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Emotional Computation in Artificial Intelligence Education

AAAI Conferences

After decades of work towards creating artificial intelligence, some researchers are now attempting to create machines that are emotionally intelligent. The standard definition of artificial intelligence is the ability for a machine to "think or act humanly or rationally" (Russell, 1995). The push towards emotionally intelligent machines is an exciting addition to this field, in the direction of machines that truly "act humanly." In this article, I will provide a survey of topics and resources for teaching emotional computation in artificial intelligence courses. I will show that this topic area serves as an excellent application of modern artificial intelligence techniques, and is an important aspect of modern research in AI. The interdisciplinary nature of work in this space is not only compelling in the classroom, it may also lead to wider interest in the field of Computer Science.


Experts say AIs will soon understand our emotions

#artificialintelligence

How would you feel about getting therapy from a robot? Emotionally intelligent machines may not be as far away as it seems. Over the last few decades, artificial intelligence (AI) have got increasingly good at reading emotional reactions in humans. If AI cannot experience emotions themselves, can they ever truly understand us? And, if not, is there a risk that we ascribe robots properties they don't have?


The rise of the robot interrogator: Experts say AIs will soon understand our emotions

Daily Mail - Science & tech

How would you feel about getting therapy from a robot? Emotionally intelligent machines may not be as far away as it seems. Over the last few decades, artificial intelligence (AI) have got increasingly good at reading emotional reactions in humans. If AI cannot experience emotions themselves, can they ever truly understand us? And, if not, is there a risk that we ascribe robots properties they don't have?


Designing For The Internet Of Emotional Things – Smashing Magazine

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More and more of our experience online is personalized. Search engines, news outlets and social media sites have become quite smart at giving us what we want. Perhaps Ali, one of the hundreds of people I've interviewed about our emotional attachment to technology, put it best: "Netflix's recommendations have become so right for me that even though I know it's an algorithm, it feels like a friend." Personalization algorithms can shape what you discover, where you focus attention, and even who you interact with online. When these algorithms work well, they can feel like a friend. At the same time, personalization doesn't feel all that personal. There can be an uncomfortable disconnect when we see an ad that doesn't match our expectations. When personalization tracks too closely to interests that we've expressed, it can seem creepy. Personalization can create a filter bubble1 by showing us more of what we've clicked on before, rather than exposing us to new people or ideas.


'Stereotyping' emotions is getting in the way of artificial intelligence. Scientists say they've discovered a better way.

#artificialintelligence

Understanding an emotion isn't as simple as noticing a smile-- but we still look to facial movements for everything from navigating everyday social interactions to the development of emotionally attuned artificial intelligence. According to a July 2019 study from researchers at Northeastern and the California Institute of Technology, facial expressions only reflect the surface of emotions: The culture, situation, and specific individual around a facial expression add nuance to the way a feeling is conveyed. For example, the researchers note that Olympic athletes who won medals only smiled when they knew they were being watched by an audience. While they were waiting behind the podium or facing away from people, they didn't smile (but were probably still happy). These results reinforce the idea that facial expressions aren't always reliable indicators of emotion.