AI Governance is critical for ensuring that AI systems are developed and deployed in a way that is ethical, transparent, accountable, and in alignment with human values and societal norms. It encompasses a wide range of considerations including privacy, security, fairness, accountability, and transparency. Effective governance aims to mitigate the risks associated with AI, such as biases in decision-making processes, potential job displacement, privacy invasion, and the development of autonomous weapons, while promoting the beneficial aspects of AI for society.
Historically, the concept of AI governance began to gain prominence in the late 2010s as the capabilities and applications of AI systems rapidly expanded, leading to increased public and academic discourse on the ethical implications of AI. The term "AI Governance" itself has been in use since around 2016, gaining traction as policymakers, researchers, and industry leaders recognized the need for comprehensive frameworks to guide the ethical development and use of AI.
Key contributors in the field of AI governance include interdisciplinary groups of ethicists, computer scientists, legal scholars, and policymakers. Organizations such as the European Commission, the IEEE (Institute of Electrical and Electronics Engineers), and the Partnership on AI have played significant roles in shaping the discourse and developing guidelines and principles for AI governance.