Drawing the line around AI

Most definitions of artificial intelligence are written to impress rather than to decide anything. A working definition has to do something harder: tell you whether a particular thing in your organisation is in scope for a particular rule.

The useful question is not whether a system is clever. It is whether the system infers. Ordinary software applies rules a person wrote down. An AI system derives its behaviour from data, which means nobody wrote down the rule it is applying, and often nobody can state it afterwards. That single property is what the obligations attach to, because it is what makes the system hard to predict, hard to explain and hard to hold anyone accountable for.

This matters more than it sounds. A spreadsheet that scores loan applications using a formula in column H is not an AI system, however consequential its output. A model trained on past lending decisions that produces the same score is, even if the two agree most of the time. The difference is not the consequence; it is whether a person can point at the rule.