. …Jeb Fainhas started as Trump war room communications director at American Bridge. He most recently was comms director for House Majority PAC.
SPOTTEDat USGLC’s State Leaders Summit on Monday: HHS Secretary Alex Azar, Rick Santorum, Jennifer Granholm, Dan Glickman, Norm Coleman, Steve Hadley, Jane Harman, Nancy Lindborg, retired Lt. Gen. Michael Nagata, Melanne Verveer, Frank Sesno, Barbara Stephenson, Sarah Thorn, Leyla Santiago, Jonathan Capehart, Selina Jackson, Jenifer Healy and Liz Schrayer.
WELCOME TO THE WORLD — Justin Barasky,a senior adviser at the DSCC and a Sherrod Brown and Priorities USA alum, andLauren Durham,former campaign manager for Kathleen Clyde’s campaign for secretary of state in Ohio, welcomed Henry Scott Barasky.Pic…Another pic
BIRTHWEEK (was yesterday):Spectator USA Life & Arts Editor Dominic Green turned 49 (hat tip: Matt McDonald) …(was Friday):NPR’s Tom Gjelten turned 71
BIRTHDAY OF THE DAY: Fred Barbash,legal affairs writer for The Washington Post.A trend he thinks deserves more attention:“Sleep deprivation, often purposeful, especially in Washington. It saps our brains, causes accidents, turns young people into cranky old people and makes old people even older. It also severely reduces male reproductive capacity. Seriously. It’s a threat to the species.”Playbook Plus Q&A
BIRTHDAYS:Dina Powell … Niall Stanage, WH columnist at The Hill, is 45 … Rep. Jerry McNerney (D-Calif.) is 68 … Rep. Paul Tonko (D-N.Y.) is 7-0 … Nick Johnston, editor at Axios, is 42 … Millie Harmon Meyers (h/ts Ben Chang) … Megan Mitchell … bipartisan Senate alumni birthday: former Sen. Jay Rockefeller (D-W.Va.) is 82 and former Sen. Mike Johanns (R-Neb.) is 69 … David Drucker is 48 … Geri M. Joseph is 96 … Reed Cordish is 45 … Scooter Braun is 38 … Ajashu Thomas … David Wood … Kate Knudson … POLITICO’s Claire Okrongly and Shannon Rafferty … Jim Stinson (h/t Jon Conradi) … Chris Allen … Bob Scutari … WNYC’s Charlie Herman … author Joanne Lipman, former EIC of USA Today … The Atlantic’s Rachel Alben (h/t Michael Falcone) … Bulgarian President Rumen Radev is 56 …
… John McCarthy,COS for Rep. Brendan Boyle (D-Pa.) … Clare Bresnahan (h/t Jill Bader) … POLITICO Europe’s Blanca Esteban Renedo is 31 … Heather Louise Finch … CNN’s DJ Judd, who is moving to Iowa in two weeks, is 29 (h/t Betsy Klein) … Kevin Landrigan … Sophia Templin … Christopher Byrd … Will Kinzel, VP at MillerCoors … Jennifer Carignan … BuzzFeed’s Mary Ann Georgantopoulos … Bert Gomez … Tom Readmond … Michael Van Der Galien … Jeremy Bronson … Meryl Governski … Craig Reed … Shubha Kamala Prasad … Narric Rome … Jason Kello … Daniel Epstein is 35 … Max Stahl is 32 … Lisa Barron … Ron Rosenblith (h/t Jon Haber) … Dick Mark … AJ Goodman (h/t Teresa Vilmain)
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Jake Sherman @JakeSherman
Daniel Lippman @dlippman
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Legal Tech Disruption And Stagnancy At Legalweek 2019
Another Legalweek has come and gone. It was a whirlwind of meetings and conversations about the future of legal tech, and before I knew it, it was over and I was back on a plane and headed home.
What struck me about this year’s show was how much has changed, and yet how much has stayed the same. Technology has bulldozed through the legal industry, just as it has in other industries and our culture in general, and left a trail of wreckage behind it.
For example, over the past few years, traditional legal publishing has been impacted tremendously, and many of the traditional publishing companies, both newspaper and treatise-focused, are struggling to find a foothold in the new world order. Some have declared bankruptcy, others have restructured, and still others have significantly reduced spending and and overhead by closing offices and cutting their budgets.
Bar associations are likewise struggling to stay afloat and few have found a way to provide value in what is now primarily a digital world. Membership is down at national and local levels and bar executives are testing out many different tactics to increase membership and interest, but are having a hard time finding success.
Similarly, mainstay legal conferences, like Legalweek, are also facing challenges. In recent years, attendee numbers for many conferences have declined, as have the number of sponsors and vendors. Lawyers now have more cost effective ways to obtain information and CLE credits online and many are taking advantage of those opportunities and choosing not to attend conferences. This, in turn, causes companies to question the value of exhibiting at the conferences, since doing so tends to be a costly endeavor.
But even as technology has undeniably restructured and torn apart the industries that support the legal profession, many members of the profession have chosen to remain blissfully unaware of its impact on their practices. That’s why, by all accounts and despite the urgings of legal tech futurists, some aspects of legal tech adoption have occurred at a slower pace than anticipated. At the same time, legal tech companies are sprouting up left and right, at rates never before seen, ever intent on meeting the perceived needs of a profession that is ambivalent, at best, to some of their offerings.
And then, in the midst of all this tumultuous change — and collective stubborn resistance to the same — came Legalweek 2019. Despite the hustle and bustle of the show, the dark cloud of change was ominously evident. It was hard to gauge attendee numbers, but the Expo Hall seemed smaller than it had in previous years, with some mainstay exhibitors appearing off the beaten path in much smaller booths than in years past.
That being said, you couldn’t walk two feet without tripping over an eDiscovery vendor, and it’s safe to say that tech adoption in that space is thriving. And if talking about legal tech with people who have a passion for it is your thing, then Legalweek is the place to do it. It’s definitely one of my favorite things to do, and as in prior years, I was lucky enough to meet up with lots interesting people and had many engaging discussions about the future of legal practice and how technology will impact the legal industry.
First I met with Josh Becker, Head of Legal Analytics and Chairman at Lex Machina. I learned that since its acquisition by LexisNexis, Lex Machina has not rested on its laurels and continues to add new practice areas to its litigation analytics platform. We spent a lot of time talking about the importance of the quality of data provided by Lex Machina, since that impacted the quality of the analytics derived from the data. Or, as Josh repeatedly opined, “it’s better to have no analytics than bad analytics.”
I also spoke with Eric Pfiefer, VP of Product Management at LexisNexis. He provided an overview of the progress being made following the recent acquisitions Lex Machina, Ravel Law, and Intelligize and shared his vision for the continuing development of those artificial intelligence tools. As always, I was impressed with the direction LexisNexis is taking these products, the way that they’re approaching the incorporation of these platforms into their own, and the speed at which they’re moving, especially given LexisNexis’s size.
Next I spoke with Mike Jones, Chief Sales Officer of ThoughtRiver, a company that provides AI-powered contract review that allows lawyers to pre-screen and triage the due diligence and risk analysis review process. He shared that one of the more interesting sessions he’d attended at the conference involved a discussion of “the current and future value around assigning a contract risk score for contracts and what you could do with that data and how it could drive your decision making.” You can watch the full interview here.
My next meeting was with Erin Hichman, Senior Analyst at ALM Media. We spent a lot of time talking about one of the trending topics at Legalweek this year: companies insourcing and building out their own legal teams rather than using outside counsel. According to Erin, “the legal service provider landscape is really going to change. We see the Big Four moving in, ASPs are making a lot of moves, and lots of tech investment. The landscape is going to change drastically in the next few years.” You can watch the full interview here.
I also caught up with Allen Alishahi and Chao Cheng-Shorland from ShelterZoom, a multi-party real estate blockchain platform that streamlines real estate rental and purchasing processes. Chao explained that although ShelterZoom began as a real estate platform, they are now expanding its application and envision it as “an industry-agnostic legal contract platform…which turns the…contracting concept into completely digital, and it’s secure and audit-able, and also transparent on Blockchain.” You can watch the full interview here.
Next I sat down with Jim Brock, founder of Trustbot.io, a tool that streamlines and automates a company’s NDA contractual process. He explained that Trustbot.io is designed to bring “the contract process into workflows like Slack, Microsoft Office, and Teams not just to get the contract done, but to predict when it needs to be done.” You can watch the full interview here.
And last, but not least, I talked to Mike Sanders, Senior Solutions Expert, and Marriott Murdock, Regional Director, and learned about the latest news from NetDocuments. We talked about the insourcing trend a bit and Mike offered up an example of a law firm that developed a software tool to solve an internal problem, which NetDocuments later acquired: “A law firm who happens to be a NetDocuments customer that does deal closings and creates deal binders, and it was taking them a lot of money and a lot of time. They digitized the entire process and integrated that into the NetDocuments platform.” You can watch the full interview here.
And that’s it folks. It’s a wrap! Legalweek 2019 has come and gone, but the good news is that there are many more legal tech conferences ahead of us in 2019. And if you missed Legalweek this year, never fear —there’s always next year! Hope to see you there!
Nicole Black is a Rochester, New York attorney and the Legal Technology Evangelist at MyCase, web-based law practice management software. She’s been blogging since 2005, has written a weekly column for the Daily Record since 2007, is the author of Cloud Computing for Lawyers, co-authors Social Media for Lawyers: the Next Frontier, and co-authors Criminal Law in New York. She’s easily distracted by the potential of bright and shiny tech gadgets, along with good food and wine. You can follow her on Twitter @nikiblack and she can be reached at [email protected].
Legal Tech Disruption And Stagnancy At Legalweek 2019 republished via Above the Law
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Celine Replica Luggage Retailer, Designer Fake Celine Pursesre Online Sale
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Laziness Does Not Exist – Devon Price – Medium
I’ve been a psychology professor since 2012. In the past six years, I’ve witnessed students of all ages procrastinate on papers, skip presentation days, miss assignments, and let due dates fly by. I’ve seen promising prospective grad students fail to get applications in on time; I’ve watched PhD candidates take months or years revising a single dissertation draft; I once had a student who enrolled in the same class of mine two semesters in a row, and never turned in anything either time.
I don’t think laziness was ever at fault.
Ever.
In fact, I don’t believe that laziness exists.
…
I’m a social psychologist, so I’m interested primarily in the situational and contextual factors that drive human behavior. When you’re seeking to predict or explain a person’s actions, looking at the social norms, and the person’s context is usually a pretty safe bet. Situational constraints typically predict behavior far better than personality, intelligence, or other individual-level traits.
So when I see a student failing to complete assignments, missing deadlines, or not delivering results in other aspects of their life, I’m moved to ask: what are the situational factors holding this student back? What needs are currently not being met? And, when it comes to behavioral “laziness”, I’m especially moved to ask: what are the barriers to action that I can’t see?
There are always barriers. Recognizing those barriers— and viewing them as legitimate — is often the first step to breaking “lazy” behavior patterns.
…
It’s really helpful to respond to a person’s ineffective behavior with curiosity rather than judgment. I learned this from a friend of mine, the writer and activist Kimberly Longhofer (who publishes under Mik Everett). Kim is passionate about the acceptance and accommodation of disabled people and homeless people. Their writing about both subjects is some of the most illuminating, bias-busting work I’ve ever encountered. Part of that is because Kim is brilliant, but it’s also because, at various points in their life, Kim has been both disabled and homeless.
Kim is the person who taught me that judging a homeless person for wanting to buy alcohol or cigarettes is utter folly. When you’re homeless, the nights are cold, the world is unfriendly, and everything is painfully uncomfortable. Whether you’re sleeping under a bridge, in a tent, or at a shelter, it’s hard to rest easy. You are likely to have injuries or chronic conditions that bother you persistently, and little access to medical care to deal with it. You probably don’t have much healthy food.
In that chronically uncomfortable, over-stimulating context, needing a drink or some cigarettes makes fucking sense. As Kim explained to me if you’re laying out in the freezing cold, drinking some alcohol may be the only way to warm up and get to sleep. If you’re under-nourished, a few clouds of smoke may be the only thing that kills the hunger pangs. And if you’re dealing with all this while also fighting an addiction, then yes, sometimes you just need to score whatever will make the withdrawal symptoms go away, so you can survive.
Kim’s incredible book about their experiences being homeless while running a bookstore.
Few people who haven’t been homeless think this way. They want to moralize the decisions of poor people, perhaps to comfort themselves about the injustices of the world. For many, it’s easier to think homeless people are, in part, responsible for their suffering than it is to acknowledge the situational factors.
And when you don’t fully understand a person’s context — what it feels like to be them every day, all the small annoyances and major traumas that define their life — it’s easy to impose abstract, rigid expectations on a person’s behavior. All homeless people should put down the bottle and get to work. Never mind that most of them have mental health symptoms and physical ailments, and are fighting constantly to be recognized as human. Never mind that they are unable to get a good night’s rest or a nourishing meal for weeks or months on end. Never mind that even in my comfortable, easy life, I can’t go a few days without craving a drink or making an irresponsible purchase. They have to do better.
But they’re already doing the best they can. I’ve known homeless people who worked full-time jobs, and who devoted themselves to the care of other people in their communities. A lot of homeless people have to navigate bureaucracies constantly, interfacing with social workers, caseworkers, police officers, shelter staff, Medicaid staff, and a slew of charities both well-meaning and condescending. It’s a lot of fucking work to be homeless. And when a homeless or poor person runs out of steam and makes a “bad decision”, there’s a damn good reason for it.
If a person’s behavior doesn’t make sense to you, it is because you are missing a part of their context. It’s that simple. I’m so grateful to Kim and their writing for making me aware of this fact. No psychology class, at any level, taught me that. But now that it is a lens that I have, I find myself applying it to all kinds of behaviors that are mistaken for signs of moral failure — and I’ve yet to find one that can’t be explained and empathized with.
…
Let’s look at a sign of academic “laziness” that I believe is anything but procrastination.
People love to blame procrastinators for their behavior. Putting off work sure looks lazy, to an untrained eye. Even the people who are actively doing the procrastinating can mistake their behavior for laziness. You’re supposed to be doing something, and you’re not doing it — that’s a moral failure, right? That means you’re weak-willed, unmotivated, and lazy, doesn’t it?
When you’re paralyzed with fear of failure, or you don’t even know how to begin a massive, complicated undertaking, it’s damn hard to get shit done. It has nothing to do with desire, motivation, or moral upstandingness. Procrastinators can themselves to work for hours; they can sit in front of a blank word document, doing nothing else, and torture themselves; they can pile on the guilt again and again — none of it makes initiating the task any easier. In fact, their desire to get the damn thing done may worsen their stress and make starting the task harder.
The solution, instead, is to look for what is holding the procrastinator back. If anxiety is the major barrier, the procrastinator actually needs to walk away from the computer/book/word document and engage in a relaxing activity. Being branded “lazy” by other people is likely to lead to the exact opposite behavior.
Often, though, the barrier is that procrastinators have executive functioning challenges — they struggle to divide a large responsibility into a series of discrete, specific, and ordered tasks. Here’s an example of executive functioning in action: I completed my dissertation (from proposal to data collection to final defense) in a little over a year. I was able to write my dissertation pretty easily and quickly because I knew that I had to a) compile research on the topic, b) outline the paper, c) schedule regular writing periods, and d) chip away at the paper, section by section, day by day, according to a schedule I had pre-determined.
Nobody had to teach me to slice up tasks like that. And nobody had to force me to adhere to my schedule. Accomplishing tasks like this is consistent with how my analytical, hyper-focused, Autistic little brain works. Most people don’t have that ease. They need an external structure to keep them writing — regular writing group meetings with friends, for example — and deadlines set by someone else. When faced with a major, massive project, most people want advice for how to divide it into smaller tasks, and a timeline for completion. In order to track progress, most people require organizational tools, such as a to-do list, calendar, datebook, or syllabus.
Needing or benefiting from such things doesn’t make a person lazy. It just means they have needs. The more we embrace that, the more we can help people thrive.
…
I had a student who was skipping class. Sometimes I’d see her lingering near the building, right before class was about to start, looking tired. The class would start, and she wouldn’t show up. When she was present in class, she was a bit withdrawn; she sat in the back of the room, eyes down, energy low. She contributed during small group work but never talked during larger class discussions.
A lot of my colleagues would look at this student and think she was lazy, disorganized, or apathetic. I know this because I’ve heard how they talk about under-performing students. There’s often rage and resentment in their words and tone — why won’t this student take my class seriously? Why won’t they make me feel important, interesting, smart?
But my class had a unit on mental health stigma. It’s a passion of mine because I’m a neuroatypical psychologist. I know how unfair my field is to people like me. The class & I talked about the unfair judgments people levy against those with mental illness; how depression is interpreted as laziness, how mood swings are framed as manipulative, how people with “severe” mental illnesses are assumed incompetent or dangerous.
The quiet, occasionally-class-skipping student watched this discussion with keen interest. After class, as people filtered out of the room, she hung back and asked to talk to me. And then she disclosed that she had a mental illness and was actively working to treat it. She was busy with therapy and switching medications, and all the side effects that entails. Sometimes, she was not able to leave the house or sit still in a classroom for hours. She didn’t dare tell her other professors that this was why she was missing classes and late, sometimes, on assignments; they’d think she was using her illness as an excuse. But she trusted me to understand.
And I did. And I was so, so angry that this student was made to feel responsible for her symptoms. She was balancing a full course load, a part-time job, and ongoing, serious mental health treatment. And she was capable of intuiting her needs and communicating them with others. She was a fucking badass, not a lazy fuck. I told her so.
She took many more classes with me after that, and I saw her slowly come out of her shell. By her Junior and Senior years, she was an active, frank contributor to class — she even decided to talk openly with her peers about her mental illness. During class discussions, she challenged me and asked excellent, probing questions. She shared tons of media and current-events examples of psychological phenomena with us. When she was having a bad day, she told me, and I let her miss class. Other professors — including ones in the psychology department — remained judgmental towards her, but in an environment where her barriers were recognized and legitimized, she thrived.
…
Over the years, at that same school, I encountered countless other students who were under-estimated because the barriers in their lives were not seen as legitimate. There was the young man with OCD who always came to class late because his compulsions sometimes left him stuck in place for a few moments. There was the survivor of an abusive relationship, who was processing her trauma in therapy appointments right before my class each week. There was the young woman who had been assaulted by a peer — and who had to continue attending classes with that peer, while the school was investigating the case.
These students all came to me willingly and shared what was bothering them. Because I discussed mental illness, trauma, and stigma in my class, they knew I would be understanding. And with some accommodations, they blossomed academically. They gained confidence, made attempts at assignments that intimidated them, raised their grades, started considering graduate school and internships. I always found myself admiring them. When I was a college student, I was nowhere near as self-aware. I hadn’t even begun my lifelong project of learning to ask for help.
…
Students with barriers were not always treated with such kindness by my fellow psychology professors. One colleague, in particular, was infamous for providing no make-up exams and allowing no late arrivals. No matter a student’s situation, she was unflinchingly rigid in her requirements. No barrier was insurmountable, in her mind; no limitation was acceptable. People floundered in her class. They felt shame about their sexual assault histories, their anxiety symptoms, their depressive episodes. When a student who did poorly in her classes performed well in mine, she was suspicious.
It’s morally repugnant to me that any educator would be so hostile to the people they are supposed to serve. It’s especially infuriating, that the person enacting this terror was a psychologist. The injustice and ignorance of it leave me teary every time I discuss it. It’s a common attitude in many educational circles, but no student deserves to encounter it.
…
I know, of course, that educators are not taught to reflect on what their students’ unseen barriers are. Some universities pride themselves on refusing to accommodate disabled or mentally ill students — they mistake cruelty for intellectual rigor. And, since most professors are people who succeeded academically with ease, they have trouble taking the perspective of someone with executive functioning struggles, sensory overloads, depression, self-harm histories, addictions, or eating disorders. I can see the external factors that lead to these problems. Just as I know that “lazy” behavior is not an active choice, I know that judgmental, elitist attitudes are typically borne out of situational ignorance.
And that’s why I’m writing this piece. I’m hoping to awaken my fellow educators — of all levels — to the fact that if a student is struggling, they probably aren’t choosing to. They probably want to do well. They probably are trying. More broadly, I want all people to take a curious and empathic approach to individuals whom they initially want to judge as “lazy” or irresponsible.
If a person can’t get out of bed, something is making them exhausted. If a student isn’t writing papers, there’s some aspect of the assignment that they can’t do without help. If an employee misses deadlines constantly, something is making organization and deadline-meeting difficult. Even if a person is actively choosing to self-sabotage, there’s a reason for it — some fear they’re working through, some need not being met, a lack of self-esteem being expressed.
People do not choose to fail or disappoint. No one wants to feel incapable, apathetic, or ineffective. If you look at a person’s action (or inaction) and see only laziness, you are missing key details. There is always an explanation. There are always barriers. Just because you can’t see them, or don’t view them as legitimate, doesn’t mean they’re not there. Look harder.
Maybe you weren’t always able to look at human behavior this way. That’s okay. Now you are. Give it a try.
Get over that wall!
…
If you found this essay illuminating at all, please consider buying Kim Longhofer / Mik Everett’s book, Self-Published Kindling: Memoirs of a Homeless Bookstore Owner. The ebook is $3; the paperback is $15.
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Measles Outbreak in Georgia: Why Can’t the “Ignorance Virus” Be Conquered? – Veterans Today | News – Military Foreign Affairs Policy
See on Scoop.it - COMPARE RISK COMMUNICATION
Health Editor’s Note: Apparently anti-vaxxers are not just here in the U.S. Ignorance virus is a very accurate name for measles. The cases of measles are seen in adults due to the fact that they were never vaccinated. Article taken from JAM News….Carol 321 cases of measles have been recorded in between 1-17 January. Experts say the reason for the spread of the disease is that many have not been vaccinated Manana Vardiashvili, David Pipia (Photo, video) Georgia ranks third among the seven European countries with the largest number of measles cases this year. Most of them have been recorded in Serbia, while Ukraine is in second place. The highest mortality rate was recorded in Serbia, where 14 people have died. Three people died in Georgia in 2018, with 2,000-2,200 measles cases detected in Georgia. By January 2019, the situation had worsened – the National Centre for Disease Control has announced that there is a measles outbreak in Georgia. From 1 January to 17 January, in just 17 days, 312 cases of measles were registered in Georgia. “Measles mainly affects the age group from 20 to 40 years. 56-58 per cent of those infected belong to this group. As for the remaining age groups, eight per cent are infected from age 0 to one year, and 14 per cent from one to five years old,” says the head of the National Centre for Disease Control, Amiran Gamkrelidze, in an interview with Netgazeti. These rates are growing, as a significant part of the population is still not vaccinated. The only thing that can stop measles is the vaccination of these people. In the civilized world, measles has long become a controlled viral infection. Why is Georgia unable to overcome it? Georgia ranks third among the top seven European countries where the number of cases of measles has increased the most, show data from the World Health Organization. Since the beginning of this year, 1,400 cases have been reported, two of which have been fatal. The first case of measles was reported in January when a hospital worker in Guria, Western Georgia, fell ill. The illness later appeared in Adjara and spread throughout most of Western Georgia. Specialists predict that the number of people infected will increase. Those that have not had measles in the past and who are not vaccinated against the disease are most at risk. The National Centre for Disease Control reports that there are about half a million people at risk in Georgia. “Research shows that these are people between 20 and 40 years old. As the number of people who are not vaccinated against measles remains high, the disease will spread,” says Paata Imnadze, the centre’s deputy director. Breakouts of measles in Georgia took place back in 2004 and 2005 as well when 14,500 fell ill and nine died. In 2014 and 2015, four people died from measles. Vaccinations against measles were first introduced in Georgia in 1968. Before that, the disease was popularly known as batonebi [ed. the Georgian word for ‘sirs, masters’] and was treated with folk medicine. Batonebi and anti-vaxxers Fifty-eight-year-old Dali remembers well how she and her sister fell sick with measles: their grandmother hung red velvet curtains on the windows, put red roses in vases and strongly warned the residents of the home not to curse or argue. The children had to sing in order not to anger the batonebi, or masters. The illness took its toll on them – Dali’s hearing suffered, while her sister had trouble with her hearing and vision. “We gave both our children scheduled vaccinations. Considering my own experience, I didn’t want to risk their health,” says Dali. However, in Georgia there are many people that think differently and do not vaccinate their children. Official data has it that 10 per cent of children up to six years of age are not vaccinated in Georgia. Irina Aliashvili is a young mother who has ensured that her three-year-old child receives all the necessary vaccinations. Aliashvili searches for the best doctors and reads up on information pertaining to vaccinations herself. “I didn’t find any reliable information anywhere that supported the idea that vaccinations can give rise to serious complications or illnesses,” Irina said. Nini Tvalavadze is 25 years old. She is the co-founder of the NGO Vaccinations and Risk Factors, which collects and distributes information about the dangers of vaccines. Nini asserts that there are many side effects to vaccines which she herself has experienced: “I began having epileptic attacks when I was five years old, and they continued until I was 18. I was afraid to go outside because I did not know when I would have an attack. The doctors didn’t understand what was the matter with me. Then we realised that it all began with a scheduled vaccination.” Nini’s daughter is three years old, and aside from vaccinations against tuberculosis (BCG) and Hepatitis B, she has not received any scheduled vaccinations. Nini says she gets her information about the dangers of vaccinations from the internet and that she herself studies the cases she has come across. “There was one case where a child received a vaccination and later became autistic. Another child lost an arm after getting polio from a vaccination,” she says. Nini says that, despite the fact that she hasn’t been vaccinated, her daughter is not ill and has a good immune system. Because of this she does not intend to begin vaccinating her in the future either. The Centre for Disease Control denies all claims that vaccinations can cause illness or complications, and attests to the quality of available vaccines. “We only get high-quality European vaccines in Georgia. After the 1990s, there has not been a single case of complications or infections after vaccination,” says Paata Imnadze. Imnadze says there are practically no complications associated with the measles vaccine. “The worst thing that can happen is an allergic reaction, but we have not had such a case to date.” Imnadze says that such cases are very rare, one in a million, and even in these cases a doctor can always act quickly and provide urgent care. Is disinformation to blame? Specialists say there are two reasons behind the epidemic in Georgia: the failure of the 1990s immunisation programme and the subsequent refusal of parents to vaccinate their children afterwards. In 2008 the government planned to have one million people between the ages of 6 and 27 vaccinated. However, only about half of their target was reached. “A media campaign began which attested to the supposed harms of vaccination – even I became afraid. The programme, of course, failed,” says Paata Imnadze. There are several myths in Georgian society pertaining to the use of vaccinations. Many continue to think that vaccinations can cause autism. The greatest harm to regular vaccinations in the world was caused by an article by English scientist Andrew Wakefield in the Lancet journal in 1998 in which he claimed that a measles vaccine was causing autism. It was later proven that the article was paid for and falsified. The journal issued an apology and had the article redacted. However, the lie spread like a virus: the consequences of that article in Europe and the USA have more or less been overcome, but in Georgia it has been difficult. “The Russian propaganda machine took an interest in the topic of vaccination against measles. It has been shown that Russian trolls have been involved in the dissemination of disinformation across European social media and internet sites,” Imnadze says. The Georgian parliament is looking at a bill which will make vaccinations mandatory. Should parents be unable to show a document attesting to their child’s vaccination history, children will not be accepted into schools. The bill was accepted in its first reading. However, the NGO Vaccinations and Risk Factors is gathering signatures to prevent this bill from coming into force. Activists of the movement say they will come out in protest. Measles Measles is a viral infection that is transmitted via the air. It is easily spread and the risk of infection is particularly high in populous areas. The measles virus causes fever and a rash on the skin and pus in the mouth. Sometimes it causes complications in the form of ear, lung or brain inflammation. According to the World Health Organization, one in 1,000 cases of measles are fatal. Symptoms should immediately be brought to the attention of a doctor. Vaccinations against measles are given in two rounds, the first at the age of one and the second at the age of five. “When a child falls ill before one year of age, this means that the mother did not have immunity against the virus. Before one year of age, the child shouldn’t fall ill. If they do, the illness is hard to treat. That’s why parents whose children are younger than one year old must ensure that they themselves are vaccinated,” Imnadze says.
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Bitcoin network
The particular bitcoin multilevel is a peer-to-peer payment market that performs on a cryptographic protocol. End users send in addition to receive bitcoins, the sections of foreign money, by displaying digitally closed messages into the network employing bitcoin cryptocurrency wallet application. Transactions usually are recorded in to a distributed, duplicated public databases known as often the blockchain, together with consensus obtained by a proof-of-work system named mining. Typically the protocol has been designed in '08 and for sale since 2009 since open source software by means of Satoshi Nakamoto, the name as well as pseudonym in the original developer/developer group.
Often the network demands minimal design to share orders. An interimistisk decentralized community of volunteers is sufficient. Emails are shown on a finest effort time frame, and clients can get away from and rejoin the networking at will. About reconnection, a new node packages and qualifies new pads from other clients to complete it has the local replicate of the blockchain.[1][2] A bitcoin is characterized by a routine of electronically signed ventures that begun with the bitcoin's creation, as being a block encourage. The owner of your bitcoin transactions it by way of digitally completing it over to a higher owner having a bitcoin financial transaction, much like selling a traditional standard bank check. Any payee can easily examine each one previous exchange to always check the company of property. Unlike regular check honest reviews, bitcoin purchases are irreparable, which eradicates risk of charge-back fraud.[3]
Although it is quite possible to handle bitcoins individually, it may be unwieldy to help require a distinct transaction for any bitcoin inside a transaction. Orders are thus allowed to incorporate multiple terme conseillé and components,[4][better source needed] allowing for bitcoins for being split plus combined. Widespread transactions can have either a sole input originating from a larger preceding transaction or simply multiple plugs combining small amounts, and something or two signals: one for any payment, then one returning the exact change, in the event any, towards sender. Almost any difference between your total insight and production amounts of any transaction would travel to miners being a transaction service charge.[1] Mining or prospecting[edit]
GPU-based mining machine, 2012
Lancelot FPGA-based mining or prospecting board, 2013 To form some sort of distributed timestamp server for a peer-to-peer multilevel, bitcoin works on the proof-of-work process.[2] This do the job is often referred to as bitcoin gold mining. The unsecured personal is identified rather than furnished by knowledge.[5] The process is strength intensive.[6] Energy can take more than much of functioning costs regarding miners.[7] A knowledge center inside China, intended mostly intended for bitcoin mining or prospecting, is required to require around 135 megawatts of electric power.[8]
Requesting a proof work to give the personal unsecured for the blockchain was Satoshi Nakamoto's major innovation.[5] The exact mining practice involves determine a mass that, if hashed 2 times with SHA-256, yields many smaller than the particular given difficulties target. Whilst the average operate required boosts in inverse proportion for the difficulty goal, a hash can remain verified simply by executing there are round regarding double SHA-256.
For the bitcoin timestamp market, a valid evidence work is available by incrementing a non-ce until a worth is found giving the block's hash hidden number of foremost zero portions. Once the hashing has made a valid final result, the prohibit cannot be modified without replacing the work. Seeing that later chunks are chained after the item, the work to modify the obstruct would include things like redoing the effort for each after that block.
The vast majority consensus throughout bitcoin is definitely represented from the longest archipelago, which expected the greatest degree of effort to provide. If a tastes computing electricity is operated by genuine nodes, typically the honest string will raise fastest and also outpace almost any competing places to eat. To modify a new past wedge, an opponent would have to replace the proof-of-work of that mass and all obstructs after them and then get past the work on the honest clients. The chances of a weaker attacker finding and catching up decreases exponentially while subsequent hindrances are included.[2]
Gold mining difficulty has grown significantly To pay for boosting hardware acceleration and changing interest in managing nodes after a while, the difficulty of actually finding a valid hash is fine-tuned roughly just about every two weeks. When blocks will be generated straight away, the difficulty improves and more hashes are required to generate a block in order to generate completely new bitcoins.[2]
Difficulty[edit] Bitcoin gold mining is a reasonably competitive endeavor. The "arms race" has been witnessed through the a variety of hashing engineering that have been accustomed to mine bitcoins: basic Processors, high-end GPUs common in a great many gaming personal computers, FPGAs along with ASICs just about all have been made use of, each lessening the profitability with the less-specialized technological know-how. Bitcoin-specific ASICs are now obtainable.[9] As bitcoins become more hard mine, computer units manufacturing companies have noticed an increase in gross sales of top quality products.[10]
Computing strength is often bundled up together or perhaps "pooled" to cut back variance with miner salary. Individual mining or prospecting rigs will have to wait to get long periods to make sure that a prohibit of deals and obtain payment. In a very pool, most participating miners get paid each time a participating storage space solves your block. That payment is dependent upon the amount of perform an individual miner contributed to support find that obstruct.[11]
Bitcoin data locations prefer to retain a low report, are sent out around the world in addition to tend to area around the option of cheap energy.[7]
Strength consumption[edit]
A gold mining farm around Iceland Inside 2013, Symbol Gimein predicted electricity value to be concerning 40. in search of megawatts (982 megawatt-hours any day).[12] Throughout 2014, Hass McCook believed 80. several megawatts (80, 666 kW).[13] As of 2015, The Economist estimated while all miners used modern day facilities, often the combined power consumption could be 166. 8 megawatts (1. 46 terawatt-hours per year).[14] In March 2017 it turned out estimated the fact that total electrical power use of bitcoin mining ended up being over 634 megawatts (20 TWh/year).[15][better supply needed]
Surgeon Matt O'Brien opined the reason is not noticeable whether bitcoin is bringing down transaction prices, since the expenditures are become pollution fees, which he / she characterizes seeing that "environmental spillovers on the competition, or what exactly economists get in touch with negative externalities. "[16]
To lower the price, bitcoin miners have placed in places including Iceland just where geothermal vitality is low-priced and cooling down Arctic weather is no cost.[16] Chinese bitcoin miners are usually known to work with hydroelectric electrical power in Tibet to reduce electrical energy costs.[17]
Process[edit]
Avalon ASIC-based mining machine
ASICMINER ASIC-based OBTAINABLE mining system A bad overview of doing this to quarry bitcoins can be:[2]
Completely new transactions are generally broadcast for all nodes. Each and every miner computer collects innovative transactions in a block. Every single miner computer works on looking for a proof-of-work computer for its wedge. When a computer finds some sort of proof-of-work, that broadcasts the exact block to all or any nodes. Having nodes verify the orders it supports and agree to only if each is valid. Clients express all their acceptance by simply moving to the office on the future block, adding the hash of the recognized block. Extracted bitcoins[edit]
Diagram featuring how bitcoin transactions usually are verified By means of convention, the primary transaction in the block is actually a special business deal that delivers new bitcoins owned with the creator of your block. This can be a incentive pertaining to nodes to guide the community.[1] It provides the web move fresh bitcoins in circulation. The particular reward regarding mining halves every 210, 000 pads. It commenced at 40 bitcoin, fell to 20 in late this and to 14. 5 bitcoin in 2016.[18] This halving process will be programmed to stay for sixty-four times just before new or maybe creation prevents.[18]
Security and safety[edit] A variety of potential episodes on the bitcoin network and it is use as the payment system, authentic or hypothetical, have been viewed as. The bitcoin protocol comes with several attributes that shield it in opposition to some of those strikes, such as unsanctioned spending, increase spending, forging bitcoins, plus tampering with all the blockchain. Different attacks, including theft of personal keys, involve due health care by end users.[19][20][21][22][23][24][25]
Not authorized spending[edit] Unauthorized shelling out is mitigated by bitcoin's implementation involving public-private critical cryptography. One example is; when Alice sends a new bitcoin that will Bob, Greg becomes the fresh owner in the bitcoin. Event observing the particular transaction might choose to spend the bitcoin Bob just simply received, although she could not sign typically the transaction but without the knowledge of Bob's private important.[20]
Increase spending[edit] A specific challenge that an online payment system ought to solve is usually double-spending, when a user makes sense the same piece to two if not more different receivers. An example of a really problem can be if Event sent your bitcoin to be able to Alice and later it was sent precisely the same bitcoin for you to Bob. Typically the bitcoin networking guards versus double-spending by means of recording all of bitcoin airport transfers in a journal (the blockchain) that is seen to all clients, and making certain for all transported bitcoins they will haven't been recently previously used.[20]: 5
Race strike[edit] In the event that Eve delivers to pay Alice a bitcoin in exchange intended for goods and also signs any corresponding purchase, it is not impossible that the woman also leads to a different financial transaction at the same time transmitting the same bitcoin to Joe. By the policies, the multilevel accepts just one single of the ventures. This is known as race episode, since there is some sort of race which usually transaction will probably be accepted initially. Alice can help to eliminate the risk of battle attack stipulating that she could not offer the goods until finally Eve's monthly payment to Alice appears inside blockchain.[21]
A plan race harm (which is called a Finney attack by way of reference to Rum Finney) calls for the engaging of a miner. Instead of submitting both transactions requests (to pay Robert and Alice with the identical coins) on the network, Event issues simply Alice's repayment request into the network, whilst the accomplice attempts to mine a new block that has the settlement to Chad instead of Alice. There is a constructive probability which the rogue miner will realize success before the market, in which case often the payment to help Alice are going to be rejected. Just as with the simply race encounter, Alice helps to reduce the risk of your Finney strike by anticipating the monthly payment to be in the blockchain.[22]
History adjustment[edit] Each one block that is definitely added to the exact blockchain, you start with the mass containing settled transaction, is termed a affirmation of that exchange. Ideally, suppliers and expert services that acquire payment inside bitcoin really should wait for no less than one confirmation to generally be distributed in the network, ahead of assuming that the particular payment seemed to be done. Cardiovascular disease confirmations the merchant is waiting for, cardiovascular disease difficult it truly is for an adversary to with success reverse typically the transaction in a very blockchain-unless often the attacker manages more than half the sum network electric power, in which case its called a 51% attack.[23]
Deanonymisation connected with clients[edit] Deanonymisation can be a strategy throughout data mining or prospecting in which private data is definitely cross-referenced for some other sources of records to re-identify the confidential data source. In conjunction with transaction data analysis, which could reveal relationships between bitcoin addresses (pseudonyms),[19][24] there is also a possible episode[25] which inbound links a customer's pseudonym that will its Internet protocol address. If the expert is using Tor, the harm includes a solution to separate the exact peer from Tor community, forcing those to use their whole real Internet protocol address for any even more transactions. Often the attack incorporates bitcoin parts of sending peer includes and anti-DoS protection. The buying price of the encounter on the total bitcoin networking is within €1500 every month.[25]
Monthly payment verification[edit] Main document: Online business deal processing Just about every miner may choose which purchases are built into or exempted from a prohibit.[26] A greater number of deals in a obstruct does not mean greater computational power instructed to solve that will block.[26]
Upon finding a new purchase a computer must verify it: for example, verify in which non-e on the transaction's terme conseillé have been recently spent. To that what is node should access the particular blockchain. Anyone who does definitely not trust his / her network friends, should preserve a full neighborhood copy with the blockchain, so any type can be approved.
As believed in Nakamoto's whitepaper, you can verify bitcoin payments not having running a entire network computer (simplified transactions verification, SPV). A user merely needs a backup of the wedge headers of your longest sequence, which are available simply by querying multilevel nodes until it eventually is noticeable that the best chain may be obtained. In that case, get the Merkle branch backlinks the financial transaction to a block. Backlinks the exchange to a set up the company demonstrates that your network computer has acknowledged it, along with blocks extra after the idea further determine the evidence.[1]
Records in the blockchain[edit] As it is possible to maintain any electronic digital file during the blockchain, the more expensive the business deal size, the more expensive any affiliated fees turn into.[27] Various objects have been set, including Web addresses to little one pornography, the ASCII fine art image with Ben He, material with the Wikileaks cables and wires, prayers coming from bitcoin miners, and the unique bitcoin whitepaper.[28]
Lawbreaker activity[edit] The use of bitcoin by scammers has enticed the attention of monetary regulators, intention bodies, police, and the music.[29] The FEDERAL BUREAU prepared a strong intelligence examination,[30] the SECOND has supplied a sharp warning with regards to investment systems using internet currencies,[29] as well as the U. T. Senate organised a ability to hear on exclusive currencies with November 2013.[31]
Various news retailers have declared that that the vogue for bitcoins depends on the ability to employ them to purchase illegitimate goods.[32][33] In 2014, researchers within the University regarding Kentucky located "robust information that education enthusiasts in addition to illegal pastime drive affinity for bitcoin, and start with limited or any support to get political plus investment purposes. "[34]
Black stores[edit] Key article: Darknet market Some sort of CMU science tecnistions estimated this in this, 4. five per cent to 9% of all orders on most of exchanges worldwide were pertaining to drug home-based trades on a single black web medications market, Egypt Road.[35] Little one pornography,[36] murder-for-hire services,[37] and also weapons[38] may also be allegedly found on black sector sites of which sell around bitcoin. A result of the anonymous dynamics and the absence of central management on these kind of markets, it is not easy to know regardless of if the services will be real or merely trying to do the bitcoins.[39]
Several deeply web dark-colored markets have already been shut by simply authorities. With October 2013 Silk Highway was power down by Ough. S. law enforcement officials[40][41][42] leading to any short-term lessing of the value of bitcoin.[43] In 2015, the originator of the internet site was sentenced to life inside prison.[44] Choice sites have been soon offered, and in first 2014 typically the Australian Displaying Corporation noted that the close-up of A silk filled duvet Road got little affect on the number of Australians selling drug treatments online, which often had basically increased.[45] At the begining of 2014, Nederlander authorities shut down Utopia, a web-based illegal things market, along with seized nine hundred bitcoins.[46] At the end of 2014, some sort of joint police force operation discovered European in addition to American professionals seize bitcoins and in close proximity 400 profound web sites like the illicit possessions market Man made fiber Road minimal payments 0.[47] Police officers activity features resulted in various convictions. Keep away from 2014, Steve Shrem appeared to be sentenced to 2 years throughout prison regarding indirectly helping send $1 million towards Silk Path drugs web page,[48] and in January 2015, it is founder, Ross Ulbricht, has been convicted in drugs rates and people a lifetime sentence.[49]
Some african american market web-sites may keep pace with steal bitcoins from shoppers. The bitcoin community labeled one web site, Sheep Souk, as a hoax when it stopped withdrawals plus shut down immediately after an so-called bitcoins fraud.[50] In a independent case, earnest accounts using bitcoins owned by patrons of an different black color market were being hacked at the begining of 2014.[51]
According to the Online Watch Basis, a UK-based charity, bitcoin is used to order child sex sites, and almost 250 such web sites accept this payment. Bitcoin isn't really the only way to invest in child sexually graphic online, like Troels Oertling, head in the cybercrime system at Europol, states, "Ukash and Paysafecard... have [also] been employed to pay for these material. micron However , the online world Watch Groundwork lists close to 30 web pages that entirely accept bitcoins.[36] Some of these internet sites have close, such as a strong web crowdfunding website that will aimed to investment the formation of new boy or girl porn.[52][better origin needed] Furthermore, backlinks to youngster porn internet sites have been added onto the blockchain as dictatorial data is usually included if a transaction is produced.[53][54]
Malware[edit] Malware obtaining[edit] Many malware could steal privately owned keys intended for bitcoin billfolds allowing often the bitcoins their selves to be compromised. The most common style searches pcs for cryptocurrency wallets to be able to upload into a remote hardware where they are often cracked and the coins ripped off.[55] Many of these furthermore log key strokes to file passwords, typically avoiding the desire to crack the exact keys.[55] Some other approach finds when a bitcoin address can be copied to your clipboard and also quickly changes it along with a different deal with, tricking persons into mailing bitcoins for the wrong street address.[56] This method is successful because bitcoin transactions are usually irreversible.[57]: 57
Just one virus, pass on through the Horse botnet, ended up being reported with February 2014 to have taken up to $220, 000 around cryptocurrencies like bitcoins via 85 purses.[58] Security corporation Trustwave, which will tracked the particular malware, studies that their latest version surely could steal one month types of a digital currency.[59]
A type of Macintosh malware dynamic in August 2013, Bitvanity inquired as a vainness wallet handle generator along with stole contact information and private take a moment from other bitcoin client computer software.[60] A different password cracker for macOS, called CoinThief was described in June 2014 to get responsible for many bitcoin thefts.[60] The software seemed to be hidden in variants of several cryptocurrency blog on Acquire. com in addition to MacUpdate.[60]
Ransomware[edit] Many types of ransomware demand repayment in bitcoin.[61][62] A person program identified as CryptoLocker, commonly spread by means of legitimate-looking email address attachments, codes the hard commute of an attacked computer, in that case displays a new countdown contatore and requirements a ransom in bitcoin, to decrypt it.[63] Boston police mentioned they given a 3 bitcoin ransom in December 2013, value more than $1, 300 then, to decrypt one of their particular hard drives.[64] Bitcoin was used as being the ransom medium sized in the WannaCry ransomware.[65] One particular ransomware different disables access to the internet and calls for credit card facts to restore the item, while confidentially mining bitcoins.[63]
Unapproved mining[edit] In July 2011, Symantec warned with regards to the possibility in which botnets can mine discreetly for bitcoins.[66] Malware used parallel control capabilities involving GPUs built in many modern-day video memory cards.[67] Although the normal PC using an integrated artwork processor will be virtually unproductive for bitcoin mining, numerous PCs crammed with gold mining malware could possibly produce a number of results.[68]
In mid-August 2011, bitcoin mining botnets were noticed,[69] and less in comparison with three months in the future, bitcoin mining or prospecting trojans possessed infected Macintosh personal computer OS A.[70]
Around April 2013, electronic activities organization E-Sports Entertainment appeared to be accused connected with hijacking 18, 000 desktops to my verizon prepaid phone bitcoins; the business later completed the case while using State of latest Jersey.[71]
German law arrested a family in December 2013 who tailored existing botnet software to accomplish bitcoin gold mining, which authorities said were definitily used to my very own at least $950, 000 truly worth of bitcoins.[72]
To get four time in December 2013 and The month of january 2014, Aol! Europe visible an offer containing bitcoin mining trojans that afflicted an estimated a couple million laptops.[73] The software, termed Sefnit, has been detected inside mid-2013 and has now been provided with many software systems. Microsoft have been removing typically the malware by way of its Microsoft company Security Basics and other security and safety software.[74]
Several information of staff members or learners using school or exploration computers for you to mine bitcoins have been publicized.[75]
Income laundering[edit] Bitcoins probably are not ideal for income laundering, mainly because all ventures are open.[76] Authorities, such as European Business banking Authority[77] often the FBI,[30] plus the Financial Steps Task Drive of the G7[78] have depicted concerns this bitcoin should be considered for money washing. In early 2014, an agent of a You. S. bitcoin exchange, Steve Shrem, has been arrested for cash laundering.[79] Later, he was sentenced to two several years in imprisonment for "aiding and abetting an unlicensed money sending business".[48] A summary by Britian's Treasury plus Home Office titled "UK state risk review of money washing and terrorist financing" (2015 October) identified that, on the twelve procedures examined inside the report, bitcoin carries this risk of becoming utilized for money washing, with the most widespread money washing method staying the finance institutions.[80]
Ponzi scheme[edit] In a Ponzi scheme of which utilized bitcoins, The Bitcoin Savings and also Trust offers investors approximately 7 per-cent weekly desire, and brought up at least 800, 000 bitcoins from in 2011 to this.[81] In September 2013 the exact U. S i9000. Securities along with Exchange Cost charged the corporation and its president in 2013 "with defrauding investors within the Ponzi plan involving bitcoin".[81] In Sept. 2014 the particular judge fined Bitcoin Enough cash & Confidence and its master $40 zillion for running a bitcoin Ponzi structure.[82]
Thievery[edit] You can find many cases with bitcoin robbery.[83] One way this can be accomplished will involve a third party opening the non-public key to your victim's bitcoin address,[84] or maybe of an on-line wallet.[85] If your private truth is stolen, every one of the bitcoins from your compromised target can be shifted. In that case, typically the network is deficient in any specifications to identify often the thief, mass further purchases of those lost bitcoins, as well as return them how to the reliable owner.[86]
Theft likewise occurs on sites exactly where bitcoins widely-used to purchase questionable goods. At the end of November 2013, an estimated 100 dollar million throughout bitcoins ended up allegedly compromised from the on the web illicit items marketplace Lambs Marketplace, which in turn immediately sealed.[87] Users ed the gold coins as they were definitely processed in addition to converted to funds, but not any funds have been recovered without culprits known to be.[87] A different charcoal market, A silk duvet Road couple of, stated that will during a Feb . 2014 identify, bitcoins highly valued at $2. 7 trillion were extracted from escrow health care data.[51]
Web-sites where consumers exchange bitcoins for dollars or retailer them with "wallets" are targets to get theft. Terme conseillé. io, a great Australian billfold service, ended up being hacked double in August 2013 plus lost in excess of $1 thousand in bitcoins.[88] In late March 2014 Mt. Gox, on the list of largest online currency transactions, filed pertaining to bankruptcy around Tokyo between reports in which bitcoins well worth $350 , 000, 000 had been ripped off.[89] Flexcoin, any bitcoin hard drive specialist within Alberta, Nova scotia, shut down about March 2014 after telling it found out a thievery of about 650 dollar, 000 inside bitcoins.[90] Poloniex, a digital foreign currency exchange, reported with March 2014 that it misplaced bitcoins greatly regarded at all-around $50, 000.[91] In Thinking about receiving 2015 UK-based bitstamp, your third busiest bitcoin exchange around the globe, was hacked and $5 million throughout bitcoins were being stolen.[92] January 2015 did find a Chinese trade named BTER lose bitcoins worth just about $2 zillion to cyber criminals.[93]
An essential bitcoin change, Bitfinex, seemed to be hacked and also nearly 120 watch, 000 bitcoins (around $60m) was taken in 2016. Bitfinex appeared to be forced to help suspend it has the trading. The exact theft is a second major bitcoin heist ever, dwarfed only by means of Mt. Gox theft with 2014. As per Forbes, "All of Bitfinex's customers,... will probably stand to give up money. This company has has announced a haircut regarding 36. 067% across the board. in[94]
Thefts have increased safety fears. Charles Hayter, founder involving digital money comparison web page CryptoCompare explained, "It’s an indication of the flaccidity of the commercial infrastructure in such a nascent industry. inches[95] According to the reading of United. S. Household of Specialists Committee for Small Business around April a couple of, 2014, "these vendors insufficiency regulatory oversight, minimum cash standards , nor provide purchaser protection against decline or thieves. "[96]
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Text
Automated root cause analysis for Spark application failures
Reduce troubleshooting time from days to seconds.
Spark’s simple programming constructs and powerful execution engine have brought a diverse set of users to its platform. Many new big data applications are being built with Spark in fields like health care, genomics, financial services, self-driving technology, government, and media. Things are not so rosy, however, when a Spark application fails.
Similar to applications in other distributed systems that have a large number of independent and interacting components, a failed Spark application throws up a large set of raw logs. These logs typically contain thousands of messages, including errors and stacktraces. Hunting for the root cause of an application failure from these messy, raw, and distributed logs is hard for Spark experts—and a nightmare for the thousands of new users coming to the Spark platform. We aim to radically simplify root cause detection of any Spark application failure by automatically providing insights to Spark users like what is shown in Figure 1.
Figure 1. Insights from automatic root cause analysis improve Spark user productivity. Source: Adrian Popescu and Shivnath Babu.
Spark platform providers like Amazon, Azure, Databricks, and Google clouds as well as application performance management (APM) solution providers like Unravel have access to a large and growing data set of logs from millions of Spark application failures. This data set is a gold mine for applying state-of-the-art artificial intelligence (AI) and machine learning (ML) techniques. In this blog, we look at how to automate the process of failure diagnosis by building predictive models that continuously learn from logs of past application failures for which the respective root causes have been identified. These models can then automatically predict the root cause when an application fails[1]. Such actionable root-cause identification improves the productivity of Spark users significantly.
Clues in the logs
A number of logs are available every time a Spark application fails. A distributed Spark application consists of a driver container and one or more executor containers. The logs generated by these containers have information about the application as well as how the application interacts with the rest of the Spark platform. These logs form the key data set that Spark users scan for clues to understand why an application failed.
However, the logs are extremely verbose and messy. They contain multiple types of messages, such as informational messages from every component of Spark, error messages in many different formats, stacktraces from code running on the Java Virtual Machine (JVM), and more. The complexity of Spark usage and internals make things worse. Types of failures and error messages differ across Spark SQL, Spark Streaming, iterative machine learning and graph applications, and interactive applications from Spark shell and notebooks (e.g., Jupyter, Zeppelin). Furthermore, failures in distributed systems routinely propagate from one component to another. Such propagation can cause a flood of error messages in the log and obscure the root cause.
Figure 2 shows our overall solution to deal with these problems and to automate root cause analysis (RCA) for Spark application failures. Overall, the solution consists of:
Continuously collecting logs from a variety of Spark application failures
Converting logs into feature vectors
Learning a predictive model for RCA from these feature vectors
Of course, as with any intelligent solution that uses AI and ML techniques, the devil is the details!
Figure 2. Root cause analysis of Spark application failures. Source: Adrian Popescu and Shivnath Babu. Data collection for training
As the saying goes: garbage in, garbage out. Thus, it is critical to train RCA models on representative input data. In addition to relying on logs from real-life Spark application failures observed on customer sites, we have also invested in a lab framework where root causes can be artificially injected to collect even larger and more diverse training data.
Structured versus unstructured data
Logs are mostly unstructured data. To keep the accuracy of model predictions to a high level in automated RCA, it is important to combine this unstructured data with some structured data. Thus, whenever we collect logs, we are careful to collect trustworthy structured data in the form of key-value pairs that we additionally use as input features in the predictive models. These include Spark platform information and environment details of Scala, Hadoop, OS, and so on.
Labels
ML techniques for prediction fall into two broad categories: supervised learning and unsupervised learning. We use both techniques in our overall solution. For the supervised learning part, we attach root-cause labels with the logs collected from an application failure. This label comes from a taxonomy of root causes that we have created based on millions of Spark application failures seen in the field and in our lab. Broadly speaking, the taxonomy can be thought of as a tree data structure that categorizes the full space of root causes. For example, the first non-root level of this tree can be failures caused by:
Configuration errors
Deployment errors
Resource errors
Data errors
Application errors
Unknown factors
The leaves of this taxonomy tree form the labels used in the supervised learning techniques. In addition to a text label representing the root cause, each leaf also stores additional information such as: (a) a description template to present the root cause to a Spark user in a way that she will easily understand (like the message in Figure 1), and (b) recommended fixes for this root cause. We will cover the root-cause taxonomy in a future blog.
The labels are associated with the logs in one of two ways. First, the root cause is already known when the logs are generated, as a result of injecting a specific root cause we have designed to produce an application failure in our lab framework. The second way in which a label is given to the logs for an application failure is when a Spark domain expert manually diagnoses the root cause of the failure.
Input Features
Once the logs are available, there are various ways in which the feature vector can be extracted from these logs. One way is to transform the logs into a bit vector (e.g., 1001100001). Each bit in this vector represents whether a specific message template is present in the respective logs. A prerequisite to this approach is to extract all possible message templates from the logs. A more traditional approach for feature vectors from the domain of information retrieval is to represent the logs for a failure as a bag of words. This approach is mostly similar to the bit vector approach except for a couple of differences: (a) each bit in the vector now corresponds to a word instead of a message template, and (b) instead of 0s and 1s, it is more common to use numeric values generated using techniques like TF-IDF.
More recent advances in ML have popularized vector embeddings. In particular, we use the doc2vec technique[2]. At a high level, these vector embeddings map words (or paragraphs, or entire documents) to multidimensional vectors by evaluating the order and placement of words with respect to their neighboring words. Similar words map to nearby vectors in the feature vector space. The doc2vec technique uses a three-layer neural network to gauge the context of the document and relate similar content together.
Once the feature vectors are generated along with the label, a variety of supervised learning techniques can be applied for automatic RCA. We have evaluated both shallow as well as deep learning techniques, including random forests, support vector machines, Bayesian classifiers, and neural networks.
Conclusion
The overall results produced by our solution are very promising. We are currently enhancing the solution in some key ways. One of these is to quantify the degree of confidence in the root cause predicted by the model in a way that users will easily understand. Another key enhancement is to speed up the ability to incorporate new types of application failures. The bottleneck currently is in generating labels. We are working on active learning techniques[3] that nicely prioritize the human efforts required in generating labels. The intuition behind active learning is to pick the unlabeled failure instances that provide the most useful information to build an accurate model. The expert labels these instances and then the predictive model is rebuilt.
Manual failure diagnosis in Spark is not only time consuming, but highly challenging due to correlated failures that can occur simultaneously. Our unique RCA solution enables the diagnosis process to function effectively even in the presence of multiple concurrent failures as well as noisy data prevalent in production environments. Through automated failure diagnosis, we remove the burden of manually troubleshooting failed applications from the hands of Spark users and developers, enabling them to focus entirely on solving business problems with Spark.
References:
[1] S. Duan, S. Babu, and K. Munagala, “Fa: A System for Automating Failure Diagnosis”, International Conference on Data Engineering, 2009. (Return)
[2] Q. Lee and T. Mikolov, “Distributed Representations of Sentences and Documents”, International Conference on Machine Learning, 2014 (Return)
[3] S. Duan and S. Babu, "Guided Problem Diagnosis through Active Learning", International Conference on Autonomic Computing, 2008 (Return)
To learn how to use analytic tools to manage your big data infrastructure, check out Shivnath Babu's session "Using Machine Learning to Simplify Kafka Operations" at the Strata Data Conference in San Jose, March 5-8, 2018—registration is now open.
Related resource:
Spark: The Definitive Guide, by Bill Chambers and Matei Zaharia
Continue reading Automated root cause analysis for Spark application failures.
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Text
Automated root cause analysis for Spark application failures
Automated root cause analysis for Spark application failures
Reduce troubleshooting time from days to seconds.
Spark’s simple programming constructs and powerful execution engine have brought a diverse set of users to its platform. Many new big data applications are being built with Spark in fields like health care, genomics, financial services, self-driving technology, government, and media. Things are not so rosy, however, when a Spark application fails.
Similar to applications in other distributed systems that have a large number of independent and interacting components, a failed Spark application throws up a large set of raw logs. These logs typically contain thousands of messages, including errors and stacktraces. Hunting for the root cause of an application failure from these messy, raw, and distributed logs is hard for Spark experts—and a nightmare for the thousands of new users coming to the Spark platform. We aim to radically simplify root cause detection of any Spark application failure by automatically providing insights to Spark users like what is shown in Figure 1.
Figure 1. Insights from automatic root cause analysis improve Spark user productivity. Source: Adrian Popescu and Shivnath Babu.
Spark platform providers like Amazon, Azure, Databricks, and Google clouds as well as application performance management (APM) solution providers like Unravel have access to a large and growing data set of logs from millions of Spark application failures. This data set is a gold mine for applying state-of-the-art artificial intelligence (AI) and machine learning (ML) techniques. In this blog, we look at how to automate the process of failure diagnosis by building predictive models that continuously learn from logs of past application failures for which the respective root causes have been identified. These models can then automatically predict the root cause when an application fails[1]. Such actionable root-cause identification improves the productivity of Spark users significantly.
Clues in the logs
A number of logs are available every time a Spark application fails. A distributed Spark application consists of a driver container and one or more executor containers. The logs generated by these containers have information about the application as well as how the application interacts with the rest of the Spark platform. These logs form the key data set that Spark users scan for clues to understand why an application failed.
However, the logs are extremely verbose and messy. They contain multiple types of messages, such as informational messages from every component of Spark, error messages in many different formats, stacktraces from code running on the Java Virtual Machine (JVM), and more. The complexity of Spark usage and internals make things worse. Types of failures and error messages differ across Spark SQL, Spark Streaming, iterative machine learning and graph applications, and interactive applications from Spark shell and notebooks (e.g., Jupyter, Zeppelin). Furthermore, failures in distributed systems routinely propagate from one component to another. Such propagation can cause a flood of error messages in the log and obscure the root cause.
Figure 2 shows our overall solution to deal with these problems and to automate root cause analysis (RCA) for Spark application failures. Overall, the solution consists of:
Continuously collecting logs from a variety of Spark application failures
Converting logs into feature vectors
Learning a predictive model for RCA from these feature vectors
Of course, as with any intelligent solution that uses AI and ML techniques, the devil is the details!
Figure 2. Root cause analysis of Spark application failures. Source: Adrian Popescu and Shivnath Babu. Data collection for training
As the saying goes: garbage in, garbage out. Thus, it is critical to train RCA models on representative input data. In addition to relying on logs from real-life Spark application failures observed on customer sites, we have also invested in a lab framework where root causes can be artificially injected to collect even larger and more diverse training data.
Structured versus unstructured data
Logs are mostly unstructured data. To keep the accuracy of model predictions to a high level in automated RCA, it is important to combine this unstructured data with some structured data. Thus, whenever we collect logs, we are careful to collect trustworthy structured data in the form of key-value pairs that we additionally use as input features in the predictive models. These include Spark platform information and environment details of Scala, Hadoop, OS, and so on.
Labels
ML techniques for prediction fall into two broad categories: supervised learning and unsupervised learning. We use both techniques in our overall solution. For the supervised learning part, we attach root-cause labels with the logs collected from an application failure. This label comes from a taxonomy of root causes that we have created based on millions of Spark application failures seen in the field and in our lab. Broadly speaking, the taxonomy can be thought of as a tree data structure that categorizes the full space of root causes. For example, the first non-root level of this tree can be failures caused by:
Configuration errors
Deployment errors
Resource errors
Data errors
Application errors
Unknown factors
The leaves of this taxonomy tree form the labels used in the supervised learning techniques. In addition to a text label representing the root cause, each leaf also stores additional information such as: (a) a description template to present the root cause to a Spark user in a way that she will easily understand (like the message in Figure 1), and (b) recommended fixes for this root cause. We will cover the root-cause taxonomy in a future blog.
The labels are associated with the logs in one of two ways. First, the root cause is already known when the logs are generated, as a result of injecting a specific root cause we have designed to produce an application failure in our lab framework. The second way in which a label is given to the logs for an application failure is when a Spark domain expert manually diagnoses the root cause of the failure.
Input Features
Once the logs are available, there are various ways in which the feature vector can be extracted from these logs. One way is to transform the logs into a bit vector (e.g., 1001100001). Each bit in this vector represents whether a specific message template is present in the respective logs. A prerequisite to this approach is to extract all possible message templates from the logs. A more traditional approach for feature vectors from the domain of information retrieval is to represent the logs for a failure as a bag of words. This approach is mostly similar to the bit vector approach except for a couple of differences: (a) each bit in the vector now corresponds to a word instead of a message template, and (b) instead of 0s and 1s, it is more common to use numeric values generated using techniques like TF-IDF.
More recent advances in ML have popularized vector embeddings. In particular, we use the doc2vec technique[2]. At a high level, these vector embeddings map words (or paragraphs, or entire documents) to multidimensional vectors by evaluating the order and placement of words with respect to their neighboring words. Similar words map to nearby vectors in the feature vector space. The doc2vec technique uses a three-layer neural network to gauge the context of the document and relate similar content together.
Once the feature vectors are generated along with the label, a variety of supervised learning techniques can be applied for automatic RCA. We have evaluated both shallow as well as deep learning techniques, including random forests, support vector machines, Bayesian classifiers, and neural networks.
Conclusion
The overall results produced by our solution are very promising. We are currently enhancing the solution in some key ways. One of these is to quantify the degree of confidence in the root cause predicted by the model in a way that users will easily understand. Another key enhancement is to speed up the ability to incorporate new types of application failures. The bottleneck currently is in generating labels. We are working on active learning techniques[3] that nicely prioritize the human efforts required in generating labels. The intuition behind active learning is to pick the unlabeled failure instances that provide the most useful information to build an accurate model. The expert labels these instances and then the predictive model is rebuilt.
Manual failure diagnosis in Spark is not only time consuming, but highly challenging due to correlated failures that can occur simultaneously. Our unique RCA solution enables the diagnosis process to function effectively even in the presence of multiple concurrent failures as well as noisy data prevalent in production environments. Through automated failure diagnosis, we remove the burden of manually troubleshooting failed applications from the hands of Spark users and developers, enabling them to focus entirely on solving business problems with Spark.
References:
[1] S. Duan, S. Babu, and K. Munagala, “Fa: A System for Automating Failure Diagnosis”, International Conference on Data Engineering, 2009. (Return)
[2] Q. Lee and T. Mikolov, “Distributed Representations of Sentences and Documents”, International Conference on Machine Learning, 2014 (Return)
[3] S. Duan and S. Babu, "Guided Problem Diagnosis through Active Learning", International Conference on Autonomic Computing, 2008 (Return)
To learn how to use analytic tools to manage your big data infrastructure, check out Shivnath Babu's session "Using Machine Learning to Simplify Kafka Operations" at the Strata Data Conference in San Jose, March 5-8, 2018—registration is now open.
Related resource:
Spark: The Definitive Guide, by Bill Chambers and Matei Zaharia
Continue reading Automated root cause analysis for Spark application failures.
http://ift.tt/2m06KlG
0 notes
Text
Automated root cause analysis for Spark application failures
Automated root cause analysis for Spark application failures
Reduce troubleshooting time from days to seconds.
Spark’s simple programming constructs and powerful execution engine have brought a diverse set of users to its platform. Many new big data applications are being built with Spark in fields like health care, genomics, financial services, self-driving technology, government, and media. Things are not so rosy, however, when a Spark application fails.
Similar to applications in other distributed systems that have a large number of independent and interacting components, a failed Spark application throws up a large set of raw logs. These logs typically contain thousands of messages, including errors and stacktraces. Hunting for the root cause of an application failure from these messy, raw, and distributed logs is hard for Spark experts—and a nightmare for the thousands of new users coming to the Spark platform. We aim to radically simplify root cause detection of any Spark application failure by automatically providing insights to Spark users like what is shown in Figure 1.
Figure 1. Insights from automatic root cause analysis improve Spark user productivity. Source: Adrian Popescu and Shivnath Babu.
Spark platform providers like Amazon, Azure, Databricks, and Google clouds as well as application performance management (APM) solution providers like Unravel have access to a large and growing data set of logs from millions of Spark application failures. This data set is a gold mine for applying state-of-the-art artificial intelligence (AI) and machine learning (ML) techniques. In this blog, we look at how to automate the process of failure diagnosis by building predictive models that continuously learn from logs of past application failures for which the respective root causes have been identified. These models can then automatically predict the root cause when an application fails[1]. Such actionable root-cause identification improves the productivity of Spark users significantly.
Clues in the logs
A number of logs are available every time a Spark application fails. A distributed Spark application consists of a driver container and one or more executor containers. The logs generated by these containers have information about the application as well as how the application interacts with the rest of the Spark platform. These logs form the key data set that Spark users scan for clues to understand why an application failed.
However, the logs are extremely verbose and messy. They contain multiple types of messages, such as informational messages from every component of Spark, error messages in many different formats, stacktraces from code running on the Java Virtual Machine (JVM), and more. The complexity of Spark usage and internals make things worse. Types of failures and error messages differ across Spark SQL, Spark Streaming, iterative machine learning and graph applications, and interactive applications from Spark shell and notebooks (e.g., Jupyter, Zeppelin). Furthermore, failures in distributed systems routinely propagate from one component to another. Such propagation can cause a flood of error messages in the log and obscure the root cause.
Figure 2 shows our overall solution to deal with these problems and to automate root cause analysis (RCA) for Spark application failures. Overall, the solution consists of:
Continuously collecting logs from a variety of Spark application failures
Converting logs into feature vectors
Learning a predictive model for RCA from these feature vectors
Of course, as with any intelligent solution that uses AI and ML techniques, the devil is the details!
Figure 2. Root cause analysis of Spark application failures. Source: Adrian Popescu and Shivnath Babu. Data collection for training
As the saying goes: garbage in, garbage out. Thus, it is critical to train RCA models on representative input data. In addition to relying on logs from real-life Spark application failures observed on customer sites, we have also invested in a lab framework where root causes can be artificially injected to collect even larger and more diverse training data.
Structured versus unstructured data
Logs are mostly unstructured data. To keep the accuracy of model predictions to a high level in automated RCA, it is important to combine this unstructured data with some structured data. Thus, whenever we collect logs, we are careful to collect trustworthy structured data in the form of key-value pairs that we additionally use as input features in the predictive models. These include Spark platform information and environment details of Scala, Hadoop, OS, and so on.
Labels
ML techniques for prediction fall into two broad categories: supervised learning and unsupervised learning. We use both techniques in our overall solution. For the supervised learning part, we attach root-cause labels with the logs collected from an application failure. This label comes from a taxonomy of root causes that we have created based on millions of Spark application failures seen in the field and in our lab. Broadly speaking, the taxonomy can be thought of as a tree data structure that categorizes the full space of root causes. For example, the first non-root level of this tree can be failures caused by:
Configuration errors
Deployment errors
Resource errors
Data errors
Application errors
Unknown factors
The leaves of this taxonomy tree form the labels used in the supervised learning techniques. In addition to a text label representing the root cause, each leaf also stores additional information such as: (a) a description template to present the root cause to a Spark user in a way that she will easily understand (like the message in Figure 1), and (b) recommended fixes for this root cause. We will cover the root-cause taxonomy in a future blog.
The labels are associated with the logs in one of two ways. First, the root cause is already known when the logs are generated, as a result of injecting a specific root cause we have designed to produce an application failure in our lab framework. The second way in which a label is given to the logs for an application failure is when a Spark domain expert manually diagnoses the root cause of the failure.
Input Features
Once the logs are available, there are various ways in which the feature vector can be extracted from these logs. One way is to transform the logs into a bit vector (e.g., 1001100001). Each bit in this vector represents whether a specific message template is present in the respective logs. A prerequisite to this approach is to extract all possible message templates from the logs. A more traditional approach for feature vectors from the domain of information retrieval is to represent the logs for a failure as a bag of words. This approach is mostly similar to the bit vector approach except for a couple of differences: (a) each bit in the vector now corresponds to a word instead of a message template, and (b) instead of 0s and 1s, it is more common to use numeric values generated using techniques like TF-IDF.
More recent advances in ML have popularized vector embeddings. In particular, we use the doc2vec technique[2]. At a high level, these vector embeddings map words (or paragraphs, or entire documents) to multidimensional vectors by evaluating the order and placement of words with respect to their neighboring words. Similar words map to nearby vectors in the feature vector space. The doc2vec technique uses a three-layer neural network to gauge the context of the document and relate similar content together.
Once the feature vectors are generated along with the label, a variety of supervised learning techniques can be applied for automatic RCA. We have evaluated both shallow as well as deep learning techniques, including random forests, support vector machines, Bayesian classifiers, and neural networks.
Conclusion
The overall results produced by our solution are very promising. We are currently enhancing the solution in some key ways. One of these is to quantify the degree of confidence in the root cause predicted by the model in a way that users will easily understand. Another key enhancement is to speed up the ability to incorporate new types of application failures. The bottleneck currently is in generating labels. We are working on active learning techniques[3] that nicely prioritize the human efforts required in generating labels. The intuition behind active learning is to pick the unlabeled failure instances that provide the most useful information to build an accurate model. The expert labels these instances and then the predictive model is rebuilt.
Manual failure diagnosis in Spark is not only time consuming, but highly challenging due to correlated failures that can occur simultaneously. Our unique RCA solution enables the diagnosis process to function effectively even in the presence of multiple concurrent failures as well as noisy data prevalent in production environments. Through automated failure diagnosis, we remove the burden of manually troubleshooting failed applications from the hands of Spark users and developers, enabling them to focus entirely on solving business problems with Spark.
References:
[1] S. Duan, S. Babu, and K. Munagala, “Fa: A System for Automating Failure Diagnosis”, International Conference on Data Engineering, 2009. (Return)
[2] Q. Lee and T. Mikolov, “Distributed Representations of Sentences and Documents”, International Conference on Machine Learning, 2014 (Return)
[3] S. Duan and S. Babu, "Guided Problem Diagnosis through Active Learning", International Conference on Autonomic Computing, 2008 (Return)
To learn how to use analytic tools to manage your big data infrastructure, check out Shivnath Babu's session "Using Machine Learning to Simplify Kafka Operations" at the Strata Data Conference in San Jose, March 5-8, 2018—registration is now open.
Related resource:
Spark: The Definitive Guide, by Bill Chambers and Matei Zaharia
Continue reading Automated root cause analysis for Spark application failures.
http://ift.tt/2m06KlG
0 notes