A new MIT Sloan article offers a fascinating window into how leading thinkers are reframing the conversation about artificial intelligence (AI) and its role in the workplace. Economists David Autor and research scientist Neil Thompson argue that the real story of AI is not simply about machines replacing human labor, but about how thoughtfully — or carelessly — we design systems that interact with human expertise.
The two have cautioned against the assumption that productivity gains are automatic. While generative AI can accelerate certain tasks, such as coding or drafting text, it often introduces new friction: time spent crafting prompts, verifying outputs, and waiting for models to respond. This paradox means that workers may feel faster and more capable, even when studies show their overall efficiency has not improved.