AI Everywhere: Transforming Our World, Empowering Humanity
Mira Murati Th’12, Chief Technology Officer of OpenAI. This exclusive discussion will explore pioneering advancements and ethical considerations of AI. Murati will share insights, experiences, and groundbreaking developments to gain a deeper understanding of AI’s role in shaping our collective future.
Moderator: Dartmouth Trustee Jeffrey Blackburn ’91
Mira Murati shared some telling insights including her blunt statement:
→ “I think so, and some creative jobs maybe will go away, but maybe they shouldn’t have been there in the first place if the content that comes out of it is not very high quality, but I really believe that using it as a tool for education, creativity will expand our intelligence, and creativity, and imagination.”
→ “And also, I think people don’t realize how much these tools are already being used, and that’s not being studied at all. And so we should be studying what’s going on right now with the nature of work, the nature of education, and that’s going to help us predict for how to prepare for these increased capabilities. In terms of jobs specifically, I’m not an economist, but I certainly anticipate that a lot of jobs will change, some jobs will be lost, some jobs will be gained. We don’t know specifically what it’s going to look like, but you can imagine a lot of jobs that are repetitive, that are just strictly repetitive and people are not advancing further, those would be replaced. ”
→ “- So yeah, these systems are already human-level in specific tasks, and of course in a lot of tasks, they’re not. if you look at the trajectory of improvement, systems like GPT-3, we’re maybe let’s say toddler level intelligence. And then systems like GPT-4 are more like smart high schooler intelligence. And then in the next couple of years, we’re looking at PhD-level intelligence for specific tasks.”
→ “So we found out that this formula actually works really well, data, compute, and deep learning, and you can put different types of data, you can increase the amount of compute, and then the performance of these AI systems gets better and better. And this is what we refer to as scaling laws. They’re not actual laws. It’s essentially like a statistical prediction of the capability of the model improving as you put in more data and more compute into it. And this is what’s driving AI progress today.”
→ “Right, yeah, exactly. And so there is this whole debate right now around, do you do more safety or do you do more capability research? And I think that’s a bit misguided because of course you have to think about the safety into deploying a product and the guardrails around that. But in terms of research and development, they actually go hand in hand. And from our perspective, the way we’re thinking about this is approaching it very scientifically. So let’s try to predict the capabilities that these models will be, the capabilities that these models will have before we actually finish training. And then along the way, let’s prepare the guardrails for how we handle them. That’s not really been the case in the industry so far. We train these models, and then there are these emergent capabilities we call them, because they emerge. We don’t know they’re going to emerge. We can see sort of the statistical performance, but we don’t know whether that statistical performance means that the model is better at translation, or at doing biochemistry, or coding or something else. And developing this new science of capability prediction helps us prepare for what’s to come. And that means…”
→ “I think really figuring out how we use these tools and AI to advance education. Because I think one of the most powerful applications of AI is going to be in education, advancing our creativity and knowledge. And we have an opportunity to basically build super high quality education and very accessible and ideally free for anyone in the world in any of the languages or cultural nuances that you can imagine. You can really have customized understanding and customized education for anyone in the world. And of course in institutions like Dartmouth, the classrooms are smaller and you have a lot of attention, but still you can imagine having just one-on-one tutoring, even here, let alone in the rest of the world. – Supplementing. – Yes. Because we don’t spend enough time learning how to learn. That sort of happens very late, maybe in college. And that is such a fundamental thing, how you learn, otherwise you can waste a lot of time. And the classes, the curriculum, the problem sets, everything can be customized to how you actually learn as an individual.”
