LIST OF PANELS

The rapid development of emerging data-driven technologies, such as artificial intelligence (AI), has had a profound impact on social behaviors, necessitating urgent government regulation, which, in turn, brought significant changes to the field of policy analysis, both in terms of theory and methodology.

Practically, the velocity of AI developments, the complexity of what to regulate, and the question of who regulates and how, all pose significant challenges for AI oversight. Theoretically, to design policies and ensure that AI is applied in an ethical, secure, transparent, and human-centric manner across all sectors are often unclear. Both policy design, implementation and policy analysis can be facilitated by AI, but this requires careful consideration of the aforementioned challenges.

Given that AI-related policies have been designed and adopted across various policy fields in numerous countries and regions, it would be beneficial to explore these policy challenges from comparative perspectives.

The panel is sponsored by the ICPA Society and the Journal of Comparative Policy Analysis (JCPA), Routledge.

This special issue aims to bring together research that explores two main themes:

Theme 1: Comparative Study of AI-related Policies

This theme invites research that examines the policies proposed by different countries regarding the development and administration of AI. Comparative studies in this area can facilitate international/regional exchange of experiences and contribute to the development of a theoretical framework for understanding AI-related policy design, dissemination, implementation, and evaluation.

Research questions under this theme could include:

1) Holistic review of literature on AI-related policies across countries/regions with theoretical framework generated to facilitate our understanding on what factors contribute to policy differences.

2) Use comparative process tracing to analyze how the design of policies to address the rise of AI is similar to and different from policies previously designed for other emerging technologies (e.g., Internet technologies or Information and Communication Policies).

3) To what extend the development of AI may have generated new challenges and concerns, such as equity, ethics, and privacy, into policy design of traditional policy areas such as environmental policy and social policy.

4) In terms of instrumentalisation, AI policy responsibilities tend to be distributed across multiple policy areas and level of governance, the composition of the AI policy portfolio, therefore, reflect both the growing complexity and interweaving of innovative policy arrangements. This may exacerbate further discussions on policy collaboration, co-ordination and coherence in AI related policy design.

5) Implementing and disseminating AI policies can be a complex process due to features such as cultural, social, economic, and political contexts of different regions or countries. What are the emerging challenges in implementation and dissemination of AI policy? How to ensure effective implementation of AI policies and deal with unexpected and unintended consequences?

Theme 2: AI as Analytical Tools in Comparative Policy Analysis

With the development of Large Language Model (LLM), Deep Learning Model, as well as ChatGPT, AI related technologies can facilitate social scientists in many ways. They can process large volumes of data and offer new analytical perspectives into societal trends and human behavior; they can be adopted to test ideas for interventions to improve policy-making; and they are used to study individuals and groups to develop theories of human behavior. This theme encourages discussions on the extent to which emerging AI technologies, such as deep learning and ChatGPT, can be adopted as nuanced analytical tools in comparative policy analysis.

Research questions under this theme could include:

1) How can AI technologies be used to enhance the quality and efficiency of comparative policy analysis?

2) What are the potential benefits and challenges of using AI technologies in comparative policy analysis?

3) How can AI technologies be integrated into existing analytical frameworks in comparative policy analysis?

4) What are the ethical considerations when using AI technologies in comparative policy analysis?

5) How can the reliability and validity of AI-assisted analysis be ensured?