Ernst Ekkehard
International Labour Organization, Department of Research, Geneva, Switzerland.
Front Artif Intell. 2022 Oct 19;5:886561. doi: 10.3389/frai.2022.886561. eCollection 2022.
Digitalization and artificial intelligence increasingly affect the world of work. Rising risk of massive job losses have sparked technological fears. Limited income and productivity gains concentrated among a few tech companies are fueling inequalities. In addition, the increasing ecological footprint of digital technologies has become the focus of much discussion. This creates a trilemma of rising inequality, low productivity growth and high ecological costs brought by technological progress. How can this trilemma be resolved? Which digital applications should be promoted specifically? And what should policymakers do to address this trilemma? This contribution shows that policymakers should create suitable conditions to fully exploit the potential in the area of network applications (transport, information exchange, supply, provisioning) in order to reap maximum societal benefits that can be widely shared. This requires shifting incentives away from current uses toward those that can, at least partially, address the trilemma. The contribution analyses the scope and limits of current policy instruments in this regard and discusses alternative approaches that are more aligned with the properties of the emerging technological paradigm underlying the digital economy. In particular, it discusses the possibility of institutional innovations required to address the socio-economic challenges resulting from the technological innovations brought about by artificial intelligence.
数字化和人工智能对工作领域的影响日益增大。大规模失业风险上升引发了对技术的恐惧。少数科技公司集中获得有限的收入和生产率增长,加剧了不平等现象。此外,数字技术不断增加的生态足迹已成为诸多讨论的焦点。这造成了一个三难困境,即技术进步带来不平等加剧、生产率增长缓慢和生态成本高昂。如何解决这一三难困境?具体应推广哪些数字应用?政策制定者应如何应对这一三难困境?本文表明,政策制定者应创造合适条件,以充分挖掘网络应用领域(交通、信息交流、供应、供给)的潜力,从而获取可广泛共享的最大社会利益。这需要将激励措施从当前的用途转向那些至少能部分解决三难困境的用途。本文分析了当前政策工具在这方面的范围和局限性,并讨论了更符合数字经济所基于的新兴技术范式特征的替代方法。特别是,本文讨论了进行制度创新以应对人工智能带来的技术创新所引发的社会经济挑战的可能性。