In 2014, 31% of annual charitable giving occurred in the month of December—and 12% in the last 3 days of the year. Why? There are many potential reasons. The traditional holiday season sparks generosity and a desire to help others. Some people make last-minute donations for tax purposes. And more recently, fundraisers’ giving campaigns are in full swing this time of year, reinforcing the trend.

People also may feel overindulgent with their holiday spending, and donating to charity helps to offset that feeling—hence the creation of #GivingTuesday, a day that saw donations increase 148% between 2013 and 2014. The monumental success of #GivingTuesday shows that most people are inherently generous; they just need a little reminder—or a nudge—to follow through. #GivingTuesday may be the most successful “moment” ever created for charitable causes, especially since it occurs year after year, maximizing its benefits and solidifying the creation of a culture of giving on this date.

While this is a positive development in the world of philanthropy, #GivingTuesday is still just one day. What I’ve heard throughout my work in the charitable giving space is that many people wish they could be better donors on the other 364 days of the year too. Yet there are few similar “moments” tailored toward giving to remind us to donate during other months. So this year, after making your #GivingTuesday donations, here are three steps informed by our work in charitable giving that you can take to extend the day’s impact way beyond Tuesday, and set yourself up to be a generous, intentional, and informed giver all year long in 2019.

Generous: Decide how much you want to give throughout an entire year

You’ve likely considered how much you want to give to a friend’s online fundraiser, to a disaster relief fund, or to an organization that specifically solicits your donation through mail, email, text message, or in person. But how often do you consider the total amount you wish to donate over the course of a whole year?

One reason Americans don’t give as much as we might aspire to is because we generally don’t take a step back to consciously decide how much of our income to dedicate to charitable causes. Without a moment of reflection, it’s easy for good intentions to get lost in the business of our daily lives. Case in point: Do you know how much you have given so far in 2018? If not, play a quick game—take a guess, and then look through your transaction history and receipts to find out if you were right! (Don’t be surprised if you were wrong. It’s quite common to feel like we give more than we actually do.)

#GivingTuesday is the perfect time to decide how much to give in 2019. Don’t know where to start? In a survey we conducted, people thought their neighbors should give on average about 6% of their yearly salary. To make it simple, begin with that amount, and then adjust as needed to get the right dollar figure for you.

Intentional: Which issues matter most to you?

Once you know how much to give, the fun part can begin—deciding how to use your money and make a difference. There are many, many worthy causes out there that could use your funds to do good in myriad ways, and it’s worth taking a little time to be thoughtful about where to direct your support. Maybe you’re most passionate about protecting the environment. Perhaps you’ve experienced what it’s like to have trouble accessing health care, and you want to make sure affordable services are available to others. Or maybe you have friends and family involved in specific charitable causes, and you want to set aside a portion of your donations to support their organizations.

Identify a few key areas where you’d like your dollars to make an impact. If you are looking for more specific guidance, the effective altruism movement is a good place to start. Once you decide which issues are most essential to address from your perspective, give to organizations that are doing just that.

Informed: Select organizations that are making a difference

While 85% of donors say an organization’s performance is important to them, only 3% actually give based on a charity’s relative performance. And it’s understandable why: there are a lot of organizations to choose from, and researching them is a hassle. But giving more is only the first step toward increasing your impact. It’s crucial to give effectively, and that means being informed about where to give.

You don’t need to conduct a literature review or write a research paper—with tools like Charity Navigator and GuideStar, you can get enough information to make an informed decision in just a few minutes. You can also check out Charity Navigator’s top 10 lists to find highly rated organizations. Also consider talking to people in your community about local organizations they donate to or have engaged with in the past. Doing some quick research now will remove one of the common barriers to giving year-round.

Finally, put your plan into action

Tackling these three simple steps today will help set you up to maximize a fresh start in January. Once you’ve done this thinking, don’t let it fade from view (and therefore your mind): write down your plan for becoming a generous, intentional, and informed giver, and physically display it somewhere you’ll see it throughout the year. (Yes, we know a behaviorally designed tool to help you do this would be great—stay tuned for future advancements as we seek to create just that!)

Following the steps we’ve outlined will help you maximize your impact as a giver, but if you want to take it even further, don’t wait on your giving. While well-intentioned, all the focus on #GivingTuesday and a year-end ‘giving season’ means that hard-working charities receive less funding during the other 11 months of the year. Sign up for automatic monthly donations when you can to help spread the wealth.

If you’re interested in learning more about behavior and charitable giving and what we’ve uncovered, check out our report, Best of Intentions, and stay tuned for future insights from our work, with support from the Bill and Melinda Gates Foundation, aimed at helping everyday donors be more effective using innovations from behavioral science.

If you’re getting yourself into the Halloween…spirit…by checking the back of closets and behind curtains for boogeymen, don’t forget to take a peek in the mirror. Sometimes we don’t find the eeriest things lurking in dark corners, but in the corners of our own minds.

That’s right, studying behavior (and examining our own behavior) can be a bit peculiar, even spooky.  Why do we do the things we do? Why do we make a certain decision in one situation, but not another? And why are we so oblivious to our own quirks?

Just in time for Halloween, we picked out some of our favorite eerie insights about human behavior that might just give you chills—and make ghost stories seem like the minor leagues–or at the very least make you think about your own habits.

Seeing an image of (super creepy) eyes changes us

We all act a little bit differently when we’re around other people. But did you know that even an image of eyes watching you can change your behavior? Hanging posters with eyes on them has been shown to reduce littering in cafeterias and on university campuses.

The eyes have specifically been shown to encourage pro-social behavior, not mere social norm following, and if you’re wondering what’s so scary about that, first look at this—

—and then consider that when you’re not being watched by a 2-D representation of eyeballs, you are more likely to drop trash on the ground or not clean up after yourself. (Plus, imagine a poster like that hanging in your office kitchen! We don’t have to imagine, because that poster is hanging in the ideas42 kitchen.)

Our failures are invisible!

Think about the last time you worked on a project or assignment that was a success. Now think about a time when things went less successfully, or even better, epically failed. What was the reason for each? If you’re anything like the rest of us, you credit your hard work for the success, but blame external forces outside of your control for the failure (i.e. fundamental attribution error).

Maybe you tell yourself (and others) you weren’t given enough time, or nobody informed you the location of the big meeting had changed, or the subway was significantly delayed (again). Unfortunately, we don’t extend the same benefit-of-the-doubt to other people when things go south, instead overlooking the environmental factors that could have impacted their efforts.

This tendency blinds us to our own mistakes or weaknesses, rendering them effectively invisible, while highlighting those of others, making us less empathetic and more egotistical. (Hey, it’s not our fault we’re this way!)

We’re all affected by our current emotional state…but none of us realize it

Ever been so angry that you said or did something you didn’t mean? Probably everyone has, many times. Yet despite our collective experience in this area we tend to underestimate how being in a “hot” or “cold” emotional state affects us. This is known as the hot-cold empathy gap, and it’s spooky for a few reasons. When we’re in a hot emotional state (angry, tired, hungry), not only can that affect our preferences and the decisions we make in that moment, but we also don’t usually recognize that we’re making different decisions than we normally would. And when we’re in a “cold” or collected state, we have trouble reliably predicting how being fired up in the future will inform our actions. We also struggle to understand the behavior of people who are in a different state than us in a given moment—so when we’re feeling calm, someone else’s frustration or fatigue can be a bit…baffling.

So you could say we all have a little Dr. Jekyll/Mr. Hyde in us, except instead of good vs. evil, we experience an internal battle of chill vs. hangry.

We each have our own Funhouse of Mirrors

Aren’t we all people of great contradictions? Perhaps, but we’re made very uncomfortable when we encounter new information that contradicts a belief or value we hold, which causes us to experience cognitive dissonance. Our brains work to “resolve” this conflict, and not always by updating our beliefs, but rather by negating evidence to the contrary. We often have no clue our brains are doing this.

Because our brains quietly work behind-the-scenes to resolve conflicts between new data and prior beliefs, without really “alerting” us to what’s going on, it’s is almost like perceiving the world (and ourselves) through a distorted mirror, or a whole fun-house of them…

We hope you’re sufficiently creeped out by your own behavior. But of course, these insights only scratch the surface of the unusual ways we all act. Got other spooky behavioral insights to add? Tweet more ideas at us via @ideas42 and share your own takes on our devilish quirks this Halloween.

It’s often said that Americans are exceptionally generous, and fortunately, it’s a claim that’s well supported by the numbers. In 2016 alone, U.S. households donated over $282 billion to charities worldwide. And when compared globally, the U.S. consistently ranks as one of the most altruistic countries by the World Giving Index. But do these absolute figures and relative rankings capture the full nature of generosity in America?

At ideas42, we’ve been examining how and why people donate. What we’ve seen is that giving is often reactive and based on an emotional response to a prompt or specific solicitation. In many ways, this approach is helpful in ensuring that we’re addressing urgent needs as they arise, but it also leaves people with an unclear sense of their giving overall. As we know from studying behavior, lack of planning and salience can prevent people from following through on their intentions.

To see whether people’s actions are matching their true philanthropic intentions, we conducted a simple survey in which we asked people how much they thought their neighbors should donate to charity. Surprisingly, the average respondent said their peers should give about 6% of their income annually – more than double what people actually donate each year! The implication of this mismatch is clear. Many Americans are likely giving less on average than we ourselves believe we should.

If we can help people be more deliberate and thoughtful about their giving, we could unlock billions of dollars for important causes. Over the past two years, we’ve been working on doing just that. With the support of the Bill & Melinda Gates Foundation, we’ve been designing and implementing behavioral solutions that aim to encourage Americans to be more generous, intentional, and informed in their giving.

The insights we’ve gathered to date are captured in our new report, Best of Intentions, which expands on the importance of thoughtful giving to donors and charities alike. It also spotlights four behavioral interventions that demonstrate how practitioners working in the philanthropic field can help donors be better aligned with their giving goals. Through these projects, we show innovative ways to:

• Increase the overall generosity of Donor-Advised Fund clients by activating their donor identities through a year-end-review of their giving activity.
• Encourage more employees to donate through their workplace giving program by reframing incentives as opportunities they should not lose.
• Help individuals reach higher levels of philanthropy by offering goal-setting tools that lead them to be more thoughtful about their donations.
• Promote more informed giving by presenting curated lists of charities to donors to help them more effectively and efficiently support the causes they care about.

These findings are just the start of our exploration into donor behavior. We will continue to identify areas of the giving context that may limit how well and how much people give. And ultimately, we will seek more innovative ways to overcome these barriers, helping people close the gap between their intended generosity and their actual donations.

Best of Intentions not only provides groundwork for future efforts—it is also a useful guide right now for practitioners seeking new strategies for improving charitable giving. Applying proven solutions to new contexts can help more Americans follow through on their generous intentions and equip charitable organizations with resources they need to improve lives.

idea42’s Josh Wright recently caught up with Tom Kalil, Chief Innovation Officer of Schmidt Futures, and former Deputy Director of the Office of Science and Technology Policy.  One of the ideas that Tom is exploring is that science and technology can and should be playing a larger role in addressing societal challenges, particularly those challenges related to economic and social mobility.

As part of this exploration, Schmidt Futures is helping ideas42 launch a public call for ideas for how the integration of behavioral science and computer science can help enable upward mobility.

How did you get interested in the role that science and technology can play in addressing societal challenges?

I had an opportunity to work for two Presidents (President Clinton and President Obama) for 16 years.  One of my jobs was to design and launch national science and technology initiatives that involved multiple agencies, like President Clinton’s nanotechnology initiative or President Obama’s BRAIN (Brain Research through Advancing Innovative Neurotechnologies) Initiative.

One of the things that I noticed over time is that some agencies, like DARPA, had the ability to set really ambitious goals and mobilize top researchers and entrepreneurs to meet them, while other agencies, like the Department of Labor, did not.  The entire Department of Defense has a research budget of $66 billion, whereas the Department of Labor has a research budget of $4 million.

This huge difference in capacity shapes what agencies can do in important ways.  For example, the Department of Defense was able to launch a program to reduce the time required for new Navy recruits to gain a technical skill from years to months, harnessing recent advances in AI.  This is not something that the Department of Labor would have the ability to conceive of, let alone fund.

It occurred to me – what if the agencies that are responsible for promoting economic and social mobility (e.g. Labor, Education, HUD, the human services components of HHS) had a research arm like DARPA?  What goals would it set?  What research projects might it support?

While in the administration were you able to act on this insight?

I worked with President Obama’s Deputy Secretary of Education Jim Shelton on a proposal to create a DARPA for Education.  President Obama included this in his budget, but we were unable to convince the Congress to support this idea.

Why do you think we should be investing more in science and technology to address societal challenges?

I think that if you are trying to make progress on a particular set of societal problems, and are generating a list of things to try, science and technology should be on the list.

That’s because we know more (e.g. the slow but steady increase in our understanding about how people learn or how we make decisions) and can do more based on the increased power and reach of technology, particularly digital technologies.

Having said that, I certainly don’t think it is the case that science and technology is going to solve all of our problems.  I also think that we need to be more cognizant of the risks of technology, not just the benefits, and to develop technology-enhanced solutions in collaboration with the communities we are trying to empower as opposed to for them.

What do you mean by “societal challenges?”

In this context, I’m referring to problems that are making it more difficult for people to make the most of their talents and to enjoy a decent standard of living. Some examples include:

• By age 4, low-income children are exposed to 30 million fewer words than their more affluent peers.  One study found that children of professionals also heard twice as many unique words and were engaged in twice as many “encouraging” as opposed to “discouraging” conversations.
• Only 20 percent of low-income students are proficient in 8th grade math.
• 36 million American adults are reading at the 3rd grade level or below.
• Twenty-five percent of Americans have no retirement savings or pension, and 40 percent do not have the savings to handle a $400 emergency expense.

What are some examples of science and technology applied to societal challenges?

Well, some examples are initiatives that ideas42 is currently pursuing – can the combination of behavioral insights and digital technologies reduce chronic absenteeism in K-12 schools, or reduce prison recidivism?

Greater progress may also be possible in workforce development.  As you know, most workforce development programs have a modest impact on the wages of non-college educated workers.  We have some preliminary evidence that it may be possible to do much better by combining AI and the science of learning to model the interaction between a novice and an expert.

Another example is depression.  Entrepreneurs such Spencer Greenberg are exploring whether a smartphone app can deliver Cognitive Behavioral Therapy to help treat depression.

My hope is that the public call for ideas that ideas42 is issuing will encourage people in academia, civil society, and the private sector to suggest additional possibilities.

How could we begin to identify the opportunities to harness science and technology to solve societal problems?

I think a good next step would be to identify ideas and insights in four categories:

1. Societal problems where the status quo is unacceptable, and where progress could reduce poverty, expand the middle class, and promote shared prosperity.
2. Insights concerning how people learn, develop, make decisions, and form habits.
3. Technological capabilities that can be used to amplify the impact of these insights about how people learn, make decisions, or form habits.
4. Models for the definition, development, rigorous evaluation, and adoption of a successful intervention.

In other words, for a given societal problem, what is the role that a science-informed, technology-enabled intervention could play in addressing it?  What roles should different public and private actors play in developing, evaluating and adopting these interventions?

For those of us in non-technical fields, what is different about the use of technology as opposed to other types of innovations in solving societal problems?

Technology and, more specifically, software and digital services or information have two overarching features that are helpful to consider when thinking about innovation.

1. Low marginal cost:  The cost of a traditional social service increases arithmetically with the number of people served.  The marginal cost of making a digital product or service available to more people can be very low, although it may have a higher fixed cost.
2. Continuous improvement:  The productivity of public sector services is generally low or negative.  For example, the U.S. has doubled real per pupil expenditures on K-12 education without significant improvements in learning outcomes.  It’s plausible that digital techniques for rapid low-cost experimentation (A/B testing) and feedback loops could improve a service over time.

For those readers that are less aware of innovation concepts, can you explain what is meant by combinatorial innovation?

Google’s chief economist Hal Varian has made the case for the importance of “combinatorial innovation.”  As he notes, occasionally we have a set of established existing technologies that “can be combined and recombined by innovators to create new devices and applications.”  The Internet is a great example of combinatorial innovation because the components (programming languages, protocols, open standards, software libraries, etc.) are all “bits” that are faster and easier to combine and recombine to create new applications.

How might we foster combinatorial innovation for societal challenges?

By describing and cataloging relevant scientific insights from the social and behavioral sciences and by describing the capabilities of different technological building blocks, we could make it easier for people and teams to envision science-informed, technology-enabled interventions that can help address a given set of societal challenges.

For example, learning scientist Ken Koedinger has identified 30 mid-level theories about how people learn that have been validated experimentally and are specific enough to inform the design of learning technologies. Behavioral economist Sendhil Mullainathan has identified seven design principles for applying behavioral science to global development.  

What are some examples of the technological building blocks that you have in mind?

Let me give 8 examples of the capabilities of digital technologies, with the caveat that this is just scratching the surface.  What I think is important to do is to describe these in ways that are accessible to people who are not technologists.

For example, if you are involved in social policy and a computer scientist starts talking to you about convolutional neural networks and stochastic gradient descent – that is not terribly helpful. Instead, it might be useful for you to know that advances in machine learning are lowering the costs of prediction, or that with enough examples, we can train an algorithm to accurately map between an input (e.g. an image) and an output (a label that humans would use to describe the image).

1. Sensing and measurement:  Low-cost sensors or instrumented online environments are increasing our ability to measure everything.  For example, companies have developed low-cost devices that allow parents to track the number of words that they speak to their children and the number of conversational turns that occur between parent and child, which could help address the word gap. Obviously, our increased ability to collect data raises important ethical issues, such as privacy, informed consent, and the fairness, accountability, and transparency of algorithmic decision-making.
2. Personalization: Machine learning is improving our ability to deliver experiences that are personalized to the needs of an individual.  For example, learning scientists are beginning to develop software that keeps students in the “Goldilocks” zone so that the material is hard enough to be challenging, but not so hard that they are frustrated and give up.  Software can often recognize and address common student misconceptions that prevent them from mastering the material.
3. Natural-language processing:  Although computers are still very far away from human-level understanding of text and speech, natural-language processing (e.g. the ability to translate between two languages, answer questions, summarize a piece of text, etc.) is becoming increasingly useful.  
4. Prediction:  With enough data, data scientists can develop predictive models that help prevent problems before they occur.  Health plans are trying to identify which patients are at greatest risk of diseases such as stroke and diabetes to target prevention programs that can reduce the incidence of these conditions.
5. Time on task:  Time on task is clearly important for learning.  Good game designers can create compelling and engaging experiences that increase time on task.
6. Simulation:  Simulation is also useful for training because it allows people to engage in learning by doing, in the same way that a would-be pilot uses a flight simulator before flying a plane.
7. Matching:  Some markets don’t rely solely on prices to clear.  For example, if I want to attend a given university, it must be the case that I want to attend, and the university wants to accept me.  Researchers at the intersection of computer science and economics are using “mechanism design” to solve societal problems that require this kind of matching, like helping a worker find a job that they would excel at.
8. Location:  Using satellites developed and deployed by the U.S. military, companies can provide location information that is accurate within 25 feet, and researchers have demonstrated systems that are accurate within one inch.  For example, by collecting data on where asthma patients use their inhalers, Louisville and digital health companies have been able to identify and mitigate “hot spots” of asthma symptoms.

Are there any non-technological building blocks that people should consider?

There are some things that are not technologies in the traditional way we think about technologies, but are instead methodologies or ways of thinking (such as behavioral design, human-centered design, or system thinking) that I think are really important.  

For example, when a Code for America team worked on increasing access to food stamps, they shadowed county workers, interviewed applicants, and actually went through the process of applying for food stamps themselves.

The combination of human-centered design and modern software engineering practices now allows Californians to apply for food stamps on a mobile phone, ask questions via online chat, take and upload images of documents needed to verify eligibility, and schedule any necessary interviews.

What are the implications of this for academia?

A number of universities are creating centers or initiatives that are at the intersection of computer science (CS) or data science and some particular problem – a trend that some are calling “CS + X.”

• In response to the explosive enrollment growth in CS, Northwestern is recruiting 20 CS faculty, but 10 of them will be in “CS +X” areas such as the intersection of computing and education.
• University of Illinois Urbana-Champaign is creating CS + X degree programs for students interested in the intersection of CS and other fields, such as crop science.
• Cornell has created a research center in computational sustainability, USC has a Center for Artificial Intelligence in Society, and UC Berkeley is the lead campus for the Center for Information Technology Research in the Interest of Society.

I think that programs like this that explored the intersection between CS and data science and some of the societal challenges we’ve been discussing would make a lot of sense.

What do you mean by “models for the development, evaluation and adoption of effective interventions?”

One key question is whether there are market failures that reduce the incentive of the private sector to invest in development, evaluation and adoption of effective interventions, and if there are, what are ways to address these market failures?

For example, it may be that the private sector has limited incentives to develop an intervention for adult literacy because the relevant population has little or no discretionary income to spend on adult literacy applications.  Or it may be that there is a market, but the size, profitability, or riskiness of the market severely constrain what companies and investors are willing to support in terms of R&D or rigorous third-party evaluation.

The global health community has developed the capability to (1) identify unmet needs; (2) create a performance-based specification for the products that would meet those needs; and (3) design the incentives that would make it attractive for firms to develop these products.

For example, pharmaceutical companies have limited incentives to develop vaccines for diseases of the poor.  To solve this problem, five countries and the Gates Foundation pledged to purchase a vaccine that could save the lives of 7 million children over the next 20 years by preventing diseases such as pneumonia and meningitis.  This “Advance Market Commitment” motivated drug companies to develop the vaccine.  The public sector agreed to bear the demand risk by pledging to purchase the vaccine at a given price, and the private sector agreed to bear the performance risk, which was whether they could develop a vaccine which was safe and effective.

I think this is an approach that we should be experimenting with domestically.  I think it is unfortunate that governments have the ability to make trillions of dollars of financial commitments that are contingent on failure, such as loan guarantees, but are just scratching the surface when it comes to making financial commitments that are contingent on success, such as advance market commitments.  This is an idea that Schmidt Futures is interested in exploring.

So that’s one model.  But there are many others as well, such as:

• Traditional grants and contracts;
• Incentive prizes;
• Milestone payments that reward teams for intermediate progress towards the development of an effective intervention;
• Hybrid value chains, where public or philanthropic support of one component of the value chain would enable a sustainable business model in another part of the value chain; and
• Impact investing in firms or social enterprises, where investors are motivated more by social impact than financial return.

What are the policy implications of the ideas we’ve been discussing?

I think there are at least three policy implications.

The first is that the Executive Branch and the Congress should increase the capacity of agencies that work on promoting economic and social mobility to harness science and technology.  For example, the Department of Labor should have a research arm. It might have as a goal reducing the time for non-college educated workers to master a skill that is a ticket to the middle class from years to months.  It might achieve this goal by sponsoring research in areas such as cognitive task analysis (what is it that top performers in a given job know and are able to do), and AI-based digital tutors. Since this is unlikely to happen in the next several years, this is an area where philanthropy can play a role by demonstrating what might be possible.

The second is that the government should increase its capacity to create incentives for innovations that would have a high social return, but a low private return.  I was able to make some progress on this idea during the Obama Administration by working with Congress to pass legislation that gave every agency the authority to support incentive prizes of up to $50 million, but there is a lot more that remains to be done.  The budget and appropriations process generally assumes that federal agencies are going to allocate funds in the same fiscal year that they receive them.  If we want agencies to make financial commitments that are contingent on success, they may never need to spend any money (if no one achieves the relevant goal).

The third is that agencies that work on promoting economic and social mobility need the capacity to support interventions that have a high fixed cost but a low marginal cost.  A science-informed, technology-enabled intervention that has been rigorously evaluated and that increases adult literacy and numeracy might have a high fixed cost, but a low marginal cost.

The reason that many agencies would find it difficult to support the development and evaluation of these types of interventions is that much of social spending is allocated as either payments to individuals or block grants to states and localities.  In an area like adult literacy, no single actor is in a position to create a market for a high-impact technology-enabled intervention. That’s because the federal money that we allocate to adult literacy is divided between 50 states, and divided again in even smaller amounts to local service providers.  I think there is a case for allocating some social spending to create markets for interventions that have high fixed costs and low marginal costs, and currently the public sector is not organized to do that.

With the ideas42 Seminar Series, we invite leading scholars to share their insights and what inspires their exploration into human behavior.

Our New York office was pleased to host Daniel Chen, researcher at Toulouse School of Economics. He has a law degree from Harvard Law School and a PhD in economics from Massachusetts Institute of Technology. His research spans several areas: Law and Development, tracing the incentives that led to what are now viewed as human rights violations; Markets and Morality, how market forces interact with normative commitments; Behavioral Judging, social and psychological, economic and political influences on legal ideas and production of justice; Law and Legitimacy, the role of legitimacy in legal compliance; and Demography of Ideas, the economics of interpretation as a source of normative commitments. After giving a talk to the ideas42 team, Daniel was kind enough to share some of his thoughts on behavioral science:

What drew you to behavioral economics? 

What drew me to behavioral economics is a combination of wonderful teachers and a long-standing fascination with human behavior. From an inspiring high school teacher who taught literature with a psychological perspective, to a college professor who exposed me to many of the classic psychology experiments and concepts that inform my empirical work today, to the Russell Sage Foundation graduate behavioral economics summer camp that showed me these ideas can be studied with mathematical tools and field data, I found a way to channel childhood interests in math, psychology, and history into my research in behavioral economics.

What would you say is one of the most surprising discoveries about human behavior?

One discovery that has really surprised me is how much judges can be influenced by behavioral factors. While a longstanding literature has documented behavioral factors as being relevant in lab studies, vignettes, or small scale field data, the advent of large datasets on judicial decisions have made it possible to study many findings in the field that were previously documented in the lab (see, for example, our recent work on the gambler’s fallacy and negatively autocorrelation in judicial decision-making). What has concerned me more recently is the juxtaposition of these findings and the argument that laboratory findings might be observed outside the lab when decision-makers are nearly indifferent between options. Such a perspective may shed light on recent discussions of legitimacy in law and perceived indifference of lawmakers. I call it “revealed preference indifference.” But if a judge is indifferent, there may be adverse downstream consequences for individuals who come to expect recognition and respect. Loss aversion with respect to that reference point can lead to anger. I’ve been thinking about how behavioral economics theory can help operationalize contemporary discussions of legitimacy, law, and recognition-respect.

In your breadth of work, tell us about one of your favorite projects related to behavioral economics and what you see as its unique value.  

One of my favorite projects is developing revealed preference methods to reflect on the classic divide between law and economics—the consequentialist view that optimal legal policies should be calculated from costs and benefits vs. the deontological view that there are duties and from the duties one derives what is fair and just. I begin with the behavioral question: Are there deontological motivations, apart from the consequentialist ones? I’ve been exploring this distinction theoretically, experimentally, and empirically in different domains. For example, methods of collecting data in experimental economics and political surveys can be biased if individuals have non-consequentialist motives. Methods to detect these motives with revealed preference can relate to perceived legitimacy of law, sometimes defined as that which motivates legal compliance irrespective of likelihood of sanction. Methods to model these motives can help shed light on EU integration policy, desertion during war, and spurring of Irish desertion in response to the British executions in World War I. A recent literature review in the Journal of Economic Literature suggests that theoretical models do not have a good way to model these motives. Agents choose between quantities (in Chicago models), but do not have preferences over choices separate from preferences over quantities. Or agents choose between acts (in identity models), but do not have preferences over acts separate from preferences over consequences of acts. In my reading, economic models have thus far focused on hypothetical imperatives–preferences over acts because of their consequences–rather than what some like Kant would call categorical imperatives–preferences over acts regardless of their consequences. Distinguishing these motives is challenging in normal circumstances. A new project has been to examine the consequences of consequentialist reasoning on the American judiciary.

What have you learned in applying behavioral insights that has changed the way you work?   

What has been critical to working with diverse research teams has been to recognize individuals’ different preferences and talents, which often begins with asking questions. Recognition-respect is pretty important to research collaborations. This can also mean being flexible in following leads, which can often result in later surprises on the deeper conceptual connections when one takes stock.

How do you use behavioral insights in your daily life (or recommend that people use behavioral insights in their daily lives)?  

I think that realizing that individuals have different reference points can go toward increasing cooperation, trust, recognition, and respect. Our research group has developed oTree, originally as a programming tool for developing economic experiments, perhaps a tool for eliciting reference points. It’s pretty easy to program, shortening by 90% the time that we previously spent to develop experiments. It’s possible to use in secondary school education (fifteen minutes to program a public goods “app”), and we’re thinking how teaching behavioral economics might increase cooperation, trust, recognition, and respect.

For the past few years, we have been applying behavioral science to city programs and services in New York and Chicago to help the city government take into account complex human behavior, and the contexts in which we make decisions. We have embedded experts into agencies themselves—a model we call Behavioral Design Teams (BDTs)—to tackle challenges at the city level.

There are many reasons people may not use helpful services available to them—sometimes applications are onerous or simply not top-of-mind, or people may believe a program is not meant for someone like them even if they are eligible to receive benefits. Fortunately, behavioral design can make a meaningful difference when it comes to problems like these, and small behaviorally-informed changes are often cost-effective, or even cost-neutral.

We’ve been refining our approach to behavioral design teams through dozens of engagements across both cities, achieving great success and impact. Given the BDT model’s effectiveness in quickly identifying and addressing behavioral barriers within government programs and services, we want to see the number of BDTs grow in order to have as much positive impact on as many people’s lives as possible. However, we know that launching a new team within an existing system is difficult, particularly when goals and needs might be unclear.

To pave the way for other municipalities to start a Behavioral Design Team, we distilled years of rigorously tested results and real-world best practices into an open-source playbook for public servants at all levels of government. The playbook introduces readers to core concepts of behavioral design, indicates why and where a BDT can be effective, lays out the fundamental competencies and structures governments will need to set up a BDT, and provides guidance on how to successfully run one. It also includes several applicable examples from our New York and Chicago teams to illustrate the tangible impact behavioral science can have on citizens and outcomes.

Thinking about starting a BDT? Here are five tips for launching (and sustaining) a city behavioral design team. For more insights, read the full playbook.

Compose your team with care

While there is no exact formula, a well-staffed BDT needs expertise in three key areas: behavioral science, research and evaluation, and public policies and programs. You’ll rarely find all three in one person—hence the need to gather a team of people with complementary skills. Some key things to look for as you assemble your team: background in behavioral economics or social psychology, formal training in impact evaluation and statistics, and experience working in government positions or nonprofits that implement government programs.

Choose an anchor agency

To more quickly build momentum, consider identifying an “anchor” agency. A high profile partner can help you establish credibility and can facilitate interactions with different departments across your government. Having an anchor agency legitimizes the BDT and helps reduce any apprehension among other agencies. The initial projects with the anchor agency will help others understand both what it means to work with the BDT and what kinds of outcomes to expect.

Establish your criteria for selecting projects

Once you get people bought-in and excited about innovating with behavioral science, the possible problems to tackle can seem limitless. Before selecting projects, set up clear criteria for prioritizing which problems need attention the most and which ones are best suited to behavioral solutions. While it is natural for the exact criteria to vary from place to place, in the playbook we share the criteria the New York and Chicago BDTs use to prioritize and determine the viability of potential undertakings that other teams can use as a starting place.

Build buy-in with a mix of project types

If you run only RCTs, which require implementation and data collection, it may be challenging to generate the buy-in and enthusiasm a BDT needs to thrive in its early days. That’s why incorporating some shorter engagements, including projects that are design-only, or pre-post evaluations can help sustain momentum by quickly generating evidence—and demonstrate that your BDT gets results.

Keep learning and growing

Applying behavioral design within government programs is still relatively novel. This open-source playbook provides guidance for starting a BDT, but constant learning and iterating should be expected! As BDTs mature and evolve, they must also become more ambitious in their scope, particularly when the low-hanging-fruit or other more obvious problems that can be helpful for building buy-in and establishing proof-of-concept have been addressed. The long-term goal of any successful BDT is to tackle the most challenging and impactful problems in government programs and policies head-on and use the solutions to help the people who need it most.

Having impacted hundreds of thousands of lives through an almost 50 combined projects to date, the New York and Chicago BDTs have demonstrated that embedding behavioral science at the city level works, for both the agencies themselves and the people they serve. Compiling into a playbook the insights from our years of working directly with cities across the United States can help others launch and sustain their own effective Behavioral Design Teams. We hope other cities will consider leveraging this proven process, and that the playbook creates a path to spread the impact of behavioral science for social good even wider.

Interested in learning more about building your own BDT? Get in touch at gov@ideas42.org.

Ten years ago, ideas42 started in a small office at Harvard University. Since then, we have partnered with foundations, non-profits, government agencies, and socially-minded companies to work on more than 100 projects in over 35 countries, using behavioral science to improve millions of lives around the world.

Today we released our first-ever Impact Report, taking stock of how a decade of behavioral interventions across finance, justice, environment, education, health, and poverty have positively affected so many lives. We feature snapshots of 40 of our many projects from our first 10 years, many of which are ongoing collaborations. We’ve also revealed just how many experiments we have conducted on ourselves, among other metrics demonstrating our commitment to doing everything playfully and through a behavioral lens. Highlights include:

Helping more Mexican citizens save for a secure retirement: To combat a high elderly poverty rate and encourage voluntary pension contributions, 20 million Mexicans now receive ideas42-designed account statements.

Keeping people out of jail in New York: Redesigning the summons citation form for low-level violations and sending text message reminders reduced failure-to-appear rates by 36%. This also reduces the number of warrants issued, as failing to appear in court automatically triggers an arrest warrant.

Encouraging water conservation in Costa Rica: Two interventions—adding colored stickers focused on social comparison to utility bills and goal-setting postcards—each reduced water consumption by up to 5.6%.

Helping more students in San Francisco stay the course in college: A social norms based video showed to low-income and underrepresented freshmen increased persistence to sophomore year from 83% to 91%.

Reframing HIV risks for South African teens: A computer game helped South African teenagers better assess their risks of contracting HIV, correcting dangerous misperceptions that had previously led to troublingly high rates of infection among teen girls.

Increasing access to healthy nutrition in California: We’ve made more than 40 actionable recommendations to improve access to WIC (Supplemental Nutrition Program for Women, Infants and Children), and we’re now working with WIC programs in California design and test some of them.

These highlights represent just a small slice of what we’ve been able to achieve using low-cost, easy-to-implement solutions across the areas we work in. And we’re just getting started. We’re looking toward the future with enthusiasm, where we have our sights set even higher. In the coming years, ideas42 will continue to optimize our existing programs by partnering with organizations and institutions and helping them discover the power of behavioral design. We’re taking important steps to scale innovative solutions, from launching an innovation lab and venture studio to sharpening the focus of our new policy lab. We also empower problem-solvers across diverse sectors with innovative strategies using executive seminars and multi-day master classes. Building on what we have learned in our first decade, we will push the envelope in all of these efforts in our ultimate goal of making the use of behavioral science a ubiquitous tool for tackling some of the world’s toughest problems.

“Our work with ideas42 has changed the way we approach voluntary savings in our pension system. By deploying more effective communications, innovative incentives, and timely reminders, we’ve seen a significant increase in voluntary savings—with enormous potential ahead.” – Carlos Ramírez Fuentes, President, CONSAR, Mexico City

In the last decade, behavioral science has gone from promising new approach for solving problems to a mainstream and essential tool for real social change. Behavioral interventions have proven time and again not only to measurably improve outcomes, but are often cheaper than traditional approaches. The evidence is clear: behavioral science for good can fuel social impact.

We’re invigorated by what lies ahead and excited to move beyond developing a proof of concept as we continue experimenting and rigorously testing innovative designs, focusing even more on creating a world designed for real people, from the ground up.

Click here to read the full Impact Report.

Our work involves devoting significant amounts of time to understanding what drives people’s behavior—and prompting them to make decisions and follow through with action that benefits them. As a member of ideas42, I can’t help but apply this same behavioral lens to my own life. When I read Daniel Pink’s new book, When: The Scientific Secrets of Perfect Timing, I realized that one thing that isn’t always salient when it comes to behavior is timing. Yet in his book, Pink illustrates how improving our understanding of time can help us change our behavior, perform tasks better, and even be happier. So, I decided to investigate how I could integrate the core insights from his book into my own life and work.

One of the main insights Pink drives home throughout When is that our energy flows in predictable waves throughout the day. Most of us often start the day in a good mood and reach a peak energy level, until dipping to a low energy point and ultimately rising again later on. As a result, how well and how easily we complete a given task depends not only on the type of task and the type of person we are, but on the time of the day.

To apply his insights, I first had to understand which type of person I am. Pink categorizes people into groups, which he calls larks, owls, and third birds, based on what time of day they perform better on certain types of tasks. Larks are morning people, owls are, well…night owls, and third birds are somewhere in between. While he explains that most people are third birds, I concluded quickly that I am a lark. I wake up between 4:30 and 5:00am on weekdays and go to sleep no later than 9:00pm most nights. Even on weekends I often wake up at the same time. To determine your own type, consider your sleep cycle—when do you tend to go to bed and wake up?—as well as your alertness and energy levels throughout the day.

Your “type” is important because, according to Pink, a lark will perform better on analytical and creative tasks at a different time of day than an owl will. As a lark, I should perform analytical tasks in the morning, when I am more alert and have high higher energy levels, allowing me to think critically about the problem at hand. I am better off tackling less-defined problems that require creative thinking in the afternoon, when I am more easily distracted. That may sound counterintuitive, but this distracted state can actually help me approach a problem in a novel way and reach that “eureka” moment. On the other hand, owls who have the reverse energy levels of larks are better at solving analytical problems in the evening and problems that require “outside the box” thinking in the morning. Third birds share a bit of both of these characteristics.

Armed with a better understanding of my most productive times, I began to examine my workdays to find opportunities to improve my own decision-making and performance—not by changing my workload, but the time I allocate for certain tasks. I reflected on my workweek to analyze the ebbs and flows of my productivity. It became clear that I get most of my best work done between 7:00 and 11:30am and 5:00 and 8:00pm. I associate these time periods with focus and little distraction. So, it makes sense for me to survey my work for the day and schedule analytical tasks in the morning and more open-ended work in the afternoon.

Of course, things are not always that simple. Like many people, I have meetings and deadlines throughout the day that aren’t flexible. Pink recognizes this and underscores that being aware of the “when” in your day-to-day life and making changes when possible, even minor ones, can affect your productivity. For example, I have started taking advantage of the 30 minutes I have between meetings that fall during my productive periods to get a jump-start on an upcoming deadline, rather than defaulting to checking my email.

I also recognize that even when the timing is right, there may be behavioral barriers that prevent optimal performance. For example, I frequently underestimate the time I need to complete a task during my morning work blocks—a common phenomenon called planning fallacy. This causes me to work past the allocated time and push back other items on my to-do list, disrupting my whole schedule. One way to address my tendency to miscalculate how long a task will take is to create multiple work blocks with buffer time for when I (almost inevitably) fall behind. This is particularly true when I need to do an analytical task in the afternoon, my least productive period.

Pink’s insights on how timing interacts with behavior offer a useful new lens for creating more productive, healthier lives. I’ve found it beneficial to draw on his findings in my own day-to-day, and incorporating the science of timing with what we know about human behavior can strengthen our ability to impact people’s lives with behavioral science.