In a talk from the cutting edge of technology, OpenAI cofounder Greg Brockman explores the underlying design principles of ChatGPT and demos some mind-blowing, unreleased plug-ins for the chatbot that sent shockwaves across the world. After the talk, head of TED Chris Anderson joins Brockman to dig into the timeline of ChatGPT’s development and get Brockman’s take on the risks, raised by many in the tech industry and beyond, of releasing such a powerful tool into the world.
From DSC: It was interesting to see how people are using AI these days. The article mentioned things from planning Gluten Free (GF) meals to planning gardens, workouts, and more. Faculty members, staff, students, researchers and educators in general may findElicit, ScholarcyandSciteto be useful tools. I put in a question at Elicit and it looks interesting. I like their interface, which allows me to quickly resort things. .
There Is No A.I. — from newyorker.com by Jaron Lanier There are ways of controlling the new technology—but first we have to stop mythologizing it.
Excerpts:
If the new tech isn’t true artificial intelligence, then what is it? In my view, the most accurate way to understand what we are building today is as an innovative form of social collaboration.
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The new programs mash up work done by human minds. What’s innovative is that the mashup process has become guided and constrained, so that the results are usable and often striking. This is a significant achievement and worth celebrating—but it can be thought of as illuminating previously hidden concordances between human creations, rather than as the invention of a new mind.
Over the past few months, the field of artificial intelligence has seen rapid growth, with wave after wave of new models like Dall-E and GPT-4 emerging one after another. Every week brings the promise of new and exciting models, products, and tools. It’s easy to get swept up in the waves of hype, but these shiny capabilities come at a real cost to society and the planet.
Downsides include the environmental toll of mining rare minerals, the human costs of the labor-intensive process of data annotation, and the escalating financial investment required to train AI models as they incorporate more parameters.
Let’s look at the innovations that have fueled recent generations of these models—and raised their associated costs.
Also relevant/see:
ChatGPT is Thirsty: a mini exec briefing — from BrainyActs #040 | ChatGPT’s Thirst Problem Between the growing number of data centers + the exponential growth in consumer-grade Generative AI tools, water is becoming a scarce resource.
Take a look at this simulated negotiation, with grading and feedback. Prompt: “I want to do deliberate practice about how to conduct negotiations. You will be my negotiation teacher. You will simulate a detailed scenario in which I have to engage in a negotiation. You will fill the role of one party, I will fill the role of the other. You will ask for my response to in each step of the scenario and wait until you receive it. After getting my response, you will give me details of what the other party does and says. You will grade my response and give me detailed feedback about what to do better using the science of negotiation. You will give me a harder scenario if I do well, and an easier one if I fail.”
Samples from Bing Creative mode and ChatGPT-4 (3.5, the free version, does not work as well)
I’m having a blast with ChatGPT – it’s testing ME! — from by Mark Mrohs Using ChatGPT as an agent for asynchronous active learning
I have been experimenting with possible ways to incorporate interactions with ChatGPT into instruction. And I’m blown away. I want to show you some of what I’ve come up with.
As Nvidia’s annual GTC conference gets underway, founder and CEO Jensen Huang, in his characteristic leather jacket and standing in front of a vertical green wall at Nvidia headquarters in Santa Clara, California, delivered a highly-anticipated keynote that focused almost entirely on AI. His presentation announced partnerships with Google, Microsoft and Oracle, among others, to bring new AI, simulation and collaboration capabilities to “every industry.”
Introducing Mozilla.ai: Investing in trustworthy AI — from blog.mozilla.org by Mark Surman We’re committing $30M to build Mozilla.ai: A startup — and a community — building a trustworthy, independent, and open-source AI ecosystem.
Excerpt (emphasis DSC):
We’re only three months into 2023, and it’s already clear what one of the biggest stories of the year is: AI. AI has seized the public’s attention like Netscape did in 1994, and the iPhone did in 2007.
New tools like Stable Diffusion and the just-released GPT-4 are reshaping not just how we think about the internet, but also communication and creativity and society at large. Meanwhile, relatively older AI tools like the recommendation engines that power YouTube, TikTok and other social apps are growing even more powerful — and continuing to influence billions of lives.
This new wave of AI has generated excitement, but also significant apprehension. We aren’t just wondering What’s possible? and How can people benefit? We’re also wondering What could go wrong? and How can we address it? Two decades of social media, smartphones and their consequences have made us leery.
Users have been asking for plugins since we launched ChatGPT (and many developers are experimenting with similar ideas) because they unlock a vast range of possible use cases. We’re starting with a small set of users and are planning to gradually roll out larger-scale access as we learn more (for plugin developers, ChatGPT users, and after an alpha period, API users who would like to integrate plugins into their products). We’re excited to build a community shaping the future of the human–AI interaction paradigm.
We’ve added initial support for ChatGPT plugins — a protocol for developers to build tools for ChatGPT, with safety as a core design principle. Deploying iteratively (starting with a small number of users & developers) to learn from contact with reality: https://t.co/ySek2oevodpic.twitter.com/S61MTpddOV
LLMs like ChatGPT are trained on massive troves of text, which they use to assemble responses to questions by analyzing and predicting what words could most plausibly come next based on the context of other words. One way to think of it, as Marcus has memorably described it, is “auto-complete on steroids.”
Marcus says it’s important to understand that even though the results sound human, these systems don’t “understand” the words or the concepts behind them in any meaningful way. But because the results are so convincing, that can be easy to forget.
“We’re doing a kind of anthropomorphization … where we’re attributing some kind of animacy and life and intelligence there that isn’t really,” he said.
10 gifts we unboxed at Canva Create — from canva.com Earlier this week we dropped 10 unopened gifts onto the Canva homepage of 125 million people across the globe. Today, we unwrapped them on the stage at Canva Create.
According to Model Rule 1.1 of the ABA Model Rules of Professional Conduct: “A lawyer shall provide competent representation to a client. Competent representation requires the legal knowledge, skill, thoroughness and preparation reasonably necessary for the representation.”
In 2012, the ABA House of Delegates voted to amend Comment 8 to Model Rule 1.1 to include explicit guidance on lawyers’ use of technology.
If Model Rule 1.1 isn’t enough of a motivator to dip your feet in legal tech, maybe paying off that mortgage is. As an extra bit of motivation, it may benefit you to pin the ABA House of Delegate’s call to action on your motivation board.
What is different with AI is the scale by which this knowledge is aggregated. While a lawyer who has been before a judge three or four times may have formed some opinions about them, these opinions are based on anecdotal evidence. AI can read the judge’s entire history of decision-making and spit out an argument based on what it finds.
The common law has always used precedents, but what is being used here is different — it’s figuring out how a judge likes an argument to be framed, what language they like using, and feeding it back to them.
And because the legal system builds on itself — with judges using prior cases to determine how a decision should be made in the case before them — these AI-assisted arguments from lawyers could have the effect of further entrenching a judge’s biases in the case law, as the judge’s words are repeated verbatim in more and more decisions. This is particularly true if judges are unaware of their own biases.
Given that we have spent time over the past few years telling people not to get to overestimate the capability of AI, is this the real deal?
“Yeah, I think it’s the real thing because if you look at why legal technologies have not had the adoption rate historically, language has always been the problem,” Katz said. “Language has been hard for machines historically to work with, and language is core to law. Every road leads to a document, essentially.”
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Katz says: “There are two types of things here. They would call general models GPT one through four, and then there’s domain models, so a legal specific large language model.
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“What we’re going to see are large-ish, albeit not the largest model that’s heavily domain tailored is going to beat a general model in the same way that a really smart person can’t beat a super specialist. That’s where the value creation and the next generation of legal technology is going to live.”
The FBI and the Defense Department were actively involved in research and development of facial recognition software that they hoped could be used to identify people from video footage captured by street cameras and flying drones, according to thousands of pages of internal documents that provide new details about the government’s ambitions to build out a powerful tool for advanced surveillance.
From DSC: This doesn’t surprise me. But it’s yet another example of opaqueness involving technology. And who knows to what levels our Department of Defense has taken things with AI, drones, and robotics.
A handful of companies control what PricewaterhouseCoopers called a “$15.7 trillion game changer of an industry.” Those companies employ or finance the work of a huge chunk of the academics who understand how to make LLMs. This leaves few people with the expertise and authority to say, “Wait, why are these companies blurring the distinction between what is human and what’s a language model? Is this what we want?”
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Bender knows she’s no match for a trillion-dollar game changer slouching to life. But she’s out there trying. Others are trying too. LLMs are tools made by specific people — people who stand to accumulate huge amounts of money and power, people enamored with the idea of the singularity. The project threatens to blow up what is human in a species sense. But it’s not about humility. It’s not about all of us. It’s not about becoming a humble creation among the world’s others. It’s about some of us — let’s be honest — becoming a superspecies. This is the darkness that awaits when we lose a firm boundary around the idea that humans, all of us, are equally worthy as is.
From DSC: I thought that the article made a good point when it asserted:
The pace of technological advancement is booming aggressively and conversations around ChatGPT snatching away jobs are becoming more and more frequent. The future of work is definitely going to change and that makes it clear that the approach toward education is also demanding a big shift.
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A report from Dell suggests that 85% of jobs that will be around in 2030 do not exist yet. The fact becomes important as it showcases that the jobs are not going to vanish, they will just change and most of the jobs by 2030 will be new.
Thus the question: What is the future of human agency? Pew Research Center and Elon University’s Imagining the Internet Center asked experts to share their insights on this; 540 technology innovators, developers, business and policy leaders, researchers, academics and activists responded. Specifically, they were asked:
By 2035, will smart machines, bots and systems powered by artificial intelligence be designed to allow humans to easily be in control of most tech-aided decision-making that is relevant to their lives?
The results of this nonscientific canvassing:
56% of these experts agreed with the statement that by 2035 smart machines, bots and systems will not be designed to allow humans to easily be in control of most tech-aided decision-making.
44% said they agreed with the statement that by 2035 smart machines, bots and systems will be designed to allow humans to easily be in control of most tech-aided decision-making.
What are the things humans really want agency over? When will they be comfortable turning to AI to help them make decisions? And under what circumstances will they be willing to outsource decisions altogether to digital systems?
The next big threat to AI might already be lurking on the web — from zdnet.com by Danny Palmer; via Sam DeBrule Artificial intelligence experts warn attacks against datasets used to train machine-learning tools are worryingly cheap and could have major consequences.
Excerpts:
Data poisoning occurs when attackers tamper with the training data used to create deep-learning models. This action means it’s possible to affect the decisions that the AI makes in a way that is hard to track.
By secretly altering the source information used to train machine-learning algorithms, data-poisoning attacks have the potential to be extremely powerful because the AI will be learning from incorrect data and could make ‘wrong’ decisions that have significant consequences.
Normally I would make the standard arguments against technologically-driven unemployment — see good summaries by Henry Hazlitt (chapter 7) and Frédéric Bastiat (his metaphor directly relevant to AI). And I will come back and make those arguments soon. But I don’t even think the standand arguments are needed, since another problem will block the progress of AI across most of the economy first.
Which is: AI is already illegal for most of the economy, and will be for virtually all of the economy.
How do I know that? Because technology is already illegal in most of the economy, and that is becoming steadily more true over time.
How do I know that? Because:
From DSC: And for me, it boils down to an inconvenient truth: What’s the state of our hearts and minds?
Have our hearts, our thinking, and/or our mindsets gone astray?
Do the products we create help or hurt others? It seems like too many times our perspective is, “We will sell whatever they will buy, regardless of its impact on others — as long as it makes us money and gives us the standard of living that we want.” Perhaps we could poll some former executives from Philip Morris on this topic.
Or we will develop this new technology because we can develop this new technology. Who gives a rat’s tail about the ramifications of it?
Here’s the list of sources: https://t.co/fJd4rh8kLy. The larger resource area at https://t.co/bN7CReGIEC has sample ChatGPT essays, strategies for mitigating harm, and questions for teachers to ask as well as a listserv.
— Anna Mills, amills@mastodon.oeru.org, she/her (@EnglishOER) January 11, 2023
Microsoft is reportedly eyeing a $10 billion investment in OpenAI, the startup that created the viral chatbot ChatGPT, and is planning to integrate it into Office products and Bing search.The tech giant has already invested at least $1 billion into OpenAI. Some of these features might be rolling out as early as March, according to The Information.
This is a big deal. If successful, it will bring powerful AI tools to the masses.So what would ChatGPT-powered Microsoft products look like? We asked Microsoft and OpenAI. Neither was willing to answer our questions on how they plan to integrate AI-powered products into Microsoft’s tools, even though work must be well underway to do so. However, we do know enough to make some informed, intelligent guesses. Hint: it’s probably good news if, like me, you find creating PowerPoint presentations and answering emails boring.
I have maintained for several years, including a book ‘AI for Learning’, that AI is the technology of the age and will change everything. This is unfolding as we speak but it is interesting to ask who the winners are likely to be.
People who have heard of GPT-3 / ChatGPT, and are vaguely following the advances in machine learning, large language models, and image generators. Also people who care about making the web a flourishing social and intellectual space.
That dark forest is about to expand. Large Language Models (LLMs) that can instantly generate coherent swaths of human-like text have just joined the party.
It is in this uncertain climate that Hassabis agrees to a rare interview, to issue a stark warning about his growing concerns. “I would advocate not moving fast and breaking things.”
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“When it comes to very powerful technologies—and obviously AI is going to be one of the most powerful ever—we need to be careful,” he says. “Not everybody is thinking about those things. It’s like experimentalists, many of whom don’t realize they’re holding dangerous material.” Worse still, Hassabis points out, we are the guinea pigs.
Demis Hassabis
Excerpt (emphasis DSC):
Hassabis says these efforts are just the beginning. He and his colleagues have been working toward a much grander ambition: creating artificial general intelligence, or AGI, by building machines that can think, learn, and be set to solve humanity’s toughest problems.Today’s AI is narrow, brittle, and often not very intelligent at all. But AGI, Hassabis believes, will be an “epoch-defining” technology—like the harnessing of electricity—that will change the very fabric of human life. If he’s right, it could earn him a place in history that would relegate the namesakes of his meeting rooms to mere footnotes.
But with AI’s promise also comes peril.In recent months, researchers building an AI system to design new drugs revealed that their tool could be easily repurposed to make deadly new chemicals. A separate AI model trained to spew out toxic hate speech went viral, exemplifying the risk to vulnerable communities online. And inside AI labs around the world, policy experts were grappling with near-term questions like what to do when an AI has the potential to be commandeered by rogue states to mount widespread hacking campaigns or infer state-level nuclear secrets.
Headteachers and university lecturers have expressed concerns that ChatGPT, which can provide convincing human-sounding answers to exam questions, could spark a wave of cheating in homework and exam coursework.
Now, the bot’s makers, San Francisco-based OpenAI, are trying to counter the risk by “watermarking” the bot’s output and making plagiarism easier to spot.
Students need now, more than ever, to understand how to navigate a world in which artificial intelligence is increasingly woven into everyday life. It’s a world that they, ultimately, will shape.
We hail from two professional fields that have an outsize interest in this debate. Joanne is a veteran journalist and editor deeply concerned about the potential for plagiarism and misinformation. Rebecca is a public health expert focused on artificial intelligence, who champions equitable adoption of new technologies.
We are also mother and daughter. Our dinner-table conversations have become a microcosm of the argument around ChatGPT, weighing its very real dangers against its equally real promise. Yet we both firmly believe that a blanket ban is a missed opportunity.
ChatGPT: Threat or Menace? — from insidehighered.com by Steven Mintz Are fears about generative AI warranted?
The rapid pace of change is driven by a “perfect storm” of factors, including the falling cost of computing power, the rise of data-driven decision-making, and the increasing availability of new technologies. “The speed of current breakthroughs has no historical precedent,”concluded Andrew Doxsey, co-founder of Libra Incentix, in an interview. “Unlike previous technological revolutions, the Fourth Industrial Revolution is evolving exponentially rather than linearly. Furthermore, it disrupts almost every industry worldwide.”
An updated version of the AI chatbot ChatGPT was recently released to the public.
I got the chatbot to write cover letters for real jobs and asked hiring managers what they thought.
The managers said they would’ve given me a call but that the letters lacked personality.
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I mentor a young lad with poor literacy skills who is starting a landscaping business. He struggles to communicate with clients in a professional manner.
I created a GPT3-powered Gmail account to which he sends a message. It responds with the text to send to the client. pic.twitter.com/nlFX9Yx6wR
From DSC:
Check out the items below. As with most technologies, there are likely going to be plusses & minuses regarding the use of AI in digital video, communications, arts, and music.
DC: What?!? Wow. I should have seen this coming. I can see positives & negatives here. Virtual meetings could become a bit more creative/fun. But apps could be a bit scarier in some instances, such as with #telelegal.
