Building a Better HAL 9000: Algorithms, the Market, and the Need to Prevent the Engraining of Bias

42 Pages Posted: 29 Mar 2017

See all articles by Anjanette Raymond

Anjanette Raymond

Indiana University - Kelley School of Business - Department of Business Law; Queen Mary University of London, School of Law; Indiana University Maurer School of Law

Emma Young

Indiana University Bloomington

Scott Shackelford

Indiana University - Kelley School of Business - Department of Business Law; Harvard Kennedy School Belfer Center for Science & International Affairs; Center for Applied Cybersecurity Research; Stanford Center for Internet and Society; Stanford Law School

Date Written: February 6, 2017

Abstract

As sci-fi fans will recall, the movie 2001: A Space Odyssey is focused on the interaction between humans and artificial intelligence. In the movie, HAL (Heuristically programmed Algorithmic Computer) 9000 computer is an artificial intelligence and the onboard computer on the spaceship Discovery 1. HAL 9000, more commonly called “Hal,” is capable of many functions, such as speech, facial recognition, lip reading, interpreting emotions, and expressing emotions. HAL is built into the Discovery 1 spacecraft, and is in charge of maintaining all mechanical and life support systems on board. As the movie progresses, the astronauts become concerned about HAL’s behavior and agree to disconnect him, in essence killing HAL. HAL becomes aware of the plan and seeks to stop his death as the movie plot climaxes in a conflict between intelligent machine and his human controllers. Interestingly, 2001: A Space Odyssey author Arthur C. Clark could not have been more accurate about one of the emerging conflicts to face humanity: what role does society want machines to play in coordinating and governing human activity? The debate resonates from the shared economy to the ethics of artificial intelligence. This article seeks to advance the debate about the need for data regulation that focuses on the impact of the use of the data. First, it provides a brief explanation of data analytics, algorithms, and machine learning. Second, the article explores some of the common mistakes associated with data modeling within algorithmic processes. Third, the paper explores the impact of the use of data, specifically data that is used to create a digital personhood, to inform algorithms that perform basic services. Fourth and finally, the article seeks to define an ethical decision-making model and regulatory structure for data focusing on the impact of the use of the data upon the individual and society.

Keywords: Big Data, Cybersecurity, Polycentric Governance

Suggested Citation

Raymond, Anjanette and Young, Emma and Shackelford, Scott J., Building a Better HAL 9000: Algorithms, the Market, and the Need to Prevent the Engraining of Bias (February 6, 2017). Northwestern Journal of Technology and Intellectual Property, 2017; Kelley School of Business Research Paper No. 17-23. Available at SSRN: https://ssrn.com/abstract=2921442

Anjanette Raymond (Contact Author)

Indiana University - Kelley School of Business - Department of Business Law ( email )

Bloomington, IN 47405
United States

Queen Mary University of London, School of Law ( email )

67-69 Lincoln’s Inn Fields
London, WC2A 3JB
United Kingdom

Indiana University Maurer School of Law ( email )

211 S. Indiana Avenue
Bloomington, IN 47405
United States

Emma Young

Indiana University Bloomington ( email )

100 South Indiana Ave.
Bloomington, IN 47405
United States

Scott J. Shackelford

Indiana University - Kelley School of Business - Department of Business Law ( email )

Bloomington, IN 47405
United States

Harvard Kennedy School Belfer Center for Science & International Affairs ( email )

79 JFK Street
Cambridge, MA 02138
United States

Center for Applied Cybersecurity Research ( email )

Wylie Hall 105
100 South Woodlawn
Bloomington, IN 47405
United States

Stanford Center for Internet and Society ( email )

Palo Alto, CA
United States

Stanford Law School ( email )

Stanford, CA 94305
United States

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