The amount of money and industrial energy that has been put into accelerating AI code has meant that there has... — Kate Crawford

The amount of money and industrial energy that has been put into accelerating AI code has meant that there hasn't been as much energy put into thinking about social, economic, ethical frameworks for these systems. We think there's a very urgent need for this to happen faster.

Author: Kate Crawford

Insight: We've built a massive engine before we figured out where we want it to go. That's the real tension with AI right now—the technical side has sprinted so far ahead that the harder questions about fairness, power, and who actually benefits have been left in the dust. It's like we invented the printing press and only later started asking who gets to operate it and what they're allowed to print. The gap matters because code moves fast but consequences move slower. A biased algorithm can affect millions of people's credit scores, job prospects, or bail decisions before anyone even notices the problem. By then, it's already baked into systems. We're not talking about shutting down innovation—it's that we need the thinking to catch up. The ethical framework questions aren't obstacles to progress; they're actually essential infrastructure, like safety standards in bridges or drugs. What's interesting is this isn't really about technologists being careless. It's a structural problem. Money, talent, and attention flow toward building the next breakthrough. Thinking carefully about societal impact is harder to fund, harder to measure, and harder to get excited about in a competitive market. But that's exactly why it needs deliberate focus—because the market alone won't provide it.