Andrew Ng: The Biggest Opportunities in AI Aren't Where You Think

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0:45Gemini and Chrome is here for it. Ready to make anything online make sense? There's no place like Chrome. Check responses set up required, compatibility and availability varies 18+. There's been a lot of misinformation about AI. This is Andrew. He co-founded Google Brain and Coursera. His machine learning course has reached millions of learners, and he is one of the most influential voices in AI today. So a handful of leading AI companies have been very loud voices, fear-mongering around AI. To try to get regulations passed, this drumbeat of fear-based messaging has skewed societal perception to be really negative on AI.

1:22People talk to me about data centers and job loss. Maybe AI could do 30, 40 % of many jobs. And what that means is, well, that 60 % that a human does has become even more valuable. What about loss of human control over AI? I think about something else that we can't control. I think you're one of the voices in AI who comes with a huge background in machine learning and teaching AI. And also your positive voice, because this is something that I've been seeing, especially this summer, how polarized the society has become, especially on social media, when I'm posting about AI and people talk to me about data centers and job loss.

2:04Why do you think this wave started recently? What do you think the causes are? There's been a lot of misinformation about AI. And the root cause of a lot of this is an unfortunate attempt that started two or three years ago of, I think, PR and regulatory capture. It turns out that one of the most valuable things in AI right now is the giant AI models, giant large language models that some companies have trained. But if you spend billions of dollars training a model, it's really inconvenient if someone else trains a model and wants to give it to anyone in the world to use for free. So a handful of leading AI companies, I think, as you know, have been very loud voices, fear mongering around AI to try to get regulations passed, to create an unfair playing field that favors incumbents so that we all have to pay a high toll for use of AI, while stymieing the other teams, be it researchers or other companies that want to just give away open way to open source models that anyone could use much cheaper.

3:04Unfortunately, fear-mongering works. When you go and say AI is like nuclear weapons, which is an analogy that has no basis in fact, what do they have to even do with each other? Or when you go around and cherry pick cases of AI making a misstep and make it much bigger than it is. Or even spread misinformation about how AI uses, data centers uses a lot more water than the actual reality. This drumbeat of fear-based messaging has skewed societal perception to be really negative on AI, which is unfortunate because this is slowing down American adoption in AI. This is making America less competitive.

3:43And unless we get the truth about AI out there, which is that it's fantastic benefit, with some problems, but not nearly the degree to which they're blown up to be, it will hurt individuals. I'm going to read out some of the problems that people are highlighting. Job loss and inequality. What do you think? The job apocalypse or jobpocalypse, this idea that AI will take over 50 % of jobs, people will be out of the world, writing in the streets. That's just not going to happen. With every wave of technology, including AI, the skills we need to do great work shifts. And so AI is changing job professions.

4:19But boy, I wish AI were, AI just doesn't work well enough. I know that a handful of businesses want to hype up AI to say, we have super intelligence or we'll have artificial general intelligence or whatever, and can do all the stuff that humans do. I wish AI worked better, which is not good enough to make AI do everything a human does. And if you look at the analysis of jobs, economists, like my friend Eric Brynolfsson at Stanford, Andy McAfee at MIT, economists have analyzed many people's jobs and by breaking it down into individual tasks, and maybe AI could do, you know, 30, 40 % of many jobs.

4:55And what that means is, well, that 60 % that a human does has become even more valuable because it's called an economic complement to the 30, 40 % is now cheaper. And so what will happen is people that use AI, maybe people that use AI will replace people that don't use AI, but AI is not in a position for the vast majority of jobs to replace people. Of all the different professions, the one that's most affected by AI now is software engineering because AI is actually fantastic at writing code. And what we see is that the number of job openings in software engineering is up, contrary to what the doom fear mongerists would say, right?

5:37AI is not actually able to replace software engineers. And all the good software engineers I know are busier than ever. Now, the flip side of it is, if someone still writes code like this 2022 before ChagGPT, they're in trouble. They need new skills. Don't do stuff that 30, 40 % of AI can automate. You've got to start doing that. Let AI do that. But then gain new skills to do the other 60, 70 % of AI cannot do. What would your advice be to new graduates? Because I talked to Eric on this podcast, and he was talking about that there is not really a lot of impact on the job market, except for, I think he mentioned people from 18 to 25 who just graduated.

6:17What would be your advice to those people who don't have the expertise maybe to strategize in their job yet? They can only do manual work that AI can do as well. So one real challenge for fresh college grads is that the university system is slow to adapt. And so, you know, I love academia. I think we should all support academia in universities. and when AI comes and transforms the way software is written, universities often take like a year or two for the faculty to master the skills, then create new courses, get curriculum committee approval or whatever, get the faculty senate to vote. It just takes years and that speed of change in academia is very poorly matched to the speed of change in AI.

7:03So sadly, many universities are still teaching students to be ready for the jobs of 2022 when we shouldn't even be teaching them for the jobs of 2026. We should be teaching them for the jobs of 2028 and beyond. And what this means is the job openings are there. Tons of employers I know just can't find enough skilled people at any level of seniority. But it turns out in my office right now, we have a lot of interns. There are current college students, fresh college grad. We're also at one high school intern. And they're amazing and productive. But the key is they're all very AI native. that they all use AI tools to do the things that I could do, but then also lean in to doing the things that humans can do that AI can't for a long time.

7:47So there's plenty of work for people to do. But so my advice to fresh college grads or the people currently in college is, by all means, work hard in classes, get good grades, learn from the instructors. But to the extent that there's still additional skills the university has not yet adapted to teaching, then find other ways to learn online. be it from Coursera or deeplearning.ai or Udemy or other places where you can gain the more cutting-edge skills, especially AI skills that universities have not yet worked in the curricula. I want to say one other thing. It turns out if you look at the skill map changes, one of the most important changes is it's so much easier to build with AI than before.

8:32When something becomes much easier, a lot more people should do it. And so now, not only should professional software engineers build software with AI, it's becoming much easier for everyone to build with AI. And people that embrace that and do so will be more productive and will accomplish more and I think have more fun than the ones that don't. And AI lets you build really fast. So for people that are not just software engineers, but marketers, recruiters, HR professionals, operations specialists, I think if they learn to build with AI, they really just do much more, whatever their job role is.

9:10Hey, Chicago, class it up with Crocs. You know back to school is coming in fast. So why wait to find your new fave footwear? Step into a local Crocs store and step into your new look. Try it. Style it. Make it yours. Because the right pair doesn't just show up. It shows off. First day fits. Handled. Walk out ready for whatever's next. Visit your nearest Croc store today. This episode is brought to you by Google Chrome. You think you know a browser, but Gemini and Chrome? That's new. It can help you with practically anything on the web, like restoring a vintage motorcycle from a 50-page restoration block, or finally break down that long article you've had open for weeks.

9:55Gemini and Chrome is here for it. Ready to make anything online make sense? There's no place like Chrome. Check responses set up required, compatibility and availability varies 18+. How do you, by the way, measure the increase in productivity when you deploy AI? Do you have like a KPI in your company? I wish there's a simple answer. I find that the business outcome of AI is more a function of the business than a function of the AI. For some, it may be increased, you know, customer growth and retention or maybe faster to serve customers or it would be increased accuracy in some tasks. So the KPIs tend to be related to the business rather than the AI.

10:34So you can't like directly measure just AI because it's an interesting thing to do because we've been deploying AI actively in my company. And I think for me as a media company, it's probably the amount of views, the output. It's just interesting how, yeah, it's just interesting how different people measure, even revenue. like if you're becoming more effective with how you make money. Actually, say more. How are you using AI in your business? Oh, my God. So, first of all, we have Claude for all of us, and we have certain projects for every social media that we're on. So, for example, for this podcast, we have a project that's called Guests, and it knows all the analytics from previous guests, and it has certain criteria on which we rank every single person who comes to the podcast, whether he or she is cited, whether they have a certain opinion on AI, whether they've been active with AI in their company or if they're a recent founder in AI.

11:24So it gives them different weights and it comes up with a grade based out of 40, 40 meaning tier one, 30 meaning tier three, et cetera. And then we have another one that analyzes every single podcast and gives me tips on how to ask questions. Same for Instagram, same for LinkedIn. It has my tone of voice, personal dossier, my business strategy. So whenever it writes something, it knows all the facts about me, how I sound. Every social media is run by person. So a person makes a strategic call. And by the way, if you can give me feedback on this, if I can improve. So what I'm working on right now is closing the loop because sometimes they send me a text.

12:01I'm like, oh, we need to change this, this and that. But that happens in a chat, in Telegram. And we have this feedback. We we have a bot that scans all of our chats. But I really want AI to be able to learn continuously from this feedback to just know my taste better. There's one thing I see a lot in AI, which is it turns out for AI's data scientists or AI's brainstorming partner, it often comes up with, you know, one or two good ideas, two or three mediocre ones and like, you know, four atrocious ones. And sometimes you wonder, how could my AI have thought, you know, like that could even be a plausible idea?

12:36And to me, this relates to the jobpocalypse point of view, which is that for a long time, humans, you, me, everyone watching this, will have a significant context advantage over AI, which is that you know something that's incredibly obvious to you that, you know, that was an awful idea, but the AI did not. And it turns out that one of the reasons why AI will not replace our jobs or whatever, or large percent of time soon, is because humans have a massive context advantage compared to AI. We know so much that, you know, from our years of experience that we talked to customer, we saw the funny facial expression that told us, ah, they don't like this.

13:15Or we talked to business or, you know, our manager said, hey, blah, blah, blah, I really care about this. And so it turns out that almost all humans, well, maybe all humans, just know a lot of stuff that the plumbing does not exist. And I don't think it exists for the foreseeable future for AI to get. I know sometimes people talk about the importance of human judgment or human taste. And sometimes you wonder, all right, what is taste? Is this fuzzy thing? But to me, the technical thing that underlies why humans have better judgment and better taste than AI is this context advantage. and because this is a long-term advantage like no one's going to solve this you know in a few years this is why we just need a lot more humans with that judgment and taste to keep on complementing the ai and doesn't this make education even more important because education always gives us context it's another another thing i'm hearing about ai like you won't need education because all the information is at your fingertips you just ask chadgpt but when you say context and taste For me, that's years of acquiring knowledge and learning from the best and seeing how they perform versus just asking a chat.

14:19I'm going to say something that may be controversial. I don't know if I've said this publicly, but I think it's true, which is frankly, AI models are terrible for learning. I know people think AI is wonderful at getting things done. Use it all the time, love it. But all the data that's coming out is that when, say, college students use AI, we know this. It's just the studies now back up as well, so we also have numbers. But the data is very clear. Students score higher on homeworks when they use AI. Yay, higher homework scores. But retention, their long-term performance is much worse because their AI do the work for them.

14:59More and more studies are coming out to back this up now that I think people think, oh, it turns out, you know, So I think Wikipedia is a wonderful tool. It has tons of facts. Web search is a wonderful tool. It has tons of facts. But it turns out that when you ask AI to do work for you, you are cognitive offloading to AI, which is great because that's how society moves forward and gets work done. But human retention is much worse. It's just so clear that LMs, as they are most commonly used, are terrible for learning. I'm not saying there's no way to use it in a way that is good for learning. I think there are ways to use that are good for learning.

15:37But even for myself, there's so many things on the AI model over the last six months or whatever. Like, I don't know, building some project. How does this front-end, back-end component work? Whatever. Give me the answer. Get the job done. It was fantastic. But six months later, I don't remember the answer when I need to redo that front-end, back-end component. I asked the AI again. So data is really clear. We should stop thinking of AI as helpful for learning. at least the vast majority of ways that the vast majority of people are using AI models today is absolutely terrible for learning. But you're building a company helping solve that, right?

16:11Because the one-to-one tutoring with AI is that where you just announced with a hundred million investment from Coursera. Yes. So I'm excited about leading a new organization called Learn Vector that is focused on building new learning experiences that is much more one-to-one than one-to-many. So, you know, 15 years ago, I was privileged to participate in the online causes movement that I think changed the way a lot of people learn. But that was and still remains largely a one-to-many experience where everyone kind of watches the same video, which is actually okay. It actually works well. But the technology now exists to create much more personalized, customized one-to-one experiences.

16:52And so our team was working hard on that. I think we'll have a lot more to show by early next year. When I think about human skill development, I feel like because AI has so heavily impacted software engineering, what we see happening in the job market for software engineering is a harbinger or is a forerunner of what we'll see in other disciplines as well. And in software engineering, people need to learn new skills. But when they do, they are thriving and creating more value and frankly getting raises and doing even more exciting projects. And what I'm seeing the early signs of in other disciplines as well, for example, in software engineering, you know, most developers like front-end, back-end developers have now become full-stack developers.

17:32Because of AI help, you could take on broader scope. I'm seeing early signs of this in other disciplines as well, where, for example, someone in marketing that did marketing coordination, coordinated marketing campaigns with AI help, they can now become more of a full-cycle marketing, take on a broader scope. And I'm seeing, frankly, sources in recruiting become more full cycle, do end-to-end recruiting. So now the good news and bad news is for people to step up to these broader roles, you do need to learn AI skills. But also it's not just learning AI. You also need to learn these other skills, like how do you do the other parts of marketing or recruiting or software engineering or AI engineering.

18:09So I think this actually creates a heavy need, a big need for people to gain new skills. But when they do, which is both AI skills, but also disciplinary skills, then they can do much more, hopefully have more fun, work on more exciting projects, hopefully get paid more as well. And one reason I kind of worry about the fear mongering is I got an email from someone that was about to enter college. And, you know, he emailed me saying, hey, Andrew, taking online courses, but I'm really struggling with what I should major in college because in four years, won't AI do all this and everything I learned will be obsolete?

18:43And the answer is no, of course it won't all be obsolete. But when we keep on pushing these fear messages, we make people wonder if they will even be relevant. And it makes people not lean in to gain these skills. They'll put them in a much better position. So I see very clearly that these fear-mongering messages are distorting how many people, including high school students, college students, fresh rats, think about the economy. and frankly, making people give up is one of the worst things we'll be doing in this era when people that lean in will thrive. Andrew has taught over 8 million people AI.

19:21He started teaching machine learning online back in 2011, years before the current AI boom. Now one of the companies he's building is focused on AI agents. From the way that it sounds, it can still feel way too technical. So I put together a step-by-step guide to building your first AI agent with no coding required. It walks you through what to automate, how to set it up, and how to make it actually useful. It is in my newsletter this week. The newsletter is called Future Proof. It's free. Link is in the description. What would you reply back to that email that somebody sent you? What would you say is the best major to study now to thrive in AI era?

19:58Do you think it's like going deep into a niche or just broader computer science so that you can acquire AI skills really fast? You know, I don't know what's the best major. There are awful lot of great majors. is like, I kind of feel like what's the best job in the world is like, what's the best major in the world? Something that you love, right? Yeah. My daughter wants to be an astronaut. I don't know if she can major in becoming an astronaut. I have to think about that. When she gets older, she may change her mind. I see so many opportunities across so many job roles. It all seems very exciting to me.

20:27But do learn AI, do learn to build with AI. The other thing that my team's been working on an AI engineering skills map to try to map out the most important the schools for AI and engineering. One thing that I felt intuitively, but I was surprised to see it show up in the data, was that a lot more job descriptions seem to be saying they want people that demonstrate a very high sense of agency. Because it turns out with AI, there are a lot more opportunities for individuals to spot problems and go build something or do something to go solve it. So I think we're really evolving. Well, we've long been evolving, but we're accelerating past the era where people sit around and wait for their boss to tell them what to do.

21:06This is what I've been feeling a lot, especially when we started doing remote work. I want people to be entrepreneurs within their niche. Like if you're helping me with LinkedIn, you're an entrepreneur there. You can hire more contractors. You can deploy different tools. You make the strategic decision whether this topic is good or not. Shall we proceed with it? I really think, and tell me if you agree with me, we're moving into that job market where everyone is kind of independent in their workplace. I think people will have much more autonomy and creativity. So I agree with that. And I'd even go one step further, which is I talked to a lot of people, engineers and others in large companies that tell me that their manager tells them to stay in their swim lane.

21:44They'll say, oh, I have this creative idea, but the manager says, no, I need to focus on this one thing, frankly, often because their manager's career depends on it. But I feel like the number of opportunities for people to spot things outside their swim lane. And then in a responsible way, explore how to get it done. That feels very exciting to me. And I think that in the future, the businesses that set up a culture that encourage people to learn AI, build fast, responsibly, talk to customers, would drive a lot more value than the more hierarchical silo organizations. Yeah, it starts with hiring the right people and then nurturing this in your organization.

22:22When you say learn how to use AI and become proficient with AI, can you give me some benchmarks of a person who's, say, a marketer, knowledge worker, advanced with AI? What are you looking for when you're interviewing this person? I'm pretty sure my team's ahead of the curve. All of my marketers know how to code. So as part of how I interview marketers, we ask them what they've built and if they have not built any software. If it's a dashboard, is it good or bad? Is it too basic? A dashboard, again, my team's somewhat ahead of the curve. It's good to hear like that. All of my marketers have built much more sophisticated things in dashboards.

22:58Like what? Oh, I feel like, I don't know, the other day, someone on the marketing team was talking about the tools that he had built to when he's considering writing an article on something, it will crawl the web, find related work, has a custom desktop app, actually build a desktop app that runs on his Mac to highlight related articles for him. Then you can chat to the whole system, navigate, you know, the thing he's writing as well as the related work. And he had a large dashboard for trolling the internet to highlight to him exciting things that are popping up. Now, even on my team, I think that market is ahead of the curve.

23:34But that's great to hear. Any other interesting use cases that will inspire people to build something similar? Let's see. Maybe my finance team uses AI extensively. So I think one of my CFOs realized that her team was spending hours every week clicking through documents, open this, copy, paste this number here. And so she started building automation scripts that runs on a routine that automatically opens files, checks what's in there, checks for consistency, highlights for her team if there's something they need to be paying attention to, if a new document has showed up. So I find that rather than waiting around for an engineer to do the work for them, the team's ability to kind of not just build dashboards, but build kind of a data management infrastructure.

24:26They can ingest data, alert them if something's happening. I think my finance and marketing teams are doing that. Oh, my recruiting team. Well, we actually have recruiting engineers, which are really professional engineers that sit in a recruiting team. They're building very sophisticated tools for recruiting. And this is actually the other trend. I think marketers, recruiters, HR professionals, ops people should all learn AI. But the other thing is when you take an engineer and embed them in these teams, then that further accelerates what you can do. We do the same. We start with something basic, build it ourselves.

24:57Then we hit the wall, an engineer comes in, we build it further. Frankly, when you look at not just software engineers, but recruiting engineers, marketing engineers, HR engineers, I think there's so much valuable engineering work that can now be done. I'm just, you know, not worried about running out of, And frankly, all my friends were so busy. We think, boy, how could we run out of engineering jobs? Yeah, there are so many cool ideas you can experiment on. But you touched upon something that is actually one of the fears. When we talk about financial information, how much you're giving to AI.

25:25So I gave my perplexity permission to scan my Fidelity account so it can track my portfolio, tell me when to rebalance. It doesn't do anything on my behalf, but it has access. Do you think there is any problem with that? This is complicated. I think AI privacy is a complex area, and it depends a lot on the company that you are sharing your data with. So, for example, I trust all the hyperscalers to really 100%, you know, follow their terms of service and to do what they say. My personal opinion, not giving me equal business advice, but I'd be shocked if, you know, the largest hyperscalers publish the terms of service with some privacy notice and if they breach that.

26:06Because that'd be not the culture, it'd be so damaging of the long-term business model. Now, that's on the largest hyperscaler side. If you look at AI company's side, there's been, you know, at least one company that I won't name that seems to occasionally change the terms of service. And if you're using it, you go to the website, so you pop up, hey, we changed the terms of service to retain your data or train your data. And if you aren't paying attention and click the wrong button, then they suddenly gave themselves permission to access your data in a way that I'm not that comfortable with. I feel like I handle, you know, some sensitive information, So then I tend to be very careful with the businesses that I just don't feel their culture and their DNA and frankly, the long-term business model is as tied to protecting individual user privacy than the hyperscalers.