TY - GEN
T1 - Preliminary Results of a Global Database on Soft Law Mechanisms for the Governance of Artificial Intelligence
AU - Gutierrez, Carlos Ignacio
AU - Marchant, Gary
AU - Carden, Alec
AU - Hoffner, Kaylee
AU - Kearl, Alexander
N1 - Funding Information:
This work was made possible by the support of the Charles Koch Foundation. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/9/21
Y1 - 2020/9/21
N2 - Soft law mechanisms create substantive expectations that are not directly enforceable by government. All kinds of organizations apply soft law to regulate the development or use of methods and applications of artificial intelligence (AI), yet limited scholarship is devoted to studying the prevalence of these tools. This article describes the methodology and preliminary results of a project that compiled a global database of AI soft law mechanisms. It provides information on the type of organizations that create them, differences in how they are enforced, their origin and jurisdiction, influence, and the themes of their text. As both developers and users of these mechanisms, stakeholders (private sector, governments, and civil society) need information about their option space on how to govern AI. The objective of this work is to make available an analysis and library of information that facilitates the development of effective soft law mechanisms. In addition, it offers readers unique insights into the role of these mechanisms in managing AI's outcomes.
AB - Soft law mechanisms create substantive expectations that are not directly enforceable by government. All kinds of organizations apply soft law to regulate the development or use of methods and applications of artificial intelligence (AI), yet limited scholarship is devoted to studying the prevalence of these tools. This article describes the methodology and preliminary results of a project that compiled a global database of AI soft law mechanisms. It provides information on the type of organizations that create them, differences in how they are enforced, their origin and jurisdiction, influence, and the themes of their text. As both developers and users of these mechanisms, stakeholders (private sector, governments, and civil society) need information about their option space on how to govern AI. The objective of this work is to make available an analysis and library of information that facilitates the development of effective soft law mechanisms. In addition, it offers readers unique insights into the role of these mechanisms in managing AI's outcomes.
KW - Soft law
KW - alternative forms of regulating emerging technologies
KW - governance of AI
UR - http://www.scopus.com/inward/record.url?scp=85100339936&partnerID=8YFLogxK
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U2 - 10.1109/AI4G50087.2020.9311078
DO - 10.1109/AI4G50087.2020.9311078
M3 - Conference contribution
AN - SCOPUS:85100339936
T3 - 2020 IEEE / ITU International Conference on Artificial Intelligence for Good, AI4G 2020
SP - 33
EP - 37
BT - 2020 IEEE / ITU International Conference on Artificial Intelligence for Good, AI4G 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE / ITU International Conference on Artificial Intelligence for Good, AI4G 2020
Y2 - 21 September 2020 through 25 September 2020
ER -