The Knowledge Jobs Most Likely to Be Automated

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Which kinds of knowledge workers are at high risk of job loss thanks to smart machines? Usually we don’t love getting that question, because the answer isn’t the simple one interviewers are seeking.

Many jobs include tasks that can and will be automated, but by the same token, almost all jobs have major elements that — for the foreseeable future — won’t be possible for computers to handle. Our advice therefore can’t boil down to a clear “avoid careers in a, b, and c” or “apply for jobs x, y, or z.” And yet, we have to admit that there are some knowledge-work jobs that will simply succumb to the rise of the robots. They are just too thoroughly composed of work that can be codified into standard steps and of decisions based on cleanly formatted data. A perfect example has just come up in the news. The headline as the Wall Street Journal writes it is this: “Financial Firms Turn to Artificial Intelligence to Handle Compliance Overload.”

Compliance, of course, refers to a company’s obligation to prove that it is following the rules spelled out by government regulators. In a financial services firm, that includes constant monitoring of possible money laundering, transactions subject to sanctions, or billing fraud, and preparedness for “know your customer” checks. All these are now being done, WSJ’s Ben DiPietro reports, by machines equipped with natural language processing systems.

But compliance with regulations isn’t only demanded of banks. Compliance professionals work in every kind of business – from health care companies challenged by legislation to food companies under a regulator’s watchful eye to airlines obliged to track anti-terrorism data. Job growth in the compliance category has far outpaced most fields in the past decade – but virtually all of its recordkeeping and communication is crying out for automation.

Compliance is ripe for automation because it is both rule-based and data-intensive. The more rules there are to follow, the more employee behavior there is to monitor, the more customer and employee transactions there are generating data—the more you need automated software to monitor compliance. The U.S. Congress or the European Union can throw all the regulations they want at banking and other industries, but politicians and bureaucrats are no match for today’s cognitive technologies. It’s hard to imagine complying with all the compliance regulations in some industries without automated help.

Not all the jobs in compliance will go away—often computers only suggest a likelihood of rule-breaking, leaving it to a person to investigate further before acting on that red flag—but many routine and information-intensive tasks will be taken away from human workers. There will undoubtedly be layoffs. Compliance workers will either be looking for work or lonelier at work, and that stinks. (And by the way, we sympathize with the fact that, just two years ago, people didn’t see this coming. The WSJ for example reported as recently as 2014 that the future was “very bright for anyone entering into compliance as a career.”)

At the level of a national economy, however, how much should we protest this particular line of labor dislocation?

Last fall, we had the pleasure of participating in the Global Peter Drucker Forum (an annual meeting of the minds in Vienna becoming known as the “Davos of management”) and we therefore spent some time brushing up our Drucker. One chapter of his work we found particularly interesting was about the “Entrepreneurial Society” that policymakers should be working harder to shape. Writing in the early eighties, Drucker was especially concerned about one major drag on entrepreneurial activity: the high cost of following ever more onerous regulations. He writes of “that dangerous and insidious disease of developed countries: the steady growth in the invisible cost of government”:

It is a real cost in money and, even more, in capable people, their time, and their efforts. The cost is invisible, however, since it does not show in governmental budgets but is hidden in the accounts of the physician whose nurse spends half her time filling out governmental forms and reports, in the budget of the university where sixteen high-level administrators work on “compliance” with governmental mandates and regulations, or in the profit-and-loss statement of the small business nineteen of whose 275 employees, while being paid by the company, actually work as tax collectors for the government, deducting taxes and Social Security contributions from the pay of their fellow workers, collecting tax-identification numbers of suppliers and customers and reporting them to the government, or, as in Europe, collecting value-added-tax (VAT).

Drucker’s complaint is that, in a world sorely in need of new solutions, these overhead costs constitute serious opportunity costs: “Does anyone, for instance, believe that tax accountants contribute to national wealth or to productivity, and altogether add to society’s well-being, whether material, physical or spiritual?” He points out that by forcing companies to devote people to such jobs, governments are misallocating “a steadily growing portion of our scarcest resource” – that is, well-educated human intellect — to “essentially sterile pursuits.”

Drucker thought of one solution to propose (we’ll let you read the chapter if you’re curious) but even he conceded it would never be accepted. Now, however, thirty-plus years later, another one is presenting itself. Artificial intelligence, by doing the sterile work of compliance, might support more entrepreneurial innovation without any compromise of the public interest.

When we talk about how smart machines should be deployed in workplaces, we constantly emphasize the importance of augmentation rather than automation. Employers, we insist, should implement cognitive computing solutions not so that they can make do with fewer people, but to enable their people to take on bigger challenges and have greater impact than they did before. Applying smart machines to the work of compliance has the potential to augment human work on an epic scale. By freeing up humans to work on more value-creating projects, it can promote the entrepreneurial society and enable the innovation that is our best hope of enhancing human well-being.

About the Author

Julia Kirby is a senior editor at Harvard University Press and longtime contributor to HBR‘s pages. Her newest book (May 2016) isOnly Humans Need Apply: Winners and Losers in the Age of Smart Machines, with Tom Davenport.

Thomas H. Davenport is the president’s distinguished professor in management and information technology at Babson College, and cofounder of the International Institute for Analytics. He also contributes to the MIT Initiative on the Digital Economy as a fellow, and as a senior advisor to Deloitte Analytics. Author of over a dozen management books, his latest is Only Humans Need Apply: Winners and Losers in the Age of Smart Machines

Article source: http://feeds.harvardbusiness.org/~r/harvardbusiness/~3/6Ae5Gwl9KJ8/the-knowledge-jobs-most-likely-to-be-automated

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