Tag Archives: smart technology

When Smart Technology Fails

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When we learned of the death of Elaine Herzberg of Tempe Arizona this week, it seemed appropriate to take a break in our current series of episodes. For those not following the technology news, Ms Herberg died after she was struck by a self-driving Uber vehicle. As our podcast deals with the very technology behind autonomous cars, we thought we should assess the challenges this accident poses to the industries that build and promote smart technologies.

We, of course, offer our sincere condolences to Ms. Herzberg’s family and friends and community. As anyone who has witnessed such an event knows, words fail in these circumstances. We can only bow our heads in respect.

In the coming days and weeks, there will be extended discussions of autonomous vehicles. There will be liability to assign and compensation to be made. We will ask if this technology is indeed ready to be deployed and if self-driving cars are being properly certified for public use on the streets. We will examine the ethics of testing these automobiles on city roadways. We’ll also consider how we are notifying residents that they are part of the trial of this technology and are sharing, perhaps inadvertently, some of the risk.

As we look at the issues surrounding these vehicles, it is useful to remember that the term “artificial intelligence” does not fully capture the nature of the technology that guides self-driving cars. The phrase “artificial Intelligence” was coined by the computer scientist John McCarthy in the 1950s. He used it to express the goal, still quite elusive, of building a machine that behaved like a human being. It is perhaps a little more illuminating to use the term “industrialized intelligence” to describe the current trend in smart machines, including autonomous vehicles. Afterall, we are not talking about technology in isolation but as part of industrial processes.

The difference between “artificial intelligence” and “industrial intelligence” is more than a slight shade semantic meaning. Both activities share common methods that organize human intelligence, combine it, systematize it, and put it in forms that can be utilized by machines. Both use these machines, to reason, to plan, to search, to aggregate, to separate, to recognize, to control. Yet, industrialized intelligence goes beyond artificial intelligence to embrace the goal of providing goods and services for the world’s population, goods and services that should enrich the lives of as many people as possible.

Behind industrialization is the motivating force of wealth. Autonomous vehicles, like the conventional automobile before them, offer the promise of great wealth. One need only tour the residential districts of Stuttgart, Yokohama and even the suburbs of the great motor city Detroit to be reminded of how much wealth automobiles have generated in the past and how much a new form of automotive transportation might offer for the future.

That potential new form of automobile, the smart car, the intelligent car, the self-driving car, the autonomous car, carries one more concept of our age: disruption. In a mature economy, new products have to elbow their way into the market. They do this by offering new benefits at reduced costs, by restructuring supply chains, re-organizing production, re-conceiving markets. As they do this, they disrupt. They move capital and people from an old industry to a new. They disrupt the lives of people, people who are suppliers, workers, customers, and even innocent bystanders such as Ms. Herzberg.

Over the history of industrialization, a history that is now 250 years long, we have seen calls to transform industry into something more compassionate. Critics have argued that we should disrupt it into an activity that is more generous and not guided solely by the selfish accumulation of wealth. Such calls are idealistic, though they are not without effect. We can certainly point to the kindness and generosity of many an individual industrialist. Yet that idealism has never yielded a system that simultaneously pulls us away from the profit motive and guarantees a more generous world. The realists keep us firmly grounded in conventional capitalism.

Yet, through idealism or realism, industrial systems can change by altering the demands on industrial leaders. By coincidence, the podcast received an email from a listener in China. (We are always somewhat surprised at the global reach of our episodes.) The writer suggested that we had found the limitations of Western economic ideas and needed to embrace theories promoted by Deng Ziao Peng and Xi Jinping in order to get the full benefit of technology. The letter is a little obscure to us, as it involves references to classic Chinese texts. Yet, it served as a reminder of how we rush to embrace wealth as the sole goal of industrialization without always thinking about what we are doing or who we are disrupting. China has certainly produced great wealth in a surprisingly short space of time. Yet to any observer, the country has paid the same price of industrial disruption that was paid by every country that proceeded it.

History teaches us that substantial social change requires a greater impetus than a single incident can provide. Perhaps most importantly, change requires a predisposing doubt, a sense that the current plan and the current leaders are not producing the best decisions. This doubt builds in stages, as individual incidents encourage the public and the public institutions to question the motives and leadership of those who guide industry. For perhaps a decade, tech industries have been bedeviled by growing doubts, doubts that their products benefit all equally, doubts that they support the best interest of consumers, and doubts that their leaders can make decisions for the benefit of all. The accident involving Ms. Herzberg and the self-driving Uber car will almost certainly add its marker to the pile of doubt. It will not be enough to change the arc of the computer and software industries. However, it should one additional sign that the leaders of those very industries need to think more broadly, more clearly and, perhaps, more generously than they have done in the past if they are not to be disrupted themselves.

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