Eric Siegel is a former Columbia University professor who helps companies deploy machine learning.
it fails to clearly define AI. Technology greatly needs oversight in certain arenas, but we should never regulate on the amorphous term “AI.”sits on Governor Gavin Newsom's desk awaiting potential passage into law, it fails to clearly define the very thing it is about, artificial intelligence. No law can be efficacious if its writing addresses only an amorphous idea, including this one.
“Can... infer from the input it receives how to generate outputs.” That's what every computer program does: It takes input and generates outputs. Its outputs “can influence physical or virtual environments.” The influence of a computer program's output is determined by how it's used. Do the outputs control a thermostat, for example? That's up to humans.Best Labor Day Clothing Sales: Score Up To 70% Off Denim, Outerwear And MoreThe bill does get a little more specific, but to no avail. It narrows the scope of what it regulates to “AI models” that fulfill certain criteria—but the result is still amorphous.
The European Commission has run into the same issue. It also announced legislative measures that define AI very broadly: as a combination of data and algorithms. Members of the Dutch Alliance on AI, it should not extend to legislative activities. Public discourse often conveys that, well, AI is hard to define—but you'll know it when you see it. That position confuses the regulation and legislation of machine learning and other technologies.
We should never try to regulate on “AI.” Technology greatly needs regulation in certain arenas, for example, to address bias in algorithmic decision-making and to oversee the development of autonomous weapons—which often use machine learning—so clarity is critical in these efforts. Using the imprecise term “AI” is gravely detrimental to the effectiveness and credibility of any initiative to regulate technology. Regulation is already hard enough without muddying the waters.
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