Academics put at risk a self-driving future by accepting industry’s optimistic predictions and obsessing over irrelevant questions, says Ashley Nunes.


Uber Technologies is set to go public this week, an event that has been described as the most anticipated technology filing since Facebook in 2012. Some forecasters expect that the ride-hailing giant could sell up to US$10-billion worth of stock. Self-driving technology features prominently in the company’s investor prospectus — after all, the company is bleeding cash, and most of the money goes towards paying its drivers. Automating the task of driving should boost the company’s balance sheets.

Some of the world’s largest car manufacturers and technology companies are competing to tap into what could be a $7-trillion revenue stream. Of course, industry talking points emphasize something besides money: safety. Many fatal road-traffic accidents are caused by errors people make when distracted by, for instance, texting, drinking or napping while driving. Self-driving technology promises to fix this.

Companies aren’t the only ones touting the virtues of driverless-vehicle technology. There is no shortage of academics speaking about how the technology will save lives. (TED talks often feature an estimate of how many people will die on the road while the talk is being delivered.) Respected journals and journalists have also forecast a public-health nirvana — after we cede control of our cars to the algorithms.

What these academics are not doing is asking the questions that society needs answered to decide what the role of driverless cars will be.

Academics love to be distracted by a future in which self-driving vehicles make life-or-death decisions while moving at high speed. Whether the robot trolley will crash into the businessman or the older woman is the question of the day. Never mind that — were this a legitimate transportation concern — regulators would have drafted guidelines and mandated the relevant driver training. Technology companies are, rightly, developing ways to control cars remotely, adding a further layer of oversight so that algorithms never have to make such decisions.

Of course, algorithms might make mistakes. Machines err much as do humans. The impact of such errors tends to be trivial when liquid-handling, fruit-picking or burger-flipping robots stumble. But the impact of a mistake made by a robot driving in the fast lane could be death to humans on the road.

This leads to something many academics overlook: driverless does not mean humanless. My research on the history of technology suggests that such advances might reduce the need for human labour, but it seldom, if ever, eliminates that need entirely. Regulators in the United States and elsewhere have never signed off on the use of algorithms crucial to safety without there being some accompanying human oversight. Rather than rehashing decisions from Philosophy 101, more academics should educate themselves on the history of the technology and the regulatory realities that surround its use.

Another problem is many academics’ acquiescence to industry talking points. Economists speak to how the technology will upend trade; urban planners describe how our cities will soon look very different after they have been reshaped, owing to the diminished need for car parks; and medical professionals proclaim the end of road-traffic accidents as we know them. These claims are often derived from those made in industry press releases rather than original — or rigorous — thought. Academics should be scrutinizing, not just repeating, such claims.

By merely rehashing the talking points of the self-driving industry, well-meaning academics draw attention away from the most important question that we should be asking about this technology: who stands to gain from its life-saving potential? Sam Harper, an epidemiologist at McGill University in Montreal, Canada, and his colleagues found that although road fatalities in the United States fell between 1995 and 2010, this benefit was not spread evenly across the socio-economic spectrum (S. Harper et al. Am. J. Epidemiol. 182, 606–614; 2015). If you live in the United States and have at least a university degree, your odds of dying on the nation’s roads have declined. But if you haven’t graduated from university, those odds have risen. In 1995, the mortality rates related to motor-vehicle accidents involving people at the bottom of the education spectrum were 2.4 times higher than those involving people at the top. By 2010, they were about 4.3 times higher.

One reason for this might be that people with less money tend to own older vehicles that lack advanced safety features, such as rear-facing cameras, blind-spot detectors and adaptive cruise control. To put it more simply: if there is a group in the United States that stands to benefit most from the life-saving potential of self-driving technology, it’s those who live in the greatest poverty, but only if they can afford the technology. Driverless-car technology might have the potential to improve public health and save lives, but if those who most need it don’t have access, whose lives would we actually be saving?

That is another of the many questions that researchers should be tackling, instead of blindly embracing the claims of the self-driving industry.



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