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Some companies and scientists present Affective Computing, the algorithmic analysis of personality traits also known as “artificial emotional intelligence”, as an important new development. But the methods that are used are often dubious and present serious risks for discrimination.

It was announced with some fanfare that Alexa and others would soon demonstrate breakthroughs in the field of emotion analysis. Much is written about affective computing, but products are far from market ready. For example, Amazon’s emotion assistant Dylan is said to be able to read human emotions just by listening to their voices. However, Dylan currently only exists in form of a patent.

So far, Amazon, Google et al. have not launched such products. Identifying unique signals that indicate that someone is sad seems to be a bit more complicated than they initially thought. Maybe someone’s voice sounds depressed because they are depressed, but maybe they are just tired or exhausted.

However, these difficulties do not prevent other companies from launching products that claim to have solved these complex problems by using voice and speech for character and personality analysis.

In Germany, two examples spring to mind. One is the company Precire, based in Aachen, a city on border with Belgium. Their idea: you record a voice sample, and based on the person’s choice of words, sentence structure and many other indicators, the software then produces an analysis of their character traits. The software can be used in staff recruitment or to identify candidates for promotion.

The company states that its software carries out the analysis based on a 15-minute language sample. The then CEO Mario Reis stated in an interview in 2016 that the results were based on science and scientifically tested. This statement is repeated in a book published in 2018. This book also cites additional studies and findings to further support the scientific grounding of the method.

By Veronika Thiel