Paper by Cass R. Sunstein: “In 1921, John Maynard Keynes and Frank Knight independently insisted on the importance of making a distinction between uncertainty and risk. Keynes referred to matters about which “there is no scientific basis on which to form any calculable probability whatever.” Knight claimed that “Uncertainty must be taken in a sense radically distinct from the familiar notion of Risk, from which it has never been properly separated.” Knightian uncertainty exists when people cannot assign probabilities to imaginable outcomes. People might know that a course of action might produce bad outcomes A, B, C, D, and E, without knowing much or anything about the probability of each. Contrary to a standard view in economics, Knightian uncertainty is real. Dogs face Knightian uncertainty; horses and elephants face it; human beings face it; in particular, human beings who make policy, or develop regulations, sometimes face it. Knightian uncertainty poses challenging and unresolved issues for decision theory and regulatory practice. It bears on many problems, potentially including those raised by artificial intelligence. It is tempting to seek to eliminate the worst-case scenario (and thus to adopt the maximin rule), but serious problems arise if eliminating the worst-case scenario would (1) impose high risks and costs, (2) eliminate large benefits or potential “miracles,” or (3) create uncertain risks…(More)”.
A synthesis of evidence for policy from behavioral science during COVID-19
Paper by Kai Ruggeri et al: “Scientific evidence regularly guides policy decisions, with behavioural science increasingly part of this process. In April 2020, an influential paper proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization…(More)”
Narrative Corruptions
Review by Mike St. Thomas: “…The world outside academia has grown preoccupied with narrative recently. Despite the rise of Big Data (or perhaps because of it), we are more keenly aware of how we use stories to explain what happens in the world, wield political power, and understand ourselves. And we are discovering that these stories can be used for good or ill. From the resurgence of nationalism on the right to the rise of identity politics on the left, the stories we tell about ourselves matter a great deal. As marketing guru Annette Simmons puts it, “Whoever tells the best story wins.” The result has been, in part, the current polarization in American life. An obvious example is the persistence of the false narrative of a stolen election, but at a deeper level, more than ever we now seem inclined—conditioned, even—to judge everything with an up or down vote.
Brooks is less than thrilled about these developments. “It was as if a fledgling I had nourished had become a predator devouring reality in the name of story,” he writes at the outset of Seduced by Story, in a clear attempt to distance himself from what he sees as the abuses of narrative in the years since Reading for the Plot was published. Though his lament contains a strain of academic pearl-clutching, Brooks’s concern is warranted. A narrative is, by nature, a hermeneutic circle—the elements of a plot gaining significance through their relation to each other—and its ever-closing loop threatening to blind its audience to the real.
Though in his new book Brooks does not back down from the claims of his old, he argues that while stories may be unavoidable, they need to be examined and critiqued constantly. A banal thesis, perhaps, but still true. After a preliminary chapter that addresses corporate storytelling and the removal of Confederate monuments, he revisits terrain covered in Reading for the Plot by examining how narratives work, using examples from Victorian-era novelists such as Honoré de Balzac, Henry James, Marcel Proust, and Sir Arthur Conan Doyle.
Within Seduced by Story are the seeds of a more trenchant claim about the ultimate purpose of storytelling—and about how our narratives have become corrupted. Brooks recalls a musical advertising slogan from his youth: “If you’ve got the time / We’ve got the beer. Miller Beer.” Jingles like this were pithy, memorable, and quite effective at communicating a quality of the product, or, more likely, at appealing to a specific emotion of the listener…(More)”.
Think, before you nudge: those who pledge to eco-friendly diets respond more effectively to a nudge
Article (and paper) by Sanchayan Banerjee: “We appreciate the incredible array of global cuisines available to us. Despite the increasing prices, we enjoy a wide variety of food options, including an abundance of meats that our grandparents could only dream of, given their limited access. However, this diverse culinary landscape comes with a price – the current food choices significantly contribute to carbon emissions and conflict with our climate objectives. Therefore, transitioning towards more eco-friendly diets is crucial.
Instead of imposing strict measures or raising costs, researchers have employed subtle “nudges”, those that gently steer individuals toward socially beneficial choices, to reduce meat consumption. These nudges aim to modify how food choices are presented to consumers without imposing choices on them. Nevertheless, expanding the use of these nudges has proven to be a complex task in general, as it sometimes raises ethical concerns about whether people are fully aware of the messages encouraging them to change their behaviour. In the context of diets which are personal, researchers have argued nudging can be ethically dubious. What business do we have in telling people what to eat?
To address these challenges, a novel approach in behavioral science, known as “nudge+”, can empower individuals to reflect on their choices and encourage meaningful shifts towards more environmentally friendly behaviours. A nudge+ is a combination of a nudge with an encouragement to think…(More)”.
Seven routes to experimentation in policymaking: a guide to applied behavioural science methods
OECD Resource: “…offers guidelines and a visual roadmap to help policymakers choose the most fit-for-purpose evidence collection method for their specific policy challenge.
The seven applied behavioural science methods:
- Randomised Controlled Trials (RCTs) are experiments that can demonstrate a causal relationship between an intervention and an outcome, by randomly assigning individuals to an intervention group and a control group.
- A/B testing tests two or more manipulations (such as variants of a webpage) to assess which performs better in terms of a specific goal or metric.
- Difference-in-Difference is an experimental method that estimates the causal effect of an intervention by comparing changes in outcomes between an intervention group and a control group before and after the intervention.
- Before-After studies assess the impact of an intervention or event by comparing outcomes or measurements before and after its occurrence, without a control group.
- Longitudinal studies collect data from the same individuals or groups over an extended period to assess trends over time.
- Correlational studies help to investigate the relationship between two or more variables to determine if they vary together (without implying causation).
- Qualitative studies explore the underlying meanings and nuances of a phenomenon through interviews, focus group sessions, or other exploratory methods based on conversations and observations…(More)”.
Disaster preparedness: Will a “norm nudge” sink or swim?
Article by Jantsje Mol: “In these times of unprecedented climate change, one critical question persists: how do we motivate homeowners to protect their homes and loved ones from the ever-looming threat of flooding? This question led to a captivating behavioral science study, born from a research visit to the Wharton Risk Management and Decision Processes Center in 2019 (currently the Wharton Climate Center). Co-founded and co-directed by the late Howard Kunreuther, the Center has been at the forefront of understanding and mitigating the impact of natural disasters. In this study, we explored the potential of social norms to boost flood preparedness among homeowners. While the results may not align with initial expectations, they shed light on the complexities of human behavior, the significance of meticulous testing, and the enduring legacy of a visionary scholar.
The Power of Social Norms
Before we delve into the results, let’s take a moment to understand what social norms are and why they matter. Social norms dictate what is considered acceptable or expected in a given community. A popular behavioral intervention based on social norms is a norm-nudge: reading information about what others do (say, energy saving behavior of neighbors or tax compliance rates of fellow citizens) may adjust one’s own behavior closer. Norm-nudges are cheap, easy to implement and less prone to political resistance than traditional interventions such as taxes, but they might be ineffective or even backfire. Norm-nudges have been applied to health, finance and the environment, but not yet to the context of natural disaster risk-reduction…(More)”.
The Rapid Growth of Behavioral Science
Article by Steve Wendel: “It’s hard to miss the rapid growth of our field: into new sectors, into new countries, and into new collaborations with other fields. Over the years, I’ve sought to better understand that growth by collecting data about our field and sharing the results. A few weeks ago, I launched the most recent effort – a survey for behavioral science & behavioral design practitioners and one for behavioral researchers around the globe. Here, I’ll share a bit about what we’re seeing so far in the data, and ask for your help to spread it more widely.
First, our field has seen rapid growth since 2008 – which is, naturally, when Thaler and Sunstein’s Nudge first came out. The number of teams and practitioners in the space has grown more or less in tandem, though with a recent slowing in the creation of new teams since 2020. The most productive year was 2019, with 59 new teams starting; the subsequent three years have averaged 28 per year[1].
Behavioral science and design practitioners are also increasingly spread around the world. Just a few years ago, it was difficult to find practitioners outside of BeSci centers in the US, UK, and a few other countries. While we are still heavily concentrated in these areas, there are now active practitioners in 72 countries: from Paraguay to Senegal to Bhutan.
Figure 1: Where practitioners are located. Note – the live and interactive map is available on BehavioralTeams.com.
The majority of practitioners (52%) are in full-time behavioral science or behavioral design roles. The rest are working in other disciplines such as product design and marketing in which they aren’t dedicated to BeSci but have the opportunity to apply it in their work (38%). A minority of individuals have BeSci side jobs (9%).
Among respondents thus far, the most common challenge they are facing is making the case for behavioral science with senior leaders in their organizations (63%) and being able to measure the impact of their inventions (65%). Anecdotally, many practitioners in the field complain that they are asked for their recommendations on what to do, but aren’t given the opportunity to follow up and see if those recommendations were implemented or, when implemented, were actually effective.
The survey asks many more questions about the experiences and backgrounds of practitioners, but we’re still gathering data and will release new results when we have them…(More)”.
The Benefits of Statistical Noise
Article by Ruth Schmidt: “The year was 1999. Chicago’s public housing was in distress, with neglect and gang activity hastening the decline of already depressed neighborhoods. In response, the city launched the Plan for Transformation to offer relief to residents and rejuvenate the city’s public housing system: residents would be temporarily relocated during demolition, after which the real estate would be repurposed for a mixed-income community. Once the building phase was completed, former residents were to receive vouchers to move back into their safer and less stigmatized old neighborhood.
But a billion dollars and over 20 years later, the jury is still out about the plan’s effectiveness and side effects. While many residents do now live in safer, more established communities, many had to move multiple times before settling, or remain in high-poverty, highly segregated neighborhoods. And the idealized notion of former residents as “moving on up” in a free market system rewarded those who knew how to play the game—like private real estate developers—over those with little practice. Some voices were drowned out.
Chicago’s Plan for Transformation shared the same challenges—cost, time, a diverse set of stakeholders—as many similar large-scale civic initiatives. But it also highlights another equally important issue that’s often hidden in plain sight: informational “noise.”
Noise, defined as extraneous data that intrudes on fair and consistent decision-making, is nearly uniformly considered a negative influence on judgment that can lead experts to reach variable findings in contexts as wide-ranging as medicine, public policy, court decisions, and insurance claims. In fact, Daniel Kahneman himself has suggested that for all the attention to bias, noise in decision-making may actually be an equal-opportunity contributor to irrational judgment.
Kahneman and his colleagues have used the metaphor of a target to explain how both noise and bias result in inaccurate judgments, failing to predictably hit the bull’s-eye in different ways. Where bias looks like a tight cluster of shots that all consistently miss the mark, the erratic judgments caused by noise look like a scattershot combination of precise hits and wild misses…(More)”.
Harvard fraud claims fuel doubts over science of behaviour
Article by Andrew Hill and Andrew Jack: “Claims that fraudulent data was used in papers co-authored by a star Harvard Business School ethics expert have fuelled a growing controversy about the validity of behavioural science, whose findings are routinely taught in business schools and applied within companies.
While the professor has not yet responded to details of the claims, the episode is the latest blow to a field that has risen to prominence over the past 15 years and whose findings in areas such as decision-making and team-building are widely put into practice.
Companies from Coca-Cola to JPMorgan Chase have executives dedicated to behavioural science, while governments around the world have also embraced its findings. But well-known principles in the field such as “nudge theory” are now being called into question.
The Harvard episode “is topic number one in business school circles”, said André Spicer, executive dean of London’s Bayes Business School. “There has been a large-scale replication crisis in psychology — lots of the results can’t be reproduced and some of the underlying data has found to be faked.”…
That cast a shadow over the use of behavioural science by government-linked “nudge units” such as the UK’s Behavioural Insights Team, which was spun off into a company in 2014, and the US Office of Evaluation Sciences.
However, David Halpern, now president of BIT, countered that publication bias is not unique to the field. He said he and his peers use far larger-scale, more representative and robust testing than academic research.
Halpern argued that behavioural research can help to effectively deploy government budgets. “The dirty secret of most governments and organisations is that they spend a lot of money, but have no idea if they are spending in ways that make things better.”
Academics point out that testing others’ results is part of normal scientific practice. The difference with behavioural science is that initial results that have not yet been replicated are often quickly recycled into sensational headlines, popular self-help books and business practice.
“Scientists should be better at pointing out when non-scientists over-exaggerate these things and extrapolate, but they are worried that if they do this they will ruin the positive trend [towards their field],” said Pelle Guldborg Hansen, chief executive of iNudgeyou, a centre for applied behavioural research.
Many consultancies have sprung up to cater to corporate demand for behavioural insights. “What I found was that almost anyone who had read Nudge had a licence to set up as a behavioural scientist,” said Nuala Walsh, who formed the Global Association of Applied Behavioural Scientists in 2020 to try to set some standards…(More)”.
How Leaders in Higher Education Can Embed Behavioral Science in Their Institutions
Essay by Ross E. O’Hara: “…Once we view student success through a behavioral science lens and see the complex systems underlying student decision making, it becomes clear that behavioral scientists work best not as mechanics who repair broken systems, but as engineers who design better systems. Higher education, therefore, needs to diffuse those engineers throughout the organization.
To that end, Hallsworth recommends that organizations change their view of behavioral science “from projects to processes, from commissions to culture.” Only when behavioral science expertise is diffused across units and incorporated into all key organizational functions can a college become behaviorally enabled. So how might higher education go about this transformation?
1. Leverage the faculty
Leaders with deep expertise in behavioral science are likely already employed in social and behavioral sciences departments. Consider ways to focus their energy inward to tackle institutional challenges, perhaps using their own classrooms or departments as testing grounds. As they find promising solutions, build the infrastructure to disseminate and implement those ideas college and system wide. Unlike higher education’s normal approach—giving faculty additional unpaid and underappreciated committee work—provide funding and recognition that incentivizes faculty to make higher education policy an important piece of their academic portfolio.
2. Practice cross-functional training
I have spent the past several years providing colleges with behavioral science professional development, but too often this work is focused on a single functional unit, like academic advisors or faculty. Instead, create trainings that include representatives from across campus (e.g., enrollment; financial aid; registrar; student affairs). Not only will this diffuse behavioral science knowledge across the institution, but it will bring together the key players that impact student experience and make it easier for them to see the adaptive system that determines whether a student graduates or withdraws.
3. Let behavioral scientists be engineers
Whether you look for faculty or outside consultants, bring behavioral science experts into conversations early. From redesigning college-to-career pathways to building a new cafeteria, behavioral scientists can help gather and interpret student voices, foresee and circumvent behavioral challenges, and identify measurable and meaningful evaluation metrics. The impact of their expertise will be even greater when they work in an environment with a diffuse knowledge of behavioral science already in place…(More)”