Not with a Bug, But with a Sticker

Foreword

We all know that AI—and machine learning in particular—has the potential to upend much of society, but it's useful to tease out the details. AI is a decision-making tool, one that can replace human decision-makers. It's not a direct replacement; it's a replacement that brings with it a raft of other changes. Specifically, AI changes the speed, scale, scope, and sophistication of those decisions.

Speed and sophistication are easy: computers are much faster than people, and the promise of AI is that they will (if not now, eventually) make better decisions than people, if for no other reason than it can keep more variables in working memory—“in mind,” if we were to anthropomorphize—than people. But I want to focus on the scale.

The promise of ML is decision-making at scale. Whether it's a medical diagnosis, content-moderation decisions, individual education, or turn-by-turn driving decisions, ML systems can scale in ways that wouldn't be possible if there were people in the loop. There simply aren't enough trained medical technicians, content moderators, private tutors, or chauffeurs to satisfy the world's demand. (Facebook alone receives something like 600,000 updates every second. Assuming a five-second average to evaluate and approve a post/photo/video and a reasonable employee workweek, Facebook would have to hire at least 160,000 human moderators to do the job—which is never going to happen.)

And it doesn't have to happen because this is the problem that ML promises ...