Table Of ContentCORPORATION
An Intelligence in
Our Image
The Risks of Bias and Errors in
Artificial Intelligence
Osonde Osoba, William Welser IV
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Preface
Algorithms and artificial intelligence agents (or, jointly, artificial agents)
influence many aspects of life: the news articles read, access to credit,
and capital investment, among others. Because of their efficiency and
speed, algorithms make decisions and take actions on the behalf of
humans in these and many other domains. Despite these gains, there
are concerns about the rapid automation of jobs (even cognitive jobs,
such as journalism and radiology). This trend shows no signs of abating.
As reliance on artificial agents continues to grow, what are the
consequences and risk of such dependence? A better understanding
of attitudes toward and interactions with algorithms is essential pre-
cisely because of the aura of objectivity and infallibility today’s culture
ascribes to algorithms. This report illustrates some of the shortcomings
of algorithmic decisionmaking, identifies key themes around the prob-
lem of algorithmic errors and bias (e.g., data diet, algorithmic disparate
impact), and examines some approaches for combating these problems.
This report should be of interest to decisionmakers and imple-
menters looking for a better understanding of how artificial intelligence
deployment can affect their stakeholders. This affects such domains as
criminal justice, public works, and welfare administration.
RAND Ventures
The RAND Corporation is a research organization that develops solu-
tions to public policy challenges to help make communities throughout
iii
iv An Intelligence in Our Image
the world safer and more secure, healthier and more prosperous. RAND
is nonprofit, nonpartisan, and committed to the public interest.
RAND Ventures is a vehicle for investing in policy solutions. Phil-
anthropic contributions support our ability to take the long view, tackle
tough and often-controversial topics, and share our findings in innova-
tive and compelling ways. RAND’s research findings and recommen-
dations are based on data and evidence and, therefore, do not neces-
sarily reflect the policy preferences or interests of its clients, donors, or
supporters.
Funding for this venture was provided by the generous contribu-
tions of the RAND Center for Global Risk and Security (CGRS) Advi-
sory Board. The research was conducted within CGRS, part of Interna-
tional Programs at the RAND Corporation.
Support for this project is also provided, in part, by the fees earned
on client-funded research.
RAND Center for Global Risk and Security
CGRS draws on RAND’s extensive multidisciplinary expertise to assess
the impact of political, social, economic, and technological trends on
global risk and security.
For more information about the RAND Center for Global Risk
and Security, visit www.rand.org/international/cgrs or contact the
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Contents
Preface ............................................................................. iii
Figure ..............................................................................vii
Acknowledgments ............................................................... ix
CHAPTER ONE
Introduction ....................................................................... 1
CHAPTER TWO
Algorithms: Definition and Evaluation ...................................... 3
Defining Algorithms ............................................................... 4
“Misbehaving” Algorithms: A Brief Review .................................... 7
A Case Study: Artificial Agents in the Criminal Justice System ............13
CHAPTER THREE
The Problem in Focus: Factors and Remedies ..............................17
Other Technical Factors ..........................................................19
Remedies ...........................................................................21
CHAPTER FOUR
Conclusion ........................................................................25
Abbreviations .................................................................... 27
References .........................................................................29
v
Figure
1. Rate of Enforcement Events per Epoch: Two
Subpopulations, Same Crime Rate, Differing Vigilance ........14
vii
Acknowledgments
We would like to thank Andrew Parasiliti for sponsoring this work
through the RAND Center for Global Risk and Security. We also want
to thank fellow researchers who provided pointed advice as this work
evolved, particularly Bart Kosko, Angela O’Mahony, Sarah Nowak,
and John Davis. Finally, we would like to thank our reviewers, John
Seely Brown and Timothy R. Gulden, for their insightful feedback.
ix
