Making sense of AI

As one fun example, I read an article about a recent social media panic - an academic paper suggested that black plastic utensils could poison you because they were partially made with recycled e-waste. A compound called BDE-209 could leach from these utensils at such a high rate, the paper suggested, that it would approach the safe levels of dosag

When models are capable enough to not just process an entire academic paper, but to understand the context in which “checking math” makes sense, and then actually check the results successfully, that radically changes what AIs can do. In fact, my experiment, along with others doing the same thing, helped inspire an effort to see how often o1 can fi

The distinction between design as mindset versus output matters more than ever—whether you are a designer or not. As AI reshapes how we create, we face uncertainty about which human capabilities will endure and which will transform.

So how do we do it? Let’s imagine that we want to come up with 20 ideas for marketing slogans for a new mail-order cheese shop. The AI can generate those for us, but we will get even better quality if we remember the principle of telling AI who it is: You are an expert at marketing. When asked to generate slogan ideas you come up with ideas that ar

So how should we use AI to help generate ideas? Fortunately, the papers, and other research on innovation, have some good suggestions. When you do include AI in idea generation, you should expect that most of its ideas will be mediocre. But that’s okay—that’s where you, as a human, come into the equation. You are looking for ideas that spark inspir

Another key aspect of idea generation is to embrace variance. Research shows that, to find good novel ideas, we likely have to come up with many bad novel ideas because most new ideas are pretty bad. Fortunately, we are good at filtering out low-quality ideas, so if we can generate novel ideas quickly and at low cost, we are more likely to generate

I’m proposing a pragmatic approach: treat AI as if it were human because, in many ways, it behaves like one. This mindset, which echoes my “treat it like a person” principle of AI, can significantly improve your understanding of how and when to use AI in a practical, if not technical, sense.

AI excels at tasks that are intensely human. It can write,