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I think these objects are maybe true but not relevant. The leading example of the article was about Zooom videos, not single frames, and in a school setting yo

I think these objects are maybe true but not relevant. The leading example of the article was about Zooom videos, not single frames, and in a school setting you presumably know what culture the students are from, so I don't think you need it to work cross-culturally. And I don't doubt that people can deliberately hide their emotions, but many settings are not adversarial, so there would be no reason to do so. E.g., if you imagine that a teacher is teaching a lecture to a large audience over zoom and is using a "puzzlement meter" to see if they seem to be getting it, then any audience member who does feel puzzled will only gain from frowning and making the lecturer slow down. In general, I think from my experience talking to people over video chat, some emotional information does get communicated over the video, so in principle computer programs should be able to pick up on it too.

crazygringo 6y ago
> about Zooom videos, not single frames The products in question are almost certainly assessing still frames from video. There's been vanishingly little research on the time component of emotions, even though we know it's hugely important. > you need it to work cross-culturally This would then require separate training models for e.g. individual subcultures within countries as well as detecting which subcultures participants belong to. That is also far beyond anything being done currently. > but many settings are not adversarial, so there would be no reason to do so It has nothing to do with an adversarial setting, people try to hide their emotions constantly. They hide that they're fed up with their boss in front of colleagues, they hide that they're stressed with their spouse at work, they hide that they're worried the project will fail. We are emotionally regulating virtually all the time. > some emotional information does get communicated over the video, so in principle computer programs should be able to pick up on it too In principle, yes, but in practice the emotional content is so dependent upon your cultural and individual mental model of the person that you would need to model their entire psychology. "What does that long pause mean?" The point is that emotional signals are so incredibly complex and vary so much from person to person, that the difficulty of accurately decoding emotions is more akin to AI that can make conceptual inferences and hold a genuinely intelligent conversation, as opposed to mere pattern recognition.

crazygringo 6y ago

> about Zooom videos, not single frames The products in question are almost certainly assessing still frames from video. There's been vanishingly little research on the time component of emotions, even though we know it's hugely important. > you need it to work cross-culturally This would then require separate training models for e.g. individual subcultures within countries as well as detecting which subcultures participants belong to. That is also far beyond anything being done currently. > but many settings are not adversarial, so there would be no reason to do so It has nothing to do with an adversarial setting, people try to hide their emotions constantly. They hide that they're fed up with their boss in front of colleagues, they hide that they're stressed with their spouse at work, they hide that they're worried the project will fail. We are emotionally regulating virtually all the time. > some emotional information does get communicated over the video, so in principle computer programs should be able to pick up on it too In principle, yes, but in practice the emotional content is so dependent upon your cultural and individual mental model of the person that you would need to model their entire psychology. "What does that long pause mean?" The point is that emotional signals are so incredibly complex and vary so much from person to person, that the difficulty of accurately decoding emotions is more akin to AI that can make conceptual inferences and hold a genuinely intelligent conversation, as opposed to mere pattern recognition.