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The current wave of technological change based on advancements in artificial intelligence (AI) has created widespread fear of job losses and further rises in inequality. A paper published by International Labour Organization (ILO) discusses the rationale for these fears, highlighting the specific nature of AI and comparing previous waves of automation and robotization with the current advancements made possible by a wide-spread adoption of AI.
The paper argues that large opportunities in terms of increases in productivity can ensue, including for developing countries, given the vastly reduced costs of capital that some applications have demonstrated and the potential for productivity increases, especially among the low-skilled. At the same time, risks in the form of further increases in inequality need to be addressed if the benefits from AI-based technological progress are to be broadly shared. For this, skills policy are necessary but not sufficient. In addition, new forms of regulating the digital economy are called for that prevent further rises in market concentration, ensure proper data protection and privacy and help share the benefits of productivity growth through a combination of profit sharing, (digital) capital taxation and a reduction in working time. The paper calls for a moderately optimistic outlook on the opportunities and risks from artificial intelligence provided policy-makers and social partners take the particular characteristics of these new technologies into account.
This article is a smaller part of a chapter about jobs and tasks. The heading of that part of the document is Changing jobs and tasks.
Changing Jobs and Tasks.
Jobs are constituted by a set of tasks. If some of these tasks are automatized, job profiles might change by adding new tasks or modifying existing ones instead of suppressing a job entirely. The task description of an administrative assistant over time can demonstrate how similar jobs continue to perform certain tasks that have not (yet) been automatized alongside other, new tasks that either did not exist before or were performed by a different group of workers. Hence, whether or not jobs disappear depends on whether it remains profitable to group certain tasks into specific job profiles and hire workers specifically for these (new) jobs, which is a question more of demand for particular products and services that these jobs are supposed to deliver than of supply of skills to fill the jobs.
Different Tasks Will be Handled Differently in Different Countries
Importantly, cross-country differences exist regarding how jobs are being designed and tasks regrouped into jobs. Tasks have different characteristics regarding their training, supervisory and production requirements, which are not necessarily aligned. Depending on the importance a company puts on training its workers, supervising them or aligning their workflows, different tasks may be regrouped to jobs from one company to another. Partly, this will depend on the country characteristics regarding education and training infrastructure, tax incentives and social
benefits systems. Hence, even companies operating in the same industry but in different countries might react to institutional differences with a very different set-up of their internal work processes and job profiles, as exemplified by the differences between Apple and Samsung in the way they externalize their production chains. Consequently, whether the automation of tasks will lead to jobs disappearing is as much a technological question as it is an institutional one and cannot be determined a priori by looking at the automation process alone. Recent evidence seems to confirm the importance of institutional factors in determining the outcome of occupational changes, as seemingly similar patterns of job polarization across countries can be driven by different factors.
We Still Need Pilots in the Aeroplanes
Even when tasks can be automated they might not disappear altogether. Rather than executing a particular task, for instance, an employee might be charged to ensure that the machine is conducting the task properly and to intervene in case of an emergency or error. In the case of air pilots, for instance, the introduction of automatic pilots has not made obsolete their role. Even though on average a pilot only flies a plane for roughly seven minutes during an entire flight, having a human sitting at the control panel is as essential as before in order to intervene in extreme situations or sudden disruptions or in technical malfunctions not foreseen by the autopilot (such as a simultaneous breakdown of both engines).
Automation Creates Needs For New Skills.
Similarly, it might still require a worker to ensure that machines are properly parameterized and set up, especially when orders change or a new production line needs to be set up. Also, the relative time spent on each individual task might change: Thanks to supporting by AI on diagnosing diseases, doctors, for instance, might spend less time on analysing symptoms and more time on ensuring a patient’s well-being and individual needs. Either way, automation of a task might not necessarily lead to that task no longer requiring human assistance. Rather, the question becomes whether it remains profitable to bundle a set of tasks to a specific job, as well as how quickly a worker can shift within the current job to perform slightly modified tasks or task sets. If that entails requiring new skills that are costly to learn, automation can be expected to lead to inequality within occupations rather than across.
The picture on the top: Fox
Lucubrate Magazine 55, March 22, 2019
The article is a part of Chapter 3 (p9+): The economics of artificial intelligence: Implications for the future of work, International Labour Organization (2018)
Categories: Magazine, Artificial Intelligence, Future Work, Technology.
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