One of the promises of AI is that it can reduce workloads so employees can focus more on higher-value and more engaging tasks. But according to new research, AI tools don’t reduce work, they consistently intensify it: In the study, employees worked at a faster pace, took on a broader scope of tasks, and extended work into more hours of the day, often without being asked to do so. That may sound like a win, but it’s not quite so simple. These changes can be unsustainable, leading to workload creep, cognitive fatigue, burnout, and weakened decision-making. The productivity surge enjoyed at the beginning can give way to lower quality work, turnover, and other problems. To correct for this, companies need to adopt an “AI practice,” or a set of norms and standards around AI use that can include intentional pauses, sequencing work, and adding more human grounding.

Federal Reserve Bank of San Francisco Working Paper 2026-02

My "MixtapeTools" repo

I have a new working paper with Bart Wilson titled: “You Wouldn’t Steal a Car: Moral Intuition for Intellectual Property.”  The title of this post, “everyone take copies,” comes from a conversation between the human subjects in an experiment in our lab, on which the paper is based. The experiment was studying how and when […]

Without a framework of “Artificial Integrity,” AI search platforms risk collapsing the information commons that made the web possible.

A New York magazine article titled “Everyone Is Cheating Their Way Through College” made the rounds in mid-2025. I think about it often, and especially when I get targeted ads that are basically variations on “if you use our AI tool, you’ll be able to cheat without getting caught.” Suffice it to say it’s dispiriting. […]

A look at the New York Fed’s new regularly updated labor market tightness index and how it tracks wage inflation.

What if organizations decided to treat their entire hiring process (not just who they hire), as a competitive advantage rather than a wearisome chore?

MIT labor economist David Autor discusses how AI is shaping the future of work and the labor market on The Ongoing Transformation podcast.

From Duolingo to GDP, how an obsession with keeping score can subtly undermine human flourishing

by Barry Goldman

The availability heuristic teaches us that easily recalled information feels more probable. But in an era of information abundance, this bias has evolved: what we don't see—when we expect to—becomes evidence of impossibility. This essay introduces 'UnAvailability Bias'—the tendency to treat absent information as proof of nonexistence, ignoring institutional, legal, or cognitive constraints that explain