MONEY & MARKETS EXTRA
Artificial intelligence for your vehicle
Rana el Kaliouby co-founded and led Boston startup Affectiva, which uses artificial intelligence to analyze mood and emotion.
Now she’s deputy CEO of Smart Eye. The Swedish eye-tracking company bought Affectiva for $73.5 million in June.
Carmakers are looking to companies like Smart Eye as they brace for new safety standards around the world that could require cameras to watch drivers inside semi-autonomous vehicles.
El Kaliouby says that’s just the beginning for in-car AI systems.
Ten years from now, a family’s in a car. What might your technology be doing? You’ve got two kids in the back seat. The kids are fighting. The car knows that and can see that mom, who’s driving, is getting a little mad, distracted. The car intervenes by recommending content for the kids. Then the car realizes mom is exhausted and starting to doze off, so it gets into this chatty mode to reengage her. It can personalize the whole cabin experience— music, lighting, temperature, based on knowing who’s inside the car and what they’re doing.
What is Affectiva bringing to Smart Eye? Smart Eye is a 22-year-old company able to very accurately determine where a person is looking and monitor eye behavior. They can identify when a driver is distracted or drowsy. Affectiva spun out of MIT 12 years ago and our focus is humanizing technology by bringing emotional intelligence to machines. We project there’s going to be an evolution in driver monitoring to everything that’s happening inside the vehicle.
How do you detect someone’s mood or emotions?
We do a lot of facial analysis but we’ve expanded to body “keypoint” tracking so we can detect what people are actually doing — are you slouched in the car? Are you agitated?
How do you protect against concerns you can misread someone’s emotion or mood based on race, gender or neurodiversity?
It starts with the diversity of the data. If you’re training an algorithm using middle-aged white men, that’s what it’s going to learn. The second thing is, how do you validate the accuracy of the algorithms?
We dissect the data to make sure no bias is creeping in. Finally, the diversity of the team is how you overcome these blind spots.
What about people who don’t want to be analyzed or watched in the car?
The good news is none of the data gets recorded. You do all the processing on the fly and make an inference, say, if the driver is drowsy. The car will hopefully respond to keep the driver safe. I imagine there will be scenarios where you can switch it off. But if it’s a safety consideration, like your semi-autonomous vehicle needs to know if you are paying attention so it can transfer control back and forth, I imagine you may not be allowed to turn it off.