AN ANALYSIS OF THE RELATIONSHIP BETWEEN PUBLIC POLICY AND POLITICAL ECONOMY IN THE ERA OF AI
Article Sidebar
Main Article Content
Abstract
The relationship between public policy and political economy is critical because it influences how governments regulate economic activity, ensure equitable resource distribution, and address societal issues. This dynamic is critical for managing technological advances, such as artificial intelligence, in order to promote long-term growth and social welfare. The paper aims to analyze the relationship between public policy and political economy in the era of AI
The finding found that the relationship between public policy and political economy in the AI era is complex and multifaceted, shaped by the need to regulate AI technologies, address labor market disruptions, and combat economic inequality. Public policy is critical in fostering global competitiveness, managing data governance and ownership, and ensuring national security in the context of AI advancements. Furthermore, ethical governance and public trust in AI systems are essential for ensuring responsible AI development and implementation. Finally, effective policy frameworks are required to navigate the challenges and opportunities presented by AI while balancing innovation, societal well-being, and economic stability.
Article Details
References
Acemoglu, D., & Restrepo, P. (2020). Artificial Intelligence, Automation, and Work. Harvard University Press.
Acemoglu, D., & Robinson, J. A. (2012). Why nations fail: The origins of power, prosperity, and poverty. Crown Business.
Binns, R. (2018). Fairness in machine learning: Lessons from political philosophy. In Proceedings of the 2018 Conference on Fairness, Accountability, and Transparency (149-159). PMLR.
Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton & Company.
Cath, C. (2018). Governing artificial intelligence: Ethical, legal, and technical opportunities and challenges. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 376(2133), 20180080.
Cath, C. (2018). Governing artificial intelligence: Ethical, legal, and technical opportunities and challenges. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 376(2133), 20180080.
Chui, M., Manyika, J., & Miremadi, M. (2016). Where machines could replace humans—and where they can’t (yet). McKinsey Quarterly.
González-Fernández, M., Avello, C., & Montalvo, D. (2021). A framework for the ethical governance of AI. IEEE Access, 9, 149685-149695.
Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389-399.
Kuner, C. (2017). The European Union General Data Protection Regulation: A commentary. Oxford University Press.
Lin, P. (2016). Ethical Autonomous Weapons: The Need for a New Paradigm. In Artificial Intelligence and National Security (67-72). Center for a New American Security.
Mayer-Schönberger, V., & Cukier, K. (2013). Big Data: A Revolution That Will Transform How We Live, Work, and Think. Houghton Mifflin Harcourt.
Miller, T. (2019). Explanation in artificial intelligence: Insights from the social sciences. Artificial Intelligence, 267, 1-38.
North, D. C. (1990). Institutions, institutional change, and economic performance. Cambridge University Press.
O’Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown Publishing.
Piketty, T. (2014). Capital in the twenty-first century. Harvard University Press.
Rodrik, D. (2018). Straight Talk on Trade: Ideas for a Sane World Economy. Princeton University Press.
Smith, A. (1776). An inquiry into the nature and causes of the wealth of nations. W. Strahan and T. Cadell.
Stiglitz, J. E. (2002). Globalization and its discontents. W. W. Norton & Company.
Zuboff, S. (2019). The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. PublicAffairs.
