“Algorithm Aversion” and Scary Headlines

If it bleeds, it leads.

That’s the long-accepted dictum of how a news organization makes its biggest profit margin. News outlets provide an essential public service, but they must survive as businesses as well. Psychology Today noted this trend, saying that “news is a money-making industry, one that doesn’t always make the goal to report the facts accurately.”

Perhaps that’s why the Washington Post’s science section recently ran an article — the meat of which ended up being an exploration of why public fears of autonomous vehicles (AVs) are irrational — under the headline “Will the Public Accept the Fatal Mistakes of Self-Driving Cars?”

The article explored the idea of “algorithm aversion,” which, according to the Post and its sources, is the idea that “people are … more inclined to forgive mistakes by humans than machines.” The story cites public anxieties about refrigerators in the 1920s as a parallel example to current concerns about AVs, noting that “although scientists understood that cold storage could cut down on food-borne illnesses, reports of refrigeration equipment catching fire or leaking toxic gas made the public wary.”

All true, and a pertinent parallel. So why did the article need to begin with the line “How many people could self-driving cars kill before we would no longer tolerate them?” It might grab a reader’s attention, but the attention-grabbing part essentially represents the direct opposite of what the piece is about. This question is discarded and never addressed as the article proceeds. What purpose does it serve other than to stoke fear and get clicks?

Other recent articles in the pages of the Post follow this trend. When Uber rolled out its self-driving test back in September, the paper covered it. Buried in the article were some important facts: in the seventh paragraph, the writer mentioned that the vehicles “will have two trained safety drivers on each ride.” The twentieth paragraph — third from the bottom — briefly described Pittsburgh Mayor William Peduto’s first ride in one of the Uber vehicles, of which he said “There was no time I was fearful or worried … I’m more worried when I’m on the road with an 18-year-old who is learning how to drive.”

That all sounds pretty good — so why did that article need the headline “Why Uber is Turning The Streets of a U.S. City into its Laboratory”? Or, in another article, why refer to voluntary Uber AV passengers as “guinea pigs”? A whole city reduced to an experimental lab? Humans as powerless and expendable as test-subject “guinea pigs”? Sounds positively dystopian. But, to anyone that knows about AV tech, it also sounds ludicrous and dramatically overstated.

Elon Musk weighed in on this issue back in October, saying “if, in writing some article that’s negative, you effectively dissuade people from using an autonomous vehicle, you’re killing people. Next question.” That’s a big statement — but unfortunately, it’s correct.

The fact of the matter is that AVs promise a level of safety that is currently impossible in our world of error-prone human drivers. The Post has quoted quite a few experts in many articles to that effect. But in order to address the logical fallacy of “algorithm aversion,” do they really need to sell the story using attention-grabbing headlines and scare quotes? The stakes are too high to be using frightening language.

Because the real “bleeding” that should “lead” are facts that, while far more dramatic than the material being covered in the AV realm, are perhaps not “news”, since they’ve been known for many years now. Each year, over 35,000 people die in car accidents. A full third of these come from intoxicated drivers. Another third are the result of reckless speeding. Distracted drivers represent another twelve percent. Human error is the cause of 94% of auto-related deaths. And across all modes of transport, these automobile deaths represent 95% of total fatalities, according to the U.S. Bureau of Transportation Statistics. And perhaps one reason the total number of airplane and watercraft deaths are in the three-digit range instead of deca-thousands is that each relies on some degree of automation to reduce human error.

If the Washington Post is actually concerned about safety, perhaps it should start covering the 92 people killed every day in this country as a result of human error behind the wheel. They wouldn’t even need clever turns of phrase or headlines that don’t correspond to the information below them: the number itself is scary enough on its own.

Apparently “algorithm aversion” leads us to forgive human error more than we do machine error. But does that make it right?

Rob Fischer is President of GTiMA and a senior advisor to Mandli Communications’ strategy team. GTiMA and Mandli Communications are both proud partners of the Wisconsin Autonomous Vehicle Proving Ground.

Follow Rob on Twitter (@Robfischeris) and Linkedin.

Choosing How to Use Our Land

Next time you’re heading out of a big shopping center or a mall, scanning the endless sea of cars and trying to remember where you parked, take a moment to picture something completely different: a narrow drop-off/pick up lane, and beyond it, a tranquil, leafy park.

For now, you’re stuck with the parking lot. But that could change – this is a story about how we, as a community, choose to use our land.

A 2014 study of six cities conducted by UConn, in partnership with the State Smart Transportation Initiative, showed that “when measuring the amount of space given to parking … tax revenues for that real estate tend to be much lower than for other types of development.”

There’s one simple reason for that. Each and every parking spot in a city is taking up space that otherwise could be occupied by business, homes, schools. The study puts this in staggering economic terms. In Hartford, Conn., whose zeal for parking lot growth is about on par with the average American city, every individual parking space represents $1,200 lost yearly in potential tax revenue.

The total cost of parking spaces to Hartford? $50 million per year. This in a city where all downtown real estate brings in $75 million in municipal revenues. Imagine what cities would be able to do with an infusion of 66% extra revenue, if only all those parking spaces weren’t necessary.

Making matters worse, car-dependent communities devote more land to parking than you might expect. A 2007 Purdue study found that “the total area devoted to parking in a midsize Midwestern county … outnumbered resident drivers 3-to-1.” That’s right — in an average county, for every car, whether it’s on the road or not, there are three parking spots out there waiting for it. A Planetizen analysis of the Purdue study, among other studies, points out that “a city must devote between 2,000 and 4,000 square feet per automobile.”

When that’s all tallied up, Planitzen writer Todd Litman says, land used for parking “exceeds the amount of land devoted to housing per capita for moderate to high development densities … and is far more land than most urban neighborhoods devote to public parks.”

Of course, if we slashed the amount of land devoted to parking in cities, we’d simply be creating massive congestion problems as people circled blocks looking for somewhere to park. The surprising amount of waste imposed by parking lots is one of many burdens on society imposed by car culture.

And this is yet another externality that AVs promise to offset. With the advent of AV tech, and its steady evolution over the next decade or two, the need for parking lots will decrease dramatically. Experts agree that AVs will eventually be safe enough to be trusted to park themselves in designated lots — in much tighter confines, without the need for people to enter or exit their cars upon parking — a few miles outside of a city after dropping you off at an area close to the entrance of the mall. When you’re ready to leave, you’d simply summon it with your smartphone and it would dutifully return to carry you to your next destination.

This advance couldn’t come at a more opportune time. The UN recently estimated that by 2050, an additional 2.5 billion people will be living in urban centers across the globe. Under the current circumstances, if just one billion of those people drive a car, that would necessitate three billion new parking spaces. This is obviously untenable, especially considering cities will need to add housing and infrastructure to fit all the newcomers.

So while hunting for your car in a gigantic parking lot in a shopping mall is annoying and visually unappealing, it’s just a tiny piece of a mounting global emergency. Luckily for us, the solution – to this, along with other crises imposed by car culture – is a top priority of tech researchers and car manufacturers across the globe. If AV tech is rolled out safely and responsibly, this sprawling predicament will soon become a thing of the past.

Rob Fischer is President of GTiMA and a senior advisor to Mandli Communications’ strategy team. GTiMA and Mandli Communications are both proud partners of the Wisconsin Autonomous Vehicle Proving Ground.

Follow Rob on Twitter (@Robfischeris) and Linkedin.

Autonomous Vehicles and Opportunity

America is the land of opportunity – unless you can’t afford to buy a car and don’t live in a city that has made significant investments in public transit.

In that case, it’s the land of inescapable poverty for millions of citizens.

According to a 2015 New York Times analysis of an ongoing Harvard study, “commuting time has emerged as the single strongest factor in the odds of escaping poverty … and building a better life.” The study determined that, on average, the longer a person’s commute, the lower the pay that person will earn for their time.

To appreciate how serious this problem is, it would help to know these facts: access to reliable and affordable transportation is a bigger factor in building a better life for oneself than crime, test scores in schools, or living in a two-parent home. When certain politicians blame a poor community’s struggles on these things and leave out transportation, they’re mistaken.

It’s pretty simple when you think about it. Imagine you live in the inner city as a person in poverty. Most of your neighbors are also poor. You rely on a bus system that only has a few stops throughout the city and that sometimes takes hours to move you just a few miles, between bus changes and unplanned delays. So you can really only make it to a job somewhere that’s within a few miles of where you live. That distance isn’t likely to to be far enough to get you to work in a more affluent area. So your options are limited to low-paying jobs. Want to go to school, improve your credentials, find a new career? Good luck getting to campus for night school when you already spend half the night riding a series of buses back to your neighborhood.

If that’s not bad enough, here’s the salt in the wound: if you are in this situation to begin with, counting on unreliable mass transit for your commute, you’re spending a higher percentage of your net income on transportation than someone who works a higher-paying job and drives a car to work. It’s simply unfair and unjust, and does not reflect the ideals the nation was founded upon.
But there is hope.

A big knock on AVs has been that they’re going to be too expensive, and the tech itself will be the province of the wealthy. That’s a false premise. People won’t need to own AVs, necessarily, to reap their benefits.

Cabs cost a lot of money for one simple reason: the drivers. People driving cabs for a living need to be paid a living wage for their work, or there would be no cabs. And the same goes for city buses. Bus drivers must be paid too. When only a small percentage of a city is using the bus system, the city is drawing on a pretty limited source of income from fares, and so the rates climb higher and higher.

But in a fully autonomous vehicle, people could ride-share for a fraction of the cost of a bus ticket, and thus make it to their destination – door to door, no vehicle changes or long walks required – in an amount of time the average person would deem reasonable for a commute. In cities where ride-shares from companies like Uber have been ongoing for a while now, the cost, even with a driver, is around a quarter of what a taxi would have cost. When there’s no need for a driver, that price is predicted to drop even more.

The same goes for buses. As buses become more reliable as a result of automation, they’ll be able to cover more ground and move more quickly. They’ll have to stay competitive with private companies offering ride-shares, and the massive reduction in overhead in terms of bus driver salaries will allow them to price their services even lower.

The result of this increased mobility could be huge. The Harvard study tracked kids in the 1980s and 90s whose families moved to areas with better public transit, and the results were astounding: the average kid who moved ended up earning about ten percent more, on average, than those who didn’t. That number would be higher, by the way, if it only focused on kids who moved early in their childhoods – the younger the child was when moved to an area with easier access to educational and extracurricular opportunities, the better off they were as adults.

So AVs don’t just offer improvements to safety, even though if you searched a news database for AV benefits, you’d find mostly safety articles. By increasing mobility for the economically disadvantaged, they have the promise of bringing the American dream in reach for millions of people. Now that is good news.

Rob Fischer is President of GTiMA and a senior advisor to Mandli Communications’ strategy team. GTiMA and Mandli Communications are both proud partners of the Wisconsin Autonomous Vehicle Proving Ground.

Follow Rob on Twitter (@Robfischeris) and Linkedin.

What We Can and Cannot Say About the Tesla Crash

Last year, the National Highway Safety Transportation Association (NHSTA) conducted an investigation of Tesla’s Autopilot Software following a deadly, May 7, Model S. accident in Williston, Florida. The accident – which killed the car’s driver – was the first in a series of high-profile AV accidents, involving a variety of AV manufacturers, which skyrocketed public concern about the safety of autonomous vehicles.

Although the accidents are tragic, it is still premature to draw any conclusions about AV safety.

Statistically speaking, it is not yet possible to make a clear comparison between the safety of autonomous vehicles and human-driven vehicles. As of July 2016, the most autonomous miles driven by any developer — which turns out to be Tesla — was about 1.3 million. According to Susan M. Paddock, a senior statistician at RAND and a professor at the Pardee RAND Graduate School, “this does not come close to the level of driving that is needed to calculate safety rates. Even if autonomous vehicle fleets are driven 10 million miles, one still would not be able to draw statistical conclusions about safety and reliability.”

With so few AV miles driven, experts can’t estimate the impact AVs would have on, for instance, the 2.3 million car-related injuries reported in 2013, of which 32,719 resulted in deaths. That’s one fatality per 100 million miles driven.

According to the NHSTA, human errors such as driving too fast, alcohol impairment, distraction, and fatigue are the cause of more than 90 percent of automobile crashes. While it is safe to say that an autonomous vehicle is not likely to get drunk or sleepy, we are still in the data collection phase of evaluating the overall safety of these autonomous systems.

That said, it would also be premature to draw conclusions that discredit the potential of this autonomous technology.

After all, we’ve been here before. Take a look at the airline industry: in the short history of airline safety, the first great turning point occurred in the 1950s with the introduction of the jet engine, which was far more reliable than the behemoth piston-engine that preceded it. The second turning point followed with advances in sensor technology, computing, and artificial intelligence: like the introduction of GPS, aircraft avoidance systems and ground-proximity alarms in the 1970s and ‘80s.

Today, an aircraft is generally flown by a computer autopilot that tracks its position using motion sensors and dead reckoning, corrected as necessary with GPS. Software systems may even be used to land commercial aircraft. In a recent survey of airline pilots, those operating Boeing 777s on a typical flight reported spending just seven minutes manually piloting their planes; pilots operating Airbus planes spend half that time.

The safety outcomes of commercial airline automation have been tremendous. The year 2015 marks the safest year of airplane travel to date. The chances of dying on any given flight with one of the world’s major airlines are just one in 4.7 million; in any given year, you have a higher chance of getting struck by lightning, at one in 1.9 million. In the 1970s, an average of 68 commercial planes crashed each year. Last year, of the total 33.4 million flights, only 21 crashed.

As aviation safety expert Carl Rochelle puts it, “the most dangerous part of your airline flight is the trip to the airport.”

So how did flying become so safe?

The unfortunate reality is that the industry learned a great deal from its failures, most notably from its crashes. By examining downed plane wreckages and black-box recorders, they engineered solutions to the problems.

In the wake of the deadly Tesla accident, what we know is that the vehicle was on a divided highway with Autopilot engaged when a tractor-trailer took a left-hand turn across the road, perpendicular to the Model S. Neither Autopilot nor the driver seemed to notice the white side of the tractor-trailer against a brightly lit sky. The brake was never applied.

Sadly, in this case, the technology appears to have failed. But let’s not allow unsubstantiated fear about the overall safety of autonomous vehicles dictate how we move forward. Instead, let’s do what we’ve always done: embrace innovation and look for technology-based solutions that captivate our imaginations while ensuring that safety is the number one priority.

Rob Fischer is President of GTiMA and a senior advisor to Mandli Communications’ strategy team. GTiMA and Mandli Communications are both proud partners of the Wisconsin Autonomous Vehicle Proving Ground.

Follow Rob on Twitter (@Robfischeris) and Linkedin.

GPS Unit

GPS Unit

The GPS unit identifies the precise position of the vehicle and aids in navigation.