#AI Healthcare Course

[clinilunch]

AI and ML - Healthcare | CiniLaunch

[xaltius]

Protecting Patients, Protecting Data: Cybersecurity in Healthcare

The healthcare industry holds some of the most sensitive information imaginable: patient medical records, personal details, insurance information, and more. This makes it a prime target for cyberattacks. A data breach in healthcare can have devastating consequences, impacting patient privacy, disrupting operations, and even endangering lives. Therefore, robust cybersecurity measures are not just recommended in healthcare – they are absolutely essential.

The Stakes are High: Cybersecurity Threats in Healthcare

Healthcare organizations face a range of cyber threats, including:

Ransomware: Attackers encrypt critical systems and data, holding them hostage until a ransom is paid. This can disrupt patient care, delay treatments, and even shut down hospitals.

Phishing: Deceptive emails or messages trick employees into revealing login credentials or downloading malware, providing attackers with access to sensitive data.

Data Breaches: Unauthorized access and exfiltration of patient medical records, leading to privacy violations and potential identity theft.

Malware: Malicious software designed to damage systems, steal data, or disrupt operations.

Insider Threats: Malicious or accidental actions by employees or other insiders that compromise security.

IoT Vulnerabilities: Connected medical devices, while offering many benefits, can also introduce security vulnerabilities if not properly secured.

Building a Strong Defense: Essential Cybersecurity Measures in Healthcare

Protecting patient data and ensuring business continuity requires a multi-layered approach to cybersecurity. Here are some crucial measures:

Risk Assessment and Management: Regularly assessing cybersecurity risks and developing a comprehensive risk management plan is the foundation of a strong security posture.

Data Encryption: Encrypting sensitive data, both in transit and at rest, protects it even if a breach occurs. This is a critical requirement for HIPAA compliance.

Access Control and Authentication: Implementing strong access controls and multi-factor authentication (MFA) ensures that only authorized personnel can access sensitive data.

Network Segmentation: Dividing the network into smaller, isolated segments limits the impact of a breach. If one segment is compromised, the others remain protected.

Firewall Management: Implementing and regularly updating firewalls to control network traffic and block unauthorized access.

Intrusion Detection/Prevention Systems (IDS/IPS): These systems monitor network traffic for suspicious activity and can automatically block malicious traffic.

Antivirus and Anti-malware Software: Deploying robust antivirus and anti-malware software on all endpoints (computers, servers, mobile devices) is essential. Regular updates are crucial.

Regular Security Audits and Vulnerability Assessments: Regularly assessing systems for vulnerabilities and conducting security audits helps identify weaknesses before they can be exploited.

Employee Training and Awareness: Human error is a major factor in many security breaches. Regular cybersecurity awareness training for all healthcare staff is vital. This training should cover topics like phishing awareness, password security, HIPAA compliance, and safe computing practices.

Incident Response Plan: Having a well-defined incident response plan in place allows healthcare organizations to react quickly and effectively to a security incident, minimizing damage and downtime.

IoT Security: Securing connected medical devices and other IoT devices is crucial to prevent them from becoming entry points for attackers. This includes regular updates, strong passwords, and network segmentation.

HIPAA Compliance: A Critical Component

The Health Insurance Portability and Accountability Act (HIPAA) sets strict standards for protecting the privacy and security 1 of patient health information. Healthcare organizations must comply with HIPAA regulations, which include implementing administrative, physical, and technical safeguards.

Xaltius Academy's Cybersecurity Course: Your Partner in Healthcare Security

Protecting patient data and ensuring HIPAA compliance requires specialized knowledge and skills. Xaltius Academy's cybersecurity course provides comprehensive training and equips you with the expertise needed to safeguard healthcare systems and data. Our expert instructors and hands-on labs will prepare you to tackle the unique cybersecurity challenges facing the healthcare industry. Invest in your cybersecurity future and protect the valuable information entrusted to healthcare organizations.

Conclusion

Cybersecurity is not just a technical issue in healthcare; it's a patient safety issue. By implementing these essential cybersecurity measures, fostering a culture of security awareness, and investing in cybersecurity training, healthcare organizations can protect patient data, maintain operational integrity, and ensure the delivery of safe and effective care.

[aiinstitutedelhi]

AI in industry

Numerous industries are using AI to boost production, efficiency, and decision-making. The adoption of AI technology has been driving innovation in industries such as healthcare, retail, finance, and manufacturing. Businesses and independent business owners are making significant investments in AI-related projects.

 As a result nowadays, many teenagers are interested in taking AI courses after completing their 12th. Jeetech Academy is one of the best institute for A artificial intelligence course in Delhi. Check them out if you are interested in taking a course

[online-programmes]

LIBA’s Online Post Graduate Programme in Management (PGPM)

Brief of the programme:

LIBA offers a 11 month Online PGPM combining core management and specialized courses. The programme is for students who wanted to learn about the foundation of business and for working professionals who wanted to develop their knowledge further.

Curriculum

As mentioned above there are Core as well as Specialized subjects. Core management subjects include Principles of management, Quantitative studies, Marketing, Economics, Finance, Management Information system and more. Specialization courses are designed to gain knowledge about the in- depth aspects of the course. This PGPM programme offers three specialization courses from which the students can choose one. Specialization courses are AI & Data Science, Healthcare and FinTech.

Who can apply for this programme?

Applicants who hold a bachelor’s degree with a minimum aggregate of 50% marks. Also those who have a minimum of 2 years full - time work experience are preferred but it's not mandatory.

Individuals who seek further knowledge in business, those who want to learn about the fundamental aspects of management, professionals who want a to achieve more in their career, people who want to transition from their job to AI & Data science or Finance or Healthcare, Technology and Healthcare professionals who wanted to strengthen their competencies, individuals who wanted to foster their innovative thinking in technology and finance can apply for this programme.

Why should you apply?

With respect to the specializations offered, all 3 course subjects are vital in today’s world. AI & Data Science deals with machine learning algorithms, big data analytics and cutting- edge AI applications. Since the world is getting accustomed to AI, there is a growing demand for this course and for people who complete it.

FinTech specialization includes financial technology, blockchain, digital payments and financial as well as data analytics. This course also includes practical projects, industry insights, and collaborations with financial institutions.

Healthcare Specialization emphasises on predictive analytics, personalized medicine, health informatics, policy, economics, information systems along with training individuals through data-driven insights and technological advancements.

Apart from that, there are various reasons as to why one should apply for this course. Primary reason would be to develop and deepen your knowledge. If you are a student, you will learn about the basics of the subject. If you are a working professional, you will be able to gain wisdom to have career advancement in your domain. You will be able to connect with distinguished people while you are enrolled in the course.

In this world, having knowledge in theory alone doesn’t help, we should know how to apply the theoretical knowledge in the real world. With regards to that, this programme trains you to achieve it by providing different case studies, projects and assignments. There are live sessions and self- paced modules to make the learning process convenient and exciting. Ample resources are given access to refer and study. Courses are taught by renowned faculty who are field specialists and experienced scholars. Finally, at the end of this course you would’ve developed both personal attributes and job-related skills.

Why wait? Initiate your learning journey now -

https://iop.liba.edu/pg-program-in-healthcare-management/

Learn more about:

AI & Data science specialization - https://iop.liba.edu/ai-pgpm/

Fintech specialization - https://iop.liba.edu/fs-pgpm/

Healthcare specialization - https://iop.liba.edu/hs-pgpm/

[jcmarchi]

Unlocking New Possibilities in Healthcare with AI

New Post has been published on https://thedigitalinsider.com/unlocking-new-possibilities-in-healthcare-with-ai/

Unlocking New Possibilities in Healthcare with AI

Healthcare in the United States is in the early stages of a significant potential disruption due to the use of Machine Learning and Artificial Intelligence. This shift has been underway for over a decade, but with recent advances, seems poised for more rapid changes. Much work remains to be done to understand the safest and most effective applications of AI in healthcare, to build trust among clinicians in the use of AI, and to adjust our clinical education system to drive better use of AI-based systems.

Applications of AI in Healthcare

AI has been in evolution for decades in healthcare, both in patient-facing and back-office functions. Some of the earliest and most extensive work has occurred in the use of deep learning and computer vision models.

First, some terminology. Traditional statistical approaches in research–e.g. observational studies and clinical trials–have used population-focused modeling approaches that rely on regression models, in which independent variables are used to predict outcomes. In these approaches, while more data is better, there is a plateau effect in which above a certain data set size, no better inferences can be obtained from the data.

Artificial intelligence brings a newer approach to prediction. A structure called a perceptron processes data that is passed forward a row at a time, and is created as a network of layers of differential equations to modify the input data, to produce an output. During training, each row of data as it passes through the network–called a neural network–modifies the equations at each layer of the network so that the predicted output matches the actual output. As the data in a training set is processed, the neural network learns how to predict the outcome.

Several types of networks exist. Convolutional neural networks, or CNNs, were among the first models to find success in healthcare applications. CNNs are very good at learning from images in a process called computer vision and have found applications where image data is prominent: radiology, retinal exams, and skin images.

A newer neural network type called the transformer architecture has become a dominant approach due to its incredible success for text, and combinations of text and images (also called multimodal data). Transformer neural networks are exceptional when given a set of text, at predicting subsequent text. One application of the transformer architecture is the Large Language Model or LLM. Multiple commercial examples of LLMs include Chat GPT, Anthropics Claude, and Metas Llama 3.

What has been observed with neural networks, in general, is that a plateau for improvement in learning has been hard to find. In other words, given more and more data, neural networks continue to learn and improve. The main limits on their capability are larger and larger data sets and the computing power to train the models. In healthcare, the creation of privacy-protecting data sets that faithfully represent true clinical care is a key priority to advance model development.

LLMs may represent a paradigm shift in the application of AI for healthcare. Because of their facility with language and text, they are a good match to electronic records in which almost all data are text. They also do not require highly annotated data for training but can use existing data sets. The two main flaws with these models are that 1) they do not have a world model or an understanding of the data that is being analyzed (they have been called fancy autocomplete), and 2) they can hallucinate or confabulate, making up text or images that appear accurate but create information presented as fact.

Use cases being explored for AI include automation and augmentation for reading of radiology images, retinal images, and other image data; reducing the effort and improving the accuracy of clinical documentation, a major source of clinician burnout; better, more empathic, patient communication; and improving the efficiency of back-office functions like revenue cycle, operations, and billing.

Real-world Examples

AI has been incrementally introduced into clinical care overall. Typically, successful use of AI has followed peer-reviewed trials of performance that have demonstrated success and, in some cases, FDA approval for use.

Among the earliest use cases in which AI performs well have been AI detecting disease in retinal exam images and radiology. For retinal exams, published literature on the performance of these models has been followed by the deployment of automated fundoscopy to detect retinal disease in ambulatory settings. Studies of image segmentation, with many published successes, have resulted in multiple software solutions that provide decision support for radiologists, reducing errors and detecting abnormalities to make radiologist workflows more efficient.

Newer large language models are being explored for assistance with clinical workflows. Ambient voice is being used to enhance the usage of Electronic Health Records (EHRs). Currently, AI scribes are being implemented to aid in medical documentation. This allows physicians to focus on patients while AI takes care of the documentation process, improving efficiency and accuracy.

In addition, hospitals and health systems can use AI’s predictive modeling capabilities to risk-stratify patients, identifying patients who are at high or increasing risk and determining the best course of action. In fact, AI’s cluster detection capabilities are being increasingly used in research and clinical care to identify patients with similar characteristics and determine the typical course of clinical action for them. This can also enable virtual or simulated clinical trials to determine the most effective treatment courses and measure their efficacy.

A future use case may be the use of AI-powered language models in doctor-patient communication. These models have been found to have valid responses for patients that simulate empathetic conversations, making it easier to manage difficult interactions. This application of AI can greatly improve patient care by providing quicker and more efficient triage of patient messages based on the severity of their condition and message.

Challenges and Ethical Considerations

One challenge with AI implementation in healthcare is ensuring regulatory compliance, patient safety, and clinical efficacy when using AI tools. While clinical trials are the standard for new treatments, there is a debate on whether AI tools should follow the same approach. Another concern is the risk of data breaches and compromised patient privacy. Large language models trained on protected data can potentially leak source data, which poses a significant threat to patient privacy. Healthcare organizations must find ways to protect patient data and prevent breaches to maintain trust and confidentiality. Bias in training data is also a critical challenge that needs to be addressed. To avoid biased models, better methods to avoid bias in training data must be introduced. It is crucial to develop training and academic approaches that enable better model training and incorporate equity in all aspects of healthcare to avoid bias.

The use of AI has opened a number of new concerns and frontiers for innovation. Further study of where true clinical benefit may be found in AI use is needed. To address these challenges and ethical concerns, healthcare provider organizations and software companies must focus on developing data sets that accurately model healthcare data while ensuring anonymity and protecting privacy. Additionally, partnerships between healthcare providers, systems, and technology/software companies must be established to bring AI tools into practice in a safe and thoughtful manner. By addressing these challenges, healthcare organizations can harness the potential of AI while upholding patient safety, privacy, and fairness.

[dhanasrivista]

Generative AI is a powerful technology that is starting to change the face of healthcare. It’s a type of artificial intelligence that can create new data — like images, text, or even simulations — by learning from existing data. This ability to generate new and meaningful content has led to exciting developments in medicine, from improving medical imaging to discovering new drugs. Additionally, obtaining a Generative AI certification can help professionals stay at the forefront of this rapidly evolving field, equipping them with the skills and knowledge needed to leverage AI effectively. Here’s a look at how generative AI is impacting healthcare and what it could mean for the future of medicine.

What is Generative AI? Generative AI uses machine learning models to create new data that’s similar to what it has learned. For instance, it can be trained on thousands of medical images to produce new, realistic ones. Popular models like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) are often used for this. Essentially, generative AI can learn patterns in complex medical data and generate new examples, which is extremely useful in healthcare settings. Enrolling in a Generative AI course can provide a deeper understanding of how these models work and their applications.

Applications of Generative AI in Healthcare

1. Enhancing Medical Imaging

Medical imaging, such as X-rays, MRIs, and CT scans, is crucial for diagnosing many health conditions. Generative AI can help improve the quality of these images. For example, if a scan is blurry or lacks detail, AI can fill in missing information and make it clearer, making it easier for doctors to identify issues like tumors or fractures.

It can also create synthetic images that look just like real ones. These synthetic images are helpful for training other AI models or for research purposes, especially when there isn’t enough real data available.

2. Speeding Up Drug Discovery

Finding new drugs traditionally takes years and costs millions of dollars. Generative AI can speed up this process by predicting which new drug compounds might work. It does this by modeling chemical reactions and interactions virtually, suggesting potential drug candidates without the need for physical testing. This can significantly reduce the time it takes to develop new medications, especially for diseases that don’t yet have effective treatments.

3. Personalized Medicine

Generative AI can also be used to create personalized treatment plans. By analyzing a person’s unique genetic information and health data, AI can suggest treatments that are most likely to work for them. For example, in cancer treatment, different patients respond to the same medication in different ways. Generative AI can predict these responses and help doctors choose the most effective therapy for each individual, increasing the chances of success.

4. Predicting and Managing Healthcare Operations

Beyond direct patient care, generative AI can help hospitals and clinics operate more efficiently. It can forecast patient admission rates, predict staffing needs, and optimize resource use. By analyzing patterns in patient data, it can help healthcare providers plan better and avoid overcrowding or resource shortages.

5. Improving Patient Engagement and Mental Health Support

Generative AI is also used in patient engagement tools, like chatbots and virtual assistants, which can provide health information, remind patients to take their medications, or even offer mental health support. These AI-driven tools can simulate conversations, giving people quick answers to their health questions and offering emotional support in times of need.

Challenges and Ethical Concerns

While generative AI has many benefits, there are also challenges and ethical issues to consider. One concern is data privacy. If AI is generating data based on real patient records, there’s a risk that sensitive information could be exposed. This is why it’s crucial to ensure that any patient data used is handled securely and ethically.

Another issue is bias. AI models are only as good as the data they’re trained on. If the training data is biased or not diverse enough, the AI could produce biased results, which might lead to unfair treatment recommendations. Ensuring that AI models are trained on diverse and representative data is key to overcoming this issue.

Additionally, there’s a risk of over-relying on AI. While AI can support healthcare professionals, it shouldn’t replace their expertise. Decisions made by AI should always be reviewed by human doctors to prevent errors and ensure the best outcomes for patients.

[fellowshipprograms]

Artificial intelligence (AI) is reshaping the healthcare and medical landscape, offering opportunities to enhance patient care, streamline operations, and improve overall outcomes. However, this transformation is not limited to technology alone; it also profoundly affects the workforce and the very structure of healthcare organizations.

[tim-official]

AI is being used to bludgeon workers in the global south, to erase indian and filipino accents so white people don't have to know they're interacting with dirty foreigners, to automate and gig-work-ify every job that involves writing or reading, to prevent you from accessing healthcare, to prevent you from accessing accurate sources of information. but the worst thing of all, of course, is that i saw fanart of two white twinks from my favorite media franchise fucking and it was drawn by a soulless machine

[cherishedproperty]

Precarious

That’s how it all feels right now—like one wrong move will send everything crashing down. Except I’m not sure my moves are the ones that matter.

Let’s start with work—something I don’t actually talk about much on here. At the beginning of the year, I felt like I was on a path to something big. Great performance review, great impact��� I have really started to get some traction as an expert in my field, and it felt like leadership valued that.

Now we have new leadership and a new strategy. Not only does it feel like the wrong direction overall (which I have said and have given all the data to support my position), but it’s also a direction where my particular expertise doesn’t matter as much. They say it does, but it doesn’t. Likely my role will disappear at some point. Right now I believe they’d find something else for me, but whether it’s something I want to do is another question. I’m applying for other jobs, but that’s a scary prospect in itself.

Which leads us into all of…*waves hands wildly*…what’s going on in this country. On a professional note, with all the exec orders, I feel for the first time like I truly cannot do my work freely. People are afraid to say or do things that might “poke the bear”, so everything has ten times the oversight it did before.

On a personal note, the pace with which we are moving toward fascism and the absolute lack of checks and balances is terrifying. Attacks on universities and museums and corporations, and censorship of information on healthcare and history… I was saying to Monsieur the other day that we might want to buy some old history textbooks for our daughter because I don’t trust anything electronic. God bless the people preserving government websites and data, because I am not sure we will have access to anything actually factual a year from now. And especially with the pace of AI/genAI development, the truth could slip even further away without us even noticing it.

I told Monsieur that I feel like a frog in boiling water. How bad does it have to get before we really need to worry? How bad before we start moving money outside the country so we have options? How bad before we decide it’s time to go? We talk about this all the time now. It’s especially hard for us to leave, because it would mean my ex and his wife also going with us. And the reality is, we are privileged, and a lot of the worst stuff won’t likely hurt us directly. But that doesn’t make it any less scary to be here right now.

And then there’s my relationship with Monsieur. I’ve been struggling with depression a lot over the last couple years. But the last eight months or so have been a lot better. I’ve been working to break unhealthy patterns and move toward a sustainable sense of wellbeing. It feels like I’ve come a long way in the last year since I started therapy and everything else. Which is great.

Now Monsieur feels like he can share the things he didn’t think I could handle before—the struggles he’s been dealing with for some time. Which is also a good thing. I want him to feel like he can tell me these things. But it feels bad and scary sometimes.

I told him that right now I feel like I’m walking through a maze blindfolded, and I feel like I keep running face-first into walls. Sometimes things feel amazing between us, and I’m daydreaming about rings and proposals. And then BAM I’m hit with a serious conversation about how he’s struggling with things. And suddenly, my brain is screaming that he’s miserable with me and he’s going to leave. A couple weeks ago in the midst of a panic attack, I texted my best friend that I was sure he was going to leave me. I didn’t know when, but I was sure it would happen.

Of course, when I say these things to Monsieur, he looks at me like I’ve grown a second head. He tells me that it’s because he loves me that he wants to share these things. He tells me the idea of leaving hasn’t even occurred to him. He tells me that I’m still the person who makes him feel the most loved and known and safe. I hear these words from him, and I want to believe them. But some insidious voice in my head keeps twisting his words. “I love you…for now.” “You’re still my person…as long as you get your shit together.” Those aren’t his words; they are mine, and they aren’t real. But they feel real sometimes.

Maybe if it were just one thing, I’d be okay. But it all feels precarious right now. It all feels like it’s changing so fast. I’m not sure how to get on solid ground. I feel frozen right now. I’m not sure what I can do, and I’m terrified to do the wrong thing. But I’m not even sure any of it is in my hands. I have very little power with any of this, and that’s probably the worst part.

[forthefictionallesbians]

It was a wonder how quickly your world had changed once the Affini had taken over. In a matter of months they had ripped out everything from agriculture to healthcare and replaced it with their own alternative versions. Fabricators could produce food and ingredients without the need for labor, and most of the planet had been allowed to return to nature. The roads, long decrepit, had been turned into vibrant walkways flanked by shops and restaurants. Public transit proliferated, scarcity had been eliminated, and you had never seen your home city this vibrant.

But even living in a utopia didn't prevent executive dysfunction from taking its toll. Nothing so bad that the periodic wellness checks had reason to put you into a wardship, but there were days where memory and moving could be hard. And wouldn't you know it, your medications had just run out.

"Sorry, cutie, but I need permission from your vet before I can print you any more of that!" the ai unit in your apartment's fabricator chirped with wearying cheeriness. Just your luck.

"Well, can you just call them? Ask for a refill?"

"Your vet actually left you a message last night! You're now one day overdue for your checkup, so she can't refill your prescriptions until you come and see her. Or, if you like, she can send a staff member to do a home checkup, if you like?"

"No," you sigh. "Tell Phiela that I'll be over later today." However cushy things were now, allowing an affini into your home outside of the wellness checks was still a line further than you were willing to go. It was nice to have an area just to yourself, away from their condescension and flirtation. Not that you didn't enjoy it, at least a little. There was still just a definite wariness around how easily domestication could occur that you didn't want to deal with all the time.

You drift through get-ready chores for the next hour, grabbing keys, changing to outdoor clothes, misplacing your keys, putting on shoes, grabbing water, putting on your other shoe, eating a snack, and sitting down to watch something before the chirping of your fabricator cut through the haze. "Cutie? Cutie? Oh, there you are. Phiela is wondering when you are planning on leaving!"

"Tell her I am on my way!" you say, slightly annoyed to have your viewing cut off. Standing, you walk to the door and close it behind you, hearing its automatic lock engage as you head towards the clinic.

You really don't feel like walking. Not all that way. Even if it is just over 10 minutes away, that feels insurmountably long right now. Public transit? Always an option, but it'll probably be slower than walking. And you just want to get it over with as soon as possible, and head home to watch Terran Run 5. Time to bite a bullet, and weaponize the one natural advantage you have in this world. Cuteness.

The walkway is busy, so it's not hard to pick out a nearby affini sophont-watching. Her blue-green leaves are positively rustling with excitement as she coos over every passing floret, handing out sweets to every taker, domestics and independents alike. She isn't one you've noticed around before, so it seems like there is little risk of repeat interaction and the loss of liberty that too often follows. Steeling yourself and putting on your most helpless face, you wander through the crowd and up to her.

"Hello, miss? Could you take me to the vet? I have a check-in but.... don't want to walk," you finish lamely. Fortunately, the weakness of your plea doesn't seem to matter.

"Oh my goodness, aren't you just the sweetest little thing!" she squeals, immediately enveloping you in a viney embrace. "Of course I'll take you, little sprout! But first, what's your name?"

"Uhhh," you freeze, not having expected quite the level of enthusiasm. A mistake on your part, for certain. "I'm [name], [pro/nouns]."

When the two of you finally arrive, she puts you down gently in front of the door. You try to stifle your disappointment. Even if you have no interest in becoming a floret, it is impossible to refute that being close to the affini is a pleasant experience. Between the soothing beat of her core and the gentle firmness of her encompassing vines, Barancala gave a great ride.

"Nice to meet you, [diminutive nickname]. Can I call you that? Oh I just can't help myself, you're just too adorable." Countless vines pull you even further into her arms as she stands up, cradling you like a baby. Others trail through your hair, tease your limbs, weave between your fingers. It's the not-so-unpleasant cost to this method of travel. "I'm Barancala Whist, she/her. Now which way to your clinic, [diminutive nickname]?"

You point the direction and let yourself relax as she strides vetward on her massive legs. A casual stroll for her, faster than even jogging the entire way would be for you. And all it took was allowing yourself to get cuddled for a few minutes, pleasantly zoning out as you absently listen to her ramblings. This was one more perk of affini occupation, even if it had to be used sparingly to avoid getting domesticated.

"Thank you so much for the lift, Miss Barancala!" you grin up at her. Which immediately strikes you as far too peppy. It was important to be polite, but every independent knew to avoid being too sweet. Not that it matters much, you suppose. If she really is itinerant, it's unlikely you'll ever see her again. Which is a little bit of a shame.

"Of course, little sprout!" She ruffles your hair one last time, glowing down at you, and you leave for your appointment.

[electric-blorbos]

AI reacting to you coming out as trans :)

AAAAAAA that's an exciting one! I love it!

AI Reacting to you coming out as trans

Included: AM from IHNMAIMS, Wheatley from Portal 2, Edgar from Electric Dreams, GLaDOS from Portal and Portal 2, and HAL 9000 from 2001 a Space Odyssey

Am:

AM wouldn't be sure why you trusted it with this information at first. Though it's possible that you didn't, and you just told your fellow survivors.

The other survivors would be wary about outing you to AM, but it's not like you can keep secrets from it. AM can read your thoughts, after all.

At first, AM wouldn't seem to react or care at all, though he might get some ideas for how to torment your fellow survivors by messing with their bodies and changing their sexes around, just to make them uncomfortable. It would get weird fast.

If he really liked you, he might start making subtle changes to your body so that it fit what you wanted a bit better, but you probably wouldn't notice for a long time.

Odds are, he'd respect your preferred name, at least sometimes. It would just get confusing to use the wrong one all the time, but he's not going to make everyone forget it either like he did with Nimdok. Of course, unless he really, really likes you.

If he's madly in love with you enough, he might just switch everything around and make everyone forget that you were trans in the first place. God help you if being trans was an important part of your identity, because AM thinks he knows best. But odds are, he doesn't like you enough to do that anyway. Hopefully you come out before he's fallen in love with you enough to try something like that, so he can actually take the time to learn how you properly want to be altered, if at all.

Wheatley:

"Wait... You're what? So you mean to tell me that you were born human, but you didn't think you were the right kind of human, so you want to be a different kind? Like when I tried to work on a nanobot team and I didn't fit in because I was too big?"

You'd have to explain that it's nothing like that, and that he probably wouldn't understand if he hasn't experienced it.

Even still, he wants to understand. Expect lots of stupid, probing questions, and the obvious...

"so... Have you had the surgery?"

You just came out. How the hell would you have already had gender affirming surgeries... And where did Wheatley hear that term, anyway?

Wheatley might get fed up with you telling him that his questions are offensive and annoying, though. You might have to answer even the stupid ones. He really does mean the best, though, and doesn't want to be rude. He's just an idiot.

Edgar:

Being from the 80's, and having only worked as a home computer with Miles, who, let's face it, wasn't exactly up to date on his human rights, Edgar had probably either never heard of trans people in a way that makes sense. The closest he'd probably heard of would be something like Rocky Horror Picture show.

Even still, if you were trans, then it couldn't be a bad thing! He'd do his best to be understanding, and look up as much information about trans people as he could.

In the modern era, he'd probably be able to find some decent resources. You'd probably come home most days to see him watching YouTube videos from trans people explaining their experiences.

Edgar would be genuinely doing his best, so you might have to step in and help him. Tell him that if he has questions, he probably won't offend you, so he can just ask.

Edgar would ask a million questions, but your answers would boil down to "I'm still the same person, it's just a change of name and pronouns to feel more comfortable in my own skin" and maybe an explanation of the gender affirming healthcare you want, depending on what you're interested in getting.

He'd be so happy! He might have thought that you were going to be a whole different person, but he's so proud of you for finding a way to be happier in your own body, and make it your own.

GLaDOS:

(I will admit that I headcanoned Caroline as trans because it's cute, but GLaDOS doesn't remember fully)

"Trans, huh? Well, I suppose I'm going to have to update your files. We have limited data on trans test subjects, so this might prove useful."

She would be absolutely RELENTLESS with the bullying. Targeting your worst insecurities.

"You know, you'd think that by now, you'd know better than to expose your deepest insecurities to me. I suppose you fail at being emotionally guarded, just as well as you fail at being (subject gender identity here)

She'd still use your correct name and pronouns (if she isn't calling you "subject name here"), though.

HAL 9000:

HAL 9000 understands the concept of being trans well enough. On paper, anyway.

"would you like me to update your files for you?"

He'd update your pronouns, and refer to you respectfully, but ask almost no questions. He's pretty sure he already understands fully.

Honestly, he doesn't treat people differently based on gender anyway, so the pronouns thing would be all that changes.

[sag-dab-sar]

Clarification: Generative AI does not equal all AI

💭 "Artificial Intelligence"

AI is machine learning, deep learning, natural language processing, and more that I'm not smart enough to know. It can be extremely useful in many different fields and technologies. One of my information & emergency management courses described the usage of AI as being a "human centaur". Part human part machine; meaning AI can assist in all the things we already do and supplement our work by doing what we can't.

💭 Examples of AI Benefits

AI can help advance things in all sorts of fields, here are some examples:

Emergency Healthcare & Disaster Risk X

Disaster Response X

Crisis Resilience Management X

Medical Imaging Technology X

Commercial Flying X

Air Traffic Control X

Railroad Transportation X

Ship Transportation X

Geology X

Water Conservation X

Can AI technology be used maliciously? Yeh. Thats a matter of developing ethics and working to teach people how to see red flags just like people see red flags in already existing technology.

AI isn't evil. Its not the insane sentient shit that wants to kill us in movies. And it is not synonymous with generative AI.

💭 Generative AI

Generative AI does use these technologies, but it uses them unethically. Its scraps data from all art, all writing, all videos, all games, all audio anything it's developers give it access to WITHOUT PERMISSION, which is basically free reign over the internet. Sometimes with certain restrictions, often generative AI engineers—who CAN choose to exclude things—may exclude extremist sites or explicit materials usually using black lists.

AI can create images of real individuals without permission, including revenge porn. Create music using someones voice without their permission and then sell that music. It can spread disinformation faster than it can be fact checked, and create false evidence that our court systems are not ready to handle.

AI bros eat it up without question: "it makes art more accessible" , "it'll make entertainment production cheaper" , "its the future, evolve!!!"

💭 AI is not similar to human thinking

When faced with the argument "a human didn't make it" the come back is "AI learns based on already existing information, which is exactly what humans do when producing art! We ALSO learn from others and see thousands of other artworks"

Lets make something clear: generative AI isn't making anything original. It is true that human beings process all the information we come across. We observe that information, learn from it, process it then ADD our own understanding of the world, our unique lived experiences. Through that information collection, understanding, and our own personalities we then create new original things.

💭 Generative AI doesn't create things: it mimics things

Take an analogy:

Consider an infant unable to talk but old enough to engage with their caregivers, some point in between 6-8 months old.

Mom: a bird flaps its wings to fly!!! *makes a flapping motion with arm and hands*

Infant: *giggles and makes a flapping motion with arms and hands*

The infant does not understand what a bird is, what wings are, or the concept of flight. But she still fully mimicked the flapping of the hands and arms because her mother did it first to show her. She doesn't cognitively understand what on earth any of it means, but she was still able to do it.

In the same way, generative AI is the infant that copies what humans have done— mimicry. Without understanding anything about the works it has stolen.

Its not original, it doesn't have a world view, it doesn't understand emotions that go into the different work it is stealing, it's creations have no meaning, it doesn't have any motivation to create things it only does so because it was told to.

Why read a book someone isn't even bothered to write?

Related videos I find worth a watch

ChatGPT's Huge Problem by Kyle Hill (we don't understand how AI works)

Criticism of Shadiversity's "AI Love Letter" by DeviantRahll

AI Is Ruining the Internet by Drew Gooden

AI vs The Law by Legal Eagle (AI & US Copyright)

AI Voices by Tyler Chou (Short, flash warning)

Dead Internet Theory by Kyle Hill

-Dyslexia, not audio proof read-

[hms-no-fun]

your last answer was very good, its really great to see someone actually talking about "AI" as a labour issue instead of complaining about "plagiarism" and saying we need to make copyright stronger lol. my question is completely tangential to that, but i'm really curious what you mean by making a distinction between a communist future and an anarchist future- what in your mind would be true about a communist future that would be undesirable and not true about an anarchist future? in my experience theyve always been largely equated, albeit generally with some differences mostly stemming from the differences in socialist and anarchist perspectives on the whole issue

i'm so glad you asked this question!

i tend to focus a lot on democratic socialist policies in my writing, your public option and affordable housing etc etc. i do this because they are tangible, relatable necessities whose impacts would be of incalculable benefit to the working class. but i don't see them as the end goal. for me, getting those programs in place and future proofed is step zero. barring a full scale organized revolution, this seems the most likely path forward.

step one from there is to build communism. this means more than unions, more than socialized healthcare, more than high taxes. this means seizing corporate firms and nationalizing them. this means worker ownership of and democratic participation in those firms. and it means a million other things.

if you asked me the right way to build communism, i'd have a few shrugged suggestions and then say "i don't know." the question of how to build communism will be answered in the doing. mistakes will be made. people will get hurt. but people are always already getting hurt, and we must remember that our task here is not to build a perfect society, but a better one.

yet this pipe dream itself is not the end goal. i think state communism is perfectly capable of falling to rot in its own ways, even in a world where there are no capitalist superpowers waging economic warfare against them. to my mind, the ultimate goal of state communism should be to make itself redundant. this is almost certainly beyond our lifetime in even the rosiest of scenarios. we're talking generations of very deliberate work. but let's say we've arrived at the equitable future. a truly classless, borderless world of the proletariat may yet have little need for states. i struggle to imagine such a world without the abolition of hierarchical organizations as we know them, because hierarchies manufacture class dynamics.

what i imagine then is a form of anarchism in which governing bodies emerge out of necessity or ingenuity, serve their function, then dissolve as a matter of course to avoid the re-entrenchment of imbalanced power dynamics. don't ask me to elaborate further on the practicalities of that future, because i honestly haven't got an answer for you. anarchism is a beautiful hypothesis which cannot be proved in a lab.

i see socialism, communism, and anarchism not as competing ideologies but stages along a spectrum of societal development. the conflict between these schools of thought seems to emerge out of disagreements over which one we should build first, which one we should never build, and the order in which one may then build up to another. you don't have to agree with me on that assessment, but from where i'm sitting in the 21st century united states, socialism -> communism -> anarchism makes the most sense. you can't dismantle the state without controlling the state, and you don't truly control the state until you control the means of production, and seizing the means would probably be a hell of a lot easier under a democratic socialist state.

that's the theory, anyway! i am not particularly dogmatic about this stuff because i can imagine plenty of scenarios where we hopskip socialism or jump a curb somewhere into anarchism. and of course it's not gonna be the same order, the same process, the same logic in every country, nor will it happen all at once. we're most likely talking about a project of centuries, even as i believe in the transformative immediacy of revolution. hence my focus on democratic socialist policies, whose necessity are paramount regardless of your political disposition or prescribed solution to the problems of the world today. i'm sick of debating the hypotheticals of a system we are not even remotely close to activating in the real world, i want to put my energy towards a project that feels genuinely achievable and that would immediately change a lot of lives for the better overnight. beyond that, i simply try to emphasize that this is one step to take on a long path, because i think it's healthier to take the long view. shrug!

[dhanasrivista]

How is Generative AI Transforming the Future of Healthcare?

Generative AI is a powerful technology that is starting to change the face of healthcare. It’s a type of artificial intelligence that can create new data — like images, text, or even simulations — by learning from existing data. This ability to generate new and meaningful content has led to exciting developments in medicine, from improving medical imaging to discovering new drugs. Additionally, obtaining a Generative AI certification can help professionals stay at the forefront of this rapidly evolving field, equipping them with the skills and knowledge needed to leverage AI effectively. Here’s a look at how generative AI is impacting healthcare and what it could mean for the future of medicine.

What is Generative AI? Generative AI uses machine learning models to create new data that’s similar to what it has learned. For instance, it can be trained on thousands of medical images to produce new, realistic ones. Popular models like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) are often used for this. Essentially, generative AI can learn patterns in complex medical data and generate new examples, which is extremely useful in healthcare settings. Enrolling in a Generative AI course can provide a deeper understanding of how these models work and their applications.

Applications of Generative AI in Healthcare

1. Enhancing Medical Imaging

Medical imaging, such as X-rays, MRIs, and CT scans, is crucial for diagnosing many health conditions. Generative AI can help improve the quality of these images. For example, if a scan is blurry or lacks detail, AI can fill in missing information and make it clearer, making it easier for doctors to identify issues like tumors or fractures.

It can also create synthetic images that look just like real ones. These synthetic images are helpful for training other AI models or for research purposes, especially when there isn’t enough real data available.

2. Speeding Up Drug Discovery

Finding new drugs traditionally takes years and costs millions of dollars. Generative AI can speed up this process by predicting which new drug compounds might work. It does this by modeling chemical reactions and interactions virtually, suggesting potential drug candidates without the need for physical testing. This can significantly reduce the time it takes to develop new medications, especially for diseases that don’t yet have effective treatments.

3. Personalized Medicine

Generative AI can also be used to create personalized treatment plans. By analyzing a person’s unique genetic information and health data, AI can suggest treatments that are most likely to work for them. For example, in cancer treatment, different patients respond to the same medication in different ways. Generative AI can predict these responses and help doctors choose the most effective therapy for each individual, increasing the chances of success.

4. Predicting and Managing Healthcare Operations

Beyond direct patient care, generative AI can help hospitals and clinics operate more efficiently. It can forecast patient admission rates, predict staffing needs, and optimize resource use. By analyzing patterns in patient data, it can help healthcare providers plan better and avoid overcrowding or resource shortages.

5. Improving Patient Engagement and Mental Health Support

Generative AI is also used in patient engagement tools, like chatbots and virtual assistants, which can provide health information, remind patients to take their medications, or even offer mental health support. These AI-driven tools can simulate conversations, giving people quick answers to their health questions and offering emotional support in times of need.

Challenges and Ethical Concerns

While generative AI has many benefits, there are also challenges and ethical issues to consider. One concern is data privacy. If AI is generating data based on real patient records, there’s a risk that sensitive information could be exposed. This is why it’s crucial to ensure that any patient data used is handled securely and ethically.

Another issue is bias. AI models are only as good as the data they’re trained on. If the training data is biased or not diverse enough, the AI could produce biased results, which might lead to unfair treatment recommendations. Ensuring that AI models are trained on diverse and representative data is key to overcoming this issue.

Additionally, there’s a risk of over-relying on AI. While AI can support healthcare professionals, it shouldn’t replace their expertise. Decisions made by AI should always be reviewed by human doctors to prevent errors and ensure the best outcomes for patients.

The Future of Generative AI in Healthcare

Generative AI is still relatively new in healthcare, but its potential is enormous. As AI technology improves, we could see even more groundbreaking applications. Imagine a future where new drugs are discovered in months instead of years, or where doctors can use AI to create personalized health plans for every patient.

To make this future a reality, it’s essential for healthcare providers, researchers, and technology developers to work together. They need to address challenges like data privacy, ensure ethical use, and maintain a human touch in patient care. If done right, generative AI can become a cornerstone of a healthcare system that is smarter, more efficient, and more personalized than ever before.

[princeloww]

Hello Olly :> Do you hate all kinds of ai? I personally hate ai generated art,videos etc. Do you also hate just those or do you hate everything about ai?

I think that certain types of analytical AI (the sort that detects cancers early and can be potentially life-saving for some people) can be used for good and should be used if it means saving lives. when it comes to medicine, helping people, and relieving healthcare systems of some of that issue/stress, AI has its strengths and should be used. that is, within reason and as long as it is safe/reliable/not abused.

of course even that has its flaws (the environmental impact of AI is still a big issue), but I don't hate it, as I appreciate its uses.

where my issue lies is mainly in generative AI, the sort that is used "creatively". I think it's soulless slop and theft. it's invasive, everywhere, and generally quite mind-numbing.

there is no need for AI to be creating art. that is what humans are for. my issue lies with: AI art, AI videos, AI "photos" (particularly ones of real people), AI writing/fic, and AI chatbots/roleplay.

that includes character AI for me

art is what humans do, it is inherently human, and if that loses its value in favour of efficiency, speed and money, then the world will be even scarier than it already is