Studie von Pricewaterhouse Coopers, 24.3.2017 (engl. Originalfassung)
Over the past few years, fears of technology-driven job losses have re-emerged with advances in ‘smart automation’ – the combination of AI (Artificial Intelligence), robotics and other digital technologies that is already producing innovations like driverless cars and trucks, intelligent virtual assistants like Siri, Alexa and Cortana, and Japanese healthcare robots. While traditional machines, including fixed location industrial robots, replaced our muscles (and those of other animals like horses and oxen), these new smart machines have the potential to replace our minds and to move around freely in the world driven by a combination of advanced sensors, GPS tracking systems and deep learning, if not now then probably within the next decade or two. Will this just have the same effects as past technological leaps – short term disruption more than offset by long term economic gains – or is this something more fundamental in terms of taking humans out of the loop not just in manufacturing and routine service sector jobs, but more broadly across the economy? What exactly will humans have to offer employers if smart machines can perform all or most of their essential tasks better in the future?
Our analysis suggests that up to 30 percent of UK jobs could potentially be at high risk of automation by the early 2030s, lower than the US (38 percent) or Germany (35 percent), but higher than Japan (21 percent). The risks appear highest in sectors such as transportation and storage (56 percent), manufacturing (46 percent) and wholesale and retail (44 percent), but lower in sectors like health and social work (17 percent). For individual workers, the key differentiating factor is education. For those with just GCSE-level education or lower, the estimated potential risk of automation is as high as 46 percent in the UK, but this falls to only around 12 percent for those with undergraduate degrees or higher. However, in practice, not all of these jobs may actually be automated for a variety of economic, legal and regulatory reasons.
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