Five Enablers for a New Phase of Behavioral Science

This article is part of a series based on “A Manifesto for Applying Behavioral Science” from the Behavioural Insights Team. In each article, Michael Hallsworth draws from the manifesto’s agenda for the future of behavioral science and offers a new angle on current thinking. This week, he reflects on the values, resources, and relationships that could help the field match its practice with its ambition. View the series here.

Over recent weeks I’ve been sharing parts of a “manifesto” that tries to give a coherent vision for the future of applied behavioral science. Stepping back, if I had to identify a theme that comes through the various proposals, it would be the need for self-reflective practice.

Behavioral science has seen a tremendous amount of growth and interest over the last decade, largely focused on expanding its uses and methods. My sense is it’s ready for a new phase of maturity. That maturity involves behavioral scientists reflecting on the various ways that their actions are shaped by structural, institutional, environmental, economic, and historical factors.

I’m definitely not exempt from this need for self-reflection. There are times when I’ve focused on a cognitive bias when I should have been spending more time exploring the context and motivations for a decision instead. Sometimes I’ve homed in on a narrow slice of a problem that we can measure, even if that means dispensing with wider systemic effects and challenges. Once I spent a long time trying to apply the language of heuristics and biases to explain why people were failing to use the urgent care alternatives to hospital emergency departments, before realizing that their behavior was completely reasonable.     

The manifesto critiques things like this, but it doesn’t have all the answers. Because it tries to both cover a lot of ground and go into detail, many of the hard knots of implementation go unpicked. The truth is that writing reports and setting goals is the easy part. Turning those goals into practice is much tougher; as behavioral scientists know, there is often a gap between intention and action.

Right now, I and others don’t always realize the ambitions set out in the manifesto. Changing that is going to take time and effort, and it will involve the discomfort of disrupting familiar practices. Some have made public commitments in this direction; my organization is working on upgrading its practices in line with proposals around making predictions prior to implementation, strengthening RCTs to cope with complexity, and enabling people to use behavioral science, among others.

The truth is that writing reports and setting goals is the easy part. Turning those goals into practice is much tougher; as behavioral scientists know, there is often a gap between intention and action.

But changes by individual actors will not be enough. The big issue is that several of the proposals require coordination. For example, one of the key ideas is the need for more multisite studies that are well coordinated and have clear goals. Another prioritizes developing international professional networks to support projects in low- and middle-income countries.

However, unfortunately, the challenge of improving applied behavioral science has characteristics of a social dilemma. Benefits are diffused across the field as a whole, while costs fall on any individual party who chooses to act (or act first). Actors who need to cooperate are often not incentivized to do so. Practitioners usually compete. Academics often want to establish a distinctive research agenda. Funders routinely avoid risks—and are rewarded for doing so.

The field of applied behavioral science itself also has similarities to the complex adaptive systems that, as the manifesto points out, are integral to many policy challenges. Therefore, rather than specifying tasks that need to be executed for change to happen, it’s perhaps better to think about the likely enablers of change for the system. The ones that seem important to me—a combination of values, resources, and relationships—are:

Purpose: The field seems unlikely to agree on a single, shared vision for the future, given the coordination barriers I just listed. But change is more likely to happen if actors have a sense of what they should aim for in different aspects of their practices. For example, behavioral scientists—particularly in large tech companies—will be confronted by increasingly urgent and specific ethical questions posed by the data science capabilities available to them. Having at least some sense of what their peers consider to be a good or acceptable choice could help them avoid the next Cambridge Analytica.  

Curiosity: Although I’ve emphasized the barriers to change, we shouldn’t underestimate the power of many different actors literally experimenting all the time. When behavioral scientists all around the world combine and recombine insights in different contexts, there is an increased likelihood that we unlock new capabilities for the whole field. One way to encourage this curiosity is to help practitioners see how they can get an immediate competitive advantage from innovations that may, later, benefit the field as a whole. Another option is to focus on the collective benefit: we have all benefited from the insights of others, and will continue to do so.

Resources: National and international research funders have considerable sway over some parts of the behavioral science field. These funders need to understand the coordination and collaboration required to tackle the most ambitious challenges and find mechanisms that adequately reward that work by recognizing the true costs involved. The new National Academy of Sciences report in the United States has an encouraging focus on the importance of adaptation and scaling, for example. The U.K. Economic & Social Research Council’s Behavioral Research Hub, which explicitly aims to fund connections for interdisciplinary innovation, is another promising signal.

Disruption: Artificial intelligence is attracting tremendous interest right now. While it is possible to overreact, there are several ways in which AI could massively disrupt the way that applied behavioral science works. For example, it could offer new, scalable ways to enable people to embed behavioral science principles in their own lives with minimal effort (giving a new angle on my previous article in this series about how to empower people to use behavioral science).

Connections: Right now, there is no single, overarching governing body for applied behavioral science. But it’s notable that several associations now exist to bring people in the field together, including BSPA, IBPPA and GAABS, all of whom do rather different things. These associations could plant the seeds of collaboration—and the sense of shared interest—that could grow into solutions for the coordination problems we see right now. After all, the social dilemma literature shows that there is a “large positive effect of communication on cooperation.”


Making generalizations about applied behavioral science is risky—the term covers a great array of approaches, topics, and actors. But what does seem clear is that this variety means that a comprehensive top-down solution to our social dilemma is unlikely. That’s not a reason for despair: there are many examples of how change can emerge when actors pursuing their own goals interact, given the right conditions. In my view, purpose, curiosity, resources, disruption, and connections can all help to establish those conditions. If you agree, then it’s worth asking: Which of these could I contribute to most? If not, then which ones would you put forward instead?

Disclosure: Michael Hallsworth is a member of the BIT, which provides financial support to Behavioral Scientist as an organizational partner. Organizational partners do not play a role in the editorial decisions of the magazine.