With all new technologies there are predictions of how good it will be for humankind, or how bad it will be. A common thread that I have observed is how people tend to underestimate how long new technologies will take to be adopted after proof of concept demonstrations. I pointed to this as the seventh of seven deadly sins of predicting the future of AI.
For example, recently the early techno-utopianism of the Internet providing a voice to everyone and thus blocking the ability of individuals to be controlled by governments has turned to depression about how it just did not work out that way. And there has been discussion of how the good future we thought we were promised is taking much longer to be deployed than we had ever imagined. This is precisely a realization of the early optimism about how things would be deployed and used did just not turn out to be.
Over the last few months I have been throwing a little cold water over what I consider to be current hype around Artificial Intelligence (AI) and Machine Learning (ML). However, I do not think that I am a techno-pessimist. Rather, I think of myself as a techno-realist.
Yogi Berra, New York Yankees Hall of Fame catcher was, indeed, a yogi behind the plate. He also had a way with words and ideas that continue to bring a wry smile to our lips decades after Yogi brought them to life in his inimitable way. “Nobody goes there anymore; it's too crowded”; “90 percent of baseball is mental; the other half is physical”; and, of course, “It's deja vu all over again.”
Rodney Brooks is a yogi of sorts, too. But instead of snakes or curveballs, Brooks charms robots.
Recently, with risk only to his reputation, Brooks decided to make a slew of predictions concerning some of the most eagerly awaited (some anxiously!) technological advances in three areas: Driverless vehicles; AI, Machine Learning and robotics; and, Space Travel. Brooks cleverly approached his predictions by putting each one in a time frame. Would the anticipated development take place Not Earlier Than (NET) a specific date, By (BY) a date, or Not In My Lifetime (NIML, which the now-63 year-old Brooks pegged as January 1, 2050)?
Before jumping into the actual predictions, Brooks describes the framework that guided his thinking: if a technology (electric cars, for example) has a solid sociotechnical history to build on (a century of experienced engineers and companies building automobiles and their components), then the timeframe for innovation is shorter than if most of what it will take for it to succeed (like, colonizing Mars) has yet to be developed.
The results are very interesting.
Of Brooks' 18 predictions about self-driving cars, three (“First time that a car equipped with some version of a solution for the trolley problem” is involved in an accident where it is practically invoked; “Individually owned cars can go underground onto a pallet and be whisked underground to another location in a city at more than 100mph; and, Flying cars reach 0.1% of US total cars") were rated NIML. Brooks anticipates the other 16 will all be operational by the early 2020s.
He's even more sanguine about the future of AI, Machine Learning, and Robotics. Among his 14 calls in this area, Brooks predicts the limits of the Deep Learning approach to AI will become apparent within the next two years, with the “next big thing” in Machine Learning coming along no earlier than 2023 and no later than 2027. Meanwhile, he believes advances in robot locomotion and dexterity will make a home caretaker robot viable, but not before 2028.
Space travel? Brooks' 11 bets in this area are bookmarked by next year's “Next launch of people (test pilots/engineers) on a sub-orbital flight by a private company” to his NIML prediction regarding regular inter-city travel via Hyperloops.
The entire article is fascinating and certainly worth reading in its entirety. For me, the big takeaway is that we have here an example of a distinguished leader in the robotics world not just saying that all the recent “existential threat,” “robot apocalypse,” “mass replacement of human workers” fear, uncertainty, and doubt is massively overblown (I recently heard similar thoughts from Facebook's AI Chief, Yann LeCun). No, what Brooks has done is not just to offer his opinion on these issues, but to specifically document his predictions (in the spirit of Philip Tetlock's accountable predictions project) so that we will be able to track their accuracy in perpetuity.
All other Yogis would benefit from following his gutsy lead.
Tom Guarriello, Ph.D.
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