Bill Hibbard is an Emeritus Senior Scientist at the University of Wisconsin-Madison Space Science and Engineering Center, currently working on issues of AI safety and unintended behaviors. He has a BA in Mathematics and MS and PhD in Computer Sciences, all from the University of Wisconsin-Madison. He is the author of Super-Intelligent Machines, “Avoiding Unintended AI Behaviors,” “Decision Support for Safe AI Design,” and “Ethical Artificial Intelligence.” He is also principal author of the Vis5D, Cave5D, and VisAD open source visualization systems.
Luke Muehlhauser: You recently released a self-published book, Ethical Artificial Intelligence, which “combines several peer reviewed papers and new material to analyze the issues of ethical artificial intelligence.” Most of the book is devoted to the kind of exploratory engineering in AI that you and I described in a recent CACM article, such that you mathematically analyze the behavioral properties of classes of future AI agents, e.g. utility-maximizing agents.
Many AI scientists have the intuition that such early, exploratory work is very unlikely to pay off when we are so far from building an AGI, and don’t what an AGI will look like. For example, Michael Littman wrote:
…proposing specific mechanisms for combatting this amorphous threat [of AGI] is a bit like trying to engineer airbags before we’ve thought of the idea of cars. Safety has to be addressed in context and the context we’re talking about is still absurdly speculative.
How would you defend the value of the kind of work you do in Ethical Artificial Intelligence to Littman and others who share his skepticism?