{"id":229101,"date":"2021-04-16T16:01:20","date_gmt":"2021-04-16T13:01:20","guid":{"rendered":"https:\/\/en.buradabiliyorum.com\/ai-is-increasingly-being-used-to-identify-emotions-whats-at-stake\/"},"modified":"2021-04-16T16:01:20","modified_gmt":"2021-04-16T13:01:20","slug":"ai-is-increasingly-being-used-to-identify-emotions-whats-at-stake","status":"publish","type":"post","link":"https:\/\/buradabiliyorum.com\/en\/ai-is-increasingly-being-used-to-identify-emotions-whats-at-stake\/","title":{"rendered":"#AI is increasingly being used to identify emotions: What’s at stake?"},"content":{"rendered":"

“#AI is increasingly being used to identify emotions: What’s at stake?<\/strong>”<\/p>\n

\n Imagine you are in a job interview. As you answer the recruiter’s questions, an artificial intelligence (AI) system scans your face<\/a>, scoring you for nervousness<\/a>, empathy<\/a> and dependability<\/a>. It may sound like science<\/a> fiction, but these systems are increasingly used, often without people’s knowledge<\/a> or consent.<\/p>\n

Emotion recognition technology<\/a> (ERT) is in fact a burgeoning multi-billion-dollar industry<\/a> that aims to use AI to detect emotions from facial expressions. Yet the science behind emotion recognition systems is controversial<\/a>: there are biases built into the systems.<\/p>\n

Many companies use ERT to test customer reactions<\/a> to their products, from cereal to video game<\/a>s. But it can also be used in situations with much higher stakes<\/a>, such as in hiring<\/a>, by airport security<\/a> to flag faces as revealing deception or fear, in border control, in policing<\/a> to identify “dangerous people” or in education<\/a> to monitor students’ engagement with their homework.<\/p>\n

Shaky scientific ground<\/b><\/p>\n

Fortunately, facial recognition technology is receiving public attention. The award-winning film Coded Bias, recently released on Netflix, documents the discovery that many facial recognition technologies do not accurately detect darker-skinned faces. And the research team managing ImageNet, one of the largest and most important datasets used to train facial recognition, was recently forced to blur 1.5 million images in response to privacy concerns<\/a>.
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Revelations about algorithmic bias and discriminatory datasets in facial recognition technology have led large technology companies, including Microsoft, Amazon and IBM, to halt sales. And the technology faces legal challenges<\/a> regarding its use in policing in the UK. In the EU, a coalition of more than 40 civil society organizations have called for a ban<\/a> on facial recognition technology entirely. <\/p>\n

Like other forms of facial recognition, ERT raises questions about bias, privacy and mass surveillance. But ERT raises another concern: the science of emotion behind it is controversial. Most ERT is based on the theory of “basic emotions”<\/a> which holds that emotions are biologically hard-wired and expressed in the same way by people everywhere. <\/p>\n

This is increasingly being challenged, however. Research in anthropology shows that emotions are expressed differently<\/a> across cultures and societies. In 2019, the Association for Psychological Science<\/a> conducted a review of the evidence, concluding that there is no scientific support<\/a> for the common assumption that a person’s emotional state can be readily inferred from their facial movements. In short, ERT is built on shaky scientific ground.<\/p>\n

Also, like other forms of facial recognition technology, ERT is encoded with racial bias. A study has shown that systems consistently read black people’s faces as angrier than white people’s faces, regardless of the person’s expression. Although the study of racial bias<\/a> in ERT is small, racial bias in other forms of facial recognition is well-documented. <\/p>\n

There are two ways that this technology can hurt people, says AI researcher Deborah Raji in an interview with MIT Technology Review<\/a>: “One way is by not working: by virtue of having higher error rates for people of color, it puts them at greater risk. The second situation is when it does work\u2014where you have the perfect facial recognition system, but it’s easily weaponized against communities to harass them.” <\/p>\n

So even if facial recognition technology can be de-biased and accurate for all people, it still may not be fair or just. We see these disparate effects<\/a> when facial recognition technology is used in policing and judicial systems that are already discriminatory and harmful to people of color. Technologies can be dangerous when they don’t work as they should. And they can also be dangerous when they work perfectly in an imperfect world. <\/p>\n

The challenges raised by facial recognition technologies\u2014including ERT\u2014do not have easy or clear answers. Solving the problems presented by ERT requires moving from AI ethics centered on abstract principles to AI ethics centered on practice<\/a> and effects<\/a> on people’s lives. <\/p>\n

When it comes to ERT, we need to collectively examine the controversial science of emotion built into these systems and analyze their potential for racial bias. And we need to ask ourselves: even if ERT could be engineered to accurately read everyone’s inner feelings, do we want such intimate surveillance in our lives? These are questions that require everyone’s deliberation, input and action. <\/p>\n

Citizen science project<\/b><\/p>\n

ERT has the potential to affect the lives of millions of people, yet there has been little public deliberation<\/a> about how\u2014and if\u2014it should be used<\/a>. This is why we have developed a citizen science project<\/a>.<\/p>\n

On our interactive website<\/a> (which works best on a laptop, not a phone) you can try out a private and secure ERT for yourself, to see how it scans your face and interprets your emotions. You can also play games comparing human versus AI skills in emotion recognition and learn about the controversial science of emotion behind ERT.<\/p>\n

Most importantly, you can contribute your perspectives and ideas to generate new knowledge about the potential impacts of ERT. As the computer scientist and digital activist Joy Buolamwini<\/a> says<\/a>: “If you have a face, you have a place in the conversation.”\n <\/p>\n\n

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Study finds that masks make little difference to facial identification<\/a>\n <\/div>\n

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\n This article is republished from The Conversation<\/a> under a Creative Commons license. Read the original article<\/a>.\"The<\/p>\n

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