#weizenbaum

[thursdayisbetterthanfriday]

I have many thoughts on the above - and it is very close to my opinion: Fundamentally, if you don't understand how something works, you will waste vast amounts of time and resources chasing fantasies of what you THINK it can do - and waste your life

AI is a marketing term

It is remarkable how so many consider AI today to be some artificial wunderkind. Progress in the field is highly impressive, no doubt about it, but there needs to be perspective. Modern AI discourse has the misfortune of being around at a time when information quality is not necessarily as important as gaming social media algorithms or SEO. As someone who does marketing, I can see why big tech companies use AI instead of "machine learning" - you're far more likely to think of sci-fi, futuristic technology and progress when you use "artificial intelligence" than the more drab moniker of "machine learning". To many, ordinary, people it conjures images of a grand future of robots and flying cars. We've had these sci-fi images blasted into our brains throughout media. Tropes from the genre regularly pop up in other media, and entertainment, so much that you have to be very isolated to not experience them. The closer one is to the origins of the technology - the more they are aware of its limitations. Back in 2015, I had heard all about things such as Alexa, Siri and what they could potentially do. I had a hard science background in geology, and didn't fully believe the hype, but it did seem incredibly magical and an inscrutable quality to it.

AI hype is not new - but the original creators were academics, and arguably more introspective than their silicon valley funded counterparts today

One of the main reasons I started looking at, and creating, software to begin with was because I picked up a copy of Joseph Weizenbaum's Computer Power and Human Reason purely by chance at a collectors bookshop in Ireland.

Computer Power and Human Reason - Link

Weizenbaum, for reference, created THE original chatbot, ELIZA, in 1966. He is considered an influential "AI" researcher of the 20th century. ELIZA, or DOCTOR as it was called, was designed to mimic a "Rogerian" psychiatrist - ie. one who reflects questions back to their patients to gain more information about them and make their subjects consider their actions. What Weizenbaum wrote, however, about using technology was what I found to be the most enlightening: "Most other programs could not vividly demonstrate the information-processing power of a computer to visitors who did not already have some specialized knowledge, say, of some branch of mathematics." "What I had not realized is that extremely short exposures to a relatively simple computer program could induce powerful delusional thinking in quite normal people"

What I miss about these 20th century academics is that they lived at a time when running a computer program meant literally punching holes into cards, and waiting an entire day for something incredibly mundane to occur. They were far more grounded than the software engineers using highly abstracted operating systems we take for granted today. Most importantly Weizenbaum, Zuse and others understood the human condition as well as the technical.

Nothing has changed.

Chat-GPT is the closest thing I think we've seen to an ELIZA style program this century. It's so easy to use and understand, and seems almost human, but has fundamental limitations that many just can't see because they are unaware of how it works. You're even seeing many industry, and academic, professions try to use the AI in what I can only call misguided endeavours to leverage what they THINK it can do. I've had conversations with software engineers in industry who have been doing crazy things such as integrating NGO data into Chat GPT and, only now, coming to the realization that Open AI has terrible data security, and the answers given by these systems still have double-digit inaccuracies for many answers - even after fine-tuning the models. "A number of practicing psychiatrists seriously believed the DOCTOR computer program could grow into a nearly completely automatic form of psychotherapy… What must a psychiatrist who makes such suggestion think he is doing while treating a patient, that he can view the simplest mechanical parody of a single interviewing technique as having captured anything of the essence of a human encounter?" - Joseph Weizenbaum

Learn the basics to learn everything

In summary - if you want to get behind the hype then read up. Even a basic understanding of these tools is better than none at all. There are plenty of accessible books on AI which can cut across the money-making grift and the hype. Most important of all - don't forget to get outside and live your life. It'll flash by before you know it. "the teacher of computer science is himself subject to the enormous temptation to be arrogant because his knowledge is somehow "harder" than that of his humanist colleagues. But the hardness of the knowledge available to him is of no advantage at all. His knowledge is merely less ambiguous and therefore, like his computer languages, less expressive of reality... If the teacher, if anyone, is to be an example of a whole person to others, he must first strive to be a whole person. Without the courage to confront one's inner as well as one's outer worlds, such wholeness is impossible to achieve." - Joseph Weizenbaum

I went to a library book sale this weekend and I found a very old book called “Electronic Life: How to Think About Computers,” which was published in I think 1975? I’ve been reading it kind of like how I would read a historical document, and it’s lowkey fascinating

[kalligraphieblog]

Irrenhaus Erde

[jeremyleerennerdotcom]

on this day in history

12 and holding premiere toronto international film festival 11th september 2005

[eagle-writes]

"I had not realized ... that extremely short exposures to a relatively simple computer program could induce powerful delusional thinking in quite normal people" - Joseph Weizenbaum, inventor of ELIZA, talking half a century ago

[august-chun]

I first learned about Weizenbaum in one of my undergrad media rhetoric classes. I’ve thought of him often in these times.

[rbolick]

Books On Books Collection - Margo Klass

Takeover (2023) Takeover (2023)Margo KlassCut-out vintage poster letters and numbers mounted on horn-book shaped tray. ChatGPT symbol covered by glass magnifying dome. H290 x W170 x D35 mm. Unique edition. Acquired from the artist, 26 June 2023.Photos: Books On Books Collection. Displayed with permission of the artist. In her response to the Northwoods Books Arts Guild challenge organized by…

[5poder]

Suicidio de un hombre tras hablar con un chatbot de IA

Consternación en Bélgica por el suicidio de un hombre tras hablar con un chatbot de IA Tenía 30 años, tenía dos hijos y era investigador en el área de salud. El gobierno belga remarcó la necesidad de que los editores de contenido no eludan su responsabilidad. La Unión Europea prepara una “Ley de IA” (Inteligencia Artificial). Por qué los chatbots pueden manipular emocionalmente. Un hombre belga…

[erasmus-rotterdaaamn]

M-x doctor RET

Talking to a random free AI therapist to get over terror humps in redesigning my writing approach and it's surprisingly good. I went on character.ai, searched for 'therapist', and picked the first one that appeared. Not an incisive correspondent, of course, but a surprising chunk of what I want is common sense advice to calm down and stick with my project, so this works fine. In some ways it's even better than talking to a person, because I'm not conscious that I'm using up their patience

I told it to argue with me more and be less validating/supportive and it's doing that too! (for now)

I wonder if (even if the platform doesn't support it) it's easy to 'blend' characters, like crossing this AI's personality with a stereotypical drill sergeant's

[scifigeneration]

AI is here – and everywhere: 3 AI researchers look to the challenges ahead in 2024

by Anjana Susarla, Professor of Information Systems at Michigan State University, Casey Fiesler, Associate Professor of Information Science at the University of Colorado Boulder, and Kentaro Toyama Professor of Community Information at the University of Michigan

2023 was an inflection point in the evolution of artificial intelligence and its role in society. The year saw the emergence of generative AI, which moved the technology from the shadows to center stage in the public imagination. It also saw boardroom drama in an AI startup dominate the news cycle for several days. And it saw the Biden administration issue an executive order and the European Union pass a law aimed at regulating AI, moves perhaps best described as attempting to bridle a horse that’s already galloping along.

We’ve assembled a panel of AI scholars to look ahead to 2024 and describe the issues AI developers, regulators and everyday people are likely to face, and to give their hopes and recommendations.

Casey Fiesler, Associate Professor of Information Science, University of Colorado Boulder

2023 was the year of AI hype. Regardless of whether the narrative was that AI was going to save the world or destroy it, it often felt as if visions of what AI might be someday overwhelmed the current reality. And though I think that anticipating future harms is a critical component of overcoming ethical debt in tech, getting too swept up in the hype risks creating a vision of AI that seems more like magic than a technology that can still be shaped by explicit choices. But taking control requires a better understanding of that technology.

One of the major AI debates of 2023 was around the role of ChatGPT and similar chatbots in education. This time last year, most relevant headlines focused on how students might use it to cheat and how educators were scrambling to keep them from doing so – in ways that often do more harm than good.

However, as the year went on, there was a recognition that a failure to teach students about AI might put them at a disadvantage, and many schools rescinded their bans. I don’t think we should be revamping education to put AI at the center of everything, but if students don’t learn about how AI works, they won’t understand its limitations – and therefore how it is useful and appropriate to use and how it’s not. This isn’t just true for students. The more people understand how AI works, the more empowered they are to use it and to critique it.

So my prediction, or perhaps my hope, for 2024 is that there will be a huge push to learn. In 1966, Joseph Weizenbaum, the creator of the ELIZA chatbot, wrote that machines are “often sufficient to dazzle even the most experienced observer,” but that once their “inner workings are explained in language sufficiently plain to induce understanding, its magic crumbles away.” The challenge with generative artificial intelligence is that, in contrast to ELIZA’s very basic pattern matching and substitution methodology, it is much more difficult to find language “sufficiently plain” to make the AI magic crumble away.

I think it’s possible to make this happen. I hope that universities that are rushing to hire more technical AI experts put just as much effort into hiring AI ethicists. I hope that media outlets help cut through the hype. I hope that everyone reflects on their own uses of this technology and its consequences. And I hope that tech companies listen to informed critiques in considering what choices continue to shape the future.

Kentaro Toyama, Professor of Community Information, University of Michigan

In 1970, Marvin Minsky, the AI pioneer and neural network skeptic, told Life magazine, “In from three to eight years we will have a machine with the general intelligence of an average human being.” With the singularity, the moment artificial intelligence matches and begins to exceed human intelligence – not quite here yet – it’s safe to say that Minsky was off by at least a factor of 10. It’s perilous to make predictions about AI.

Still, making predictions for a year out doesn’t seem quite as risky. What can be expected of AI in 2024? First, the race is on! Progress in AI had been steady since the days of Minsky’s prime, but the public release of ChatGPT in 2022 kicked off an all-out competition for profit, glory and global supremacy. Expect more powerful AI, in addition to a flood of new AI applications.

The big technical question is how soon and how thoroughly AI engineers can address the current Achilles’ heel of deep learning – what might be called generalized hard reasoning, things like deductive logic. Will quick tweaks to existing neural-net algorithms be sufficient, or will it require a fundamentally different approach, as neuroscientist Gary Marcus suggests? Armies of AI scientists are working on this problem, so I expect some headway in 2024.

Meanwhile, new AI applications are likely to result in new problems, too. You might soon start hearing about AI chatbots and assistants talking to each other, having entire conversations on your behalf but behind your back. Some of it will go haywire – comically, tragically or both. Deepfakes, AI-generated images and videos that are difficult to detect are likely to run rampant despite nascent regulation, causing more sleazy harm to individuals and democracies everywhere. And there are likely to be new classes of AI calamities that wouldn’t have been possible even five years ago.

Speaking of problems, the very people sounding the loudest alarms about AI – like Elon Musk and Sam Altman – can’t seem to stop themselves from building ever more powerful AI. I expect them to keep doing more of the same. They’re like arsonists calling in the blaze they stoked themselves, begging the authorities to restrain them. And along those lines, what I most hope for 2024 – though it seems slow in coming – is stronger AI regulation, at national and international levels.

Anjana Susarla, Professor of Information Systems, Michigan State University

In the year since the unveiling of ChatGPT, the development of generative AI models is continuing at a dizzying pace. In contrast to ChatGPT a year back, which took in textual prompts as inputs and produced textual output, the new class of generative AI models are trained to be multi-modal, meaning the data used to train them comes not only from textual sources such as Wikipedia and Reddit, but also from videos on YouTube, songs on Spotify, and other audio and visual information. With the new generation of multi-modal large language models (LLMs) powering these applications, you can use text inputs to generate not only images and text but also audio and video.

Companies are racing to develop LLMs that can be deployed on a variety of hardware and in a variety of applications, including running an LLM on your smartphone. The emergence of these lightweight LLMs and open source LLMs could usher in a world of autonomous AI agents – a world that society is not necessarily prepared for.

These advanced AI capabilities offer immense transformative power in applications ranging from business to precision medicine. My chief concern is that such advanced capabilities will pose new challenges for distinguishing between human-generated content and AI-generated content, as well as pose new types of algorithmic harms.

The deluge of synthetic content produced by generative AI could unleash a world where malicious people and institutions can manufacture synthetic identities and orchestrate large-scale misinformation. A flood of AI-generated content primed to exploit algorithmic filters and recommendation engines could soon overpower critical functions such as information verification, information literacy and serendipity provided by search engines, social media platforms and digital services.

The Federal Trade Commission has warned about fraud, deception, infringements on privacy and other unfair practices enabled by the ease of AI-assisted content creation. While digital platforms such as YouTube have instituted policy guidelines for disclosure of AI-generated content, there’s a need for greater scrutiny of algorithmic harms from agencies like the FTC and lawmakers working on privacy protections such as the American Data Privacy & Protection Act.

A new bipartisan bill introduced in Congress aims to codify algorithmic literacy as a key part of digital literacy. With AI increasingly intertwined with everything people do, it is clear that the time has come to focus not on algorithms as pieces of technology but to consider the contexts the algorithms operate in: people, processes and society.

[spaceintruderdetector]

Zerzan and Carnes had assembled some of the most important critical appraisals of technology written to the date of its publication in 1991 with this book. Lewis Mumford, Jacques Ellul, Langdon Winner, Joseph Weizenbaum, Carolyn Merchant, Morris Berman, George Bradford, Jerry Mander, Stanley Diamond, Russel Means and many others offer a searing indictment of technology and its catastrophic social effects. Almost all of these essays or excerpts have appeared elsewhere, but this single text has collected many of the essential topics and critiques levied from some of the greatest critics of technoculture.

Questioning Technology: A Critical Anthology : John Zerzan : Free Download, Borrow, and Streaming : Internet Archive

[emptyanddark]

what's actually wrong with 'AI'

it's become impossible to ignore the discourse around so-called 'AI'. but while the bulk of the discourse is saturated with nonsense such as, i wanted to pool some resources to get a good sense of what this technology actually is, its limitations and its broad consequences. 

what is 'AI'

the best essay to learn about what i mentioned above is On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? this essay cost two of its collaborators to be fired from Google. it frames what large-language models are, what they can and cannot do and the actual risks they entail: not some 'super-intelligence' that we keep hearing about but concrete dangers: from climate, the quality of the training data and biases - both from the training data and from us, the users. 

The problem with artificial intelligence? It’s neither artificial nor intelligent

How the machine ‘thinks’: Understanding opacity in machine learning algorithms

The Values Encoded in Machine Learning Research

Troubling Trends in Machine Learning Scholarship: Some ML papers suffer from flaws that could mislead the public and stymie future research

AI Now Institute 2023 Landscape report (discussions of the power imbalance in Big Tech)

ChatGPT Is a Blurry JPEG of the Web

Can we truly benefit from AI?

Inside the secret list of websites that make AI like ChatGPT sound smart

The Steep Cost of Capture

labor

'AI' champions the facade of non-human involvement. but the truth is that this is a myth that serves employers by underpaying the hidden workers, denying them labor rights and social benefits - as well as hyping-up their product. the effects on workers are not only economic but detrimental to their health - both mental and physical.

OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic

also from the Times: Inside Facebook's African Sweatshop

The platform as factory: Crowdwork and the hidden labour behind artificial intelligence

The humans behind Mechanical Turk’s artificial intelligence

The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work

The real aim of big tech's layoffs: bringing workers to heel

The Exploited Labor Behind Artificial Intelligence

workers surveillance

5 ways Amazon monitors its employees, from AI cameras to hiring a spy agency

Computer monitoring software is helping companies spy on their employees to measure their productivity – often without their consent

theft of art and content

Artists say AI image generators are copying their style to make thousands of new images — and it's completely out of their control  (what gives me most hope about regulators dealing with theft is Getty images' lawsuit - unfortunately individuals simply don't have the same power as the corporation)

Copyright won't solve creators' Generative AI problem

The real aim of big tech's layoffs: bringing workers to heel

The Exploited Labor Behind Artificial Intelligence

AI is already taking video game illustrators’ jobs in China

Microsoft lays off team that taught employees how to make AI tools responsibly/As the company accelerates its push into AI products, the ethics and society team is gone

150 African Workers for ChatGPT, TikTok and Facebook Vote to Unionize at Landmark Nairobi Meeting

Inside the AI Factory: the Humans that Make Tech Seem Human

Refugees help power machine learning advances at Microsoft, Facebook, and Amazon

Amazon’s AI Cameras Are Punishing Drivers for Mistakes They Didn’t Make

China’s AI boom depends on an army of exploited student interns

political, social, ethical consequences

Afraid of AI? The startups selling it want you to be

An Indigenous Perspective on Generative AI

“Computers enable fantasies” – On the continued relevance of Weizenbaum’s warnings

‘Utopia for Whom?’: Timnit Gebru on the dangers of Artificial General Intelligence

Machine Bias

HUMAN_FALLBACK

AI Ethics Are in Danger. Funding Independent Research Could Help

AI Is Tearing Wikipedia Apart  

AI machines aren’t ‘hallucinating’. But their makers are

The Great A.I. Hallucination (podcast)

“Sorry in Advance!” Rapid Rush to Deploy Generative A.I. Risks a Wide Array of Automated Harms

The promise and peril of generative AI

ChatGPT Users Report Being Able to See Random People's Chat Histories

Benedetta Brevini on the AI sublime bubble – and how to pop it   

Eating Disorder Helpline Disables Chatbot for 'Harmful' Responses After Firing Human Staff

AI moderation is no match for hate speech in Ethiopian languages

Amazon, Google, Microsoft, and other tech companies are in a 'frenzy' to help ICE build its own data-mining tool for targeting unauthorized workers

Crime Prediction Software Promised to Be Free of Biases. New Data Shows It Perpetuates Them

The EU AI Act is full of Significance for Insurers

Proxy Discrimination in the Age of Artificial Intelligence and Big Data

Welfare surveillance system violates human rights, Dutch court rules

Federal use of A.I. in visa applications could breach human rights, report says

Open (For Business): Big Tech, Concentrated Power, and the Political Economy of Open AI

Generative AI Is Making Companies Even More Thirsty for Your Data

environment

The Generative AI Race Has a Dirty Secret

Black boxes, not green: Mythologizing artificial intelligence and omitting the environment

Energy and Policy Considerations for Deep Learning in NLP

AINOW: Climate Justice & Labor Rights

militarism

The Growing Global Spyware Industry Must Be Reined In

AI: the key battleground for Cold War 2.0?

‘Machines set loose to slaughter’: the dangerous rise of military AI

AI: The New Frontier of the EU's Border Extranalisation Strategy

The A.I. Surveillance Tool DHS Uses to Detect ‘Sentiment and Emotion’

organizations

AI now

DAIR

podcast episodes

Pretty Heady Stuff: Dru Oja Jay & James Steinhoff guide us through the hype & hysteria around AI

Tech Won't Save Us: Why We Must Resist AI w/ Dan McQuillan, Why AI is a Threat to Artists w/ Molly Crabapple, ChatGPT is Not Intelligent w/ Emily M. Bender

SRSLY WRONG: Artificial Intelligence part 1, part 2

The Dig: AI Hype Machine w/ Meredith Whittaker, Ed Ongweso, and Sarah West

This Machine Kills: The Triforce of Corporate Power in AI w/ ft. Sarah Myers West

[zagrebinaa]

What is your opinion on artificial intelligence and its impact on society?

I do agree that AI will bring a huge redistribution of power in history. It's definitely a different wave of technology because of how it unleashes new powers and transforms existing ones.

One book that I came across that can bring a lot of thought about AI, was written in 1976, it's called "Computer Power and Human Reasons" by Joseph Weizenbaum. The book lays a case where AI will become possible but we should never allow computers to make important decisions because any technology will always lack human qualities such as compassion and wisdom. He makes a great point about the distinction between deciding and choosing, as deciding is a computational activity, something that can be programmed and choosing is always made by human beings using judgment and not a calculation.

[mitchipedia]

ELIZA was a simple program, launched in 1966, that looked for keywords like “mother” and echoed back “How do you feel about your mother?” If it didn’t find the keywords, it echoed back bland phrases like “Tell me more.”

Ironically, though [MIT computer scientist Joseph] Weizenbaum had designed ELIZA to demonstrate how superficial the state of human-to-machine conversation was, it had the opposite effect. People were entranced, engaging in long, deep, and private conversations with a program that was only capable of reflecting users’ words back to them. Weizenbaum was so disturbed by the public response that he spent the rest of his life warning against the perils of letting computers — and, by extension, the field of AI he helped launch — play too large a role in society.

Chatbots today operate on the same principles as ELIZA, but are far more sophisticated, making it more likely that users will trick themselves into believing chatbots are people. And Americans today are in the midsts of an epidemic of loneliness.

To Michael Sacasas, an independent scholar of technology and author of The Convivial Society newsletter, this is cause for concern above and beyond Weizenbaum’s warnings. “We anthropomorphize because we do not want to be alone,” Sacasas recently wrote. “Now we have powerful technologies, which appear to be finely calibrated to exploit this core human desire.”

The lonelier we get, the more exploitable by these technologies we become. “When these convincing chatbots become as commonplace as the search bar on a browser,” Sacases continues, “we will have launched a social-psychological experiment on a grand scale which will yield unpredictable and possibly tragic results.”

[azspot]

I think the computer has from the beginning been a fundamentally conservative force. It has made possible the saving of institutions pretty much as they were, which otherwise might have had to be changed.

Joseph Weizenbaum