Some of the basic components of AI - algorithms, data, analytics and machine learning - have been around in the workplace for a long time. We invite people to use the term "Artificial Intelligence" broadly to mean a computer program that uses data to execute a task that humans typically perform. AI is not new. Robots performing human tasks also are not new - we've had robots in manufacturing facilities for decades. But the volume and variety of data we have available, the speed at which we can process it, and the ability for the machine to learn more sophisticated human-like decision making...these are what make AI more interesting and novel than other automation we've seen. And where things can get a bit slippery is the high level of uncertainty about the quality of the data going into the machine. If any part of your decision making today uses algorithms, advanced analytics, or advanced automation, then you have some version of AI - even without robots - and we need to focus on the quality of the data and responsibility of decisions made by us and the machine.
This past April, the European Commission released a proposal for the first-ever regulatory framework on Artificial Intelligence (AI), which includes a proposed set of rules meant to provide safety, transparency, and ethical AI development. While still in the proposal phase, leading experts believe that much like the domino effect the EU's General Data Protection Regulation (GDPR) had on states like California and its Consumer Privacy Act, we may see similar AI legislation popping up in the US over the next few years.
Sarah Alt, Director of Process Improvement & Technology Integration at Michael Best and Fellow with the Ethical AI Consortium, Inc., breaks down the timeline of when we can expect AI regulations to go into effect and how the US Federal Trade Commission has addressed AI ethics thus far in this quick informational video. Please note, Sarah is not licensed to practice law and this is merely an overview.
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