C 465/84
EN
Official Journal of the European Union
6.12.2022
Tuesday 3 May 2022
g) Recurring findings in all six case studies
95.
Notes that there are clear societal benefits and opportunities associated with adopting AI technologies, which can only be reaped if transversal obstacles are addressed in the EU, in accordance with fundamental rights, values and legislation; states that overlap of legislation, market fragmentation, bureaucratic hurdles, a lack of accessible digital infrastructure and digital skills in the broader society, and insufficient investment in research and development can be observed in particular as barriers to the successful application of trusted AI in all fields analysed;
96.
Concludes from the case studies examined, furthermore, that there are certain use cases that are risky or harmful, but that it is not necessarily specific AI technologies themselves but their areas of application; recognises that future regulation needs to address legitimate concerns related to these risks in order for AI technologies to find broad application in the EU;
97.
States that while it is important to examine and categorise potential risks posed by AI, the case studies illustrated that AI technologies can provide us with effective countermeasures that are able to mitigate or eliminate these risks; underlines that as AI is still in its early stages of development within a wider context of emerging technologies, its full potential as well as its risks are not certain; points out that there is a need to look not only at risks to individuals, but also at the broader societal and non-material individual harms; highlights the significant imbalances of market power present in data markets and the adjacent AI economy; stresses that fair competition and removing obstacles to competition for start-ups and SMEs are essential to fairly distribute the potential benefits of AI in economic and societal terms, which appear to be significant both in the EU and globally;
3.
The EU’s place in global AI competition
98.
Observes fierce global AI competition, where the EU has not yet met its aspirations; examines in the following sections the EU’s global competitiveness with regard to AI by comparing it with that of China and the US, focusing on three core elements: regulatory approach, market position and investments; recognises, however, that transnational markets and corporations cannot easily be delineated across national borders, as most tech companies have customers, shareholders, employees and suppliers in many different countries;
a) Regulatory approach
99.
Notes that the US has not yet introduced horizontal legislation in the digital field, and has so far focused on sector-specific laws and facilitating investments, including through tax measures on private sector innovation, in particular among its tech giants and leading universities; observes that, despite recent developments showing a more active policymaking role, the US approach has so far mostly reflected a focus on providing legal guidance to businesses, investing in research projects and removing perceived barriers to innovation;
100.
Stresses that the 2019 American AI Initiative Act ushered in a slight realignment, as besides redirecting funding, retraining workers and strengthening digital infrastructure, the US Government announced the development of common standards for trustworthy AI; notes, however, that the resulting 10 principles were very broadly formulated in order to allow each government agency to create sector-specific regulations; expects that although the current US administration plans to bring forward a new bill of rights to limit AI harms in 2022, the US approach will remain market-driven;
101.
Highlights that the Chinese President Xi Jinping underlined in as early as 2013 the importance of technologies in geopolitics, the role of public policies in defining long-term objectives and the fact that AI technologies offer an opportunity to relaunch its military power; stresses further that the Chinese Government subsequently put forward the Made in China 2025 plan in 2015 and the Next Generation AI Development Plan in 2017, both of which had the clear targets of making China the global leader in AI by 2030; notes that the 2018 Chinese AI standardisation white paper further outlined how the socialist market economy can develop international standards and strategically engage in international standardisation organisations; notes the introduction of rules on recommender systems as well as an ethics code on AI in China;