Bill Gurley argues on CNBC that we are 25 years away from autonomous vehicle market penetration in the USA because we’re too litigation-hungry. And concludes that AVs will instead take hold in a country like China which has relatively uncrowded roads and an authoritarian government that can make central planning decisions.
I don’t agree. Precisely because of rampant litigation in the USA, insurers are going to do the cold, hard math (like they always do), and realize that AVs will save a passel of lives and hence be good for their book. They will therefore indemnify manufacturers or otherwise shield them from opportunistic lawsuits launched in the inevitable few cases where the cars are apparently at fault. Money will smooth the path to AV adoption.
He also says:
The part we haven’t figured out yet, the last 3 percent, which is snow, rain, all the really, really hard stuff — it really is hard. They have done all the easy stuff.
While I would agree that there are still some really, really hard things to work out in AVs, rain and snow aren’t among them. Sensors like radar can penetrate that stuff far more effectively than human eyesight. Even pattern recognition in the optical spectrum could outperform humans.
The hard part part is getting the cars to know when they can break the rules. A recent viral posting about how to trap AVs hints at that. When a trash truck is taking up your lane making stops and you need to cross a double yellow to get around it, will an AV be smart enough to do that? Sure, it can just sit there and let the human take manual control, but that doesn’t get us to the Uber-utopia of cars making their way unmanned around the city to their next pickup.
This excellent article by Sam DeBrule explores how to survive the coming changes:
To position oneself to be augmented, rather than replaced by AI, one should embrace the benefits of AI enabled technology and invest in the “soft” skills that will empower her to stand out as an adaptable, personable and multi-faceted employee.
These skills are the higher-order reasoning that AI is not yet close to emulating: Creative thinking, emotional intelligence, problem solving. These are excellent arguments for those people on the higher end of the IQ scale. What does the future hold for people who are not as intellectually equipped?
Vanity Fair describes a meeting between Elon Musk and Demis Hassabis, a leading creator of advanced artificial intelligence, which likely propelled Musk’s alarm about AI:
Musk explained that his ultimate goal at SpaceX was the most important project in the world: interplanetary colonization.
Hassabis replied that, in fact, he was working on the most important project in the world: developing artificial super-intelligence. Musk countered that this was one reason we needed to colonize Mars—so that we’ll have a bolt-hole if A.I. goes rogue and turns on humanity. Amused, Hassabis said that A.I. would simply follow humans to Mars.
This did nothing to soothe Musk’s anxieties (even though he says there are scenarios where A.I. wouldn’t follow).
Mostly about Musk, the article is replete with Crisis of Control tropes that are now playing out in the real world far sooner than even I had thought likely. Musk favors opening AI development and getting to super-AI before government or “tech elites” – even when the elites are Google or Facebook.
I predicted that mass correlation of scientific papers by AI would happen much sooner than the 20 years that some in the field think it will take. Now read that in the course of a Watson project:
Machine learning software on a laptop can extract the critical information from scientific papers in seconds, enabling the creation of vast knowledge graphs across wide bodies of research in weeks rather than decades.
IBM will build quantum computers “millions of times faster than anything before.” Classic cryptography will become inadequate to protect information against these devices.
The repercussions of the January Asilomar Principles meeting continue to reverberate:
Importance Principle:Advanced AI could represent a profound change in the history of life on Earth, and should be planned for and managed with commensurate care and resources.
As AI professor Roman Yampolskiy told me, “Design of human-level AI will be the most impactful event in the history of humankind. It is impossible to over-prepare for it.”
This is about effects vs probability. It evokes what I said in Crisis of Control, that the probability of being killed by an asteroid impact is roughly the same as that of dying in a plane crash: probability of event happening times number of people killed. Advanced AI could affect us more profoundly than climate change, could require even longer to prepare for, and could happen sooner. All that adds up to taking this seriously, starting now.
The UK’s Guardian produced this little set piece that neatly summarizes many of the issues surrounding AI-as-existential-threat. The smug ethicist brought in to teach a blossoming AI is more interested in defending human exceptionalism (and the “Chinese Room” argument), but is eventually backed into a corner, stating that “You can’t rely on humanity to provide a model for humanity. That goes without saying.” Meanwhile the AI is bent on proving the “hard take-off” hypothesis…
In an op-ed, Bill Gates warns that genetic engineering or just random mutation could spawn a virus that wipes out 30 million people, and we are not prepared to deal with such an event.
Venture capitalists point out that robots are taking over the jobs we’d rather they leave alone. Artificial intelligences are making useful progress at creating original art, music, and prose, the sort of tasks we’d hoped they would free us up to be able to do ourselves. Meanwhile, the jobs we want them to do are proving “shockingly hard to automate”:
The cleaning robot Roomba was one of the first commercially available robots to everyday consumers in 2002. Almost 15 years later, there has not been any real innovation in terms of cleaning robots that has seen commercial success.
Textile manufacturing, one of the first industries to be automated, remains incredibly hard to automate completely. Robots work best when manipulating solid objects, but textiles shear, stretch, and compress, making them difficult for robots to handle.
Automating the harvesting of crops that are today picked by hand has so far been hard because many of these crops can be damaged easily and computers have had trouble with visual recognition of the fruit or produce they are trying to pick.
Google’s DeepMind can now win at Breakout… and that makes the company worth half a billion dollars.
Of course, that’s not all it can win at. Go and Poker are the most important recent victories. And now, it has set its sights on StarCraft II.
The exciting (or scary) thing is many experts did not think AI would defeat a Go champion for 10 more years. I repeat: people who have devoted their lives to advancing AI did not believe this could be accomplished for 10 years. That should give us pause when pundits question how quickly AI will change the world.