Ben Todd: evaluation

Transcript context

…Yeah, in the book there's many different frameworks, but we have this one which I call the career framework. And if you're comparing a list of options and you want to do a side by side on them, what things should you look for? And yeah, that in brief is the impact of the option, the career capital you'll get from it, which is overall career development, skills, connections, credentials, character, your personal fit. So how good you will be at it compared to other people, all the other things that matter for job satisfaction and your personal goals. And then you could have exploration value at the end. So that's what will this taking this job tell you about which jobs are best for you in general? What will you learn about your career from taking this? Because many jobs are an experiment as well. And then with the effect of AI, the key thing is the longer your time horizon, the more important gaining career capital and exploring are, because you have more time to make use of those skills you've gained and that information you've gained about what fits you best. And the more you have a short time horizon, the more you just focus on doing whatever is best in the next couple of years. And so as AI timelines have come down, career capital and exploration value are a bit less weighted. But you wouldn't ignore them entirely. And one way to see that is like, suppose you have a very short timeline and you think, okay, and also to be clear here, when I say timeline, what I actually mean is not when we will have AGI. It's not an AGI timeline. What matters is which years will be most impactful. So if you want to have an impact, which At which point will you be able to have the biggest impact? And the time between now and then is basically your time horizon for acting. It's like when the best opportunities are. And so if you're very focused on AI, that will probably be the years immediately before and after AGI is developed. Though in a slower takeoff, it could be 10 or 15 years after might still be all kinds of crazy stuff happening that you could help with. So probably your timeline shouldn't be 3 years. Like in expectation, there will be things to do after three years that are really impactful as well. So you should probably be planning over. Ajaya Kotra had this recent post about whether you should get married. And she said the expected length of your marriage now is 10 years, which was like her averaging over different timelines in terms of like when the world would just become like so crazy that it's not worth planning beyond that. And maybe 10 years, it feels like a little bit long for a career planning timeline, but something like 5 or 10 years, I think everyone should be thinking about at least that long a period. And then, should you ignore career capital and skill development? No, because if you could spend one year and make yourself 20% more productive, you would recoup that after roughly four or five years. And then, should you ignore career capital and skill development? No, because if you could spend one year and make yourself 20% more productive, you would recoup that after roughly four or five years. So even if you only had a five year timeline, time horizon, you should still make those investments that will pay off over that period. And there's often a lot of things people can do to increase their impact by more than 20%. Yeah, retraining in machine learning, lots of people have done that. Or entering a policy career, you can often transfer into one in a year and then maybe have much more impact after that. So yeah, I still think it is really worth thinking about. what you can do to maximize your impact over that whole time horizon, but it's just a bit shorter than in the conventional world where maybe you have 40 years to play with and you can really invest for 10 or 20 years and then pay it all off in your 50s. Let's also talk for a minute about what you think people should be trying to move the needle on. AI is one of the premises of this show and one of the reasons I enjoy making it so much is that it's obviously a general purpose technology, a horizontal layer, something that kind of intersects with everything. And so increasingly like work in AI is almost saying nothing because it's like in any sector, in any business, there's going to be some sort of AI touch point soon, if not already. What do you think are the big levers that really matter most? And maybe give a little argument for each of those big focus areas.…

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