Tag: trustworthy AI

The term “explainability” is a multifaceted concept within the realm of computer science. In essence, it encompasses various aspects and capacities of a system to effectively convey its internal processes, decision-making, capabilities, and constraints to its users. Providing explanations can notably enhance initial trust, especially when trust is measured as a multidimensional concept that includes aspects such as competence, benevolence, integrity, intention to return, and perceived transparency.

This special issue published in cooperation with IEEE Transactions on Technology and Society (December 2021) is dedicated to examining the governance of artificial intelligence (AI) through soft law. These programs are characterized by the creation of substantive expectations that are not directly enforced by government.

Just as the “autonomous” in lethal autonomous weapons allows the military to dissemble over responsibility for their effects, there are civilian companies leveraging “AI” to exert control without responsibility.

And so we arrive at “trustworthy AI” because, of course, we are building systems that people should trust and if they don’t it’s their fault, so how can we make them do that, right? Or, we’ve built this amazing “AI” system that can drive your car for you but don’t blame us when it crashes because you should have been paying attention. Or, we built it, sure, but then it learned stuff and it’s not under our control anymore—the world is a complex place.