As artificial intelligence reshapes the workplace, this former OpenAI researcher has some advice for how professionals can succeed.
"For motivated, ambitious, early-career individuals, I now have a clearer perspective on what skills are valuable in the coming decade," Phil Chen, who has since gone on to found an AI startup, recently said in an online post titled "Career advice in the age of AI."
Chen, who previously worked as a software engineer at Google DeepMind and Scale AI, wrote that as AI becomes more capable of handling "complex, well-defined problems," the people who will have the greatest impact will be those who excel at identifying important problems "and then allocating tokens and time to solving them."
"The most important skills will be the ones related to problem selection and resource allocation," Chen said.
At the top of his post, Chen wrote, "AI models get better at anything you can write a loss function for," and argued that school is "mostly loss functions: well-defined problems graded against known answers."
"Therefore," he said, "the valuable work of the next decade is everything that can't be graded within the span of model training."
Chen advised early-career professionals to focus on what he called the only "truly limited" resources: "time, relationships, and reputation."
Capital is easier than ever to secure, he argued, but strong, human connections are still hard to come by.
"Proven excellence in past, related endeavors remains of the highest signal, so my concrete advice is to spend time doing good work and ensuring it's known to other reputable people who themselves do good work," he wrote.
Chen added, "Relentlessly prioritize your time so that whatever you work on, whether it be school, projects, or internships, you focus on problems that you find meaningful."
He also encouraged young professionals to "work on the most ambitious form of a problem" and "sprint the last mile."
Looking further ahead, Chen said that he does not believe that artificial superintelligence will replace humans in what he called "knowledge work jobs" because "humans have differential capabilities in selecting meaningful problems for ASI to solve, and in allocating capital to solve these problems."
"Not every opportunity will materialize into a goal, but being in the right position to see the opportunities is the first step to scoring goals," he wrote. "This again comes down to reputation and expertise."