How (and how not) to fix AI

While artificial intelligence was once heralded as the key to unlocking a new era of economic prosperity, policymakers today face a wave of calls to ensure AI is fair, ethical and safe. New York City Mayor de Blasio recently announced the formation of the nation's first task force to monitor and assess the use of algorithms. Days later, the European Union enacted sweeping new data protection rules that require companies be able to explain to consumers any automated decisions. And high-profile critics, like Elon Musk, have called on policymakers to do more to regulate AI. Unfortunately, the two most popular ideas -- requiring companies to disclose the source code to their algorithms and explain how they make decisions -- would cause more harm than good by regulating the business models and the inner workings of the algorithms of companies using AI, rather than holding these companies accountable for outcomes. The first idea -- "algorithmic transparency" -- would require companies to disclose the source code and data used in their AI systems.