Facilitating Data-Driven Innovation for Sustainability: Opportunities and Challenges in Public Policy
Project Description

Data-driven innovation, including the Internet of Things (IoT), blockchain, and artificial intelligence (AI), has significant potential to address various challenges identified in the Sustainable Development Goals (SDGs). In-depth research needs to investigate what kinds of policy frameworks and measures would be effective in collecting, sharing, and using data among stakeholders and what impacts would be made on facilitating data-driven innovation while addressing societal concerns, including data security and privacy. This project intends to conduct theoretical as well as empirical studies that examine various policy measures and approaches to facilitating data-driven innovation and addressing key issues involved, such as the ownership of and accessibility to data, interoperability and integration of data, incentives to the collection, disclosure, and sharing of data, the protection of data security and privacy, and trust and engagement in data governance.

Supervisor
YARIME Masaru
Quota
10
Course type
UROP1100
UROP2100
UROP3100
UROP4100
Applicant's Roles

We will investigate with students various issues in this topic, including the following questions:
• How are various kinds of data collected, shared, and used for innovation among stakeholders?
• What incentives are provided to stakeholders with different interests and motivations to facilitate data sharing?
• What kinds of governance systems are established to manage data availability, accessibility, and ownership?
• What policy measures and institutional arrangements are introduced to deal with sensitive data in terms of data security and privacy?
• What are the impacts and consequences of policy measures on facilitating innovation while addressing societal concerns?

Case studies in different countries and regions would be conducted to examine the mechanisms and processes involved in data collection, sharing, and use for innovation, as local specificities of the relevant actors and institutions would be significant. Policy implications and recommendations are explored for maximizing the potential of data-driven innovation while minimizing risks to individuals and communities in addressing SDGs.

Applicant's Learning Objectives

Students will learn basic concepts and methodologies on sustainability and innovation systems and obtain experiences of conducting statistical analysis and case studies. They will also explore implications for public policy and institutional design.

Complexity of the project
Challenging