In 1994, Intel acknowledged a bug in its Pentium processor that produced incorrect results in some rare circumstances. Intel calculated that the average user would hit this bug once every 27,000 years. Consumers reacted quite negatively to this news, and Intel was eventually forced to recall processors worth some 500 million USD.

Ever since computers were invented we have marveled their perfection. Machines are good at what human’s aren’t: reproducibly repeating billions and billions of calculations, never once making a mistake. We have come to embrace this expectation as a fundamentally held belief: machines are flawless. Intel violated this expectation through its now infamous FDIV bug, and it reaped customers’ wrath for it.

AI is about to do what Intel failed to do in 1994: reshape our expectations in computers.

The past of computers belongs to software and software is deterministic. If you send data through a program, there is a certain output we expect, and we can reason over why that output was produced, or why not.

AI is inherently non-deterministic. One of the strength of AI is that it allows us to solve problems we simply don’t know how to write algorithms for. For decades researchers struggled to write algorithms that recognize handwriting, for example. The advent of modern machine learning solved this problem without actually solving it. We still have no clue how to design an algorithm that recognizes handwriting, but we successfully used machine learning to create models that do so.

The caveat is that AI recognizes handwriting probabilistically. Even a perfectly well shaped letter or number may at any time be completely misread by a model. Well trained models are mostly right, most the time, and well … sometimes randomly wrong.

And thats not a bug. Its simply a fundamental property of AI as a probabilistic data-driven system. The key strength of AI is that it can produce often correct results for data it has never seen before. And this key strength is also its key weakness. There is simply no guarantee that the results will be correct for any particular input. At best we can make probabilistic predictions regarding accuracy.

So are consumers going to revolt against AI making mistakes the way they revolted against the FDIV bug 20 years ago? I don’t think so. The more “human-level” problems (voice recognition, image recognition) AI solves, the easier it becomes for us humans to relate to machines making mistakes. We make similar mistakes ourselves, after all. If Siri misunderstands my voice command in a noisy environment, its hard to get upset about that. Humans sometimes also have to ask again if there is a lot of background noise. Machines solving problems that humans naturally solve and sometimes fail at on a daily basis will help us adapt to this new world where machines make mistakes. To use psychology terminology, its a lot easier to have empathy for AI than for an algorithm.