Tools and Weapons: The Promise and the Peril of the Digital Age

by Brad Smith

While each of these four principles was important, we realized that they all rested on two other principles that were foundational to the others’ success. The first was transparency. To us, this meant ensuring that information about how AI systems were making consequential decisions was public and understandable. After all, how can the public have confidence in AI and how can future regulators evaluate its adherence to the first four principles if the inner workings of AI are kept in a black box? Some argue that AI developers should publish the algorithms they use, but our own conclusion was that these were likely to be less than enlightening in most circumstances or reveal valuable trade secrets that would undermine competition in the tech sector. We had already been working in the Partnership on AI with academics and other tech companies to develop better approaches. The emerging focus is on making AI explainable, like describing the key elements that are being used to make decisions.