Research works best when it takes account of multiple viewsby Vincent Conitzer / March 6, 2017 / Leave a comment
Progress in artificial intelligence has been rapid in recent years. Computer programs are dethroning humans in games ranging from Jeopardy to Go to poker. Self-driving cars are appearing on roads. AI is starting to outperform humans in image and speech recognition.
With all this progress, a host of concerns about AI’s impact on human societies have come to the forefront. How should we design and regulate self-driving cars and similar technologies? Will AI leave large segments of the population unemployed? Will AI have unintended sociological consequences? (Think about algorithms that accurately predict which news articles a person will like resulting in highly polarised societies, or algorithms that predict whether someone will default on a loan or commit another crime becoming racially biased due to the input data they are given.)
Will AI be abused by oppressive governments to sniff out and stifle any budding dissent? Should we develop weapons that can act autonomously? And should we perhaps even be concerned that AI will eventually become “superintelligent”—intellectually more capable than human beings in every important way—making us obsolete or even extinct? While this last concern was once purely in the realm of science fiction, notable figures including Elon Musk, Bill Gates, and Stephen Hawking, inspired by Oxford philosopher Nick Bostrom’s Superintelligence book, have recently argued it needs to be taken seriously.
These concerns are mostly quite distinct from each other, but they all rely on the premise of technical advances in AI. Actually, in all cases but the last one, even just currently demonstrated AI capabilities justify the concern to some extent, but further progress will rapidly exacerbate it. And further progress seems inevitable, both because there do not seem to be any fundamental obstacles to it and because large amounts of resources are being poured into AI research and development. The concerns feed off each other and a community of people studying the risks of AI is starting to take shape. This includes traditional AI researchers—primarily computer scientists—as well as people from other disciplines: economists studying AI-driven unemployment, legal scholars debating how best to regulate self-driving cars, and so on.
A conference on “Beneficial AI” held in California in January brought a sizeable part of this community together.…