Artificial intelligence — already a much-discussed science in recent years — moved to the center of public conversation in 2017. Leading tech voices continued to ring the alarm about the potential for a super-intelligent bot to take over the world in a very unpleasant way; others said the fears are vastly exaggerated. The latter gained more converts, namely because AI is nowhere near super-human intelligence at the moment.
We surveyed the community asking the following question: What was the most important AI story of 2017? Their answers follow.
Rodney Brooks, founder, Rethink Robotics
Andrew Ng, CEO, Landing.AI
Andrew Moore, dean, Carnegie Mellon’s School of Computer Science
The victory of the Libratus AI over four top professional poker players. This victory in no-limit Texas Hold ’em heralds a new kind of game in which the AI has to take into account that its opponent might be deliberately misleading. In a world of increasing scrutiny of what information is real or unreal, it is amazing that we are seeing the emergence of a new generation of AI that is more skeptical about raw facts.
Geoffrey Hinton, University of Toronto
- Neural architecture search: This uses neural networks to automate the black art of designing neural networks, and it’s beginning to work.
- Machine translation that uses attention to avoid the need for recurrence or convolutions.
- Alpha-zero for chess: This quickly learns to play chess in the style of a person but at a level well beyond the best chess engines.
Greg Diamos, senior researcher, Baidu
This year I was extremely impressed by the team of researchers at Stanford University who developed the first AI radiologists, which can detect heart arrhythmias and better inform human doctors. I think medical applications of AI will be very visible and surprising to many people as technology develops.
Azeem Azhar, founder Peer Index, curator The Exponential View
- The first was a talk by Kate Crawford (of Microsoft Research), who described how machine learning algorithms can go wrong, reinforcing and amplifying existing prejudices.
- The second is a paper by Adrian Weller (of the University of Cambridge), on building algorithmic systems that map to our intuitions of fairness. It is essential that we manage the downsides addressed by Kate and Adrian in order to spur the acceptance of the tech.
Terah Lyons, executive director, Partnership on AI
Been Kim, research scientist, Google Brain
Richard Socher, chief scientist, Salesforce
Perhaps the most important theme of 2017 came at the NIPS conference, earlier this month. Ethics was a core theme amongst the impressive innovation coming from the research community, serving as an important reminder to everyone that the success of AI depends on core values of trust, transparency and equality.
Alison Snyder contributed reporting to this post.
Note: this post has been updated with Geoffrey Hinton’s contribution.