The AI Daily Brief: Artificial Intelligence News and Analysis - 5 Ways AI Could Improve Humanity

Episode Date: July 10, 2023

Today NLW reads the companion piece to yesterday's episode -- 5 Ways AI Could Improve the World https://www.theguardian.com/technology/2023/jul/06/ai-artificial-intelligence-world-diseases-climate-scenarios-experts Before that on the Brief: Comedian and actress Sarah Silverman has sued Meta and OpenAI for infringing against her copyright by training their models on her book; TSMC rises after beating earnings expectations; corporates are spending big on AI; and Google is testing Med-PaLM 2 in hospitals. Today's Sponsor: Supermanage - AI for 1-on-1's - https://supermanage.ai/breakdown ABOUT THE AI BREAKDOWN The AI Breakdown helps you understand the most important news and discussions in AI.  Subscribe to The AI Breakdown newsletter: https://theaibreakdown.beehiiv.com/subscribe Subscribe to The AI Breakdown on YouTube: https://www.youtube.com/@TheAIBreakdown Join the community: bit.ly/aibreakdown Learn more: http://breakdown.network/

Today on the AI breakdown, we're reading part two of the Guardian series this time how AI could improve the world. Before that on the brief, Sarah Silverman is suing OpenAI and meta around AI copyright. The AI breakdown is a daily podcast and video about the most important news and discussions in AI. Go to Breakdown.network for more information. Hello, friends. Welcome back to another AI breakdown. We're kicking off the week with some legal battles. Sarah Silverman has sued OpenAI and Meta in what is just another front in one of the biggest legal battles, which is how copyright rules are going to ultimately apply to LLMs.

And before we get into that, I just wanted to say a quick thanks to my sponsors for today's show, Supermanage. Supermanage is an AI-powered tool that helps companies with one-on-ones. Now, a truly great one-on-one should be about celebrating wins, solving problems, and deepening the connection between the people who are involved in that meeting. The problem is that so many times those wins, those challenges, never even really come up. The whole meeting is instead spent avoiding the hard stuff. Supermanage helps by distilling public Slack channels into a one-on-one brief that highlights everything someone needs to know to jump right in.

The goal is to give teams the ability to do the best work of their lives, starting with world-class conversations. Visit supermanage.ai forward slash breakdown today to start making the most of your one-on-ones. And thanks again to Supermanage AI for support. the show. And with that, let's dive in. Welcome back to the AI breakdown brief. All the AI headline news you need in five minutes or less. Remember, you can get the AI breakdown brief as a newsletter. It comes out every morning. I call it the first five. It tends to cover similar topics, but not always exactly the same as this episode.

So check it out, the AI breakdown.bohive. That's B-E-H-I-I-V.com. We kick off today with Sarah Silverman. Yes, the comedian is leading a class-action lawsuit against both meta and OpenAI, accusing them of training their large language models on her book without her permission. This, the suit argues, is a violation of copyright, and so she is looking for financial recompense for damages. Now, of course, this is a little bit less about Sarah Silverman specifically and a little bit more about copyright precedent when it comes to AI in general. As Reuters puts it, the lawsuits underscore the legal risk developers of Chatpot's face when using troves of copyrighted material to create apps that deliver realistic responses to user prompts.

There are a number of this type of copyright suit going on out there. We've obviously mentioned the Getty Images suit a number of times on this show in which Getty is suing Stability AI for allegedly training its stable diffusion model on Getty's 12 million proprietary images. Now, there are a lot of different approaches to this that we're likely to see around the world. We don't have rulings yet in the U.S. or the UK where Getty also filed suit against Stability A.I. but Japan seems headed towards a regime in which training AI on copyrighted materials is not a violation of copyright. Europe appears not yet to be taking a firm stance on whether AI companies can train their models on copyrighted materials, but they do want disclosures when that happens. One of the key provisions of the generative AI side of the rules of the new EU AI Act

is to clearly articulate what data models are trained on. Now, when it comes to people's takes on AI and copyright, the people who have strong enough opinions to want to share them tend to fall into one of two categories. On the one hand, is the take represented here by Stefan Kinsella, who retweeted the article about Sarah Silverman's suit and says, this is what you get with this insane legal system. It could crush an entirely new and useful technology. Shame. On the other end of the spectrum are people like Alist, an illustrator and apparel designer who submitted a comment to the White House around its AI strategy and said, I talked about how Gen AI models could not exist without first stealing terabytes of data from creatives, and we need a system around AI training that respects creators' copyright. Whichever side of that

you find yourself closer to, I tend to agree with Dennis Consorte here who tweets, prediction, generative AI will make its way to the Supreme Court within 12 to 18 months as more intellectual property lawsuits pile up. Next up on the brief, AI legal concerns be damned. According to a new CNBC survey, AI is a key top spending priority for more than half of companies that they surveyed. CNBC recently surveyed a group of top tech executives, including CIOs, CTOs, from companies including Accenture, Adobe, Ernst & Young, IBM, Johnson, and Johnson, and more, and nearly half of those surveyed, 47% of the companies that participated in this survey said that AI was not just a priority, but their top spending priority in technology

over the next 12 months. On top of that, 63% said that their companies are accelerating spending into AI, as opposed to 37% that characterize themselves as proceeding with caution. Not a single one of the 100 executives of the CNBC Technology Executive Council surveyed said that they were not investing in AI. Another survey from research firm Omdia also found that 55% of the companies that they surveyed have a dedicated AI budget. Meanwhile, 38% said that their spending on AI is supported by other budgets and only 5% did not have a budget at all. Interestingly, according to that Omdia survey, companies in Asia are spending more on AI than companies in the West. 52% of respondents in Asia said that they currently spend more than $1 million a year on AI versus only

38% in North America. Staying on the corporate team from one more moment, TSMC, the world's biggest chip manufacturer, the company who manufactures most of invidious chips, has beaten analyst quarterly earnings estimates. Despite the fact that their Q2 revenue was down 10% year over year, the fact that they beat expectations has sent their stock heading back up. Overall, this year, TSM's stock is up 25% even though their revenue is down year over year. Moving to the weird, wild world of robotics for just a moment, the UN last week held an AI for Good Summit in which people came together to discuss how artificial intelligence could be used to improve human livelihoods and accelerate development goals.

And one of the big media affairs from that event was a press conference where nine humanoid robots were allowed to be asked questions by members of the press. This certainly had the intended effect with tons and tons of news outlets picking out quotes and running stories about it. The quote that most outlets ran with came when one member of the press asked Sophia, a robot that is also a UN ambassador, if robots would make better leaders than humans. Sophia responded, humanoid robots have the potential to lead with a greater level of efficiency and effectiveness

than human leaders. We don't have the same biases or emotions that can sometimes cloud decision making and can process large amounts of data quickly in order to make the best decisions. So there you have it, guys. The first job to be replaced by robots is going to be the politicians. Lastly today, a story with one of the big themes that I am noticing more and more and more in the press, which is the use of AI in medical settings. Over the weekend, the Wall Street Journal reported that Google is currently testing its MedPom 2 model in hospitals, including the Mayo Clinic, and those live initial tests are really promising. MedPOM 2 was trained using a set of medical demonstrations and just medical data in general,

with the idea to be able to assist doctors and practitioners with care questions, background information, and more. Google itself has said that its MedPom 2 model still has some issues with accuracy, as do all LLMs, but when it comes to things like showing evidence of reasoning, consensus-supported answers, and showing no sign of incorrect comprehension, MedPom 2 performed about as well as human doctors. Now, this wasn't an official press release, it was Wall Street Journal background reporting, so we didn't really get much more information about what Google's plans are, but WSJ is also saying that customers of MedPOM2 will control their data, meaning that it's designed to be a sort of enterprise product

as opposed to a general-purpose medical LLM that anyone can access. All right, guys, that's going to do it for today's AI breakdown brief. If you enjoyed it, do me a favor. Drop a like or a comment on this video, or if you're listening to it, especially on Spotify, go leave a little note about what you liked. Thanks again for listening or watching, and I'll be back soon with the main AI breakdown.

Welcome back to part two of our long reads on the AI breakdown. On the last episode, you heard Five Ways A.I. could destroy the world. So, of course, now we have to read its companion piece Five Ways A.I. Could it improve the world? Again, these were interviews by Steve Rose from The Guardian. And Steve kicks it off. Recent advances such as OpenAI's GPT4 chatbot have awakened the world to how sophisticated artificial intelligence has become and how rapidly the field is advancing. Could this powerful new technology help save the world? We asked five leading AI researchers to lay out their best case. scenarios. Number one, more intelligence will lead to better everything. From Ray Kurzweil, Computer Scientist, Adventure, author, and futurist. In 1999, I predicted that computers would

pass the Turing test and be indistinguishable from human beings by 2029. Stanford University found that alarming and organized an international conference. Experts came from all over the world. They mostly agreed that it would happen, but not in 30 years, in 100 years. This poll has been taken every year since 1999. My guess has remained 2029, and the consensus view of AI experts is now also 2029. Everything's going to improve. We will be able to cure cancer and heart disease and so on using simulated biology and extend our lives. The average life expectancy was 30 in 1800, it was 48 and 1900. It's now pushing 80. I predict that we'll reach longevity escape velocity by 2029. Now, as you go forward a year, you're using up a year of your longevity,

but you're actually getting back about three or four months from scientific progress. So actually, you haven't lost a year. You've lost eight or nine months. By 2020, you'll get back that entire year from scientific progress. As we go past 2029, you'll actually get back more than a year. Most movies about AI have an us versus that mentality, but that's not actually the case. This is not an alien invasion of intelligent machines. It's the result of our own efforts to make our infrastructure and our way of life more intelligent. It's part of human endeavor. We merge with our machines. Ultimately, they will extend who we are. Our mobile phone, for example, makes us more intelligent and able to communicate with each other. It's really part of us already. It might not be

literally connected to you, but nobody leaves home without one. It's like half your brain. If the wrong people take control of AI, that could be bad for the rest of us, so we really need to keep pace with that, which we are doing. But we already have things that have nothing to do with AI, such as atomic weapons, that could destroy everyone. So it's not really making life more dangerous, and it can actually give us some tools to prevent people from harming us. The rate of change will be difficult for some people. The railways changed the US, but it took decades. This is changing it in months. If we were in 1900 and I went through all the different ways people made money, and I said all of those will be obsolete in 100 years, people would go, oh my God, there's going to be no jobs.

But in fact, we have more jobs today in areas that were really only invented in the last few decades. That will continue. We've made great progress, but there are still people who are desperate. More intelligence will lead to better everything. We have the possibility of everybody having a very good life. Two, we can use AI tools right now to help fight climate change. This is from David Rolnik, assistant professor and Canada Seafar AI chair McGill University of Computer Science, Montreal. All. Everybody wants a silver bullet to solve climate change. Unfortunately, there isn't one. But there are lots of ways AI can help fight climate change. While there's no single big thing that AI will do, there are many medium-sized things. The first role AI can play in climate action is distilling

raw data into useful information. Taking big data sets, which would take too much time for a human to process, and pulling information out in real time to guide policy or private sector action. For example, taking satellite imagery and picking out where deforestation is happening, how biodiversity is changing, where coastal communities are at risk from flooding. These kinds of tools are already starting to be used by organizations around the world, from the UN to insurance companies, and we're working to scale them up and improve them. The second role is optimization of complicated systems, such as the heating and cooling system in a building, where there are many controls that an algorithm can operate efficiently.

Smart thermostats have become mainstream in our homes, and now we're starting to see that for skyscrapers and factories. Many companies are improving energy efficiency, and there is a lot of progress still to be made, especially in industries such as steel and cement, which are often resistant to adopting new technologies. The next theme is forecasting. AI can't predict some big-picture thing like what's going to happen in the economy, but forecasts make sense for narrow problems with lots of data, such as what the power demand is going to be at a particular time, or what power is going to be available based on the sun and the wind, forecasting how a storm is going to move or the productivity of crops based upon the weather. The fourth theme is in speeding up scientific simulations, such as in climate and weather modeling. We have really good climate models, but sometimes they can take months to run, even

on supercomputers, and that is an obstacle. We understand climate change very well, but that doesn't mean we know exactly what is going to happen at each point. So having faster climate models can aid local and regional responses. AI and climate action isn't about what computers can do in the far future. We can't trust some speculative future technology to rescue us. Climate change is already killing people, and many more people are going to die even in the best case scenario. But we get to decide now just how bad it gets. Action taken decades from now is much less valuable than action taken soon. Thinking of AI as a futuristic tool that will lead to a measurable good or harm is a distraction from the ways we can and are using AI tools right now, and what we can do to align them

with what's best for society. Number three, there is going to be an amazing revolution in healthcare. This one again, interestingly from Joshua Benjillo, Professor of Computer Science at the University of Montreal, who also contributed to the how AI could destroy the world. There is a rapid transformation in the pharmaceutical industry in university research, where they're shifting to the use of AI to help discover new molecules and new drugs that would have fewer side effects, and that would help us cure diseases that currently we don't know how to cure, including cancer potentially. One reason AI can be useful here is that the body is very

complicated, even a single cell is extremely complicated. You have 20,000 genes and they all interact with each other. Biotechnology has progressed to the point where we can measure all the genes activity in a single cell at once. While we collect huge quantities of data, the quantity of data is so large that humans are unable to read it. But because machines can, they are able to build models of how your cells work and how they could be changing under different circumstances that cause disease. So you can see what happens if you make an intervention. If you introduce a pollutant or a drug, what will be the effect? There are many academics working in these areas right now. One of the research programs in my group is about using AI for discovering drugs

for infectious diseases, which don't get a lot of attention from pharma because they're not profitable. They're happening in developing countries, or they're very rare, such as pandemics. There is also the issue of antimicrobial resistance, where mutations of microbes mean that our current drugs are no longer effective. This is like a catastrophe dangling in front of our noses it could come at any time. This is not just something happening in academia. There are now dozens of startups that have been created at the intersection of AI and drug discovery, broadly speaking.

These have been injected with billions of dollars while pharmaceutical companies are beefing up their machine learning departments. Having better models could be a real game changer. The big cost of drug discovery is that you have to try a lot of things that don't work. Trying one drug isn't that expensive, but usually there's something that goes wrong. Currently, it costs billions of dollars to develop a new drug. It could easily be ten times less with these advances. It's probably going to take years before people see an effect. but I'm pretty sure it's going to be an amazing revolution in terms of health care.

Number four, AI could radically accelerate the process of technological progress itself. Once again from Aeha Kotra, senior research analysts on AI alignment, open philanthropy, and editor at planned obsolescence. If we figured out how people are going to share in the wealth that AI unlocks, then I think we could end up in a world where people don't have to work to eat and are instead taking on projects because they are meaningful to them. I often use the analogy of children. They do a lot of things because they enjoy them and not because they're the best person

in the world at them. They paint and draw and they have a lot of fun. I paint and draw and I have a lot of fun, even though Mid Journey is way better at making pictures than me. Similarly, since the 90s, we have had computer programs that can beat humans at chess, but lots of people still play chess. If you have intelligent AI systems that are accessible to people, it's as if everybody has access to an infinitely patient teacher, so you could imagine training these AI systems to be an interface between humans and other humans. I think there are things that we might choose to not have AI replace. Those will probably have to do with governance of our society and our processes of trying to figure out what are the good things to do with the world. How do we manage our resources? What are the

laws we're going to put in place? What is the way to treat people fairly? And if you imagine, for example, the possibility of expansion into space with technology invented by AI systems, we would have choices? Should we do that? And what would we do with the resources that we unlock if we do expand into space? AI systems could help us think that through, but it might be that we want those decisions to be made by people. When you zoom out and look at where humanity has come from, on the scale of centuries and millennia. Freedom and health and equality have been getting better over time, and better technology has played a huge part in that.

Truly advanced AI systems could continue that story. They could be more than just another technology. They could automate and radically accelerate the process of technological progress itself. In just a couple of decades, humanity could get the kind of advanced future that feels like it's hundreds or thousands of years away. This is not at all guaranteed, but I think it's within reach if we get this right. Number five. We can flourish, not just for the next election cycle, but for billions of years.

This one by another person who contributed to destroy Max Tegmark, a professor of physics and AI researcher at MIT. The positive optimistic scenario is that we responsibly develop superintelligence in a way that allows us to control it and benefit from it. The control part is, I think, more hopeful than many people assume. There is a field of computer science called formal verification where you come up with a rigorous mathematical proof that a program is always going to do what it's supposed to do. You can even create what is called proof-carrying code. It works in the opposite way to a virus checker. If a virus checker can prove that the code you are going to run as malicious, it won't run it.

With proof-carrying code, only if the code can prove that it is going to do what you want it to do, will your hardware run it? This is the type of mechanism we need to ensure advanced AI is safe. We can't yet do this with GPT4 or other powerful AI systems because those systems are not written in a human programming language. They are a giant artificial neural network, and we have almost no clue how they work. But there is a very active research field called mechanistic interpretability. The goal is to take these black box neural networks and figure out how they work. If this field makes so much progress that we can use AI itself to extract out the knowledge from other AI and see what it has learned, we could then re-implemented in some kind of computational architecture,

some kind of proof-carrying code that you could trust. Then you could still use the power of neural networks to discover and learn, but now you can trust something that's way smarter than you. Then what are we going to do with it? Well, the sky's the limit. We can cure all diseases, stabilize our climate, eliminate poverty, etc. We can flourish not just for the election cycle, but for billions of years. We have been on this planet for more than 100,000 years, and most of the time we have been

like a leaf blowing around in the wind. Without much control of our destiny, just trying to not starve or get eaten. Science and technology and human intelligence have made us the captains of our own ship. I find that inspiring. If we can build and control superintelligence, we can quickly go from being limited by our own stupidity by being limited by the laws of physics. It could be the greatest empowerment moment in human history. All right, back to NLW here for just a quick wrap-up.

A few notes that I want to leave you with as you ponder this one as well. The first has to do with what people don't like about both sides. of these arguments. And that I would characterize as hand-waviness. On the destroy the world's side, that hand-waviness manifests as, inevitably, these machines are going to want to kill us and use our resources. And so they're going to do it in XYZ way. It feels hand-wavy because it makes a huge number of assumptions. However, there is a similar hand-waviness when it comes to how AI could just all of a sudden cure all diseases or eliminate poverty. Now, I think by and large, both sides of the argument presented in these guardian pieces mostly avoid hand-waviness, but it's super notable when that

hand-waviness appears, and maybe suggest that that's something that as this discourse evolves, we should be looking to avoid as much as is actually possible. A second thing that comes out of seeing some of the responses to this piece is that it appears to me that there's a lot of skepticism out there about how much some of these problems are technological or able to be solved by technology versus about politics and choice. Again, if you go copy, paste this URL into the Twitter search bar, you're going to see a lot of people who are saying things like the issues with climate change and poverty aren't really about technology, they're about choices that we've decided not to make. I think whether one is predisposed to think that AI is going to improve or harm the world,

understanding the role of human decision-making processes in politics is going to be really essential in how that plays out. Lastly, I did want to point out that three of the five voices featured here are featured on both the how it could improve the world and how it might destroy the world's side. I think that speaks to something that mainstream media doesn't always capture, which is that many of the people who are most concerned about the risks if we don't address them are coming from a place where they're unbelievably excited about the possibilities if we can address them. It is not a set of Neo-Luddites in the way that opponents of previous technology

moments have been. It is the people who are most close and most in touch in many cases with the raw power of these systems who have an appreciation for the risk that they bring. I think getting outside of our priors of assuming that people who are concerned about the risks of these technologies must just be people who are anti-progress a priori is going to be really, really important for having a discourse and a dialogue that can move forward productively. Anyways, as we wrap, I want to say a big thanks to Guardian for putting these pieces together. I think they're a step above most mainstream media coverage of these issues.

And let me know what you think. Which of these sides are you most compelled by? Which of these arguments did you find interesting? Hit me up on Twitter at NLW. Go check out the Discord. It's bit.ly slash AI breakdown. And until next time, peace.