Governing through Artificial Intelligence Driven Policy Processes
Kirori Mal College, University Of Delhi
Volume III, Issue IV, 2020
Failure and redundancy of public policy, its processes and impact has been spoken of since the inception of modern democracies. While the reasons of failure remain distinct; from a structured nexus of corruption to operational human errors, the resolutions are standard, incompetent and inefficient. Thus, the problem persists. However, this paper contemplates that an incremental model based blend of technology, digitalization and Artificial Intelligence (AI) if structured and incorporated within the policy processes and systems can be revolutionary in bringing forth the necessary adjustments and improvements. The paper introduces AI, its incorporation in the systems of governance and goes ahead to examine its relationship with Data Driven Policy (DDP) processes. It further emphasizes the importance AI and DDP will have in the upcoming decade and looks at AI as a linkage and apparatus to introducing multiple sets of opportunities and advantages within the policy framework. On an operational vertical the paper looks at how AI can be structurally embedded in policy processes right from agenda setting till monitoring and evaluation. The paper delves deeper into the domain of leveraging AI by recommending to follow best practices from previously implemented models of AI in governance. Holistically the paper aims at being a standpoint to enable further research in a discourse that looks at amalgamation of technology and governance as a resolution of frequent public policy failures.