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2019 AI Hype Countdown #1: Tesla’s Robotaxis—Tales of a Phantom Fleet

Musk put out a tweet on December 22, saying “Sorry, it's been a bit of a struggle.” At last, a claim we can unreservedly believe

The number one AI hype story this year had to be Tesla’s robotaxi fleet. While other autonomous vehicle companies are dialing back their claims of near-future glory, Tesla has been pushing the propaganda volume up to an ear-splitting 11.

Tesla has been touting its cars’ “self-driving” abilities since 2016. At the end of last year, after selling “self-driving” vaporware for several years as an add-on feature, it looked like the company was going to take the responsible approach and stop selling the feature. They pulled the option from their web site, and basically stopped talking about it. However, that didn’t last long, and soon they were selling full self-driving vaporware again.

In fact, in 2019, when raising cash for a debt raise for the company, they doubled down on self-driving claims, saying that they will have a million robotaxis on the road in 2020.

Because Tesla has yet to make a yearly profit in any of its sixteen years of existence, it depends on capital raises of various forms (equity, debt, etc.) to stay in business. Capital raises require big promises and Tesla’s overstatements about its self-driving cars are always good for a few billion.

However, as the schedule gradually tightened, Musk has had to walk back some of his firm’s claims. While still selling the product as “Full Self-Driving,” apparently the capitalized letters indicate that the words can mean whatever Tesla wants them to mean, as “feature-complete” is not in any way “self-driving,” much less “fully” so. At Mind Matters News, we put together a timeline of Musk’s autonomous vehicle claims so readers can see how the hype cycle plays out over time.

So, to follow the timeline, we start with Musk saying in 2016 that Teslas will be able to drive themselves across the country by 2018, with the only problem being regulators.

Then he is saying later in 2016 that Teslas can already drive themselves and the driver doesn’t have to do anything. Again, the video stated that the only reason for the driver at all is because of those annoying regulators.

Unfortunately, as the differences between promises and deliveries become more stark, Tesla has resorted to beta-testing its software on the public at large. Musk has continually reiterated that Tesla’s not-even-close-to-self-driving-Full-Self-Driving will be “feature complete” (again, don’t confuse this with actual self-driving) by the end of this year, which is less than 36 hours away EST.

On this note, Musk put out a tweet on December 22, saying “Sorry, it’s been a bit of a struggle. Software team has been working all weekend to resolve last minute issues. Hopefully starts rolling out tonight.”

Bit of a struggle? At last, a claim we can unreservedly believe.

We would like to think that automotive companies only push out software onto public roads after vigorous testing both in the lab and on the road. But it turns out that Tesla doesn’t understand the difference between the responsibilities of a Silicon Valley startup website and a motor vehicle company that will be putting 3,600-lb vehicles on Autopilot throughout the country. “Resolving last-minute issues” means that the resolution has only been tested last-minute.

It would be one thing if only Tesla users, who seem to appreciate this type of behavior, were affected. But we all share the roads which means that we are all subjects of Musk’s beta-testing program. But don’t worry, Tesla will hold the driver responsible when its code malfunctions.

So why does Tesla do this? Because, if we have learned nothing else about artificial intelligence, it’s that many people seem to need the hype. They do not ask—perhaps do not want to know—what underlies it. Thus the hype must, and does, go on.


Counting back:

2019 AI Hype Countdown #2: Big Data is our crystal ball! The biggest problem is that human behavior is not as predictable as the models imply. Many models are ridiculously simplistic, making the results worse than worthless. They become a way of solidifying biases.

2019 AI Hype Countdown #3: Quantum Supremacy? Less supreme than it sounded. It’s possible that Google’s quantum result can be generalized to more useful scenarios than the test case though it isn’t immediately obvious how. What Google really achieved was increased stability in its quantum computing platform. Keeping qubits stable has been a hard problem in quantum computing for a long time. This event was certainly a step forward, but advertising it as “quantum supremacy” was a classic exercise in hype.

2019 AI Hype Countdown #4: Investment: AI beats the hot stock tip… barely At the end of the day, AI-based investing actually performed like a bad index fund. Artificial intelligence may do well summarizing data, but the new insights that will lead the economy forward cannot be gleaned that way. What we need is not old data but new truths.

2019 AI Hype Countdown #5: Transhumanism never grows old. The idea that we can upload our brains to computers to avoid death shows a fundamental misunderstanding of the differences between types of thinking. Computers are very effective but they operate with a very limited set of causal abilities. Humans work from an entirely different set of causal abilities. Uploading your brain to a computer is not a question of technology. It can’t work in principle.

2019 AI Hype Countdown #6: In May of this year, The Scientist ran a series of pieces suggesting that we could automate the process of acquiring scientific knowledge. In reality, without appropriate human supervision, AI is just as likely to find false or unimportant patterns as real ones. Additionally, the overuse of AI in science is actually leading to a reproducibility crisis.

2019 AI Hype Countdown #7: “Robot rights” grabs the mike. If we could make intelligent and sentient AIs, wouldn’t that mean we would have to stop programming them? AI programs are just that programs. Nothing in such a program could make it conscious. We may as well think that if we make sci-fi life-like enough, we should start worrying about Darth Vader really taking over the galaxy.

2019 AI Hype Countdown #8: Media started doing their job! Yes, this year, there has been a reassuring trend: Media are offering more critical assessment of off-the-wall AI hype. One factor in the growing sobriety may be that, as AI technology transitions from dreams to reality, the future belongs to leaders who are pragmatic about its abilities and limitations.

2019 AI Hype Countdown #9: Hype fought the law and… Autonomy had real software but the hype around Big Data had discouraged Hewlett Packard from taking a closer look. Autonomy CFO Sushovan Hussain was sentenced this year to a five year prison term and a ten million dollar fine because he was held “ultimately responsible for Autonomy’s revenues having been overinflated by $193m between 2009 and the first half of fiscal 2011.”

2019 AI Hype Countdown #10: Sophia the robot still gives “interviews”. In other news, few popular media ask critical questions. As a humanoid robot, Sophia certainly represents some impressive engineering. It is sad that the engineering fronts ridiculous claims about the state of AI, using partially scripted interactions as if they were real communication.

and

Top Ten AI hypes of 2018


Jonathan Bartlett

Fellow, Walter Bradley Center for Natural & Artificial Intelligence
Jonathan Bartlett is a senior software R&D engineer at Specialized Bicycle Components, where he focuses on solving problems that span multiple software teams. Previously he was a senior developer at ITX, where he developed applications for companies across the US. He also offers his time as the Director of The Blyth Institute, focusing on the interplay between mathematics, philosophy, engineering, and science. Jonathan is the author of several textbooks and edited volumes which have been used by universities as diverse as Princeton and DeVry.

2019 AI Hype Countdown #1: Tesla’s Robotaxis—Tales of a Phantom Fleet