We can look at a friend and tell by his or her face that this person is tired or pre-occupied—or perhaps that this person is drunk. Soon, our cars will be able to do the same.
Advances in facial recognition technology mean machines can not only recognize different people, but also how they are feeling. This means the next generation of automobiles may contain features that scan drivers’ faces for fatigue or other signs of impairment.
Companies, including Boston-based Affectiva, are already making software to help the auto industry integrate such technology. According to CEO Rana el Kaliouby, software that reads emotion is not focused only on drivers, but on passengers, too.
This will mean that automakers may come to build vehicles that may adjust comfort factors like heat, lighting, and entertainment based on visual cues from their individual occupants—features that could be especially appealing as more autonomous cars hit the roads.
“It’s really important technology not only have IQ, but lots of EQ too,” said el Kaliouby, speaking on Tuesday morning at Coins2Day‘s CEO Initiative in New York.
She added that building empathy into machines is especially important given that humans use words for only 7% of their communications. The other 93%, el Kaliouby says, consists of vocal intonations, expression, and body language.
While the auto industry appears well-suited to integrate emotion-reading software, it is just one business where facial recognition could have a big impact.
According to el Kaliouby, the personal care industry could also benefit from the technology. She described a scenario where a nurse works in tandem with a team of empathetic robots to take care of patients.
Such a scenario, however, may also exacerbate fears of machines replacing humans—especially as the ability to understand emotions is what differentiates us from robots. But el Kaliouby said this should not be concern.
“It’s not a competition between humans and machines. It’s more like a partnership,” she says, claiming that people will always be the ones in charge of the machines.
El Kaliouby also addressed the risk of facial recognition makers perpetuating bias by training their algorithms on a narrow segment of society. She said Affectiva takes pains to avoid this by ensuring their databases are diverse in terms of gender, ethnicity, and age.
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