Why Your Next AI Hire Should Have a Major Failure on Their Resume
Artificial IntelligenceStartupsfailure
Everyone wants to hire from successful AI teams. This is a mistake. The most valuable people for your next AI project are the ones who have been through an initiative that completely cratered. Success stories are clean, retrospective narratives. Failures are messy, complex systems problems.
Synthesized Answer
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When hiring for AI projects, it's beneficial to look for candidates who have experienced significant failures in their previous endeavors. These individuals have gained practical knowledge about the complexities and challenges associated with AI initiatives, such as biased training data, brittle data pipelines, and unrealistic stakeholder expectations. They have developed a critical perspective that allows them to identify potential pitfalls and ask crucial questions, making them valuable assets for future projects. By focusing on failure experiences, you can assess a candidate's systems thinking and intellectual honesty more effectively than by solely examining their success stories. This approach enables you to build a more resilient team capable of proactively mitigating risks that commonly derail AI projects.
Key Takeaways
Candidates with failure experience have practical knowledge about AI challenges
They develop a critical perspective to identify potential pitfalls
Focusing on failure experiences assesses systems thinking and intellectual honesty
When I interviewed candidates I asked them to drill down with a little more detail. And after that response, if I did not get a sense they were pounding their head on a wall, I’d ask them to drill down another level. At some point, I was looking for them to walk me thru some incredible complexity that really challenged them. I’d expect them to be able to explain it, as they should if they experienced it first hand.