My opinion on the subject of AI safety has to-and-fro'd from "not a concern" to "we are headed to our doom" to finally "it probably won't be as bad". My intention with this writeup is to provide some assurances that, although very much real, these risks would not become a concern if we assume that the basics of technical product development, safety engineering, and economic principles are followed. Let's first unpack what we mean by intelligence (artificial or not). Objectively, it is the ability to predict and/or to have control of the future for ones benefit. The farther the time horizon for this prediction and control, the more intelligent that entity is.

Inspired by news that Vladimir Putin had told Russian students the country that leads in artificial intelligence will rule the world, the Tesla and SpaceX CEO declared the global race to dominate AI might turn into real war--and that the first strike could well be launched by an algorithm rather than a flesh-and-blood leader. Chastised by one of his followers for the gloomy prognostication, he apologized and then confessed, "I was depressing myself too. Musk is a techno-provocateur with few equals. However, plenty of people share his take on AI. Even sunnier forecasts about the future of AI, detailing how self-driving cars might radically reduce highway carnage, are typically too long-range to offer much of a sense of comfort.

A robot looks at visitors at the Soft Bank robotics stand at the Cebit technology fair in Hannover on March 20, 2017. The Digital Business fair CEBIT in Hanover with Japan as partner country runs from March 20 until March 24. I've written a number of times about the impact automation will have on both the wider world and on the way we work, and am broadly speaking optimistic about the role new technologies will play in the labor market. Indeed, a recent paper highlighted the minimal impact technology has had on the amount of jobs created in recent economic recoveries. Of course, this doesn't stop a great many articles emerging in the past few months highlighting the huge (negative) impact automation will have.

For the past several years, we have been using robots in our introductory computer science course. Although this has been challenging for many reasons, it has also been very rewarding on a number of fronts, both for the students and for us. However, in order for this to occur, we had to adapt to what we perceived as “chaotic code.” In this paper we describe lessons learned by watching what the students do, where they have trouble, and what they enjoy. Further, we discuss what the implications of focusing on creativity has had on teaching and assessment.