Artificial Intelligence for economic competitiveness and Grand Challenges?
What is the purpose of developing and using Artificial Intelligence (AI)? Is it to boost economic growth and competitiveness? Or should it contribute to tackling grand societal challenges and achieving Sustainable Development Goals in areas such as health, environment and energy? Can AI contribute to the both?
I examine these questions in my new article ‘Emerging technology for economic competitiveness or societal challenges? Framing purpose in Artificial Intelligence policy’ (Ulnicane 2022). This article is part of my broader research programme on AI governance, politics and policy.
Demystifying hopes & hypes of emerging tech
AI is one of the key emerging technologies of our times. As all emerging technologies, it is surrounded by hopes and hype about major economic and societal benefits it is expected to bring. Critical interrogation of values and norms embedded in these discourses helps to demystify this rhetoric and problematise how it is defined, debated, and acted upon.
In debates about emerging tech, it is possible to distinguish two stylized frames – one more traditional focusing on economic growth and competitiveness and another more recent one highlighting potential of emerging tech to tackle grand challenges. According to the traditional frame, emerging tech is seen as contributing to economic growth and competitiveness. It depicts global technology development as a race where one country is winning and reaping major economic, political and military gains while others are left behind, which is misleading and highly problematic. Recently, this frame has been increasingly questioned – should economic growth be the main priority in times of climate crisis and escalating societal concerns? In this context, a new frame highlights the potential of emerging technologies to contribute to tackling Grand societal challenges (Ulnicane 2016) and achieving Sustainable Development Goals (SDGs). However, these are complex and uncertain ‘wicked problems’ without straightforward solutions.
A recent shift towards prioritizing tech contribution to tackling societal challenges has been described as ‘a normative turn’. This can be misleading because it would imply that the traditional economic frame is purely technocratic, value-free and non-normative. It is important to recognize that both policy frames are normative. Prioritizing economic growth and competitiveness also is a highly normative choice based on certain values, norms and priorities. Recognizing that each of the frames is based on certain values and norms is necessary to critically examine ongoing policy debates where both frames co-exist and compete for attention, legitimacy and resources.
Can we have it all?
The two stylized frames of economic competitiveness and societal challenges can be found in recent debates about AI. In this article (Ulnicane 2022), I apply these frames to analyse recent AI policy documents launched by national governments, international organizations, think tanks and others.
While AI is presented as novel, revolutionary and transformative, the policy documents contain many traditional ideas about the need for investments and qualified workforce to fully exploit economic opportunities offered by AI. AI is seen as crucial for boosting productivity, efficiency and cost savings and for maintaining, increasing and improving international competitiveness. If right measures are not in place, countries and regions fear lagging behind and missing out on opportunities offered by the AI revolution. As one document puts it, ‘European industry cannot miss the train’. Why? It can take another train. And where does it actually want to go? What is that crucial, life-saving moment it will miss if it does not catch this particular train?
At the same time, AI documents contain highly optimistic claims about the potential of AI to solve societal challenges and contribute to achieving SDGs. However, here AI is typically presented as a technical fix rather than one element in tackling complex and uncertain wicked problems. Documents tend to mention both frames next to each other, implying that they are complementary rather than competing alternatives. However, examination of the compatibility of both frames and what kind of measures and trade-offs that would require is missing. Rhetoric of AI contributing to economic and societal aims remains rather superficial, with little or no reflection on the values and norms each of them entail.
Dr. Inga Ulnicane is Senior Research Fellow at De Montfort University, UK. Her research focusses on governance, politics and policy of science, technology, and innovation.
Ulnicane, I. (2022) Emerging technology for economic competitiveness or societal challenges? Framing purpose in Artificial Intelligence policy. Global Public Policy and Governance. https://doi.org/10.1007/s43508-022-00049-8
Ulnicane, I. (2016). ‘Grand Challenges’ concept: A Return of the ‘Big Ideas’ in Science, technology and Innovation Policy? International Journal of Foresight and Innovation Policy, 11(1-3), 5-21. https://doi.org/10.1504/IJFIP.2016.078378