Machines Like Us and People Like You: Toward Human–Robot Shared Experience

Building Machines That Learn and Think Like People

Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans in some respects. Despite their biological inspiration and performance ach...

If You Like Radiohead, You Might Like This Article

the world of music. Musicians use inexpensive personal computers instead of expensive recording studios to record, mix, and engineer music. Musicians use the Internet to distribute their music for free instead of spending large amounts of money creating CDs, hiring trucks, and shipping them to hundreds of record stores. As the cost to create and distribute recorded music has dropped, the amount...

Moving Beyond eHealth Systems for 'People Like Us'

and Objective The tendency to design personal ehealth systems for well to do technically literate professionals, rather than average or disadvantaged users (the PLU problem), has been described previously, but is not yet well understood. This interactive workshop will introduce attendees to the PLU problem, expose them to a simulated experience of being a disadvantaged system user, and encourag...

What you like...what you don't.

Why do I like people like me?

In many dimensions the ability to assess knowledge depends critically on the observer's own knowledge of that dimension. Building on this feature, this paper offers both theoretical and empirical evidence showing that, in those tasks where multidisciplinary knowledge is required, evaluations exhibit a similar-to-me effect: candidates who excel in the same dimensions as the evaluator tend to be ...