A/B tests, 65–66. See also Randomized controlled trials
Acceptability, 102
Animal spirits (Keynes), 34, 45
Ashraf, Nava, 74–75
Attendance at recruitment events, 88–89
increasing (see SMS invitations to employee recruitment events)
Automatic System, 39, 40, 46, 47, 184
behavioral insights and, 40, 182–183
disrupting the, 182–183
growing recognition of the power of, 39
rational choice theory and, 46
Reflective System and, 159, 163, 183, 184
Availability heuristic, 30
Bedford Jobcentre, 81, 92, 99, 101, 105–108, 116, 118, 132
Behavioral economics, 45–46, 55
animal spirits approach and, 34, 45
evolution of, 26–35
internalities and, 148
meanings and connotations of the term, 32
origins of, 32
rational choice theory and, 27–28, 32, 45
regulation and, 50
Behavioral insights, 1–5
barriers to more strategic use of, 125–126
impact, 20–23
increasing interest in, 193
the “key” insight of, 2
as a lens, 12–14
meaning of the term, x
as a movement, 60–65
origin of the term, 21
sparking wider engagement, 184–185
steps in applying, 82
Step 1: establish the scope, 83–85
Step 2: break the challenge into addressable parts, 86, 87f, 88
Step 3: identify the target outcome, 88–91
Step 4: map the relevant behaviors, 91–94, 93f, 95f
Step 5: identify the factors that affect each behavior, 94–98, 97f
Step 6: choose priority behaviors to address, 98–99, 100f, 101
Step 7: create evidence-led interventions to produce the priority behaviors, 101–108
Step 8: implement, 108–110
Step 9: assess the effects, 110–119
Behavioral insights (cont.)
Step 10: take actions based on the results, 119–122
ways they can produce enduring change, 129–130
Behavioral insights approach
ethics and acceptability of, 145–165
as practical and empirical, 16–20
robustness of the theory and evidence, 133–143
what to do in face of this crisis of evidence, 143–145
theory of, as incomplete and simplistic, 134–136
what it delivers in practice, 124
limited impact on high-level policy, 124–126
longevity and habituation, 128–131
measurement problems, 126–128
surviving scale-up, 131–133
what it offers, 6
incentives, 7–9
information, 6–7
legislation, 10–12
Behavioral insights “ecosystem,” emergence of a, 65–69
Behavioral Insights Group (Harvard University), 68
Behavioral prompts, internalization of external, 130
Behavioural Insights Team (BIT)/”Nudge Unit,” 55–61, 178
birth/creation of, 54–57
coining the term “behavioral insights,” 21
EAST framework, 105
goals, 57–59
size, 56–57
unemployment centers and, 109–110, 121
Bias, 39, 149. See also specific biases
among behavioral scientists, 174–175
Bias blind spot, 154
Big Five personality traits, 142–143
“Boost” approach, 40, 134, 154
Bounded rationality, 27–28
Capability, individual, 95
Capability, opportunity, and motivation. See COM-B model
Carbon emissions, reducing, 72–73, 125
Causal inference, 111
Choice architecture, 47
behavioral insights and, 129–130, 149, 180
compromise effect and, 12–13
impact on decisions, 46–47
role of, and level of responsibility, 153
Cialdini, Robert, 37
Citizen forums, 164
Citizen juries. See Deliberative forums/citizen juries
Clinical trial registration. See Preregistration
Cluster randomization (RCTs), 117–118
Colonoscopies made more bearable by exploiting the peak-end effect, 78–79
Complex adaptive systems (CAS), 189
behavioral insights and, 187
cause and effects in, 188–189
overview and nature of, 185–186
Compromise effect, 12–13
Condoms, female
sales of, 74–75
Confirmation bias, 25, 149, 172
Contraception, 74–75
Control, illusion of, 189, 191
Control groups and treatment groups (RCTs), 113–114
Cost–benefit analysis, 42, 59, 90
Crime. See Deterrence
Dark patterns, 146
Defaults, 53f, 72–73, 120, 125, 126, 163, 172
Deliberative forums/citizen juries, 164–165, 184
Design thinking, 180
Desire lines, 181
Deterrence, 41–42. See also Rational choice theory
Dolan, Paul, 51–54
Dual-process theories, 66, 134–136, 171, 177
essence of the dual-process perspective, 37
the path toward, 35–40
EAST framework (BIT), 105
Ecological rationality, 39–40
Economics, 27. See also Behavioral economics; Homo economicus
Employment law, 86
Ethical critiques of behavioral insights, 148. See also Ethics; Manipulation; Paternalism
Ethical dilemmas, 162
Ethics, 102
of behavioral insights approach, 145–165
nudges/nudging and, 124, 163, 164
of using behavioral insights, 146–156, 158
Expected utility theory, 30
Express volitional deliberation, 37. See also Reflective System
External validity, 140. See also Generalizability
Fair Tax Mark, 185
File-drawer effect, 136–137, 143–144
Financial incentives. See Incentives
Food choices, 47. See also Sugared drink tax
Framing, 25
Friction, 146
Gallagher, Rory, 191
Generalizability, 123, 140–143
Gigerenzer, Gerd, 39–40
Good enough decision, 28
Good enough improvement, 90
Governments. See also specific topics
a shift in how they think about behavior, 40–46
Green consumer behavior, 72–73
Greener household energy tariffs, 72–73
Halpern, David, 51–55
Hansen, Pelle Guldborg, 214n46
Hassle factor, 72, 109, 110. See also “Sludge”
Health care and health decisions, 8–9, 10f, 47, 74–75, 78–79, 181–182
Heuristics, 28–30, 39–40, 134, 182, 183. See also Rules of thumb
Heuristic thinking, 134
Hindsight bias, 175
Hobbes, Thomas, 41
Homo economicus (economic man), 27, 29–32
Human-centered design, 178–183, 185
Hypothesis testing, 137, 143–144
standard assumptions of, 137
Incentives, 53f
when nonfinancial rewards are better than money, 74–75
Influence (Cialdini), 37
Information. See also specific topics
the effect of who says what, and how they say it, 76–77
Institute for Government (UK), 51–52
Internalities, 148
Internalization of external behavioral prompts, 130
Internal validity, 140
International Rescue Committee, 178
Involuntary action, 39. See also Automatic System
Ioannidis, John, 136–138
James, William, 35–37
Jespersen, Andreas Maaløe, 214n46
Kahneman, Daniel, 28–31, 36–37, 40
King, Dominic, 51–54
“Knowledge brokers,” behavioral insights teams and experts acting as, 192
Legislation, 10–12
Leviathan (Hobbes), 41
Libertarian paternalism, 48, 54, 151
Loss aversion, 30–31
Malpractice, 138
concern that use of behavioral insights is manipulative, 153–156
use of behavioral insights in ways that are manipulative, 146
Market failures, 42–43
Marshmallow test, 141–143
Medical care. See Health care and health decisions
Mere exposure effect, 25
Methodology. See Research practices
Milkman, Katy, 130–131
Mill, John Stuart, 26–27
Motivated reasoning, 155
Motivation, 97
Network analysis, 187
Nosek, Brian, 138–139
Nudge: Improving Decisions about Health, Wealth, and Happiness (Thaler and Sunstein), 46–50, 66, 151, 170
Nudge(s)/nudging, 153, 163, 170, 174, 179
advantages of and arguments in favor of, 48–49
behavioral science, behavioral insights, and, 50, 55, 125, 170, 181, 184
vs. “boost,” 134
categories of, 172, 179, 214n46
to change food consumption, 172
complementing vs. replacing other approaches, 124–125
criticisms of, 49, 50, 124–125
definition, scope, and uses of the term, 170
development of the concept of, 48
guidelines for, 47
limitations of, 49
research on, 172
vs. “sludge,” 146
Thaler and Sunstein’s vision of, 183
Nudge plus networks, 188
“Nudge Unit.” See Behavioural Insights Team (BIT)/”Nudge Unit”
“Nudge unit” in India, 63
Nudging companies, 185
Null hypothesis, failing to (dis)prove the, 137, 143–144
O’Donnell, Gus, 51–54
Omission bias, 160f
Opportunity, 95
Packard, Vance, 65
Pain perception, peak-end effect and, 78–79
Paluck, Betsy Levy, 78
Partisan nudge bias, 163
Paternalism, 156
behavioral science, behavioral insights, and, 148, 149, 151, 153, 159–161
criticism of, 149
public opinion and, 164
Peak-end effect, exploiting the, 78–79
Peak-end rule, 79
Persuasion, everyday, 37. See also specific topics
Power calculation, 113
Pragmatism, 193
Predictive analytics, 173–176
Preregistration (registered reports), 144
Publication bias, 140. See also File-drawer effect; Replication crisis
Publicity principle, 155
Public opinion on behavioral insights, 162–165
Public policy, behavioral, 195
Qualitative research approaches, 178
pairing quantitative approaches with, 178
Random assignment, 114–118
defined, 114
Randomized controlled trials (RCTs), 19, 20, 62, 65, 118, 187–188, 192
behavioral insights approach and, 18, 20, 126–127, 188
Behavioural Insights Team (BIT) and, 58–59
core principle, 18–19
features, 111–115
nature of, 110–112
paired with qualitative approaches, 178
purpose, 188
Rational actor model, 42
Rational choice theory, 32, 41–42, 46, 134
behavioral economics and, 27–28, 32, 45
vs. bounded rationality, 27–28
shortcomings and criticisms of, 27–32, 43, 44
Reasoned action, theory of, 36
Recruitment events. See Attendance at recruitment events; SMS invitations to employee recruitment events
Reflective System, 37, 128, 159, 163, 183, 184
Registered reports. See Preregistration
Reisch, Lucia, 162–163
Replication crisis, 133, 136–140
features of scientific publication that contribute to the, 136–138
Reproducibility Project, 138–139
Research practices, 145
“there is no neutral design,” 48, 153
Risk assessment, 30
Rules of thumb, 2, 7, 28, 40, 73. See also Heuristics
Scalability, 102
Scale-up, surviving, 131–133
Self-control, 141–142
Similarity, illusion of, 104
Skunk works, 57
“Sludge,” 146
SMS (short message service), 117f, 118f
SMS invitations to employee recruitment events, 81–82, 89–91, 94, 97f, 99, 100f, 101–103, 102f, 108–110
SMS system, 120
Social and Behavioral Sciences Team (SBST), 62
Social marketing, 43–44
Soda tax. See Sugared drink tax
Soft Drinks Industry Levy. See Sugared drink tax
Stanford marshmallow experiment. See Marshmallow test
Suicide, 161
Sunstein, Cass R., 46, 48–50, 162–163. See also Nudge
Behavioural Insights Team (BIT) and, 56
on libertarian paternalism, 48
on nudge/nudging, 47–49, 170, 183
policy, regulation, and, 50
Superiority bias, 191
Taxation, 14, 44, 58, 76, 125, 164. See also Sugared drink tax
Tax compliance, 19, 44, 58, 76, 185
Temptation bundling, 130–131
Test, Learn, Adapt process, 59
Text messaging. See SMS
Thaler, Richard H., 31–32, 46, 48–50. See also Nudge
Behavioural Insights Team (BIT) and, 56
Conservative Party (UK) advised by, 55
on libertarian paternalism, 48
on mental accounting, 32
on nudge/nudging, 47–49, 57, 170, 183
Token interference transparency, 214n45
token interference, 214n45
Treatment groups, 113–114
Unemployment, goal of reducing, 81–83, 86, 87f
Unemployment centers, 86, 88, 92–94, 109–110, 119–122. See also Bedford Jobcentre
Behavioural Insights Team (BIT) and, 109–110, 121
Unemployment policy, 90
“Upstreaming” (strategic) decision making, 192–193
Utility, 30
Validity, 140. See also Generalizability
Vlaev, Ivo, 51–54
Voting behavior, 130
WEIRD (Western, Educated, Industrialized, Rich, and Democratic), 140
WEIRD science and the problem of generalizability, 140–143
Workplace safety, improving
by redesigning the floor space around workstations, 77–78
Wu, Sherry Jueyu, 78
The MIT Press Essential Knowledge Series
AI Ethics, Mark Coeckelbergh
Algorithms, Panos Louridas
Annotation, Remi H. Kalir and Antero Garcia
Anticorruption, Robert I. Rotberg
Auctions, Timothy P. Hubbard and Harry J. Paarsch
The Book, Amaranth Borsuk
Behavioral Insights, Michael Hallsworth and Elspeth Kirkman
Carbon Capture, Howard J. Herzog
Citizenship, Dimitry Kochenov
Cloud Computing, Nayan B. Ruparelia
Collaborative Society, Dariusz Jemielniak and Aleksandra Przegalinska
Computational Thinking, Peter J. Denning and Matti Tedre
Computing: A Concise History, Paul E. Ceruzzi
The Conscious Mind, Zoltan E. Torey
Contraception: A Concise History, Donna J. Drucker
Critical Thinking, Jonathan Haber
Crowdsourcing, Daren C. Brabham
Cynicism, Ansgar Allen
Data Science, John D. Kelleher and Brendan Tierney
Deep Learning, John D. Kelleher
Extraterrestrials, Wade Roush
Extremism, J. M. Berger
Fake Photos, Hany Farid
fMRI, Peter A. Bandettini
Food, Fabio Parasecoli
Free Will, Mark Balaguer
The Future, Nick Montfort
GPS, Paul E. Ceruzzi
Haptics, Lynette A. Jones
Information and Society, Michael Buckland
Information and the Modern Corporation, James W. Cortada
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The Internet of Things, Samuel Greengard
Irony and Sarcasm, Roger Kreuz
Machine Learning: The New AI, Ethem Alpaydin
Machine Translation, Thierry Poibeau
Macroeconomics, Felipe Larrain B.
Memes in Digital Culture, Limor Shifman
Metadata, Jeffrey Pomerantz
The Mind–Body Problem, Jonathan Westphal
MOOCs, Jonathan Haber
Neuroplasticity, Moheb Costandi
Nihilism, Nolen Gertz
Open Access, Peter Suber
Paradox, Margaret Cuonzo
Phenomenology, Chad Engelland
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Quantum Entanglement, Jed Brody
Recommendation Engines, Michael Schrage
Recycling, Finn Arne Jørgensen
Robots, John Jordan
School Choice, David R. Garcia
Science Fiction, Sherryl Vint
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Smart Cities, Germaine R. Halegoua
Spaceflight: A Concise History, Michael J. Neufeld
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Sustainability, Kent E. Portney
Synesthesia, Richard E. Cytowic
The Technological Singularity, Murray Shanahan
3D Printing, John Jordan
Understanding Beliefs, Nils J. Nilsson
Virtual Reality, Samuel Greengard
Visual Culture, Alexis L. Boylan
Waves, Frederic Raichlen
Michael Hallsworth, PhD, is Managing Director of the Behavioural Insights Team (BIT) North America. He is an Assistant Professor (Adjunct) at Columbia University and an Honorary Lecturer at Imperial College London.
ELSPETH KIRKMAN founded BIT’s North American office before returning to the UK to run the organization’s social policy portfolio out of London. She has taught behavioral insights courses at Harvard and Warwick Universities and is a Visiting Senior Research Fellow at King’s College London.