TY - CHAP
T1 - Business and Regulatory Responses to Artificial Intelligence
T2 - Dynamic Regulation, Innovation Ecosystems and the Strategic Management of Disruptive Technology
AU - Corrales Compagnucci, Marcelo
AU - Fenwick, Mark
AU - Vermeulen, Erik P.M.
PY - 2018/11/1
Y1 - 2018/11/1
N2 - Identifying and then implementing an effective response to disruptive new AI technologies is enormously challenging for any business looking to integrate AI into their operations, as well as regulators looking to leverage AI-related innovation as a mechanism for achieving regional economic growth. These business and regulatory challenges are particularly significant given the broad reach of AI, as well as the multiple uncertainties surrounding such technologies and their future development and effects. This chapter identifies two promising strategies for meeting the “AI challenge,” focusing on the example of Fintech. First, “dynamic regulation,” in the form of regulatory sandboxes and other regulatory approaches that aim to provide a space for responsible AI-related innovation. An empirical study provides preliminary evidence to suggest that jurisdictions that adopt a more “proactive” approach to Fintech regulation can attract greater investment. The second strategy relates to so- called “innovation ecosystems.” It is argued that such ecosystems are most effective when they afford opportunities for creative partnerships between well-established corporations and AI-focused startups and that this aspect of a successful innovation ecosystem is often overlooked in the existing discussion. The chapter suggests that these two strategies are interconnected, in that greater investment is an important element in both fostering and signaling a well-functioning innovation ecosystem and that a well-functioning ecosystem will, in turn, attract more funding. The resulting synergies between these strategies can, therefore, provide a jurisdiction with a competitive edge in becoming a regional hub for AI-related activity.
AB - Identifying and then implementing an effective response to disruptive new AI technologies is enormously challenging for any business looking to integrate AI into their operations, as well as regulators looking to leverage AI-related innovation as a mechanism for achieving regional economic growth. These business and regulatory challenges are particularly significant given the broad reach of AI, as well as the multiple uncertainties surrounding such technologies and their future development and effects. This chapter identifies two promising strategies for meeting the “AI challenge,” focusing on the example of Fintech. First, “dynamic regulation,” in the form of regulatory sandboxes and other regulatory approaches that aim to provide a space for responsible AI-related innovation. An empirical study provides preliminary evidence to suggest that jurisdictions that adopt a more “proactive” approach to Fintech regulation can attract greater investment. The second strategy relates to so- called “innovation ecosystems.” It is argued that such ecosystems are most effective when they afford opportunities for creative partnerships between well-established corporations and AI-focused startups and that this aspect of a successful innovation ecosystem is often overlooked in the existing discussion. The chapter suggests that these two strategies are interconnected, in that greater investment is an important element in both fostering and signaling a well-functioning innovation ecosystem and that a well-functioning ecosystem will, in turn, attract more funding. The resulting synergies between these strategies can, therefore, provide a jurisdiction with a competitive edge in becoming a regional hub for AI-related activity.
UR - https://www.springer.com/gp/book/9789811328732
M3 - Book chapter
SN - 978-981-13-2873-2
T3 - Perspectives in Law, Business and Innovation
SP - 81
EP - 104
BT - Robotics, AI and the Future of Law
A2 - Corrales Compagnucci, Marcelo
A2 - Fenwick, Mark
A2 - Forgó, Nikolaus
PB - Springer Nature Singapore
CY - Singapore
ER -
