Benjamin Todd

For example, it's much easier to get to the top of a brand new field that's growing rapidly than an established area like law, since there are far fewer people to compete with.

Likewise, being part of the right scene can be a huge factor.

So if you've stumbled across a community, person, or organization with momentum, sticking with that may pay off.

In short, try to maximize your rate of useful learning.

In the next section, we'll cover some concrete types of jobs that people we've worked with have often found useful for improving their career capital.

There's also a lot you can do within your existing job to invest in yourself and improve your career capital.

We cover it in Appendix 2, which includes advice on building character, networking, saving money, and becoming more generally effective.

We also cover how to sell your existing career capital effectively in Chapter 10, on how to get a job.

What skills will be most valuable in the future?

Thinking of becoming an illustrator, legal clerk, or medical technician?

These jobs might soon be gone.

A 2020 analysis looked at the effects of three kinds of automation on the labor market over the past few decades, standard software, robots, and AI.

The author found that advances in IT and standard software have reduced the number of people working in highly routine or administrative jobs, while advances in robotics have replaced many manual jobs, but not those requiring social intelligence or creativity.

But it's the rapid recent advances in AI, in particular machine learning, which we think could have the biggest impact on your career.

To date, machine learning has worked best when you can gather lots of data to train an algorithm on a specific test.

So we're already seeing automation in places like running power plants or analyzing medical tests.

As we saw in Chapter 5, in the last few years, we've seen huge advances in far more general and more creative AI systems.

The most advanced AI systems can pass complex academic exams better than most humans, generate extremely realistic images from text, and solve some difficult coding problems.

None of this was possible even a year ago.

A paper from 2013, which we've written about in the past, speculated that tasks involving creativity would be among the hardest to automate.