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3 U. Bologna L. Rev. 180 (2018)
Artificial Intelligence Policy: A Primer and Roadmap

handle is hein.journals/bologna3 and id is 189 raw text is: 

               Artificial Intelligence Policy: a Primer and Roadmap

                                    RYAN CALOT

TABLE OF CONTENTS: 1. Introduction: 2. Background; 2.1. What Is AI?; 2.2. Where Is AI
Developed and Deployed?; 2.3. Why AI Policy?; 3. Key Questions for AI Policy; 3.1. Justice
and Equity; 3.1.1. Inequality in Application; 3.1.2. Consequential Decision-Making; 3.2. Use
of Force; 3.3. Safety and Certification; 3.3.1. Setting and Validating Safety Thresholds; 3.3.2.
Certification; 3.3.3. Cybersecurity; 3.4. Privacy and Power; 3.4.1. The Problem of Pattern
Recognition; 3.4.2. The Data Parity Problem; 3.5. Taxation and Displacement of Labor; 3.6.
Cross-Cutting Questions (Selected); 3.6.1. Institutional Configuration and Expertise; 3.6.2.
Investment and Procurement; 3.6.3. Removing Hurdles to Accountability; 3.6.4. Mental
Models of Al; 4. On the Al Apocalypse; 4.1. Conclusion.

ABSTRACT: Talk of artificial intelligence is everywhere. People marvel at the capacity of
machines to translate any language and master any game. Others condemn the use of
secret algorithms to sentence criminal defendants or recoil at the prospect of machines
gunning for blue, pink, and white-collar jobs. Some worry aloud that artificial intelligence
will be humankind's final invention.
This essay, prepared in connection with UC Davis Law Review's 5oth anniversary
symposium, explains why Al is suddenly on everyone's mind and provides a roadmap to
the major policy questions AI raises. The essay is designed to help policymakers, investors,
technologists, scholars, and students understand the contemporary policy environment
around AI at least well enough to initiate their own exploration.
Topics covered include: justice and equity, use of force, safety and certification, privacy
(including data parity) and taxation and displacement of labor. In addition to these topics,
the essay will touch briefly on a selection of broader systemic questions: institutional
configuration and expertise, investment and procurement, removing hurdles to
accountability and correcting mental models of AL.

KEYWORDS: Artificial Intelligence; Law; Policy; Ethics; Governance

                                  EDITORIAL NOTE
     This essay is reprinted with author permission from Volume 51 of the UC Davis Law

                               UNIVERSITY OF BOLOGNA LAW REVIEW

                                     ISSN 2531-6133

                                     [VOL.3:2 2018]
         This article is released under the terms of Creative Commons Attributionl 4.0 International License


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