The turn of the year is often a time of new beginnings, from New Year’s Resolutions to Presidential Inaugurations. And as this year dawns, I feel that it’s time for my chosen field of applied Behavioral Science to commit to a new path forward.

For the past decade or more, we’ve pursued impact through the growth of dedicated Behavioral Science teams and efforts. We’ve encouraged and supported organizations to build “nudge units” and launched consultancies to develop, pursue and implement projects. And to be fair, there have been notable success stories, including both well-established internal units (at Commonwealth Bank of Australia, Edward Jones and Blue Cross Blue Shield of Massachusetts, among others) and a number of healthy, growing consultancies.

But more recently, we’ve also seen several notable setbacks, including the dissolution of dedicated Behavioral Science units at Allstate, Johnson & Johnson, Truist Bank and more. Meanwhile, the largest dedicated Behavioral Science consultancies (such as BIT, ideas42 and Busara) continue to focus primarily on the public sector. To be transparent, it appears that none have found a successful formula for truly scaling their work and impact within a private sector context.

Given this reality, it’s now time for the field to collectively step back, reconsider our working model — and find a new path to increasing the adoption and impact of behavioral science.

Limitations of the “BeSci Projects & Teams” Model

In prior articles, I’ve written in depth about the challenges facing Behavioral Science within the Private Sector and suggested several strategies for overcoming them. However, it’s important to also acknowledge the key structural challenges inherent in the “BeSci teams and projects” model, which have become increasingly apparent over time:

With respect to dedicated Behavioral Science teams, the unfortunate reality is that they are subject to (and often victims of) nearly inevitable changes in organizational leadership, priorities and performance.

These teams are dependent on having the right advocates or “champions” at Senior Management levels. But these senior people and positions change frequently, leaving the BeSci teams/roles extremely vulnerable to changing priorities (such as investments in AI tools/technology) and to budget cuts. And paradoxically, as a dedicated team becomes larger (and presumably more impactful), it also becomes a more prominent line-item on the budget.

With respect to dedicated Behavioral Science projects, the primary challenge is that they are generally perceived to be incremental investments/costs rather than valuable and integrated assets in the business.

Thus, they are often engaged in a “zero-sum” struggle for budgeting, in which they compete for funds against better-established and supported efforts. In order for a Behavioral Science project to happen, something else needs to be dropped — and this is nearly always an uphill battle, because it’s a fight against the status quo (on both cognitive and financial levels). And of course, there’s the larger issue is that leaders need to be able to recognize an opportunity or problem as “behavioral” before they typically reach out to Behavioral Science professionals or consultancies. (In fact, business leaders’ lack of awareness or fluency in identifying behavioral issues is a massive impediment to Behavioral Science teams gaining a meaningful foothold within corporate structures.)

In order for a Behavioral Science project to happen, something else needs to be dropped — and this is nearly always an uphill battle.

So while we’ve now built an abundance of case studies demonstrating the value of our work, I’ve now come to believe that pursuing dedicated Behavioral Science teams and projects will ultimately limit the field’s potential for growth and impact.

Finding a New Path Forward

But what can be done to supplement the current model for applying Behavioral Science? I believe that the most promising route forward has been apparent from the start, when Richard Thaler noted that “All economics should be behavioral economics.” By this, he meant that as the insights from behavioral economics become more widely accepted and integrated into mainstream decision-making, the need to explicitly label them as “behavioral” may fade away, as they are simply considered standard practice.

My former BIT colleague Michael Hallsworth elaborated on this theme in his Manifesto for Applying Behavioral Science. Applying the analogy of a house, he argued that more energy should be placed on Rewiring Organizations for Behavioral Science — integrating behavioral science into an organization’s core processes (for budgeting, incentives, recruiting and more) — relative to building more “Behavioral Science rooms” (i.e. dedicated units and teams).

If we follow this line of thinking, it leads us to a somewhat ironic and counterintuitive conclusion: The best way to grow the field’s impact is by making it invisible. Instead of explicitly championing (and perhaps defending) behavioral science — and pursuing dedicated teams and projects — we should be focused on silently integrating it within the DNA of organizations. But what exactly does “integration” really mean? What would success look like? And what are the most promising strategies or paths for getting there?

The experience of the best decade leads us to a somewhat ironic and counterintuitive conclusion: The best way to grow the field’s impact is by making it invisible.

I’ve been giving these issues some thought — and I feel that the answer or solution begins with “behaviorally-informed executives.” By this, I mean that success would be a future in which far more organizations, divisions and teams are led by people with a working knowledge of Behavioral Science, including:

• The ability to apply a “behavioral science” lens to challenges and identify promising opportunities for impact
• The ability to frame situations or problems in terms of desirable behaviors or behavior changes
• The ability to integrate basic behavioral science frameworks into existing policies, processes, divisions, departments, and projects
• The ability to know when it’s necessary and appropriate to bring in specialists with a deeper understanding of the field (and how to work effectively with such experts).
• The ability to effectively engage and empower teams to recognize and realize opportunities for implementing behavioral science solutions

Success would be a future in which far more organizations, divisions and teams are led by Behaviorally-Informed Executives.

How can we foster more leaders with these capabilities? At this point, I can envision two complementary strategies:

First, by steering the growing cohort of Behavioral Science graduates and enthusiasts towards “mainstream” roles/titles

As I’ve elaborated upon in An Open Letter to Behavioral Science Graduates (& Enthusiasts), it’s quite natural for graduates of Behavioral Science Masters programs to seek dedicated “behavioral” roles and organizations. But the reality is that these opportunities are still quite limited. The larger opportunity is to bring Behavioral Science thinking to “traditional” roles across many disciplines (Research/Insights, Human Resources, Compliance, Marketing, Sustainability, Sales, Operations, etc.). And here, they can find many ways to apply their Behavioral Science skills (and mindset) to bring needed ideas, innovation and impact to their organizations.

Second, by significantly “stepping up” our collective efforts within MBA and Executive Education

Until recently, I thought that this required developing new behavioral-science courses and certifications, which could be added to MBA and Executive Ed curricula. However, I’ve come to realize that this “dedicated” model has its limitations, akin to those facing Behavioral Science teams and projects. So instead, I’ve been focusing my personal efforts on developing “Behavioral Science modules’ within mainstream programs (on Leadership, Organizational Change, HR, Marketing/Insights, etc.). To me, it’s one example/manifestation of “making Behavioral Science invisible” as a path to reaching a wider audience — and ultimately making a bigger impact.

A Final Word (& a New Year’s Resolution)

Finally, I’d be remiss if I didn’t acknowledge that this path forward is also an uncomfortable one for many behavioral science practitioners. After all, it involves a degree of subjugating our excitement/enthusiasm — and that’s a tall order for those who have pursued advanced degrees and/or built their careers and reputations in the field. But ultimately, I believe that we’re (regrettably) reaching the limits of “dedicated Behavioral Science” units — and that the future most likely lies in integration (within traditional roles, processes and projects).

So my personal New Year’s Resolution is to re-dedicate myself to helping make this happen, by reaching out to help support the education and development of more behaviorally-informed executives.

I hope that many of you within the Behavioral Science community will join me — and as a starting point, I’d love your feedback and ideas. So please reach out to me at scott.young@bescy.org and let’s continue the conversation.

Scott Young is an independent advisor and educator, whose passion and expertise lies in helping leaders and organizations to apply Behavioral Science ethically and effectively. He can be reached at scott.young@bescy.org.

Is It Time for a New Start? was originally published in Behavioral Design Hub on Medium, where people are continuing the conversation by highlighting and responding to this story.

In the wake of President Trump’s victory, questions surrounding the role of online mis and disinformation in shaping voter behaviour have become more pressing than ever. At the start of 2024, a year with 60 countries holding national elections and nearly two billion people casting their vote, Thinks Insight & Strategy published research [1] on how to address the spread of mis and disinformation online. The research highlighted the public’s vulnerability to engaging with misleading content and the potential of ‘brain training’ interventions to curb its spread.

As the stakes continue to climb, understanding and countering these threats remains crucial. Trump’s victory, marked by a highly charged social media environment, underscores the urgent need to address how digital disinformation impacts democracy and potentially incites real-world consequences.

Mis and disinformation are a threat

Thinks used an innovative simulation of a social media platform to capture people’s actual behavioural responses (likes, comments, shares and more) to mis and disinformation as well as all the cat videos, recipes and other content commonly found on social media. The experiment, using a UK sample, found:

• The general public in the UK are vulnerable to amplifying disinformation (for example by liking, sharing or commenting). Four in ten (38%) people in the ‘control’ arm of our experiment amplified at least one piece of mis and disinformation they encountered. The fake post with the highest reactions being deepfake of Keir Starmer abusing his staff.
• Taking part in a short ‘brain training’ game (based on inoculation interventions shown to work in academic research [2]) reduced the amount of people amplifying at least one piece of misinformation to three in ten (32%).
• Rolling out a brain training game of this type could meaningfully reduce the spread of mis and disinformation in the UK and globally.

Since our research was published the General Election in the UK has been and gone. Despite the historic nature of the result there are few, if any, questions about its legitimacy or suggestions that disinformation influenced the final result.

But threats evolve

Online mis and disinformation about the identity of the person who was suspected of committing the murders in Southport spread quickly [3] online and via social media and may have been an important catalyst for the far-right riots that plagued England in early August. These events raise three key questions about how the threat of misinformation is evolving:

1. How can we treat the underlying causes, as well as the symptoms

Whilst the spread of disinformation online may have helped to spark the riots in August, the rioters were clearly motivated by pre-existing Islamophobic, racist and anti-asylum seeker sentiments. As we said when we published our research earlier this year, treating people who have ‘fallen down the rabbit hole’ due to exposure to mis and disinformation online, or those who already hold such views, require much more than a brain training game. Policy considerations will need to assess again how we engage, challenge and support people whose views may predispose them to incite, or participate, in disorder.

2. Are ‘authority’ effects significant enough to warrant a targeted response?

Authority effects are well studied — we are more influenced by or respond more to celebrities, people who we believe to have relevant expertise or people with formal authority such as elected politicians [4]. Figures such as Tommy Robinson (or his real name Stephen Yaxley-Lennon) and Andrew Tate may have been expected to spread disinformation about the Southport murders but the disorder and disinformation was amplified (whether knowingly or unknowingly) by both Nigel Farage (a sitting MP and the leader of Reform, who had the third largest vote share in the General Election) and Elon Musk, the owner of X with 197.4m followers on the platform. A review of the Online Safety act was suggested by a minister [5] in response. We suggest that regardless of regulation there is a case for further research on how authority effects work in online environments and whether there is a case for a targeted response whether that is updated regulation, inoculations or other efforts.

3. How should traditional news media cover real world events inspired by online disinformation?

• The August 2024 UK riots were an example of how disinformation can jump from being a purely online phenomenon into the ‘real world’. Once the riots had begun, the traditional news media had to cover them, but some received criticism for the tenor of that coverage (for example describing them as protests rather than riots). A key aspect of this criticism related to the idea that the coverage potentially both lent credibility to the disinformation that had sparked the protests and helped to spread it to ‘less online’ audiences.
• Similarly, the decision by major newspapers like the LA Times and Washington Post to abstain from endorsing US political candidates reflects a shift in how traditional media perceives its role in potentially polarising situations.
• When covering real-world events inspired by online disinformation, traditional media is navigating how its reporting may unintentionally validate or amplify the very falsehoods that sparked the events. To complicate things, there’s currently little evidence available about the extent to which the language used by established media can actually either boost or temper misleading content

So our response also needs to evolve

Firstly, it is still clear that the brain training game we tested and other similar ‘inoculation’ interventions have the capacity to positively influence people’s behaviour online, reducing the spread of disinformation on social media platforms. Whilst stopping the spread is only part of the picture limiting the impact of mis and disinformation, it is an important one as people are unlikely to act on false information that they haven’t been made aware of. It is therefore vital that we take advantage of the interventions that we know can make a significant difference. Great work is being done by academics, civil society and companies to explore and develop these interventions but not enough is being done yet to roll inoculation interventions out where it matters — on the platforms themselves.

It is also clear, however, that the threat is evolving rapidly, and that further work is required to evolve our response. In light of the evolution of misinformation, researchers and other concerned groups might focus their effort in the following ways:

• Targeted inoculations to address issues of concern before they lead to violence. Specific issues of concern such as racism, misogyny and discrimination against the LGBT community can be treated with targeted inoculation interventions. The academic evidence on the efficacy of these interventions is strong [6] and they are backed by our own research — further development and testing, ideally in the field, could evidence the impact of further targeted inoculations.
• Policy responses that balance freedom of speech and the rule of law. The amplification of disinformation (both on this topic and others) by authority figures raises questions about whether the algorithms used on social media sites will remain ‘content neutral’ or whether they may already actively boost specific content [7] that drives engagement but also, potentially, disorder [8]. To craft effective policy responses government and regulators will require rigorous evidence about the specific risks and impact of authority figures on social media platforms and the processes by which their content is pushed to users.
• Guidance for news organisation on how to report on disinformation without spreading it or lending it credibility. Intuitively, we all know that the language used in a news report about a protest or riot can help to build or undermine the credibility of the protest or riots’ cause. For example, an “anti-weather control protest” sounds more credible than a “protest by anti-weather control conspiracy theorists”. However, there is little evidence of the behavioural impact of traditional news media using different language and framings for real world events prompted by online disinformation. Behavioural science experiments, like the one we ran, can help to provide robust evidence about how the different language used in news reporting affects online behaviours, ultimately informing guidance for news media that helps them to combat disinformation.

Thinks is a global insight and strategy consultancy. We combine pioneering research skills with outstanding thinking to help our clients make better decisions, drive positive behaviour, communicate more persuasively, and engage more effectively.

Max Mawby, Founder, Applied Behavioural Science
Max is a leading practitioner in applying insights from behavioural science to drive positive change.

Max Templer, Director
Max is a specialist mixed-methods researcher, utilising qualitative and quantitative methods to address clients’ objectives.

Eoin Campbell, Associate Director, Behavioural
Eoin develops and applies solutions grounded in behavioural science literature to enhance user experience.

References

1. https://www.thinksinsight.com/case-studies/addressing-disinformation-online
2. Lu, C., Hu, B., Li, Q., Bi, C., & Ju, X. D. (2023). Psychological inoculation for credibility assessment, sharing intention, and discernment of misinformation: Systematic review and meta-analysis. Journal of Medical Internet Research, 25, e49255.
3. https://fullfact.org/news/misinformation-southport-stabbings/
4. Tyler, T. R. (1997). The psychology of legitimacy: A relational perspective on voluntary deference to authorities. Personality and social psychology review, 1(4), 323–345.
5. https://theconversation.com/what-is-the-online-safety-act-and-why-have-riots-reopened-debates-about-it-236654
6. See the meta analysis at reference 2.
7. https://github.com/twitter/the-algorithm/issues/436
8. https://edition.cnn.com/2024/08/06/tech/elon-musk-civil-war-uk-riots/index.html

Mis and Disinformation was originally published in Behavioral Design Hub on Medium, where people are continuing the conversation by highlighting and responding to this story.

Introduction

Consistency is crucial for success in any exercise or diet program, but absolute adherence day in and day out is neither feasible nor advisable. Incorporating periodic breaks, whether “rest days” from exercise or “cheat days” from dieting, can promote better long-term sustainability and results.

This concept of strategic recovery is gaining more mainstream attention with the rise of wearable fitness trackers like WHOOP and Oura that advise users when to dial back training based on strain data. Similarly, many modern diet plans emphasize flexibility over rigid restrictions.

Most exercise and diet plans operate on a weekly schedule, which means that there are likely patterns in when people take their rest and cheat days. However, not every day is the same when it comes to taking a break. The ideal timing of these breaks may be influenced by psychological factors. One example is the “fresh start effect” — our tendency to tackle goals with increased motivation at the beginning of new temporal milestones like weeks, months, or years.

A recent study of over 60,000 gym-goers found that they were more likely to stick to their workout routines when exercising on Mondays compared to other days of the week. This raises the question: Do people strategically schedule rest and cheat days later in the week to capitalize on the motivating power of a “fresh start”?

To explore people’s preferences and habits around recovery breaks, I ran a short survey asking about the specifics of rest days and cheat days. Read on below for the findings. I discuss the results of the rest days first, and then the cheat days.

Rest Days

160 out of the 225 respondents reported having an exercise routine.

1. The number of days rested

Having two rest days was the most common, with 41% of the respondents reporting so, while 30% reported having just one. Resting was common in general, with only 4% of the respondents, or 7 out of the 160 reporting not resting at all.

2. Most common rest days

For those who rested just one day a week, Sunday was the most common rest day, followed by Saturday and Friday.

This trend continued in those who rested 2 days a week, with the weekend being the most common time to rest.

The breakdown for 3 days a week was a little mixed. The most common strategy was to alternate rest and break days, though taking 3 consecutive days off was also reported by a notable portion of respondents.

Finally, the following figure combines the overall data, revealing the overall distribution of rest days. Again this shows that the weekends (including Friday) were the most likely days to be resting.

3. Discussion

These results indicate that most respondents incorporate a healthy amount of rest into their exercise routines, with only 4% reporting no rest days at all. Among those who do take scheduled breaks, weekends are the most common rest days. This pattern is unsurprising, as maintaining a consistent exercise routine often relies on stable environmental cues and contexts. Weekdays generally provide more regularity for most people, while weekends bring changes in routine due to social and contextual factors, making them a natural choice for rest.

Notably, Monday emerged as the least common day for rest days. This may be intentional or is perhaps due to the logistics of the workout program or the gym hours. Regardless, the respondents in this sample do appear to be taking advantage of the potential of a fresh start effect in their exercise routines.

Cheat Days

112 out of 225 of the survey respondents indicated they were dieting or on some type of diet plan

1. Number of cheat days

It was most common to have just one cheat day, with 48% of the respondents reporting this option, whereas 32% reported having two. In contrast to the rest day findings, a substantial portion, around 14% reported having no cheat days at all.

2. Most common cheat days

For those who had just one cheat day a week, the most common days were tied between Saturday and Sunday, with Friday being the third most common response.

For those who had 2 cheat days, the weekend was the most common choice. With the second most common being Friday and Saturday.

Finally, when looking at the data overall, the most likely days to be cheat days were Friday, Saturday, and Sunday, with none of the weekdays being picked a significant amount of times.

3. Discussion

The results above showed that having just one cheat day was the most common. This may be because dieting, unlike exercise, doesn’t physically fatigue the body to require multiple days of breaks in a weekly period. However, the more likely explanation is probably psychological. Dieting is a behavior where adherence is seen as critical and any misstep is seen as a defect in willpower. Even the name ‘cheat day’ signifies the guilt of breaking away and giving in to your desires. The relatively sizeable proportion reporting zero cheat days suggests the goal for many is strict adherence with minimal built-in flexibility.

When people did take breaks, the most common days were around the weekend. This is again not surprising for the same reasons as when people rest from exercising. Most social gatherings happen over the weekend, and dieting, being naturally restricting, can be difficult to maintain during social gatherings.

Again, weekdays were the least common rest days, excluding Friday. Monday was not the lowest chosen day in this instance, but the differences in the margins were non-significant. So, perhaps the same fresh start phenomenon is at play here.

Implications

We set out to explore how often and when people take breaks from diet and exercise, and whether the fresh start effect influences this. We found that the most common rest and cheat days were over the weekend and that weekdays, especially at the start of the week (Monday/Tuesday) were far less common for taking a break than later in the week (Wednesday onwards).

What are the implications of this for supporting behavior change? The findings here are fairly common sense and should not come as a surprise to anyone in the exercise and diet world. What is surprising, however, is that this knowledge is not widely used to inform the design of exercise and diet apps.

Most apps don’t inquire about when someone is taking a rest or a cheat day. For example, a search of ‘rest days’ for Apple Fitness will only lead you to frustration-filled posts from users, or in other cases, hacks on how to trick the app to allow rest.

However, the fitness world is not entirely behind. Many apps, especially those focused on strength training, allow users to set their workout days in advance. Additionally, companies like WHOOP, OURA, and Garmin have explicitly incorporated rest and recovery into their designs. This integration reflects the fitness community’s understanding of adaptation and periodization, which emphasize the importance of rest.

The story is quite different when it comes to dieting. The guilt-inducing label of a ‘cheat’ day has likely prevented this concept from being integrated into diet apps.

While cheat days are the elephant in the room for most dieting apps, scientific research points to the benefits of including a planned day of indulgence. For example, planned overeating during dieting has been shown to increase leptin levels, which can help curb hunger throughout the week. In another study, it was found that those who took intermittent breaks had greater weight loss during dieting, and managed to keep more of it off after the diet.

The benefits of cheat days are not just physiological. Including a planned day of indulgence was also shown to help with self-regulation, motivation, and mood overall.

What could this look like in production?

At its simplest, users would have the ability to set different goals on different days of the week, allowing them to indulge on a planned day. For example, the calorie tracking app, MyFitnessPal allows you to set custom macro goals, a feature that could be used to build in treat day(s).

Ideally, the app itself provides encouragement and guidance on including a break from dieting, and this sentiment is ingrained into the overall behavioral design. For example, the messaging on a treat day could be different, see the example below.

This explicit acknowledgment is necessary because when diet apps treat every day as the same, users are likely to refrain from logging their meals on the cheat day due to guilt and shame. This is problematic for the individual, but also creates a blind spot for the product team, as they lose crucial information about eating behavior.

Final Thoughts

Breaks from exercise and diet are not only beneficial for physiological reasons but also provide psychological benefits. This survey found that such breaks are common. In contrast, many diet and exercise apps do not commonly incorporate breaks into their design. Incorporating this concept into an app’s design could bring success to both the individual and the product.

Limitations

This was a short survey with a small sample size. However, the trends observed are clear. In the future, additional questions about the type of diet or exercise program an individual is using could help better understand some of the findings.

Lastly, this is self-report data, which may contrast with usage data on diet and exercise apps. If you have such data, send me a message at hassan@nuancebehavior.com!

Additional Notes

• The online testing platform, Prolific was used to recruit the participants. Each participant was paid for their participation.
• As a control, all participants were asked to state when their week ‘starts’. Around 93% reported Monday. Those who reported different start days did not differ in their responses.
• Of those who had both diet and exercise routines, 67% had overlap in their rest and cheat days. This pairing is often recommended by health experts!

Hassan Aleem, PhD, is the Co-Founder of Nuance Behavior, an agency dedicated to leveraging behavioral science to drive digital behavior change. Hassan’s research in Neuroaesthetics has explored how aesthetic elements impact decision-making, moods, and identity. Currently, he consults on usability, engagement, and growth for digital products, helping companies integrate behavioral science into their product development for better user outcomes

When do people rest and cheat? was originally published in Behavioral Design Hub on Medium, where people are continuing the conversation by highlighting and responding to this story.

Through my involvement at Bescy and my guest lectures at Masters and Executive Education programs, I’m fortunate to encounter many people interested in entering the Behavioral Science field. Certainly, it’s exciting and encouraging to see so many people who share my passion and are eager to build (or perhaps pivot) their careers in this direction. And of course, I’m often asked for career advice, about where to find jobs in the field — and/or which organizations or roles present the best opportunities.

With these inquiries in mind, I’d like to share several thoughts, as I think they apply both to new graduates entering the field — and/or mid-career professionals looking to apply Behavioral Science to their work.

Searching: Don’t Limit Yourself to “Behavioral” Roles

After investing in a Behavioral Science graduate degree — or perhaps an Exec Ed program or certificate — it’s quite understandable for you to gravitate towards “BeSci roles.” This could take the form of a dedicated consultancy (such as BIT, ideas42 or Cowry) or perhaps an internal role with the words “behavioral” in the title.

Of course, these opportunities may be worth exploring — and there are several good places to search for roles of this nature, beginning with the jobs board at Habit Weekly. But the reality is that they are still quite limited — and arguably, there’s a much larger scope of opportunity to bring Behavioral Science thinking to “traditional” roles across many disciplines (Research/Insights, Human Resources, Compliance, Marketing, Sustainability, etc.).

Rather than “looking for Behavioral Science” per se, think of your new skills (and mindset) as a powerful point-of-difference, which will help you secure a new/desired role.

So rather than “looking for Behavioral Science” per se, I’d encourage you to think of your new skills (and mindset) as a powerful point-of-difference, which will help you secure a new/desired role — and more importantly, bring new ideas, innovation and impact to the position and organization. This links to a broader piece of advice, which is to start with your own passion (and/or your area of expertise) — and then work backwards to find ways to apply Behavioral Science to it.

Avoid falling into the trap of becoming “a hammer looking for a nail” (i.e. a Behavioral Scientist looking for an application)

Interviewing: Focus on The Organization’s Challenges

After immersing yourself in Behavioral Science, it’s only natural to want to share your knowledge and convey your enthusiasm to others. But as you head into interviews, it’s very important to remember that most people — particularly those in more mainstream roles — have limited awareness. And while they may find it interesting, the reality is that they are probably far more interested in their own problems (and how you might help solve them).

So while it’s fine to share an anecdote or framework, it’s far more important to quickly transition to how your BeSci knowledge can contribute to the organization’s mission — or address a team’s specific challenge. For example, if you are applying for a People/HR role, have your ideas (and examples) ready about how behaviorally-informed approaches might increase employee engagement or retention.

Demonstrate how BeSci thinking can drive movement on the key metrics that matter to the organization.

This highlights the importance of learning (and adopting) the “language of business” (i.e. how the organization measures performance and defines success), rather than speaking solely in terms of heuristics and RCTs. To secure the right position, you’ll need to effectively link these two languages — and demonstrate how BeSci thinking can drive movement on the key metrics that matter to them.

Remember to speak to their challenges and metrics, rather than only your new knowledge and terminology.

Applying: Be Flexible (& Patient) with Your Colleagues

In your program, you will most likely have been taught the “right” way to apply Behavioral Science (with respect to problem definition, sampling, testing, etc.) — and you will probably be inclined to apply this academic knowledge in your new role.

However, in most “real-world” scenarios, you’ll soon encounter people approaching and applying Behavioral Science with varying degrees of rigor and competence. There will be those who latch onto a specific heuristic from a book or podcast — and claim that they “already do” Behavioral Science. There will be those looking for ideas, with limited appetite or patience for testing and measurement. There will be those who equate the field with nudging, with no conception of the breath of the field.

Of course, it is tempting to lecture these people, correct their misperceptions and insist that they “do it right.” However, in my experience, this is usually counter-productive. Instead, it’s best to be supportive, build trusting relationships — and gradually leverage those relationships to drive change, when the next opportunity comes along.

To effectively promote Behavioral Science within an organization, you’ll need to understand where your colleagues are coming from — and uncover the real-world barriers driving their thinking.

This form of patience is challenging — and certainly there is a degree of nuance involved, in terms of how to best balance rigor and pragmatism (and when to push people’s thinking). But to effectively promote Behavioral Science within an organization, you’ll need to understand where your colleagues are coming from — and uncover the real-world barriers (i.e. tight timelines, limited budgets, etc.) driving their thinking. These insights (and relationships) are what will set you up for long-term success in your role.

Err on the side of being positive and approachable, rather than pedantic.

Maximizing Your Positive Impact

Along with job inquiries, I’m often questioned about ethical considerations, as people seek to maximize their positive social impact. This is admirable — and I’m always a bit hesitant to preach or impose my views, as it is such an individual matter. In my experience, there are some people whose values lead them to social impact organizations (charities, NGOs, etc.), while others are perfectly comfortable in profit-driven companies, provided that they feel that their own work is “for good.”

Ensure that you have some ethical framework in place, with which to consider both individual projects and new career opportunities.

Personally, I fall into the latter camp, as my mission is to help leverage the private sector’s enormous reach and resources to positively impact consumers, employees and society. Thus, I search for “win-win-win” opportunities and make ethical judgments largely on a project-by-project basis, rather than choosing categorically not to work with (or at) specific companies or industries. Yet I realize that others may reach different conclusions — and thus, my primary advice is to ensure that you have some ethical framework in place, with which to consider both individual projects and new career opportunities. While the right path may not always be clear, having a set of principles (or questions to ask yourself), about the implications of your work on those directly impacted (and society more broadly) will help you avoid drifting down a slippery slope.

After nearly 10 years in applied Behavioral Science, I remain quite optimistic, as I see so many opportunities to apply its principles ethically and effectively. I also find myself encouraged by the many excellent programs to educate executives and develop skilled new practitioners — and most importantly, by the many talented, motivated people who are drawn to the field.

Think beyond “behavioral roles” — and focus instead on bringing “a Behavioral Science lens” to existing roles and challenges.

Yet for individuals (and organizations) to fully leverage this opportunity, they will need to think beyond “behavioral roles” — and focus instead on bringing “a Behavioral Science lens” to existing roles and challenges. By applying their newfound skills and perspective in this direction — and patiently bringing along their colleagues — new graduates and enthusiasts can help successfully embed Behavioral Science within organizations and maximize their positive impact.

Scott Young is an independent advisor and educator, whose passion and expertise lies in helping leaders and organizations to apply Behavioral Science ethically and effectively. He can be reached at scott.young@bescy.org.

An Open Letter to Behavioral Science Graduates (& Enthusiasts) was originally published in Behavioral Design Hub on Medium, where people are continuing the conversation by highlighting and responding to this story.

Erik leads research and development at the Center for Behavior and the Environment at the environmental non-profit Rare. His work focuses on conducting the research necessary for taking behavioral science out of the lab to driving change in the field. He received his PhD in Psychology from the University of Pennsylvania studying social norm change.

Habit Weekly (HW): Can you share an example of a successful sustainability initiative that effectively leveraged insights from behavioral science to drive widespread change?

Erik Thulin (ET): One of my favorites at the moment is Solarize, a Department of Energy funded initiative that has taken off across the country. Solarize leverages community campaigns to drive the adoption of rooftop solar. They do a ton of things right. They reduce ambiguity by having experts from the community pre-vet installers. They reduce financial burdens by leveraging their group purchasing to secure discounts. But perhaps most impactfully, they both use and shift solar norms through the highlighting of ambassadors within the community who already have solar to change social expectations around the entire process. Perhaps just as relevant as what they do do is what they don’t. Critically, they don’t assume you can just nudge someone into spending tens of thousands of dollars. Instead, they leverage a far more intensive program leveraging behavioral insights to drive change.

The question simply comes down to what actions have the largest impact including the largest ripples.

How do you approach the challenge of balancing the promotion of sustainable behaviors at the individual level with the need for systemic changes in industries and policies?

ET: I think this question represents a dichotomy in thinking which often undermines the opportunity for change. Systems are emergent constructs from the individuals within them. If we want to understand the impact of changing some element of that system (like the behavior of a given actor), we need to consider the impacts across the entire system.

Is putting solar on your roof an individual action? It impacts the probability of those around you installing solar, influences the grid mix in your local area, and influences public utility revenue. Is choosing to purchase a vegetarian meal rather than a meat meal an individual action? To believe so would require some fundamental rejection of how we conceptualize supply and demand. Is voting? Petitioning your elected representative? Protesting? All of these are actions that actors within a system can take which have ripple effects throughout the system. So to me, there isn’t any such tension. The question simply comes down to what actions have the largest impact including the largest ripples.

What are the key psychological barriers that prevent individuals from adopting sustainable behaviors, and what strategies might overcome these obstacles?

ET: I think we too often try to cleave behavioral challenges by domain. Before I joined the Center for Behavior & the Environment, I had never worked on sustainability. That same holds for most of the scientists at the Center. Two things are true about environmental behavioral challenges: (1) they aren’t fundamentally different from challenges in other domains, and (2) within the environmental domain, there are radical differences in the psychological barriers to adopting different behaviors.

We see a lot of challenges around efficacy, in terms of self-efficacy, collective efficacy, and outcome-efficacy.

But after all that throat-clearing, I will highlight a few psychological barriers we see come up frequently, often together with one another. We see a lot of challenges around efficacy, in terms of self-efficacy (belief you can perform the behavior), collective efficacy (collective belief that the group can perform the behavior), and outcome-efficacy (belief that the behavior will have the intended impact). We see challenges in social norms, both people believing that others aren’t engaging in the target behaviors and that others don’t think they should. Importantly, these are often pluralistic ignorance situations, where far more people think these behaviors should be adopted than others expect. Finally, a lot of driving adoption is both making it both feel easier to do as well as making it actually easier to do. Part of good design is recognizing that the solutions to those barriers is often heavily context and behavior specific so I hesitate to point too much attention to any given solution.

What are the common hurdles businesses face when trying to implement behavioral science-informed sustainability strategies, and how can they more effectively engage customers and employees?

ET: I don’t have a lot of faith in a broad push from businesses to implement behavioral science-informed sustainability strategies, because I think their barriers to doing so are structural. The incentives in a business context are rarely aligned with high-impact behavior change, which often means consuming less of their product. I would note that consumers are often those with the power in this dynamic, as it is their preferences that businesses are strategizing to address. In many firms, sustainability is literally the purview of the marketing team. Recognizing that dynamic, sustainability teams are often in the position of needing to justify green positioning in terms of brand equity.

Consumers are often those with the power, as it is their preferences that businesses are strategizing to address.

While plenty of one-off counter examples exist, I don’t think we should be looking to businesses to be leaders in promoting effective sustainability strategies beyond those that directly benefit their own bottom line such as internal efficiencies. Large-scale change in that context is going to come from changes in consumer demand and the regulatory environment.

Can you discuss how cultural differences shape attitudes and behaviors towards sustainability, and how might we use this understanding to promote change?

ET: There are a few different angles to think about this. Some of your readers may be familiar with the Environmental Kuznets Curve (see figure below), which documents the broad finding that as incomes rise, so does environmental sustainability concerns. The most common explanation for this phenomenon is that caring about things like sustainability is something you have the luxury of once your basic needs are met. While there is some broad truth to this, it neglects the degree to which many people in low-income contexts rely heavily on the environment to meet those same basic needs, Rare’s work in coastal fisheries being an excellent example.

However, I think the framing of cultural differences in sustainability can actually divert us from the cultural differences that are actually most important to driving high-impact environmental behaviors. That is because how the behavior itself is framed may in fact be where the cultural discrepancies lie. Most of the fishers we work with in small-scale coastal fisheries see overfishing as not primarily an environmental challenge but as a challenge to their livelihoods and way of life. A rural Texan with solar panels may not see those panels as reducing greenhouse gas emissions but as a way to express her independence. To think cross-culturally (whether that is between or within countries), one of the most important things to do is often to recognize that while the environmental benefits may seem salient to you as the designer, they may not be the salient factor for those you hope to influence.

I see a future where far more behavioral science based interventions are intensive community based approaches applying a layered strategy addressing multiple barriers simultaneously.

Looking ahead, what emerging trends or developments in behavioral science do you foresee having the most significant impact on sustainability efforts?

ET: I have two thoughts, one in the short term one the long term. I am heartened by the reckoning applied bevhavioral science is experiencing at the moment, in which the field as a whole is coming to terms with (1) while nudge style interventions may have high ROI, they tend not to have large effects particularly when targeting our greatest challenges like shifting livelihoods and (2) behavioral and social sciences have much more to offer than only the minimalism of nudging. I see a future where far more behavioral science based interventions are intensive community based approaches applying a layered strategy addressing multiple barriers simultaneously. These strategies won’t be as cheap, as easy to evaluate, or as simple to implement as the nudges of the past decade and a half, but I have hope for them truely delivering on the transformative promise of behavioral science for behaviors that matter.

My second thought is much more speculative but also I think has even more potential. The advancements in the Cultural Evolution (CE) space over the past twenty years or so have been really underappreciated by those hoping to translate science into practice. I think CE has the potential for transforming behavioral science from a laundry list of biases into a unified theory, one which is already giving insights highly applicable to practitioners. A focus area for my team over the next few years will be translating some of these insights, such as those on optimal targeting within a social network and social norm diffusion and stabilization, into applied tools for the field.

If you had the power to instill one sustainable habit in every person overnight, what would it be and why?

ET: Many sustainability focused behaviors are most appropriate for some subset of the population, so that wouldn’t be applicable for everyone. That being said, one which breaks that mold is sustainable diets, particularly reducing our meat consumption. Ours and others research finds that it is on of the most commonly underappreciated direct impacts we can have, despite it being often both healthier and cheaper than the status-quo.

I will take the liberty of adding a second repeated behavior accessible to everyone in a democracy, which is to regularly engage with your elected representatives on the environmental issues that matter to you. Politicians keep a surprisingly close watch on the support or backlash they receive from their constituencies, yet they receive very little input on the vast majority of high-impact legislation. If you live in the United States, you might consider downloading the Climate Action Now app, which will give you an easy path to engaging your elected representatives tailored to your specific geography and the opportunities where your voice could have the most impact.

Bonus Question: There are a lot of films and TV shows trying to depict the consequences of neglecting our climate. Do you have a favorite one?

I am excited to see climate coming into focus on screen! To take this in a perhaps surprising direction, I think a climate film worth watching and sharing is the 2022 How to Blow Up a Pipeline. First off, it was a pretty well-made film (as of right now, it has a 95% on Rotten Tomatoes). But second, the social and behavioral science angle on its impact is both nuanced and interesting. Radical action does not necessarily engender support for that radical action. In fact, there have been many instances where it does the opposite. But the more holistic social science perspective requires you to zoom out a bit to see how this sort of depiction can affect a broader set of views and behaviors. Through this broader lens, this sort of depiction has the opportunity for impact through what researchers have called the Radical Flank Effect, where observing radical action can increase support for moderate approaches. For example, previous research has found that radical campaigns by organizations like Just Stop Oil have increased support for more moderate organizations and policies, likely by shifting the discourse window. I think that narrative fiction has an incredible opportunity to establish that window, and I look forward to more depictions that seize that opportunity to drive support for highly impact action.

Thank you so much Eric, for sharing your insights. If you want to connect with Eric, you can find him on LinkedIn.

Green Decisions: Sustainability & Behavioral Science was originally published in Behavioral Design Hub on Medium, where people are continuing the conversation by highlighting and responding to this story.

A curated selection of podcasts to help you learn how human behaviors drive sustainability.

Imagine learning about valuable behavior change concepts in a fun and easy way from a mix of experts with exciting perspectives. Sounds too good to be true? Enter: Habit Weekly PodCourses.

We curate our favorite behavioral science podcasts into insightful playlists. The fourth part of our PodCourses focuses on the future forward topic of sustainability.

Is it enough to toss a soda can in the recycling? Why do we think of images like polar bears and melting glaciers when thinking about the climate crisis? How can we create a sustainable future that is both authentic and profitable? Learn the answers to these questions and so much more!

You can listen to the Full PodCourse on Spotify here, or you can browse the selection of podcast episodes below.

Now, time to get listening — Enjoy! 🎧

— April English

Missed the first three parts of our PodCourse series? Check them out below.

• Habits 101— Your Curated PodCourse
• Emotions 101 — Your Curated PodCourse
• Personality 101 — Your Curated PodCourse

Part 1: Level One — Individual and Community Factors

Is Nudging Enough?

In the “No Stupid Questions” podcast episode, Angela Duckworth and Maria Konnikova underscore the ongoing debate within the behavioral science community about the efficacy of nudges versus more empowering strategies like boosts, suggesting that a combination of both might be necessary to foster meaningful change in behavior.

SBC in the Planetary Crisis

From the minds at UNICEF and Common Thread, this podcast highlights several success stories and potential applications, demonstrating how Social Behavior Change (SBCs) can empower people to take action against the planetary crisis at a grassroots level.

Net Zero as the Easy Option

New research in Behavioural Insights Team (BIT) new report How to build a Net Zero society, finds that most people find it hard to make more sustainable choices in their own lives, despite 9 in 10 wanting to do so. This episode features BIT’s Head of Sustainability, Toby Park, and Andrew Schein and Izzy Brennan from the team discussing how to close this gap between public appetite and available opionts.

The Real Psychology Behind Why We Make Environmental Changes

In this episode, Professor Florian Kaiser explains the deeper nuances of how attitude drives behavior from his research into The Campbell Effect. His insights illustrate that we can’t short-change the development of a person’s deeper environmental attitude and jump straight to simple behavioral incentives if we want to achieve deep and permanent social change.

Part 2: Level Two — Communication

Does Climate Change Have an ‘Image Problem’?

A limited set of images have come to dominate how we think of climate change — like polar bears and melting glaciers — which haven’t kept up with the changing conversation about the crisis. How can we develop a new, and more effective visual language for climate change? What kind of images ‘work’ to both convey the urgency of the crisis as well as inspire behavioural change? All of this and more, with host Neal Razzell.

Transport Your Thinking; Why We Need to Reframe Travel

As we become increasingly aware of the way our travel decisions affect climate change, how can behavioral science positively impact the journeys we make? Dive in, with guests Roy Sutherland and Pete Dyson.

The Climate Paradox

In this episode, psychologist Per Espen Stoknes, discusses his book: What We Think About When We Try Not to Think About Global Warming. His book presents a series of psychology-based steps designed to painlessly change people’s minds and avoid the common mistakes scientists tend to make when explaining climate change to laypeople.

Keeping Cool in the Face of Eco-Anxiety

Britt Wray, author of Generation Dread and a Human and Planetary Health Fellow at Stanford University and the London School of Hygiene and Tropical Medicine, talks about her work around eco-anxiety, the reasons and extent to which different people feel it, and the tools people can deploy to harness it and achieve positive, climate-friendly outcomes.

Part 3: Level Three — A Deep Dive

Applying Behavior Science for Conservation

Erik Thulin discusses the relationship between applied conservation work and behavioral science and research in academia, the role and challenges of behaviorally-oriented policy panaceas, Erik’s own findings on the importance of social influence in directing behavior, and the role that emotions play in behavior change. Erik is Behavioral Science Director at Rare, an NGO dedicated to employing behavioral and social change for the benefit of the environment.

Carbon Accounting and Climate Change

Kristian Rönn is the CEO and Co-founder of Normative. In this episode Kristian talks about the differences between net zero and carbon neutral, carbon offsets, carbon accounting, ton-year accounting, greenwashing, the impact of AI on carbon accounting, and many more topics.

Saving Peru’s Environment One Nudge at a Time with BE OEFA

The Brainy Business dives in with guests, Karina Montes and Mario Drago, to discuss their work with BE OEFA in Peru. OEFA is the environmental enforcement agency in Peru, and BE OEFA is the nudge unit Karina created to test the incorporation of behavioral economics into their work.

Can Behavioral Science Help Purpose-Driven Brands Drive Sustainability Action?

In this episode, Jonathan Hall is joined by Alex Peters, Global Purpose Insights Lead at Reckitt and Dr. Nicki Morley, Head of Behavioural Science and Innovation at Kantar UK, to discuss the importance of authenticity in sustainability and how it can be achieved through purpose and a focus on driving real action through behaviour change.

Behavior Mapping for Climate Action

If you’re interested in influencing humans to take action for the climate — say hello to behavior mapping. Host Katie Patrick, put 96 techniques together in her custom Behavior Mapping Template, and in this episode Katie takes you through a short tutorial on her custom mapping process for climate action.

Habit Weekly is the top behavior design newsletter packed with the best articles, videos, podcasts, and exclusive premium content from the world of behavioral science and business. Get smarter about habits and behavioral design, effortlessly.

Habit Weekly

Sustainability 101 — Your Curated PodCourse was originally published in Behavioral Design Hub on Medium, where people are continuing the conversation by highlighting and responding to this story.

Have you noticed how the world is becoming more engaging? Everything from apps that keep you using a little too long to marketing that makes you feel a vital need to purchase something seems designed to get you to act. Even the latest city policies seem designed to get you to act; my parking ticket gave me a discount if I paid within 48 hours. That is behavioral science at work, quietly orchestrating us from the wings of businesses and government offices alike.

This field isn’t just a background player; it’s becoming a commonly referenced piece.

This field isn’t just a background player; it’s becoming a commonly referenced piece. Product teams drop terms like BJ Fogg’s B=MAP Model or the Habit Loop into everyday convo. Policymakers nod to the triumphs of outfits like the Behavioral Insights Team and Ideas42. Marketers naturally embed aspects of scarcity and loss aversion as if it were required. The commonality of all this is considerable progress, yet the field is still developing and is facing both considerable potential and significant setbacks.

My journey with behavioral science kicked off over a decade ago, long before it hit the mainstream. Back then, it was a quirky side note beside the towering legacies of Daniel Kahneman and Amos Tversky. A few companies were trying to replicate the successes of the Behavioral Insights Team in various settings, but if you were to mention Behavioral Sciences, only some thought of anything outside of therapy.

I remember my own ‘a-ha’ moment, reading Nudge as an undergrad. I was about to dive into a consulting gig armed with all the classic change theories you could think of. Yet, this book told me about minor tweaks that could lead to massive shifts. It was a game-changer. Behavioral science to change management felt like agile was to waterfall in software development — an outright revolution.

I couldn’t stop talking about it. I was all in, evangelizing to anyone who’d listen (and even those who wouldn’t). Most nodded politely but couldn’t see it as a career. They thought it was more akin to therapy than a professional pathway. Undeterred, I abandoned the consulting track and plunged into a master’s program. By the time I landed a role at Microsoft, pioneering their behavioral research, the field was just starting to ripple through the mainstream.

Behavioral science to change management felt like agile was to waterfall in software development — an outright revolution.

Now, it’s a different story. Mention behavioral science in most professional circles, and you’ll get nods of recognition — whether it’s about dieting hacks, habit formation, or even that pesky hotel booking pop-up warning you that “15 people are looking at this property right now!” It’s in the media, with celebs like Richard Thaler popping up in films like The Big Short. Yet, despite its growth and glamour, behavioral science struggles to carve out a standalone department akin to user research or data science.

Since my master’s, I’ve held various roles with a “behavioral” title. If I had stayed put, my team’s focus might have shifted from pure behavioral science to product analytics. The other role? Axed in layoffs, wiping out the company’s commitment to behavioral science overnight. In job hunts since, I’ve found it smoother to market myself as a user researcher or product developer with a niche in behavioral science. It reflects a broader trend — a field in flux, still finding its footing.

A decade in, it’s clear: behavioral science has its ups and downs, but it’s here to stay. The challenge now? Building a robust pathway that turns raw enthusiasm into structured expertise. I’m on that path, along with hundreds of others, crafting a future for this field that’s as impactful as it is intriguing. What that future looks like is still up in the air, but one thing’s for sure — it will be a fascinating journey for those who choose to participate.

Trends Over this Past Decade

Over the last decade, I’ve watched certain trends in applied behavioral science not just emerge but firmly take hold. The most striking trend? A steady surge in general awareness and understanding of behavioral techniques. A quick look at Google searches for “What is behavioral science?” illustrates this beautifully — a modest climb from 2013 to 2022, followed by a sharp uptick. This pattern mirrors my own observations of how companies have increasingly engaged with the field in recent years.

Initially, behavioral science was the playground of niche researchers and those curious about its application within organizational frameworks. However, a significant shift occurred in the past two to three years as industries awakened to the potential of enhancing nearly any product with a sprinkle of behavioral science. Today, it’s a topic of conversation across various domains, with numerous subfields exploring ways to integrate these techniques into their workflows. This blossoming interest is undoubtedly a boon for the field, yet it brings with it the risk that the voices of those with deep expertise might be lost amidst the cacophony of newcomers eager to apply their fragmentary understanding.

The spike in interest around late 2021 and early 2022 could be attributed to a less encouraging reason — the replication crisis that shook the foundations of applied behavioral science. The controversy surrounding the celebrated professor Dan Ariely and allegations of fraudulent data brought a wave of attention to the field, though not all of it welcome. This moment in the spotlight drew people’s focus to how research might be influencing their lives, not always under the best circumstances. While this doesn’t spell doom for the field, it certainly highlights the need to clarify misconceptions and establish trust with those newly acquainted with behavioral science.

As we move forward, the task remains to channel this burgeoning interest into meaningful and well-founded applications that can withstand the rigors of both scientific scrutiny and practical utility.

These trends, both uplifting and challenging, map the complex landscape we navigate today. They underscore the growing relevance of behavioral science in various sectors, even as we grapple with the critical need for integrity and clarity in our research. As we move forward, the task remains to channel this burgeoning interest into meaningful and well-founded applications that can withstand the rigors of both scientific scrutiny and practical utility. This is not just about riding a wave — it’s about steering it wisely to ensure the field continues to thrive and expand responsibly.

Behavioral Interventions Work, but Personalization is Needed

The buzz around behavioral science isn’t just noise — it’s backed by a slew of successes. Think about those classic nudges, like tweaking organ donation defaults to align with people’s actual desires or boosting 401(k) savings through automatic increases tied to salary bumps. These examples aren’t just anecdotes; they’re clear demonstrations of how minor changes can trigger major impacts. And if you’re looking for more evidence, a quick flip through this publication or a scroll on the Behavioral Scientist will flood you with case studies of interventions that have effectively steered behaviors in beneficial directions.

Yet, for every headline-grabbing success, there’s a tale of a high-profile flop, often resulting from the intervention’s inability to replicate or scale effectively. There was even chatter at one point that “nudge is dead!” — a premature eulogy that overlooks a fundamental truth we’ve seen repeatedly across the social sciences: Humans are intricate beings. Our behaviors are too varied and personalized for broad-brush strokes.

To drive behavioral change effectively at scale, personalization isn’t just helpful; it’s essential.

This is where Katy Milkman and her colleagues’ work shines. Their mega studies, which pitch numerous nudges against each other, don’t just unearth the most effective general strategies; they reveal how these approaches resonate differently across various demographics. This is a lesson well understood by data science teams in tech: Different strokes for different folks. To drive behavioral change effectively at scale, personalization isn’t just helpful; it’s essential.

I’ve delved into this topic extensively, and it’s clear that the trend towards personalization isn’t just a phase — it’s the future. The days of one-size-fits-all solutions are waning. Thanks to advancements in Generative AI, the cost of creating targeted, nuanced content is plummeting, paving the way for interventions that can be fine-tuned to the individual level. We’re stepping into an era of hyper-personalized nudges. But, let’s not forget, the effectiveness of these finely tuned strategies will still rely heavily on robust scientific underpinnings — a scenario that bodes well for the demand for behavioral scientists’ expertise moving forward. This isn’t just a shift; it’s a significant leap towards more thoughtful, personalized interventions that could redefine the landscape of behavioral science.

The Role of Behavioral Scientist

When I teamed up with a group of consultants to attempt building a Behavioral Science practice at Deloitte, the idea of calling ourselves Behavioral Scientists seemed a distant dream. As I progressed through my Master’s program, that title became a hopeful emblem for me and my peers, a marker of our aspirations. Post-graduation, as I stepped into the role of Behavioral Researcher, the job market seemed to embrace the term, with ‘Behavioral’ increasingly appearing in job titles. However, by the time I was laid off in 2021, such roles had dwindled dramatically, becoming rare gems in the professional landscape.

My career trajectory mirrors the rise and tempering of enthusiasm for the title of Behavioral Scientist. Initially, the 2010s buzzed with predictions that Behavioral Science might become the new “data scientist” — the hot job of the early decade across various industries. The field seemed poised to explode, drawing in curious minds from every conceivable background, expanding rapidly from a tight-knit group to a diverse and sprawling community.

At one peak, it appeared Behavioral Science could solidify into a department as integral as user research or data science. Yet, reflecting back, this might have been more a symptom of an era flush with zero-interest funding — companies were unusually willing to bet long-term. This surge in interest was exciting, yet it underscored a pivotal shift needed in our field: more effective communication about the practical benefits of applied behavioral science.

The boom brought visibility but also highlighted the field’s nascent infrastructure for cultivating expertise. While a few master’s programs and boot camps sprang up, they couldn’t possibly meet the burgeoning demand. Many enthusiasts were left to forge their own paths into the field, some successfully applying rigorous science, others unfortunately veering towards pseudoscience without a solid academic foundation. This muddied the waters of what constitutes credible behavioral science, leaving companies often needing to lean on expensive consultants to build in-house expertise.

Today, the field is populated by a small elite with deep experience, supported by fresh graduates from leading programs, and a larger group dabbling in behavioral science without much formal training. This disparity contributes to companies’ hesitancy to invest in behavioral science roles — they’re unsure of what they really need and if it’s attainable.

In response, I advocate viewing behavioral science more as a “minor” than a “major” — a supplementary skill rather than the sole focus. We’re seeing the rise of behavioral designers: professionals trained in traditional design who enhance their craft with a nuanced understanding of human behavior. This integration creates superior products and more impactful user experiences.

For every dedicated individual striving to earn the title of Behavioral Scientist, many more could benefit from integrating behavioral insights into their primary careers. This approach not only secures more stable career paths but also broadens the impact of behavioral science. My vision involves a few critical architects of behavioral science within organizations, surrounded by teams that incorporate fundamental behavioral insights into their work. This model leverages a core of expertise to inform and elevate a broad range of professional practices, ensuring that the transformative potential of behavioral science is fully realized across industries.

Behavioral Science Products

The past decade has brought us a tale of two outcomes for companies steeped in behavioral science. Let’s start with the poster child for success: OPower. This company harnessed the power of social norms to encourage better energy use, sending homeowners simple notifications on how their consumption stacked up against the neighborhood. This strategy not only celebrated the energy-efficient but also nudged the rest towards greener habits. OPower’s approach was so effective that Oracle snapped it up for a cool $532 million back in 2016.

But the journey hasn’t been rosy for all. Take Humu, a software-as-a-service company designed to foster organizational change. Despite high-profile backing and leadership, Humu struggled and was eventually sold off quietly in 2023 after its founders left. Lemonade, another firm endorsed by top scientists, also experienced a brief heyday as a market favorite before it tumbled alongside many tech peers.

What’s the key to success or failure here? It boils down to whether outcomes can be readily measured. Sectors like finance, health, and consumer goods, where the effects of interventions are easily quantifiable, provide fertile ground for behavioral techniques. Curious about which companies are serious about behavioral science? Look up the ones with chief behavioral officers — that’ll give you a clue.

However, many firms find it tough to integrate behavior-focused metrics alongside their product usage stats, often defaulting to the simpler, more traditional measures of success. This hesitancy can stifle the development of truly innovative behavioral science-infused products. To combat this, I’m penning a book on how I’ve managed to implement these principles across various industries. But until this mindset becomes more widespread, many will stick to what they know: usage and usability as their benchmarks.

I envision a future where behavioral science isn’t just a tool for crafting standalone products but is an integral part of the product development life cycle.

I’m optimistic, though, that we’re on the cusp of a shift. I envision a future where behavioral science isn’t just a tool for crafting standalone products but is an integral part of the product development life cycle. This evolution will likely be driven by the rise of ‘behavioral science minors’ — professionals in development, design, and sales who bring behavioral savvy to their primary roles. As more consulting firms in this space move beyond one-off projects to foster deeper cultural shifts in the companies they assist, we’ll see this integrative approach take hold, transforming how products are conceptualized, developed, and sold. It’s a future where behavioral science is baked into the DNA of product creation, enriching the landscape of innovation.

Academic and Applied Divide

When I helped kickstart the organization that would evolve into the Applied Behavioral Science Association, the gap between academia and real-world application was vast. Academics were ensconced in theory while practitioners hustled in the trenches of organizational behavior. Bridging these worlds, I collaborated with many sharp minds, marrying rigorous academic methods with the nimble, pragmatic approach needed in business. Although not without its debates, this cross-pollination taught us to appreciate and respect our differing viewpoints.

Over the past five years, this divide has noticeably narrowed. Academics are now embracing large-scale nudge studies reminiscent of those in corporate settings, and corporate behavioral scientists are championing the cause of rigorous, methodical experimentation. This convergence has facilitated smoother collaborations between scholars and businesses, enhancing the quality of science executed in both realms. Today, it’s not unusual to find consulting firms teeming with PhDs who toggle between consulting and lecturing, or startups like Noom and BetterUp that leverage rigorous academic studies to validate their products’ effectiveness.

However, this blend of academic and applied efforts comes at a price. As more businesses engage with academic institutions, there’s an increased risk of obfuscation and potential suppression of negative outcomes. Several high-profile incidents have cast shadows over the achievements of the past decade, questioning the integrity of collaborative efforts. The fusion of academic and applied realms, while productive, also opens doors to questionable practices.

Despite these challenges, I remain hopeful about the potential of these collaborations. My vision for the future includes a balanced approach where academics can pursue pure research that advances the field without the constant pressure to commercialize findings. Ideally, this research will continue to inform and elevate applied practices, ensuring that both sectors can thrive without compromising the integrity and pioneering spirit of behavioral science.

A Pipeline for the Next Decade

As we look to the future of behavioral science over the next decade, I see three critical areas where we need to focus our efforts: expanding the supply of behavioral science skills, increasing demand for these skills across all industries, and cultivating more thought leaders to tackle the challenges I’ve outlined.

From my repeated efforts to get the Applied Behavioral Science Association off the ground, I’ve come to understand that the most pressing need in our field is a robust pipeline. This system would guide those intrigued by behavioral science — helping them decide whether to dive in fully or integrate these skills into another career path — and provide the necessary educational framework. This pipeline would transcend the limitations of current advanced degrees and boot camps, finally scaling the development of behavioral science capabilities to meet growing demand.

When I mention a “pipeline,” you might wonder what I’m really talking about. Consider how one typically becomes a behavioral scientist today; you’ll likely hear many personal stories. Now, think about the career paths for accountants or lawyers — careers with clearly defined routes from education to certification. We need a similar structure in behavioral science. Universities and related organizations should create programs that guide students through the necessary training, culminating in certification and readying them to enter the field fully equipped.

While I’ll save the nitty-gritty of building such a pipeline for another discussion, imagine it including accessible certification, cost-effective educational programs, and a wealth of case studies and resources that outline what working in behavioral science really entails. It should provide a clear path from initial interest to professional integration.

Establishing this pipeline will not only increase the supply of trained professionals but also boost demand for these skills. Currently, organizations interested in behavioral science can choose from a myriad of consultants, each promoting their unique approach. This fragmentation makes it tough for companies to understand what they really need. A standardized pipeline would clarify the capabilities of an applied behavioral scientist, helping organizations shape their strategies around solid expectations.

The final ingredient for success is a new generation of thought leaders. Over the past decade, we’ve seen brilliant minds emerge, applying behavioral science to finance, health, and tech. These pioneers must continue their work, but we also need fresh voices — early career professionals like I was, brimming with innovative ideas and eager to share them.

Turning applied behavioral science from a burgeoning field into a well-established discipline requires this developmental pipeline. I’ve attempted to contribute to this effort with some success, as have others. Moving forward, I remain committed to refining and advancing this initiative, eager to see the diverse and transformative approaches the next wave of behavioral scientists will bring to the table.

Concluding Reflection

I vividly recall the moment I told my parents and friends about my decision to leave a secure consulting job to pursue a master’s in this exciting, uncharted field called behavioral science. Most advised against it, cautioning me of the risks. Looking back, I’m so glad I followed my gut — it’s been a whirlwind decade filled with incredible opportunities and eye-opening experiences. Yet, whenever someone asks how they can emulate my path, I find myself hesitating. The landscape has shifted since I first stepped into the field during its rapid ascent; the same opportunities that were available to me in that nascent stage might not be as accessible now.

The field of behavioral science is undoubtedly in a state of evolution, wrestling with its identity and the scope of its application within organizations. With advancements in artificial intelligence and increasing capabilities for personalization, the potential for behavioral science to make a significant impact has never been greater. However, we’re still searching for a cohesive narrative and a unified approach that can clearly articulate and guide this potential.

Despite these challenges, I’m optimistic. The passion and enthusiasm among those in the field are palpable. The Applied Behavioral Science Association, despite its fluctuating membership as we experiment with its direction, continues to attract those eager to shape the future of this discipline. If you share this vision or have thoughts on how we can collectively advance our field, I would love to connect and discuss further. Feel free to reach out on LinkedIn — let’s keep the conversation going and build on the exciting possibilities that lie ahead.

Connor Joyce is a behavioral science evangelist in writing, speaking, and community building. If you are interested in connecting with him, reach out on LinkedIn!

My Decade with Applied Behavioral Science was originally published in Behavioral Design Hub on Medium, where people are continuing the conversation by highlighting and responding to this story.

The study of the mind, brain, and behaviour (i.e., psychology) has fascinated researchers and the general public for hundreds of years. Perhaps one of the sexiest (in my opinion), and one of the most undiscovered, subfields of this area involves neuroscience, which focuses on the brain, nervous system, and cognitive functioning. With the advent of neuroimaging techniques, like functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and positron emission tomography (PET), neuroscientists allowed us to take a glance into the magical human brain and show us how it actually works. The coolness factor of neuroscience has even led to an entire field of marketing, known as neuromarketing, which studies how people’s brains respond to advertising, packaged goods, and brand-related messages. However, with so many unknowns and answers to be discovered, pop psychology fans (and nonscientists who think they are experts in the field) have taken it upon themselves to assume how the brain works without any concrete evidence to support (or sometimes deny) their statements. Below are some of these myths (and I’m sure there are more), that we should all stop repeating.

1. System 1 and System 2 are distinct regions of the brain that explain cognitive processing and behaviour — FALSE

There is no such thing as a dedicated and independent System 1 and System 2 region of the brain. This theory is based on Daniel Kahneman’s book, Thinking, Fast and Slow, but this dual system theory of cognitive processing lacks any strong empirical evidence, and many articles have been written on the rejection of the concept since it is fraught with errors. In fact, Kahneman himself even mentioned that the two systems are meant to be used as metaphors and that there are no distinct regions in the brain functioning in this manner. (This one fact alone just demonstrates how many people haven’t actually read Kahenman’s book, but still repeat the theory in a broken telephone manner.) Just because a decision-making process is “fast” or “slow” does not inherently mean it is being executed by one system or the other, since personal experience, learning, and heuristics influence all systems of thinking. The brain is a sophisticated and integrated network, which functions holistically across its 86 billion (give or take ~8 billion) neurons to perform various behaviours, regardless of whether the behaviour is implicit, explicit, conscious, or subconscious. The neurons of the brain communicate constantly with each other through all types of “fast” and “slow” cognitive processes and behaviours.

2. The brain is region-specific and different behaviours are controlled by specific brain areas — FALSE

Similar to the explanation above, the brain is an integrated network of many regions and neurons that rarely act independent of each other. There is not a one-to-one mapping between a function or behaviour and a specific location in the brain. Although there are specific regions of the brain that may be more sensitive to certain functions or behaviours, many other brain regions are usually activated as well during this process.

3. 95% of all decisions are subconscious — FALSE

There is no quantifiable empirical evidence to show that a precise proportion of “all decisions” are 95% subconscious. There are slightly different worded versions of this myth, including, “95% of our behaviours are not conscious”, “95 percent of brain activity is unconscious”, and “95% of purchasing decisions are subconscious”. There is some obsession with the number “95%”, and this myth is one of the most falsely quoted statements in neuromarketing and neuroscience in general.

It is virtually impossible to determine exactly how much of every decision under every circumstance in every possible situation is proportionally based on conscious and subconscious cognitive processing.

There is no scientific data to reference this statement, and it would be extremely difficult to accurately measure the exact proportion of conscious or subconscious decisions humans make in a day. It is possible that many decisions are made subconsciously, but it is virtually impossible to determine exactly how much of every decision under every circumstance in every possible situation is proportionally based on conscious and subconscious cognitive processing.

4. We make 35,000 (or any other number of) decisions a day — FALSE

Similar to the myth above, there is no quantifiable empirical evidence to show that we make any specific amount of decisions per day. Daily decisions can be conscious or subconscious, and depending on the person and the complexity of their daily life, decisions can be made on any number of topics (e.g., work, health, food, children, family, driving, vacation, sex, movies, etc.). Furthermore, it is extremely difficult to accurately calculate the amount of decisions humans make in a day since many of those decisions could be forgotten or misremembered. Of course, we are capable of making thousands of decisions a day, but to state an exact number would be to falsely generalize human behaviour.

5. We only use 10% of our brains — FALSE

We use 100% of our brains, and many neuroimaging studies will demonstrate that any given cognitive task or behaviour can excite many different regions of the brain. We may not use 100% of our brains simultaneously for a given behaviour, but across all possible human behaviours and cognitive processes, all regions of our brains may be used. In fact, one MythBusters episode debunked this myth by showing that we use more than 10% of our brains during even the simplest processes such as resting with closed eyes.

6. Some people are “left-brained” while others are “right-brained”– FALSE

There is no scientific evidence for the notion that there are left-brain dominant individuals, who are logical, analytical, and mathematical, and right-brain dominant individuals, who are spontaneous, creative, and artistic. Again, the brain functions holistically as a single (complex) unit across its ~80–90 billion neurons to process all types of tasks. There is no one dominant hemisphere that overrides the majority of one’s behaviour, or elicits a specific type of personality or thinking in an individual.

7. Male and female brains have different structures and functionalities — FALSE

There is no such thing as “male brains” and “female brains”. Overall, there are no major differences between male and female brains in terms of patterns of connectivity or amount of grey or white matter.

There are more unique individual differences within each sex than between sexes, and all brains are more alike than they are different.

Even if there are studies that show some average structural brain differences between sexes, there are more unique individual differences within each sex than between sexes, and all brains are more alike than they are different. Additionally, sex differences in brain structure can be due to a number of reasons, including overall body differences between men and women in general, so these studies cannot infer anything about how these differences relate to behaviour or brain function.

8. Humans have an ancient “reptilian brain” underneath the neocortex that controls our subconscious and immediate emotional reactions toward stimuli — FALSE

This idea, also known as the Triune brain model, states that human evolution developed a brain circuitry that started with the reptilian layer, followed by the limbic and neocortex layers. The correct view of human evolution is that animals did not linearly increase in complexity, but instead evolved from common ancestors. Similarly, brains in all vertebrates evolved to possess the same basic brain regions of the forebrain, midbrain, and hindbrain. The brain works together as a sophisticated network; there is no one single layer that overrides another during cognitive processing or behaviour execution.

9. The brain processes images 60,000 times faster than it does text — FALSE

This myth is rampant across the internet, yet has absolutely no scientific origin. Think about this statement for a moment using a concrete example: let us say that it takes exactly 1 second to process a certain image; if we multiply this number by 60,000, then it would take nearly 17 hours to process text! Does that even make logical sense? Now it is true that in some contexts, a picture may be processed faster than words, for example, if we compare a simple, small image to a paragraph of words. However, this statement does not even make sense to compare because how it does not consider the size or complexity of the image or text. Thus, it is incorrect to make any general statements that images are processed faster than text because this is just not an equal comparison from a methodology standpoint.

10. Humans have the same attention span as goldfish, about 8 seconds — FALSE

Some of these myths even go as far as to say that humans have a smaller attention span than goldfish, or that humans’ attention spans have been shrinking over the years. However, if humans’ attention spans are only about 8 seconds, then how is it possible to do anything longer than 8 seconds? If our attention spans are so short, it would be impossible to watch a movie, play video games, write a novel, or drive a car, all for hours on end. Even more interesting, research has shown that goldfish can have memories for several weeks, as shown by another fun episode of MythBusters. So, let’s stop giving humans, and goldfish, such a bad reputation for having small attention spans.

11. The brain can process 11 million bits of information per second through unconscious processing, but only 50 bits per second through conscious processing — FALSE

First of all, WTF is a “bit” of information? How do you quantify that? It’s virtually impossible to measure all of the information that is received by the brain through independent conscious and nonconscious routes. Related to the points above, the brain is a vastly interconnected web of neurons with both conscious and nonconscious processing that occurs simultaneously every waking moment. The fact that anybody tried to quantify perceived environmental data with ambiguous units is sheer rubbish.

12. Each person has a unique learning style, with some being visual-, auditory-, or kinesthetic- (tactile) learners — FALSE

Learning styles are a myth. There is no empirical justification to tailor different types of instructions to different students based on different types of learning modalities. Instead, most people generally learn efficiently through a combination of multiple sensory representations of information, which can enhance memory and understanding of all forms of material.

13. The more specialized a behaviour, the more neurons in the brain are used and allocated for that behaviour — FALSE

It is counterintuitive to think of a specialized form of behaviour as having fewer neurons dedicated to its execution. However, through a process called synaptic plasticity, our brains selectively prune other neurons that would otherwise cause interference or inhibition with a more direct and focused neuronal pathway to perform the specialized behaviour. For example, research has shown that expert athletes have less neuronal activity (i.e., more neural efficiency) in brain regions associated with those athletic behaviours, compared to non-experts.

14. Brain damage is always permanent — FALSE

This is somewhat related to the myth that the brain stops developing once you reach a certain age, which is also false. Neuroplasticity enables different connections across various regions of the brain during all types of development. For example, if someone suffers a serious brain injury, the brain will usually find alternative routes to function with undamaged neural pathways.

15. Neuroscience answers “why” people perform certain behaviours — FALSE

Neuroscience techniques can only reliably answer “how” people behave or process information, but they should never answer “why” people behave the way they do.

Neuroscience techniques can only reliably answer “how” people behave or process information, but they should never answer “why” people behave the way they do. For example, if a neuroscience tool, such as skin conductance response, demonstrates physiological arousal when someone is watching a movie, we cannot assume that the person is either excited, scared, surprised, or anxious, because many different stimuli may cause the exact same arousal levels. The question of “why” people perform certain behaviours or feel a certain way may only be asked using more explicit-based questionnaire techniques.

16. Implicit measures of behaviour are better than explicit measures of behaviour — FALSE

To date, some of the most common, reliable, and valid measures of behaviour/personality/attitudes are based on explicit self-report questionnaires because they are the only measures that can provide depth and reasoning into how people feel about the world.

There is a time and place for all forms of implicit and explicit measurement. Implicit measures are used to assess behaviour that is below the awareness of the participant (e.g., how long it takes to solve a puzzle, or how someone’s brain is reacting to a picture). It is used to examine subconscious behaviour as well as preconceived attitudes and bias toward stimuli without the participant knowing the purpose of the study. This contrasts with explicit measurement, in which participants are asked directly about their attitudes and feelings about stimuli and behaviour. To date, some of the most common, reliable, and valid measures of behaviour/personality/attitudes are based on explicit self-report questionnaires because they are the only measures that can provide depth and reasoning into how people feel about the world.

17. Implicit measures always assess fast/quick responses, while explicit measures always assess slow/methodical responses — FALSE

Implicit measures can also be “slow”, and explicit measures can also be “fast”. For example, response times measured from an implicit cognitive task (e.g., the time it takes to solve a game of Where’s Waldo), may take several seconds or minutes, or hours to complete, even though the participant is unaware of any difference in their behavioural performance. Alternatively, explicit responses given by a participant on how they feel about a certain stimulus may take less than a second to verbally express their emotion, even though the participant is fully consciously aware of their decision.

18. Qualitative measures capture better in-depth understanding than quantitative measures — FALSE

Qualitative (i.e., open-ended discussion-based) metrics offer initial insight into a theory and can be used to better interpret quantitative findings. However, the most reliable and valid metrics for any type of attitudinal, emotional, or behavioural context are derived from standardized forms of measurement based on quantitative, empirical data. Asking one-off questions to small samples of individuals based on subjective intuition rarely results in reliable or valid findings that generalize to a population. Even gaining data from small samples of participants can be improved by using standardized measures with coded responses to evaluate a consistent scale across participants.

19. What people say and what people do are drastically different — FALSE

It is true that sometimes what people say and do are different, but it would be untrue to make this general claim for all forms of behaviour. Sometimes, there is a very consistent relationship between what people say and what people do (e.g., a self-proclaimed Apple computer lover may consistently and exclusively buy Apple brand products).

20. Neuroimaging tools, like EEG and fMRI measure human emotions — FALSE

EEG is used for measuring the timing of cognitive processes, while fMRI measures the functional connectivity of brain regions that are most sensitive to specific cognitive processes. Both techniques can infer participant arousal, attention, engagement, and motivation, which may be connected to correlational research with other questionnaire-based data. However, we can never understand how someone is “feeling” using these tools, because they are not used for measuring “emotions”, which are subjective constructs. Neuroimaging tools allow us to understand how the brain responds to specific stimuli, as an indirect approach to map cognitive and functional brain processing. However, emotions can only be evaluated using explicit self-report measures.

21. EEG can be used to measure real-life situations, such as walking and shopping through a store — FALSE

The brain has billions of neurons, and every time a behaviour is performed (e.g., looking, breathing, thinking, talking, chewing, reading, walking, writing, etc.), some of those neurons fire. When those neurons fire, they cause an electrochemical signal to pass on to the next neuron, and so on. During this neuronal activity, some of that electricity gets passed outside of the neural cell, through the other regions of the brain, and eventually through the skull, where those electrical signals (usually measured in millivolts) can be measured at the scalp. These electrical brain waves are what EEG measures. Because EEG is extremely sensitive to any of these brainwaves, it is crucial that participants should not be moving, chewing, talking, blinking, or moving their eyes throughout any study task, because these signals will cause artifacts in the data and alter the proper signal to measure (e.g., how the brain reacts to viewing a certain stimulus). Thus, participants should be resting or seated in a chair viewing a monitor, rather than walking around a room (even though it looks cooler for neuromarketing studies). In other words, if someone is walking around a room while wearing an EEG headset, the measurement is most likely to detect noisy signals from movement alone rather than how that person’s brain is responding to their environment.

22. EEG measures the location of where in the brain cognitive processes are happening — FALSE

EEG is very accurate at measuring temporal information (i.e. when a cognitive process occurs); however, it is not accurate at measuring spatial information (i.e., where a cognitive process occurs in the brain, which is the specialty of fMRI). EEG measures the summed electrical potential of cognitive processes at the scalp, but that signal could have originated from multiple areas at different regions within the brain. For example, a brain wave that is measured at the back of the scalp could have potentially originated from the front of the brain, but that brain wave was simply maximal at the posterior area of the scalp.

23. Small differences in reaction times (e.g., in the range of milliseconds) for different cognitive task conditions are not meaningful differences in real life — FALSE

When dealing with cognitive tasks, a 20–50 ms difference between conditions can have a very meaningful difference in understanding brain processing.

Since the connections of cognitive processes are so fast, a small difference can mean a large difference in brain functioning.

A difference this small may not seem like anything special since it takes more than double or triple that time to blink one’s eyes. However, neurons in the brain can fire at speeds of up to 120 m/s (270 mph). Since the connections of cognitive processes are so fast, a small difference can mean a large difference in brain functioning. As an analogy, when running a marathon, the difference between the first place and second place runner might be several minutes, which makes sense since the race is so long, and the runners are not moving very fast; however, in a 100 m sprint, the difference between the first place and second place runner might be less than a hundredth of a second since the runners are moving so fast over such a small distance. It would be difficult to argue that the difference between first place and second place in the sprint was essentially the “same” and not meaningful. This is because each runner ran their fastest and a slight edge could mean the difference between gold and silver medals.

24. Human memory is highly accurate, especially when participants are confident in their responses — FALSE

Human memory is very prone to error since our brains typically fill in gaps and alter previously encoded memories with new memories and different contexts continually. Even so-called “flashbulb memories” (i.e., detailed/vivid memories stored from specific occasions, usually associated with important historical or autobiographical events) are prone to inaccuracies. Furthermore, it does not matter how confident a person is when recalling specific memories since humans can be brainwashed by their own new experiences over time.

25. Humans are irrational beings, acting completely out of erroneous emotion, rather than logical cognition — FALSE

If we had to consciously think about every waking moment of our lives, we wouldn’t be able to focus on any number of more important things in life.

There is a perception that humans are mindless, happy-go-lucky, beings with no rational perception of their world. Some examples supporting this notion are when people don’t save enough money for retirement, or when they eat unhealthy foods. However, these “irrational” behaviours may not be irrational at all. For example, many individuals simply cannot afford to save money for an unknown future that can have unpredictable events decades from now, when it is difficult enough to focus on the necessities of today; the same goes for eating unhealthy foods, since the pleasure of eating a donut today outweighs a possibly healthier future, since you may get hit by a bus tomorrow. Additionally, if humans were so irrational, then we wouldn’t be able to put a man on the moon or accomplish the numerous other incredible achievements in history. Second, using “irrational” heuristics in everyday life can be quite advantageous, including all of our (sometimes incorrect) biases of decision-making. If we had to consciously think about every waking moment of our lives (e.g., what to eat, how to walk, etc.), then we wouldn’t be able to focus on any number of more important things in life.

Adam is a seasoned researcher with extensive academic training and hands-on experience in various scientific methodologies. Specializing in human factors studies, Adam applies his expertise to drive advancements in both research and commercial applications across diverse market sectors. With a PhD in Behavioural and Cognitive Neuroscience Psychology, Adam brings innovative research methodologies and a passion for unraveling human behaviour. Connect with him on LinkedIn to join the conversation!

25 Neuroscience Myths was originally published in Behavioral Design Hub on Medium, where people are continuing the conversation by highlighting and responding to this story.

A curated selection of podcasts to help you learn about the science of personality.

Imagine learning about valuable behavior change concepts in a fun and easy way from a mix of experts with exciting perspectives. Sounds too good to be true? Enter: Habit Weekly PodCourses.

We curate our favorite behavioral science podcasts into insightful playlists. The third part of our PodCourses focuses on the popular topic of personality.

Are personality tests legit? Where do we belong in the personality tribes? What are the superpowers of extroverts and introverts? How do we navigate different types of personalities at work? Learn the answers to these questions and so much more!

You can listen to the Full PodCourse on Spotify here, or you can browse the selection of podcast episodes below.

Time to dive in — Happy listening! 🎧

— April English

Missed the first two parts of our PodCourse series? Check them out below.

• Habits 101— Your Curated PodCourse
• Emotions 101 — Your Curated PodCourse

Part 1: The Science of Personality

Personality Tests: Who Are You Really?

Skeptics argue that personality tests like Myers-Briggs lack credibility, raising questions about their legitimacy. To unravel the truth behind personality assessments, psychologists Dr. Alexander Swan, Dr. Emorie Beck, and Dr. Ted Schwaba offer their insights. Through their expertise, the episode explores what science can truly reveal about personality, shedding light on the reliability and limitations of these tests.

The Personality Myth

Many of us think that our position in life has a lot to do with our personality. Invisibilia examines the concept of personality as destiny in American society.

The Sorting Hat

Hidden Brain delves into the universal desire to find our place in a tribe or community, examining the thriving industry of personality tests, which promise quick insights into who we are and where we belong.

Personality with Sanjay Srivastava

A conversation with renowned personality expert, Dr. Sanjay Srivastava. This conversation promises an engaging listen for anyone fascinated by the science of personality — from the curious curly fry problem to the design and utility of corporate personality tests.

The Psychology of Personality

We round out Part 1 with an insightful David Pizarro, PhD and Tamler Sommers, PhD of the Very Bad Wizards Podcast. We can some final thoughts on questions like; What are the different dimensions of personality that distinguish one person from another? How many dimensions are there — do the Big Five capture all of them? Do we share some of these differences with other species?

Part 2: Understanding Your Own Personality

Adam Grant: Givers and Takers and the Resilient Mind

Are you a giver or a taker? Have you ever struggled to find work/life balance? How do you build resilience in yourself, your team, or your children? Each of these topics and many more are discussed with guest and organizational psychologist, Adam Grant.

Can You Change Your Personality?

Are you the same person you were a decade ago? How fixed is your personality? Learn all about it from No Stupid Questions hosts, Angela Duckworth and Mike Maughan.

Susan Cain: Leading the Quiet Revolution

For decades, society has favored traits like charisma, outspokenness, and self-promotion, leaving introverts feeling pressured to conform to extroverted behavior or retreat further into themselves. However, Susan Cain, argues that both approaches are misguided. As a self-proclaimed introvert and author of the bestselling book “Quiet: The Power of Introverts in a World that Can’t Stop Talking,” Cain believes that introverts have unique contributions to offer when they embrace their authentic selves. Cain discusses how introverts can thrive in a noisy world by staying true to their nature. Whether you identify as an extrovert, introvert, or ambivert, this interview offers valuable insights for all.

The Introvert’s Guide to Extroversion

Dr. Laurie Santos explores research suggesting that introverts have the capacity to learn and cultivate enjoyment from being more outgoing, challenging the notion that they are destined to lead less socially fulfilling lives.

Part 3: Personalities and the Workplace

Can a personality test show if you’re right for a job? With Fred Oswald, PhD

Companies may use assessments such as personality tests as part of the hiring process or in career development programs. Fred Oswald, PhD, director of the Organization and Workforce Laboratory at Rice University, discusses why companies use these tests, what employers and workers can learn from them, and how new technologies, including artificial intelligence, are changing workplace assessments.

Understanding Humans in the Wild

Sam Harris engages in a conversation with Adam Grant, diving into the realm of social science within the workplace. Together, they explore various facets of effective team dynamics, the dynamics of power, personality types, and fundamental styles of interaction. They also touch upon essential skills such as learning to say “no,” fostering creativity, and building resilience. The discussion provides a rich exploration of the complexities of human behavior and organizational dynamics.

How To Handle A Narcissist (Including, Maybe…Yourself)

Joined by Keith Campbell, a seasoned researcher in the field of narcissism for over 30 years, Keith introduces his latest book, “The New Science of Narcissism.” Delving into the nuances between grandiose and vulnerable narcissism, offering insights into navigating relationships with narcissistic individuals. Whether you’re curious about understanding narcissism or seeking strategies for dealing with it, this episode provides valuable insights and actionable tips.

Habit Weekly is the top behavior design newsletter packed with the best articles, videos, podcasts, and exclusive premium content from the world of behavioral science and business. Get smarter about habits and behavioral design, effortlessly.

Habit Weekly

Personality 101 — Your Curated PodCourse was originally published in Behavioral Design Hub on Medium, where people are continuing the conversation by highlighting and responding to this story.

Personality Testing Is All The Buzz — Rightfully So?

Interview with Kajsa Asplund, PhD

Kajsa is a Psychologist, specialising in talent management, she is Lead People Science at Alva Labs where they aid clients in better decision-making with the help of science-based and data-driven solutions. She has also authored a popular book on the topic and is a regular keynote speaker on topics related to industrial and organisational psychology, evidence-based HR, and talent acquisition.

Habit Weekly (HW): What led you to start working with personality tests and assessments, and what initially sparked your interest in this field?

Kajsa Asplund (KA): I first started working with personality tests and other psychometric assessments during my psychology studies at Uppsala University in the early 2010s. I did an internship at an assessment provider and quickly realized the many benefits companies could get from working with scientifically grounded tests for selection, in terms of accuracy, objectivity, and efficiency alike.

I was really fascinated by the fact that many of the most common selection methods were so ineffective in finding the best candidates for the job.

I first became interested in this topic because I was introduced to the vast research that had been conducted on the accuracy and predictive capacity of different selection methods. I was really fascinated by the fact that many of the most common selection methods were so ineffective in finding the best candidates for the job. But also, of course, that there were other methods that were all the more accurate, but less well-spread.

Can you share an example of how personality assessments improved team dynamics and outcomes in recruitment?

KA: I have seen so many cases where personality assessments have helped improve selection processes, particularly when being used at the early stages of selection. When organizations switch from a manual CV screen to an automated personality test screening, they are often stunned by the increase in diversity among candidates that make it to the first interview.

For some reason, however, when something is called a ‘test’ or an ‘assessment’, people sometimes seem to be more prone to see the result as the truth.

From your experience, what are some of the limitations of using personality assessments in hiring decisions?

KA: Like with all selection methods, it’s important to keep in mind that a personality assessment does not paint a complete picture and does not say everything about an individual. There are always more pieces of the puzzle that need to be taken into account.

For some reason, however, when something is called a ‘test’ or an ‘assessment’, people sometimes seem to be more prone to see the result as the truth. What I usually tell organizations is that personality assessments do their best job early on in the selection funnel, to help make the decision on which candidates to move forward to the next stage. Once they get there, interviews and case exercises are examples of methods that will help paint a more nuanced and contextualized image.

How should cultural differences affect the design and use of personality tests?

KA: In today’s globalized world, it is of course very important to cross-validate personality models and — tests in various different cultures, to make sure that they remain reliable and valid across settings. It might, for instance, be important to consider cultural differences in how candidates use response scales. In some cultures, people are more prone to use the extremes (e.g., ‘completely agree’ and ‘don’t agree at all’), whereas in other cultures, candidates might stick more to the mid-points of the scale.

Overall, however, personality assessments have turned out to hold up pretty well against different kinds of cultural biases, which is a clear advantage of this method.

Based on your work and experience, how should the effectiveness of personality assessments be measured, and what indicators should we track?

KA: The most important success indicator of all is accuracy: To what extent is this personality assessment capable of identifying the candidates most suitable for the job?

This requires some work, obviously, but it’s such an important thing to try to capture. The most straight-forward way is to make sure to document how candidates that get hired fare, and then put that in relation to their personality scores.

Secondly, we want to see that the personality assessment produces a fair and objective selection, i.e., that it is not prone to bias or adverse impact against any protected group.

Third and finally, we also want the personality assessment to be efficient and ideally result in time saved for the hiring team. If you, for instance, replace a manual CV screen with a personality test at the beginning of the process, there is usually a very substantial increase in efficiency. Manually reading through a large number of CVs and making your selection based on this is not only very subjective, it’s also extremely time-consuming. An automated, digitized personality assessment can save you tons of time while also improving objectivity.

Can you share insights into how your company customizes or tailors personality assessments to align with its unique organizational culture, values, and job requirements?

KA: Needless to say, there is no one right or wrong personality: You always need to consider the specific requirements of the organization, team, and role. At Alva Labs, we use so-called test profiles which represent the ideal scores that we would like to see for the role. These can differ a lot depending on the position and company. Sometimes, companies have certain personality traits that reappear in basically all their profiles, because they consider them key to their culture.

What future trends do you see in personality assessments and recruitment, especially related to the evolving technological landscape?

KA: First and foremost, I think the trend to focus more on candidate experience is only in its infancy. Over time, we will see a lot more innovation on how to save time for candidates, help them prepare and take away personal learnings from the test, and use these insights later on.

AI might help us get more specific and concrete in personality assessment, by e.g. focusing more on specific situations and work contexts.

I’m also really excited to see what the future of AI will bring to personality assessment. Perhaps we will see new and innovative interfaces, perhaps more conversational and contextualized. AI might help us get more specific and concrete in personality assessment, by e.g. focusing more on specific situations and work contexts. It might also help us ask questions more specifically tied to the role, culture, and industry that one is applying to. At the same time, there are numerous risks here: So far AI, is a black box in terms of how the outcome is actually produced, so we need to be very attentive to how objectivity and transparency are affected.

Bonus Question: What are your thoughts on astrology and horoscopes?

KA: Fun fact: I was absolutely obsessed with astrology as a teenager! To this day, I think there is an aesthetic and narrative beauty to this space that gets the imagination going. This is probably one reason why it’s still so attractive to people. In terms of substance when it comes to actual decision-making, however, it’s obviously no better than a children’s game. If we are talking about hiring in particular, don’t let it anywhere near your recruitment process!

Hear, hear Kajsa! And thank you so much for sharing your insights. Want to connect with Kajsa? You can find her on LinkedIn, and we also recommend exploring one of her blog posts explaining the Big Five Method — an amazing read!

Personality Testing Is All The Buzz — Rightfully So? was originally published in Behavioral Design Hub on Medium, where people are continuing the conversation by highlighting and responding to this story.