Introducing his students to the study of the human brain Jeff Lichtman, a Harvard Professor of Molecular and Cellular Biology, once asked: “If understanding everything you need to know about the brain was a mile, how far have we walked?”. He received answers like ‘three-quarters of a mile’, ‘half a mile’, and ‘a quarter of a mile’.
The professor’s response?: “I think about three inches.”
Last month, Lichtman’s quip made it into the pages of a new report by the Royal Society which examines the prospects for neural (or “brain-computer”) interfaces, a hot research area that has seen billions of dollars of funding plunged into it over the last few years, and not without cause. It is projected that the worldwide market for neurotech products – defined as “the application of electronics and engineering to the human nervous system” – will reach as much as $13.3 billion by 2022.
“How do we get humans to trust in all this AI we’re building?”, asked Affectiva CEO Rana El-Kaliouby, at the prestigious NYT New Work Summit at Half Moon Bay last week. She had already assumed a consensus that trust-building was the correct way to proceed, and went on to suggest that, rather than equipping users and consumers with the skills and tools to scrutinize AI, we should instead gently coax them into placing more unearned faith in data-driven artifacts.
But how would this be accomplished? Well, Affectiva are “on a mission to humanize technology”, drawing upon machine and deep learning to “understand all things human.” All things human, El-Kaliouby reliably informed us, would include our emotions, our cognitive state, our behaviors, our activities. Note: not to sense, or to tentatively detect, but to understand those things in “the way that humans can.”
Grandiose claims, indeed.
This article by Fiona J McEvoy (YouTheData.com) was originally posted on All Turtles.
The way we interact with technology keeps changing. Of late, many more of us are using speech and gesture to give instructions to our devices, and it’s actually starting to feel natural. We tell Alexa to turn the lights off, silence our smart watches by smothering them with our palms, and unlock our phones with a look. For this to work as seamlessly as it does, our devices have to pensively watch and listen to us. Pretty soon they could begin to understand and anticipate our emotional needs, too.
The move towards what’s been called implicit understanding – in contrast with explicit interaction – will be facilitated by technologies like emotion-tracking AI. Technology that uses cues from our vocal tone, facial expressions and other micro-movements to determine our mood and, from there, our needs. According to researchers at Gartner, very soon our fridge will be able to suggest food to match our feelings, and research VP Annette Zimmerman has even claimed that, “By 2022, your personal device will know more about your emotional state than your own family.”