Report Showcases How Elon Musk Undermined His Own Engineers And Endangered Public Safety

from the first-do-no-harm dept

For a long time now, it's been fairly clear that consumer safety was an afterthought for some of the more well known companies developing self-driving technology. That was made particularly clear a few years back with Uber's fatality in Tempe, Arizona, which revealed that the company really hadn't thought much at all about public safety. The car involved in the now notorious fatality wasn't even programmed to detect jaywalkers, and there was little or no structure at Uber to meaningfully deal with public safety issues. The race to the pot of innovation gold was all consuming, and all other considerations (including human lives) were afterthoughts.

That same cavalier disregard for public safety has been repeatedly obvious over at Tesla, where the company's undercooked "autopilot" technology has increasingly resulted in a nasty series of ugly mishaps, and, despite years of empty promises, still doesn't work as marketed or promised. That's, of course, not great for the public, who didn't opt in to having their lives put at risk by 2,500 pound death machines for innovation's sake. Every week there's new evidence and lawsuits showing this technology is undercooked and dangerous, and every week we seemingly find new ways to downplay it.

This week the scope of Elon Musk's failures on this front became more clear thanks to a New York Times piece, which profiles how corner cutting on the autopilot project was an active choice by Musk at several points in the development cycle. The piece repeatedly and clearly shows that Musk overstated what the technology was capable of for the better part of the last decade:

"As the guiding force behind Autopilot, Mr. Musk pushed it in directions other automakers were unwilling to take this kind of technology, interviews with 19 people who worked on the project over the last decade show. Mr. Musk repeatedly misled buyers about the services’ abilities, many of those people say. All spoke on the condition of anonymity, fearing retaliation from Mr. Musk and Tesla."

Musk's bravado, and the exaggeration of the sophistication of Autopilot, helped encourage some customers to have too much trust in the product or actively misuse it. Constantly pushing undercooked software and firmware updates without proper review also created safety challenges. But the article tends to focus heavily on how Musk repeatedly undermined his own engineers through stubborn decisions that undermined both overall safety and engineer expertise, like Musk's unyielding belief that full automated driving could be accomplished with just cameras, and not cameras and radar (or other detection tech):

"Within Tesla, some argued for pairing cameras with radar and other sensors that worked better in heavy rain and snow, bright sunshine and other difficult conditions. For several years, Autopilot incorporated radar, and for a time Tesla worked on developing its own radar technology. But three people who worked on the project said Mr. Musk had repeatedly told members of the Autopilot team that humans could drive with only two eyes and that this meant cars should be able to drive with cameras alone."

The article also makes it clear that employees that were overly happy to please Musk's whims only tended to make the overall quality and safety issues worse. And when employees did challenge Musk in a bid to improve quality and safety, things very often didn't go well:

"In mid-2015, Mr. Musk met with a group of Tesla engineering managers to discuss their plans for the second version of Autopilot. One manager, an auto industry veteran named Hal Ockerse, told Mr. Musk he wanted to include a computer chip and other hardware that could monitor the physical components of Autopilot and provide backup if parts of the system suddenly stopped working, according to two people with knowledge of the meeting.

But Mr. Musk slapped down the idea, they said, arguing it would slow the progress of the project as Tesla worked to build a system that could drive cars by themselves. Already angry after Autopilot malfunctioned on his morning drive that day, Mr. Musk berated Mr. Ockerse for even suggesting the idea. Mr. Ockerse soon left the company."

None of this is particularly surprising for folks who have objectively watched Musk, but it does catalog his erratic bravado and risk taking in a comprehensive way that makes all of it seem notably more concrete. For a man whose reputation is one of engineering savvy, the report repeatedly showcases how Musk refused to actually listen to his own engineers. There's little doubt Musk has been innovative, but the report does a fairly solid job showcasing how a not insubstantial portion of his near-deified reputation is more than a little hollow.

Filed Under: autonomous vehicles, elon musk, safety, self-driving
Companies: tesla

Report Suggests Rampant Negligence In Uber Self Driving Car Fatality

from the I'm-sorry-I-can't-do-that,-Dave dept

Earlier this year you might recall that a self-driving Uber in Tempe, Arizona killed a woman who was trying to cross the street with her bike outside of a crosswalk. The driver wasn't paying attention, and the car itself failed to stop for the jaywalking pedestrian. Initial reporting on the subject, most of it based on anonymous Uber sources who spoke to the paywalled news outlet The Information, strongly pushed the idea that the car's sensors worked as intended and detected the woman, but bugs in the system software failed to properly identify the woman as something to avoid:

"The car’s sensors detected the pedestrian, who was crossing the street with a bicycle, but Uber’s software decided it didn’t need to react right away. That’s a result of how the software was tuned. Like other autonomous vehicle systems, Uber’s software has the ability to ignore “false positives,” or objects in its path that wouldn’t actually be a problem for the vehicle, such as a plastic bag floating over a road. In this case, Uber executives believe the company’s system was tuned so that it reacted less to such objects. But the tuning went too far, and the car didn’t react fast enough, one of these people said."

Thanks to that report, a narrative emerged that the vehicle largely worked as designed, and the only real problem was a modest quirk in uncooked programming.

But a new report by Bloomberg this week shatters that understanding. According to NTSB findings seen by Bloomberg, the vehicle in question wasn't even programmed to detect jaywalkers. Like, at all:

"Uber Technologies Inc.’s self-driving test car that struck and killed a pedestrian last year wasn’t programmed to recognize and react to jaywalkers, according to documents released by U.S. safety investigators."

Assuming Bloomberg's read of the 400 page report (only a part of which has been made public) is accurate, that's a far cry from a bug. The NTSB report found that Uber staff had also disabled Volvo auto-detection and breaking software that could have at least slowed the vehicle if not avoided the pedestrian impact altogether. Investigators also noted that despite the fact that Uber was conducting risky trials on public streets, the company had little to no real system in place for dealing with safety issues. Again, not just underwhelming public safety protocols, but none whatsoever:

"The Uber Advanced Technologies Group unit that was testing self-driving cars on public streets in Tempe didn’t have a standalone safety division, a formal safety plan, standard operating procedures or a manager focused on preventing accidents, according to NTSB."

Again, that's not just buggy or "poorly tuned" software, it's total negligence. Despite the fact the driver was distracted, the car was never adequately programmed to detect jaywalkers, some safety features were disabled, and Uber had little to no safety protocols in place, prosecutors have already absolved Uber of criminal liability (though the driver still may face a lawsuit). The NTSB also hasn't formally affixed blame for the crash (yet):

"The documents painted a picture of safety and design lapses with tragic consequences but didn’t assign a cause for the crash. The safety board is scheduled to do that at a Nov. 19 meeting in Washington."

Self driving cars are remarkably safe, and most accidents involve autonomous vehicles getting confused when people actually follow the law (like rear ending a human-driven vehicle that stopped at a red light before turning right). But that's only true when the people designing and conducting trials are competent. If the NTSB report is anything to go by, Uber fell well short, yet got to enjoy a lot of press suggesting the problem was random bad programming luck, not total negligence and incompetence. Later this month we'll get to see if Uber faces anything resembling accountability for its failures.

Filed Under: arizona, autonomous vehicles, jaywalkers, self driving cars, sensors, tempe
Companies: uber

Politicians Start To Push For Autonomous Vehicle Data To Be Protected By Copyright Or Database Rights

from the battle-for-the-internet-of-things dept

Autonomous vehicles are much in the news these days, and seem poised to enter the mainstream soon. One of their key aspects is that they are digital systems -- essentially, computers with wheels. As such they gather and generate huge amounts of data as they move around and interact with their surroundings. This kind of data is increasingly valuable, so an important question poses itself: what should happen to all that information from autonomous vehicles?

The issue came up recently in a meeting of the European Parliament's legal affairs committee, which was drawing up a document to summarize its views on autonomous driving in the EU (pdf). It's an area now being explored by the EU with a view to bringing in relevant regulations where they are needed. Topics under consideration include civil liability, data protection, and who gets access to the data produced by autonomous vehicles. On that topic, the Swedish Greens MEP Max Andersson suggested the following amendment (pdf) to the committee's proposed text:

Notes that data generated during autonomous transport are automatically generated and are by nature not creative, thus making copyright protection or the right on databases inapplicable.

Pretty inoffensive stuff, you might think. But not for the center-right EPP politicians present. They demanded a vote on Andersson's amendment, and then proceeded to block its inclusion in the committee's final report.

This is a classic example of the copyright ratchet in action: copyright only ever gets longer, stronger and broader. Here a signal is being sent that copyright or a database right should be extended to apply not just to works created by people, but also to the data streams generated by autonomous vehicles. Given their political leanings, it is highly unlikely that the EPP politicians believe that data belongs to the owner of the vehicle. They presumably think that the manufacturer retains rights to it, even after the vehicle has left the factory and been sold.

That's bad enough, but there's a bigger threat here. Autonomous vehicles are just part of a much larger wave of connected digital devices that generate huge quantities of data, what is generally called the Internet of Things. The next major front in the copyright wars -- the next upward move of the copyright ratchet -- will be over what happens to all that data, and who, if anyone, owns it.

Follow me @glynmoody on Twitter or identi.ca, and +glynmoody on Google+

Filed Under: autonomous vehicles, copyright, database right, eu, eu parliament, iot, juri

Arizona Bans Self-Driving Car Tests; Still Ignores How Many Pedestrians Get Killed

from the plenty-of-blame-to-go-around dept

By now, most folks have read about the fact that Uber (surprise) was responsible for the first ever pedestrian fatality caused by a self-driving car in the United States. Investigators in the case have found plenty of blame to go around, including a pedestrian who didn't cross at a crosswalk, an Uber driver who wasn't paying attention to the road (and therefore didn't take control in time), and Uber self-driving tech that pretty clearly wasn't ready for prime time compared to its competitors:

"Uber’s robotic vehicle project was not living up to expectations months before a self-driving car operated by the company struck and killed a woman in Tempe, Ariz.

The cars were having trouble driving through construction zones and next to tall vehicles, like big rigs. And Uber’s human drivers had to intervene far more frequently than the drivers of competing autonomous car projects."

All of the companies that contribute tech to Uber's test vehicle have been rushing to distance themselves from Uber's failures here. Many of them are laying the blame at the feet of Uber, including one company making it clear that Uber had disabled some standard safety features on the Volvo XC90 test car in question:

"Uber Technologies Inc. disabled the standard collision-avoidance technology in the Volvo SUV that struck and killed a woman in Arizona last week, according to the auto-parts maker that supplied the vehicle’s radar and camera.

“We don’t want people to be confused or think it was a failure of the technology that we supply for Volvo, because that’s not the case,” Zach Peterson, a spokesman for Aptiv Plc, said by phone. The Volvo XC90’s standard advanced driver-assistance system “has nothing to do” with the Uber test vehicle’s autonomous driving system, he said."

Mobileye, the company that makes the collision-avoidance technology behind Aptiv's tech, was also quick to pile on, noting that if implemented correctly, their technology should have been able to detect the pedestrian in time:

"Intel Corp.’s Mobileye, which makes chips and sensors used in collision-avoidance systems and is a supplier to Aptiv, said Monday that it tested its own software after the crash by playing a video of the Uber incident on a television monitor. Mobileye said it was able to detect Herzberg one second before impact in its internal tests, despite the poor second-hand quality of the video relative to a direct connection to cameras equipped to the car."

In response to Uber's tragic self-driving face plant, Arizona this week announced that it will be suspending Uber's self-driving testing technology in the state indefinitely:

Plenty have justly pointed out that Arizona also has plenty of culpability here, given the regulatory oversight of Uber's testing was arguably nonexistent. That said, Waymo (considered by most to be way ahead of the curve on self-driving tech) hasn't had similar problems, and there's every indication that a higher quality implementation of self-driving technology (as the various vendors above attest) may have avoided this unnecessary tragedy.

Still somehow lost in the finger pointing (including Governor Doug Ducey's "unequivocal commitment to public safety") is the fact that Arizona already had some of the highest pedestrian fatalities in the nation (of the human-caused variety). There were ten other pedestrian fatalities the same week as the Uber accident in the Phoenix area alone, and Arizona had the highest rate of pedestrian fatalities in the nation last year, clearly illustrating that Arizona has some major civil design and engineering questions of its own that need to be answered as the investigation continues.

Again, there's plenty of blame to go around here, and hopefully everybody in the chain of dysfunction learns some hard lessons from the experience. But it's still important to remember that human-piloted counterparts cause 33,000 fatalities annually, a number that should be dramatically lower when self-driving car technology is inevitably implemented (correctly).

Filed Under: arizona, autonomous vehicles, pedestrians, safety, self-driving cars
Companies: uber

Uber's Video Shows The Arizona Crash Victim Probably Didn't Cause Crash, Human Behind The Wheel Not Paying Attention

from the everyone-error dept

In the wake of a Tempe, Arizona woman being struck and killed by an Uber autonomous vehicle, there has been a flurry of information coming out about the incident. Despite that death being one of eleven in the Phoenix area alone, and the only one involving an AV, the headlines were far closer to the "Killer Car Kills Woman" sort than they should have been. Shortly after the crash, the Tempe Police Chief went on the record suggesting that the victim had at least some culpability in the incident, having walked outside of the designated crosswalk and that the entire thing would have been difficult for either human or AI to avoid.

Strangely, now that the video from Uber's onboard cameras have been released, the Tempe police are trying to walk that back and suggest that reports of the Police Chief's comments were taken out of context. That likely is the result of the video footage showing that claims that the victim "darted out" in front of the car are completely incorrect.

Contrary to earlier reports from Tempe’s police chief that Herzberg “abruptly” darted out in front of the car, the video shows her positioned in the middle of the road lane before the crash.

Based on the exterior video clip, Herzberg comes into view—walking a bicycle across the two-lane road—at least two seconds before the collision.

Analysis from Bryan Walker Smith, a professor at the University of South Carolina that has studied autonomous vehicle technology indicates that this likely represents a failure of the AVs detection systems and that there may indeed have been enough time for the collision to be avoided, if everything had worked properly.

Walker Smith pointed out that Uber’s LIDAR and radar equipment “absolutely” should’ve detected Herzberg on the road “and classified her as something other than a stationary object.”

“If I pay close attention, I notice the victim about 2 seconds before the video stops,” he said. “This is similar to the average reaction time for a driver. That means an alert driver may have at least attempted to swerve or brake.”

The problem, of course, is that AVs are in part attractive because drivers far too often are not alert. They are texting, playing with their phones, fiddling with the radio, or looking around absently. We are human, after all, and we fail to remain attentive with stunning regularaty.

So predictable is this failure, in fact, that it shouldn't surprise you all that much that the safety operator behind the wheel of this particular Uber vehicle apparently is shown in the video to have been distracted by any number of things.

A safety operator was behind the wheel, something customary in most self-driving car tests conducted on public roads, in the event the autonomous tech fails. Prior to the crash, footage shows the driver—identified as 44-year-old Rafaela Vasquez—repeatedly glancing downward, and is seen looking away from the road right before the car strikes Herzberg.

So the machine might have failed. The human behind the wheel might have failed. The pedestrian may have been outside the crosswalk. These situations are as messy and complicated as we should all expect them to be. Even if the LIDAR system did not operate as expected, the human driver that critics of AVs want behind the wheel instead was there, and that didn't prevent the unfortunate death of this woman.

So, do we have our first pedestrian death by AV? Kinda? Maybe?

Should this one incident turn us completely off to AVs in general? Hell no.

Filed Under: ai, arizona, autonomous vehicles, driverless cars, pedestrians
Companies: uber

Tempe Police Chief Indicates The Uber Self-Driving Car Probably Isn't At Fault In Pedestrian Death

from the human-error dept

The internet ink has barely dried on Karl's post about an Uber self-driving vehicle striking and killing a pedestrian in Arizona, and we already have an indication from the authorities that the vehicle probably isn't to blame for the fatality. Because public relations waits for nobody, Uber suspended its autonomous vehicles in the wake of the death of a woman in Tempe, but that didn't keep fairly breathless headlines being painted all across the mainstream media. The stories that accompanied those headlines were more careful to mention that an investigation is required before anyone knows what actually happened, but the buzz created by the headlines wasn't so nuanced. I actually saw this in my own office, where several people could be heard mentioning that autonomous vehicles were now done.

But that was always silly. It's an awkward thing to say, but the fact that it took this long for AVs to strike and kill a pedestrian is a triumph of technology, given just how many people we humans kill with our cars. Hell, the Phoenix area itself had 11 pedestrian deaths by car in the last week, with only one of them being this Uber car incident. And now all of that hand-wringing is set to really look silly, as the Tempe police chief is indicating that no driver, human or AI, would likely have been able to prevent this death.

The chief of the Tempe Police has told the San Francisco Chronicle that Uber is likely not responsible for the Sunday evening crash that killed 49-year-old pedestrian Elaine Herzberg.

“I suspect preliminarily it appears that the Uber would likely not be at fault in this accident," said Chief Sylvia Moir.

Herzberg was "pushing a bicycle laden with plastic shopping bags," according to the Chronicle's Carolyn Said, when she "abruptly walked from a center median into a lane of traffic."

After viewing video captured by the Uber vehicle, Moir concluded that “it’s very clear it would have been difficult to avoid this collision in any kind of mode (autonomous or human-driven) based on how she came from the shadows right into the roadway."

So, once again, this tragedy has almost nothing to do with automobile AI and everything to do with human beings being faulty, complicated creatures that make mistakes. We don't need to assign blame or fault to a woman who died to admit to ourselves that not only did the self-driving car do nothing wrong in this instance, but also that it might just be true to say that the car's AI had a far better chance of avoiding a fatality than the average human driver. The car was not speeding. It did not swerve. It did not adjust its speed prior to the collision.

This obviously isn't the conclusion of the police's investigation, but when the police chief is already making these sorts of noises early on, it's reasonable to conclude that the visual evidence of what happened is pretty clear. Sadly, all this likely means is that the major media websites of the world will have to bench their misleading headlines until the next death that may or may not be the fault of a self-driving vehicle.

Filed Under: arizona, autonomous vehicles, fatalities, pedestrian, self-driving cars, tempe
Companies: uber

Pedestrian Deaths By Car In Phoenix Area Last Week: 11. But One Was By A Self-Driving Uber

from the I-can't-do-that,-Dave dept

Despite worries about the reliability and safety of self-driving vehicles, the millions of test miles driven so far have repeatedly shown self-driving cars to be significantly more safe than their human-piloted counterparts. Yet whenever accidents (or near accidents) occur, they tend to be blown completely out of proportion by those terrified of (or financially disrupted by) an automated future.

So it will be interesting to watch the reaction to news that a self-driving Uber vehicle was, unfortunately, the first to be involved in a fatality over the weekend in Tempe, Arizona:

"A self-driving Uber SUV struck and killed a pedestrian in Tempe, Arizona, Sunday night, according to the Tempe police. The department is investigating the crash. A driver was behind the wheel at the time, the police said.

"The vehicle involved is one of Uber's self-driving vehicles," the Tempe police said in a statement. "It was in autonomous mode at the time of the collision, with a vehicle operator behind the wheel."

Uber, for its part, says it's working with Tempe law enforcement to understand what went wrong in this instance:

Bloomberg also notes that Uber has suspended its self-driving car program nationwide until it can identify what exactly went wrong. The National Transportation Safety Board is also opening an investigation into the death and is sending a small team of investigators to Tempe.

We've noted for years now how despite a lot of breathless hand-wringing, self-driving car technology (even in its beta form) has proven to be remarkably safe. Millions of AI driver miles have been logged already by Google, Volvo, Uber and others with only a few major accidents. When accidents do occur, they most frequently involve human beings getting confused when a robot-driven vehicle actually follows the law. Google has noted repeatedly that the most common accidents it sees are when drivers rear end its AI-vehicles because they actually stopped before turning right on red.

And while there's some caveats for this data (such as the fact that many of these miles are logged with drivers grabbing the wheel when needed), self-driving cars have so far proven to be far safer then even many advocates projected. We've not even gotten close to the well-hyped "trolly problem," and engineers have argued that if we do, somebody has already screwed up in the design and development process.

It's also worth reiterating that early data continues to strongly indicate that self-driving cars will be notably safer than their human-piloted counterparts, who cause 33,000 fatalities annually (usually because they were drunk or distracted by their phone). It's also worth noting that 10 pedestrians have been killed by drivers in the Phoenix area (including Tempe) in the last week alone by human drivers, and Arizona had the highest rate of pedestrian fatalities in the country last year. And it's getting worse, with 197 Arizona pedestrian deaths in 2016 compared to 224 in 2017.

We'll have to see what the investigation reveals, but hopefully the tech press will view Arizona's problem in context before writing up their inevitable hyperventilating hot takes. Ditto for lawmakers eager to justify over-regulating the emerging self-driving car industry at the behest of taxi unions or other disrupted legacy sectors. If we are going to worry about something, those calories might be better spent on shoring up the abysmal security and privacy standards in the auto industry before automating everything under the sun.

Filed Under: accidents, autonomous vehicles, pedestrian fatalities, self-driving cars
Companies: uber

Slowing Down Driverless Cars Would Be A Fatal Mistake

from the people-are-already-dying dept

Unsubstantiated driverless car hype may be annoying, but that shouldn't blind us to the real cost of unnecessarily delaying autonomous vehicle (AV) deployment.

Last week, after exploring new data from the California AV disengagement reports, Ross Marchand of the Taxpayers Protection Alliance argued that we should "put driverless cars back in the slow lane." California requires AV companies testing in the state to report each time a human operator takes over for a driverless car — an event otherwise known as a "disengagement." Marchand offers some interesting analysis, but ultimately reads far too much into a limited dataset and pushes for a restrictive policy prescription that would undermine public safety. The discussion is worth fleshing out because it reveals important limits to the "precautionary principle" mindset that is so common in AV discussions.

In 2017, Waymo — the self-driving car project formerly belonging to Google — reported driving over 350,000 miles on California roads with 63 total disengagements. Marchand claimed that, based on these data, Waymo's test vehicles are still not as safe as human drivers and that they are improving at a slower rate than those hyping AVs would have us believe. Further, he argued that until driverless cars can prove they are safer than human operators, we should keep them off public roads — and instead test them on expensive private tracks.

There are a few glaring issues with this argument. First, it overestimates how applicable and reliable the California disengagement data really are. As many commentators have pointed out, disengagement data are a poor measure of AV progress. Not only are disengagement reports an apples-to-oranges comparison across vehicle manufacturers who use different definitions, strategies and road conditions for testing, but Marchand drills down by comparing particular disengagement subcategories, leaving him with sample sizes of less than 20 — several orders-of-magnitude too small to make meaningful comparisons. Furthermore, comparing disengagements to would-be fatalities is problematic given that a safety driver's presence enables testing in regions that the vehicle is still learning to handle.

Marchand also left aside the successful testing and deployment of Waymo's fully driverless cars in Arizona. Since November 2017, hundreds of AVs have been providing free taxi services in the suburbs of Phoenix without any safety driver in the front seat. To date, there have been no reported accidents or fatalities. This suggests what we've known all along: these companies already face a host of legal, political, economic, regulatory and publicity pressures that incentivize them to prioritize safety in AV deployment. They know that every bump, scrape and crash will make headlines (regardless of who is at fault) and will slow or — if it's serious enough — completely derail their path to market. Waymo obviously feels confident enough to take its hands off the wheel, and so far has been right. Why rip AVs off the roads when no one has been harmed?

Marchand's larger argument against AV testing on public roads provided a textbook example of the precautionary principle in practice. Simply put, the precautionary principle requires innovators to prove that their new technology will not harm society, rather than placing the onus on regulators and litigators to demonstrate that an innovation actually causes harm.

And to that point, Marchand fails to specify what exactly the harm of public testing has been. Public testing has not unleashed mass fatalities on society, or even mass fender-benders. Rather, it appears to be speeding up the feedback loop of better data and more-rigorous test environments, leading to faster improvements in autonomous technology.

As a society, we can't afford to wait until we are 100-percent certain that driverless cars are statistically safer than humans before letting them on the roads. As a report from RAND highlighted, it could take several decades to accumulate enough miles on private test courses to know beyond a shadow of a doubt that AVs are safer than their human counterparts. Relying on Marchand's precautionary principle approach would mean waiting decades while nearly 40,000 people die on our roads every year. Regulatory delay of this magnitude could, conservatively-speaking, cost tens of thousands of lives.

That's not to say private test courses don't have a role to play in AV development. Indeed, Waymo already operates an extensive test track in Arizona where operators take real-world scenarios and experiment with hundreds of possible variations. This hybrid approach combines the advantages of real-world testing and private test courses. But forcing all AV testing onto private test tracks cuts off the real-world data necessary for this complementary approach and substantially raises the barrier to entry for new competitors.

To be clear, we should avoid over-hyping the progress made in AV development. Carefully taking into account the safety data will be a key part of this effort. But halting all real-world AV deployment is a heavy-handed "solution" desperately in search of a problem.

Caleb Watney (@calebwatney) is a technology policy associate at the R Street Institute. Marc Scribner (@marcscribner) is a senior fellow at the Competitive Enterprise Institute.

Filed Under: autonomous vehicles, california, driverless cars, human drivers, ross marchand

Waymo And Uber's Settlement Is A Good Thing: Focus On Innovating, Not Litigating

from the took-too-long-already dept

Back in December, right before the Waymo/Uber trial was supposed to begin (before it got delayed due to an unexpected bombshell about withholding evidence that... never actually came up at the trial), I had a discussion with another reporter about the case, in which we each expressed our surprise that a settlement hadn't been worked out before going to trial. It seemed as though part of the case was really about the two companies really disliking each other, rather than there being a really strong legal case.

A year ago, when the case was filed, I expressed disappointment at seeing Google filing this kind of lawsuit. My concern was mainly over the patent part of the case (which were dropped pretty early on), and the fact that Google, historically, had shied away from suing competitors over patents, tending to mostly use them defensively. But I had concerns about the "trade secrets" parts of the case as well. While there does seem to be fairly clear evidence that Anthony Levandowski -- the ex-Google employee at the heart of the discussion -- did some sketchy things in the process of leaving Google, starting Otto, and quickly selling Otto to Uber, the case still felt a lot like a backdoor attempt to hold back employee mobility.

As we've discussed for many years, a huge part of the reason for the success of Silicon Valley in dominating the innovation world has to do with the ease of employee mobility. Repeated studies have shown that the fact that employees can switch jobs easily, or start their own companies easily, is a key factor in driving innovation forward. It's the sharing and interplay of ideas that allows the entire industry to tackle big problems. Individual firms may compete around those big breakthroughs, but it's the combined knowledge, ideas, and perspective sharing that results in the big breakthroughs.

And even though that's widely known, tech companies have an unfortunate history of trying to stop employees from going to competitors. While non-competes have been ruled out in California, a few years back there was a big scandal over tech companies having illegal handshake agreements not to poach employees from one another. It was a good thing to see the companies fined for such practices.

However, the latest move is to use "trade secrets" claims as way to effectively get the same thing done. The mere threat of lawsuits can stop companies from hiring employees, and can limit an employee's ability to find a new job somewhere else. That should concern us all.

However, in this lawsuit, everything was turned a bit upside down. Part of it was that there did appear to be some outrageous behavior by Levandowski. Part of it was that, frankly, there are few companies out there disliked as much as Uber. It does seem that if it were almost any other company on the planet, many more people would have been rooting against Google as the big incumbent suing a smaller competitor. But, in this case, many many people seemed to be rooting for Google out of a general dislike of Uber itself.

My own fear was that this general idea of "Uber = bad" combined with "Levandowski doing sketchy things" could lead to a bad ruling which would then be used to limit employee mobility in much more sympathetic settings. Thankfully, that seems unlikely to happen. As Sarah Jeong (who's coverage of this case was absolutely worth following) noted, despite all the rhetoric, it wasn't at all clear that Waymo proved its case. Lots of people wanted Google/Waymo to win for emotional reasons, but the legal evidence wasn't clearly there.

And now the case is over. As the trial was set to continue Friday morning, it was announced that the two parties had reached a settlement, in which Uber basically hands over a small chunk of equity to Waymo (less than Waymo first tried to get, but still significant). As Jeong notes in another article, both sides had ample reasons to settle -- but the best reason of all to settle is so that they can focus on just competing in the market, rather than the courtroom and in not setting bad and dangerous precedent concerning employee mobility in an industry where that's vital.

Filed Under: anthony levendowski, autonomous vehicles, competition, employee mobility, innovation, patents, self driving cars, settlement, trade secrets, travis kalanik
Companies: google, otto, uber, waymo

Fighting The Future: Teamsters Demand UPS Ban Drones And Autonomous Vehicles

from the giving-unions-a-bad-name dept

As I've occasionally mentioned in the past, my undergraduate studies were in (of all things) "industrial and labor relations," which involved many, many courses of study on the history of unions, collective bargaining and the economics around such things. I tend to have a fairly nuanced view of unionizing that I won't get into here, other than to note that a big part of the reasons why unions get a bad name is when they take indefensible positions that they think will "protect" their members, but which actually are long term suicidal. This is one of those stories. Reports are coming out that as the Teamsters are entering negotiations on a new contract with shipping giant UPS, their demands include a ban on both drone deliveries and on the use of autonomous vehicles. These are, not surprisingly, both technologies that UPS has been experimenting with lately (as has nearly every other delivery company).

You can understand the short term thinking here, of course, UPS drivers see both of those options as potential "competition" that would decrease the number of drivers and potentially cause many to lose their jobs. And that might be true (though, it also might not be true as we'll discuss below). But, at the very least, demanding that the company that employs you directly choose not to invest in the technologies of the future is demanding that a company commit suicide -- in which case all those jobs for drivers would likely be eliminated anyway. While there are obviously a lot more variables at work here, it's not hard to see how a competing delivery company -- whether Fedex, the US Postal Service, Amazon or someone else entirely -- could get drone/driverless car delivery right, and suddenly UPS's service is seen as slower, more expensive and less efficient in many cases. If that's the case, UPS would likely have to layoff tons of workers anyway.

The other key point: the idea that these technologies are simply going to destroy all the jobs is almost certainly highly overstated. They very likely will change the nature of jobs, but not eliminate them. Professor James Bessen has been doing lots of research on this for years, and has found that in areas of heavy automation, jobs often increase (though they may be changed). That links to an academic paper he wrote, but he also wrote a more general audience targeted piece for the Atlantic on what he calls the automation paradox. As Bessen explains:

Automation reduces the cost of a product or service, and lower prices tend to attract more customers. Software made it cheaper and faster to trawl through legal documents, so law firms searched more documents and judges allowed more and more-expansive discovery requests. Likewise, ATMs made it cheaper to operate bank branches, so banks dramatically increased their number of offices. So when demand increases enough in response to lower prices, employment goes up with automation, not down. And this is what has been happening with computer automation overall during the last three decades. It’s also what happened during the Industrial Revolution when automation in textiles, steel-making, and a whole range of other industries led to a major increase in manufacturing jobs.

He does note that the nature of many jobs can change, and also recognizes that just because this has happened in most industries in the past it doesn't necessarily mean the same thing will happen in the future.

But, if we were to game out the scenarios here, which one makes more sense? As explained above, forcing UPS to put a complete ban on these technologies will be devastating for the company and the people it employs should the technology take off. If, instead, as Bessen suggests, jobs change and demand increases, then wouldn't the union's membership be much better served by working with the company together on a program that enables the experimentation and deployment of these technologies combined with programs to help its current workforce transition into new or related jobs around the likely increased demand for shipping? Even if we see the worst case scenario that the union clearly believes, of drones/autonomous vehicles destroying jobs -- as already discussed that will happen anyway if the Teamsters ban UPS from innovating while their competitors do.

This is, yet again, an example of short term thinking on the part of the union, and a near total lack of strategic vision for what will best serve membership in the long term. It is focused on pretending the future doesn't exist, and if everyone just covers their eyes and ears and pretends these technologies don't exist, they somehow, magically, won't change the market. If I were a member of the Teamsters I'd be quite angry at this kind of short-term, destructive thinking by my union, rather than being forward-looking and aiming for solutions that will actually help the members in the long run.

Filed Under: adapting, autonomous vehicles, competition, drones, future, innovation, teamsters, unions
Companies: teamsters, ups