The Intersection of Human Psychology with AI

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1:49Pattie Maes:Bloomberg Audio Studios. Podcasts. Radio. News. You're listening to Bloomberg Business Week with Carol Masser and Tim Stenevek on Bloomberg Radio. Well, the AI spend and build out is on. You know that. We talk about it a lot here at Bloomberg. Lots of questions still abound over the impact on the workforce. Does it destroy some jobs? Does it create others? There are questions on how much more productive we become. Will it create problems for younger individuals? Might it destroy our creativity? But. Might it spark it? might we get discoveries when it comes to healthcare and pharmaceuticals? That's right.

2:27So the yin and yang, right, of AI. And we're just kind of watching this in real time. Wired reported out last night about some work that MIT researchers are doing, led by Patty Moss. She's a professor at the Institute's Media Lab. They've worked on a new benchmark that could help AI developers build systems that better understand, Tim, how to inspire healthier behavior among users. We wanted to know more. Let's get to the Business Week Women's Health segment where we focus on key issues in developing technologies impacting the present and future of women's health around the world. We head to the MIT Media Lab in Cambridge, Massachusetts, and to Dr.

3:00Patty Moss, professor of Media Arts and Sciences and head of Fluid Interfaces Group. She does research at the intersection of human-computer interaction and AI. So let's talk about these LLMs, these models, and how we can interact with them to actually benefit our health, because so much of what we've heard about has been the detrimental effects on our health and well-being. Yeah, pleasure to be here. So basically, LLMs today, of course, are everywhere. They're being pushed to us in our text editors, Google search, all of that. But we still don't know what the impact is of using these chatbots for assistance in our daily lives.

3:44And one of the things that we are looking at here at the MIT Media Laboratory is exactly the impact of using these technologies, technologies day in, day out on our cognitive functioning, on our ability to think critically, our ability to learn, our ability to solve problems, our socializing, our loneliness, and so on. Yeah, you know, that's the thing. One of the things I think about, Dr. Moss, is we did so well in keeping on top of social media, so it did no harm. She's being sarcastic. Thank you so much. He's right, though. So my fear is, how do we keep on top of this? So tell us about the work you are doing to try and get a handle on how it might impact our brain, our psychological health, and how that might inform the companies that are in the thick of it.

4:42Yeah, so we've been doing studies here at the MIT Media Lab showing that when you use these technologies to help you with a particular work task or with writing an essay, etc., It may actually improve your performance in the moment when you have access to these tools, but it can actually erode some of those same skills in the long term if you rely on these technologies for too much of your work, basically. So it's really important that we think about how these technologies should be integrated in our daily life and in our work lives in such a way that they don't erode skills that we don't want to lose.

5:29And that's exactly what we try to focus on with our work. So how do we do that when we are encouraged? Because we are encouraged to use these. I mean, you have people come on our program and say, if you're not using these tools, then you are essentially, you know, erasing yourself from the workforce in the future. But there's that balance that we want to make sure we continue to be able to think. Yeah, well, the emphasis of LLM development has been especially on increasing their capacity, their efficiency, things like that. But it hasn't exactly been on the design of these systems and designing them in a way so that ultimately the benefit for people is a net positive, especially in the long term.

6:16So we believe that we actually have to increase the friction in these systems and that they shouldn't too readily just do all the work for us, but they should play a more augmentative role, basically, and support us in also developing our skills and keeping our skills sort of up to a certain level. So what do we do? Is it create guardrails? Like, or when we ask a question, like, that's pretty easy. Don't you want to do that on your own? And, you know, then there are those of us who are going to be like, yeah, it might be easy, but I don't have the time. Like, I just wonder how do we actually manage this?

6:59Yeah. And, you know, I was going to say, and we and we're in a world where the government and you have, you know, is it open AI? Right. That has been pushing back about concerns about weapons that can ultimately, you know, or systems that can think on their own. So or anthropic, anthropic, forgive me. Anthropic is who we're thinking about. But like this pushback and the concern about what this means for weapons. But I do think about these systems that can maybe almost have a life personality of their own. and what damage they can create, especially for a younger population, but not just younger, all of us.

7:34Yeah, well, these systems are not necessarily 100 % correct yet. All the time, they still hallucinate. They don't really deeply understand our world. And so it's important that we still are able to understand things, solve problems, and that we can supervise these systems so we know when they may be incorrect or when we maybe shouldn't be trusting them. So one of the things we do here at MIT is we've been developing a set of best that actually evaluate the impact of LLM use on people, on their ability to think critically, for example, and to think for themselves. So it's very important that LLMs don't just always give you the answer, depending on the context and who's the user and what they're using the LLM for, it may be better for that chatbot to just ask a question first of the user to engage them in thinking because our tests show that when an LLM just gives you the answer readily, people stop thinking for themselves.

8:47They're naturally a little bit lazy. Dr. Moss, does that align with the incentives? of these LOMs? No, it doesn't exactly align with the incentives, which is another reason why we are developing these benchmarks, the benchmark for the human impact of AI, because if we have a benchmark like that, we can put pressure on these companies to actually do well on that particular human impact benchmark. I believe also, yeah, we've only got to... Go ahead. I was going to say, there's only 20 seconds left. Are you optimistic that we're going to be able to manage this? Are you more nervous and just very quickly?

9:31I'm optimistic, actually. I think we're going a little bit too quickly with rolling out these systems to billions of people, honestly, and affecting their lives in a big way. The science is only now catching up. But I believe that we can design these systems in a way that they actually lead to human flourishing and people doing well. Be sure to come back soon because I do feel like, again, we're learning as we go. But it's an important subject. Dr. Patty Moss at the MIT Media Lab in Cambridge, Massachusetts. If you follow markets, you know the value of long term thinking. You plan, you diversify, you prepare for volatility.

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