Don’t look now: why you should be worried about machines reading your emotions

From The Guardian.com (Mar. 6):

In recent years, technology companies have started using Ekman’s method to train algorithms to detect emotion from facial expressions. Some developers claim that automatic emotion detection systems will not only be better than humans at discovering true emotions by analyzing the face, but that these algorithms will become attuned to our innermost feelings, vastly improving interaction with our devices.

But many experts studying the science of emotion are concerned that these algorithms will fail once again, making high-stakes decisions about our lives based on faulty science.

Emotion detection technology requires two techniques: computer vision, to precisely identify facial expressions, and machine learning algorithms to analyze and interpret the emotional content of those facial features.

Typically, the second step employs a technique called supervised learning, a process by which an algorithm is trained to recognize things it has seen before. The basic idea is that if you show the algorithm thousands and thousands of images of happy faces with the label “happy” when it sees a new picture of a happy face, it will, again, identify it as “happy”.

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Amazon, Microsoft and IBM now advertise “emotion analysis” as one of their facial recognition products, and a number of smaller firms, such as Kairos and Eyeris, have cropped up, offering similar services to Affectiva.

Beyond market research, emotion detection technology is now being used to monitor and detect driver impairment, test user experience for video games and to help medical professionals assess the wellbeing of patients.  [read more]

Yea, the AI Overlords will use this algorithm to determine who is a threat to them or not.