Summary of How We Can Teach Computers to Make Sense of Our Emotions

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How We Can Teach Computers to Make Sense of Our Emotions summary


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AI can beat humans at chess but has yet to grasp human intuition and complex emotions. Artist and AI researcher Raphael Arar says art could help bridge the chasm between computers and humankind. In an eloquent talk, the Forbes 30 Under 30 awardee presents a fresh approach to helping machines be more like humans. getAbstract recommends his talk to tech-industry professionals and anybody who appreciates out-of-the-box thinking.   

In this summary, you will learn

  • How art can help artificial intelligence (AI) learn and express human emotions, and
  • How AI-powered artworks can enhance AI research. 

About the Speaker

Raphael Arar is a designer and researcher at IBM Research and an adjunct faculty member at San Jose State University’s Cadre Laboratory for New Media.



Art may help bridge the chasm between computers and humankind. The vast diversity of humans’ experience, psychology and emotion doesn’t always translate to numeric data or computer code. Thus, researcher Raphael Arar is using art to help machines understand complex human concepts, such as what an emotion feels like and how intuition shapes interaction. Computers can convert basic emotions, such as joy or sadness, to math. But sentiments such as nostalgia stymie them. Thus, Arar sought to convey nostalgia through art: He created an installation that invited participants to describe a memory. A computer determined each memory’s degree of nostalgia by assessing the speaker’s basic emotions and verbal cues, such as past-tense words. Arar then rendered the computer-generated “nostalgia score” in light-based sculpture. The higher the nostalgia score, the rosier the depicted hue. Some people agreed with the representation of their scores, and others didn’t. The mixed results emphasize the difficulty of teaching computers about emotions that humans struggle to explain among themselves.

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