Is this Controversial Technology Used by Law Enforcement?

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Emotion-detecting technologies, or affect recognition systems, help vet job seekers, test criminal suspects for signs of deception, and more. AI Now, a US-based research center, has called for new laws to restrict its use. The center’s annual report says the sector is undergoing a period of significant growth and could already be worth as much as $20bn.

The center wants such software to be banned from use in important decisions that affect people’s lives and/or determine their access to opportunities.

The technology detects inner-emotional states “by interpreting the micro-expressions on our face, the tone of our voice or even the way that we walk,” explained the Center’s co-founder Prof Kate Crawford. “It’s being used everywhere, from how do you hire the perfect employee through to assessing patient pain, through to tracking which students seem to be paying attention in class.

“At the same time as these technologies are being rolled out, large numbers of studies are showing that there is… no substantial evidence that people have this consistent relationship between the emotion that you are feeling and the way that your face looks.”

Emotion expressions change “across cultures, across situations, and even across a single day,” she said.

Oxygen Forensics was cited for offering emotion-detecting software to the police, but defended its efforts. “The ability to detect emotions, such as anger, stress, or anxiety, provide law-enforcement agencies additional insight when pursuing a large-scale investigation,” said its chief operating officer, Lee Reiber. “Ultimately, we believe that responsible application of this technology will be a factor in making the world a safer place.”

Another example was HireVue, which sells AI-driven video-based tools to recommend which candidates a company should interview. It uses third-party algorithms to detect “emotional engagement” in applicants’ micro-expressions to help make its choices.

Cogito has developed voice-analysis algorithms for call-center staff to help them detect when customers are becoming distressed, was also mentioned. “Before emotion detection can own making automated decisions, the industry needs more proof that machines can in fact effectively and consistently detect human emotion,” its chief executive Joshua Feast told BBC.com. “What can be done today, is to evaluate the behaviours that proxy for certain emotions and provide that intelligence to a human to help them make a more informed decision. For tomorrow and the future, it’s up to all practitioners and leaders in the field to collaborate, research, and develop solutions that help foster deeper, common understanding that will eventually lead to more connected relationships with one another – not in spite of technology, but because of it.”