By Scott Zoldi
For decades, leaders in many industries have held a blanket, negative view that government regulation inhibits innovation. With AI, this view couldn’t be further from the truth, with necessity being the mother of invention. Regulators and legislators are, in fact, trying to protect consumers from the negative effects of technology-in reality, the human creators that misuse AI/ML. These regulations cause constraints, create new requirements, and necessitate standards that require non-stop innovation.
Granted, at the opposite end of the regulatory spectrum, there are the companies that clasp their metaphorical hands and say, “We are ethical. We will do no evil with your data, and need no external oversight,” although, without a standard of accountability, we won’t know for sure.
Effective AI regulation will do much to ensure fairness and inculcate responsibility. As I saw in my crystal ball of AI Predictions for 2020, international standards are emerging to define a framework for safe and trusted artificial intelligence.
Model governance is essential in regulating AI, and blockchain technology is at the heart of building AI models that are ethical and auditable. Blockchain, which records transactions of any kind and maintains the record across a peer-to-peer network, is in use today to ensure that all decisions made about a machine learning model are immutably captured and auditable.
Although AI is a pervasive technology, there is growing mistrust of the propriety and ethics of many companies that use it. As a data scientist, this is disheartening, and not exactly what I envisioned blogging about when I started my AI Predictions blogs in 2016. However, as modern society discovers more about the damage that can be done by misuse of artificial intelligence, it’s clear that experience, not “move fast and break things” matters. AI regulation is necessary because, simply put, regulation keeps companies honest.
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Scott Zoldi is the Chief Analytics Officer of FICO. Follow him on Twitter @ScottZoldi.
