For Work / Against Work
Debates on the centrality of work

"Rulers of the world, unite! The challenges and opportunities of artificial intelligence"

by Kaplan, Andreas; Haenlein, Michael (2020)


A decade ago, we published an article in Business Horizons about the challenges and opportunities of social media with a call to action: “Users of the world, unite!” To celebrate its anniversary, we look at artificial intelligence and the need to create the rules necessary for peaceful coexistence between humanity and AI. Hence, we now are urging: “Rulers of the world, unite!” In this article, we outline six debates surrounding AI in areas like artificial superintelligence, geographical progress, and robotics; in doing so, we shed light on what is fact and what is utopia. Then, using the PESTEL framework, we talk about the six dilemmas of AI and its potential threat and use. Finally, we provide six directions on the future of AI regarding its requirements and expectations, looking at enforcement, employment, ethics, education, entente, and evolution. Understanding AI’s potential future will enable governments, corporations, and societies at large (i.e., the rulers of this world) to prepare for its challenges and opportunities. This way, we can avoid a scenario in which we return in 10 years to write the article: “Dreamers of the world, unite!”

Key Passage

Although massive job displacement due to AI is not necessarily likely, some industries will clearly see a very significant change. Restaurants of the future will more likely be staffed by service robots than by human waiters, and call center agents are likelyto be replaced by chatbots. Similar to how domestic appliances reduced the need for householdstaff and mechanical looms put weavers out of ajob, AI will touch some pink- and white-collar jobsin the same way as blue-collar workers wereaffected by automation on the shop floor decadesago. At first, governments may decide to keeppeople in the job by forcing companies to reducethe use for automation, train employees for newtasks, or distribute the total work hours differ-ently, or they may restrict the use of automationaltogether. In France, for example, a law alreadyrequires that electronic platforms are only usableduring  normal  office  hours  under  certainconditions.Yet it seems unrealistic to expect that all em-ployees will have the skills to train for a newoccupation or the ability to develop such skills. AImay increase unemployment rates to a certainextent, at least for some groups of society. Thisbrings us to the idea of a universal basic income.Whether such an idea should apply to every citizenor be targeted toward certain groups is a matter ofongoing debate. A recent study in Finland provides empirical evidence that a broad universal basic income may be less beneficial than initially antic-ipated. There is also the question of who shouldpay for such an idea. One obvious solution may beto collect additional taxes on automation, similarto how VAT works today; however, that coulddistort competition in a severe way. Connected to this are philosophical and ethical questions aboutthe value of work and the importance of meaningful work to personal happiness.What does all of this mean for managers? First, managers need to be aware that many employees will be scared of being replaced by AI, indepen-dent of whether this fear is justified or not. This requires strong skills in leading an open dialogue,resolving  conflict,  and broadly  speakingdahuman, ethical, open, and transparent leadership style. Second, managers need to identify the skillsof their human employees and find a place forthem in an ecosystem in which humans and ma-chines will work hand in hand. This will include astronger focus on emotional or feeling tasks forhumans, for which they have an inherent advantage over machines. Third, allof this needs to be done in a bottom-up versus top-down approach. Involving employees in the pro-cess of developing and implementing AI systems makes such systems more successful. In short, managers will need to act as empathetic mentors and data-driven  decision  makers. (p.46)


Artificial Intelligence, Artificial Superintelligence, Human-Machine Symbiosis, Machine Learning, Robotics, Work Displacement



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