Are friends electric?

This discrepancy between the relative ease of teaching a machine abstract considering and the problem of teaching it basic sensory, social, and motor skills is what’s referred to as Moravec’s paradox. Named after an commentary the roboticist Hans Moravec made back within the late Eighties, the paradox states that what’s hard for humans (math, logic, scientific reasoning) is simple for machines, and what’s hard for machines (tying shoelaces, reading emotions, having a conversation) is simple for humans. 

In her latest book, , science author Eve Herold argues that because of recent approaches in machine learning and continued advances in AI, we’re finally beginning to unravel this paradox. Consequently, a brand new era of private and social robots is about to unfold, she says—one that can force us to reimagine the character of all the pieces from friendship and like to work, health care, and residential life. 

To present readers a way of what this brave recent world of social robots will seem like, Herold points us toward Pepper, a doe-eyed humanoid robot that’s made by the Japanese company SoftBank. “Robots like Pepper will soon make themselves indispensable due to their unique, highly personalized relationships with us,” Herold writes, before describing with press-release-like zeal how this chest-high companion can effortlessly read our expressions and emotional states and respond appropriately in its own childlike voice.

If Pepper sounds vaguely familiar, it might be since it was relentlessly hyped because the world’s first “emotional robot” within the years following its 2014 introduction. That abruptly stopped in 2021, nevertheless, when SoftBank pulled the plug on Pepper production due to lack of demand and—probably not unrelatedly—the $2,000 android’s general incompetence. Books can obviously take an extended time to write down, and so much can change when you’re writing them. However it’s hard to reconcile this particular oversight with the undeniable fact that Pepper was canned some the book’s publication.  

Positioning a defunct product that no one seems to have liked or bought as a part of some vanguard for a brand new social-­robot revolution doesn’t encourage confidence. Herold might respond by stating that her book’s focus is less on the robots themselves than on what we humans will bring to the brand new social relationships we forge with them. Fair enough. 

But while she dutifully unpacks our penchant for anthropomorphizing and walks readers through some rudimentary research on deep learning and the uncanny valley, Herold’s conclusions about human nature and psychology often seem either oversimplified or divorced from the evidence she provides. For somebody who says that “the one technique to write concerning the future is with a high degree of humility,” there are also an unusually large variety of deeply questionable assertions (“Thus far, the trust we’ve placed in algorithms has been, on balance, well placed …”) and sweeping predictions (“There’s little doubt some version of a companion robot shall be coming soon to homes throughout the industrialized world”).   

Early on within the book, Herold reminds readers that “science writing that attempts to examine the long run often says far more concerning the time it was written than it says concerning the future world.” On this respect, is indeed quite revealing. Amongst other things, the book reflects the best way we are inclined to reduce discussions of technological impacts into binary terms (“It’ll be amazing”/”It’ll be terrible”); the shrugging acquiescence with which we seem to treat undesirable outcomes; the readiness of science and technology writers to succumb to industry hype; and the disturbing extent to which the logic and values of machines (speed, efficiency) have already been adopted by humans. It’s probably not one in all Herold’s intended takeaways, but when the book demonstrates anything, it’s not that robots have gotten more like us; it’s that we’re becoming more like them. 

MIT PRESS, 2024

For a more rigorous take a look at one in all the pillars of human social expression—and, specifically, how we’ve tried to transfer it to machines—Sarah A. Bell’s offers a compelling and insightful history of voice synthesis through the twentieth century. Bell, a author and professor at Michigan Technological University, is occupied with how we attempt to digitally reproduce different expressions of human embodiment, be it speech, emotions, or visual identities. As she points out early on within the book, understanding this process often means understanding the ways wherein engineers (almost universally male ones) have decided to measure and quantify facets of our bodies.