Teaching AI to think ethically

| | July 15, 2020
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This article or excerpt is included in the GLP’s daily curated selection of ideologically diverse news, opinion and analysis of biotechnology innovation.

[M]athematicians have developed a model that can help businesses spot when commercial AI systems might make shady choices in the pursuit of profits.

Modern AI is great at optimizing—finding the shortest route, the perfect pricing sweet spot, or the best distribution of a company’s resources. But it’s also blind to a lot of the context that a human making similar decisions would be cognizant of, particularly when it comes to ethics.

As an example, most people realize that while jacking the price of a medicine up during a health crisis would boost profits, it would also be morally indefensible. But AI has no sense of ethics, so if put in charge of pricing strategy this might seem like a promising approach.

The key is to focus on the strategies likely to provide the biggest returns, as these are the ones the optimization process is likely to settle on. The authors recommend ranking strategies by their returns and then manually inspecting the highest-ranked ones to determine if they’re ethical or not.

Related article:  Viewpoint: Working with drug companies to help terminally ill patients gain access to experimental drugs

This will not only weed out the unethical strategies most likely to be adopted, they say, but will also help develop intuition about the way the AI approaches the problem and therefore have a better understanding of where to look for other problematic strategies.

The hope is that this would make it possible to then redesign the AI to avoid these kinds of strategies.

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