Aristotle may have called you a “rational animal,” but behavioral scientists think you’re, well, a bit dim. Okay, maybe not exactly, but the field does assume that you’re innately irrational. How rude, right? They don’t even know you!
Don’t worry, we’re not here to tell you that the entire discipline is a sham. We believe in the power of BehSci! For years, we’ve been staunch advocates for integrating behavioral science into policymaking. Understanding common patterns of thinking, biases, and heuristics is a crucial piece of the puzzle in effecting change.
But when designing interventions, should we really be assuming we’re irrational from the jump? I mean, we don’t make decisions in a vacuum. What seems irrational at first might actually be a logical response to the information available and the environment we’re in… and that’s exactly what we’re exploring in this newsletter.
Today, we’re shining the spotlight on the work of one of our esteemed advisors here at TDL, Dr. Jens Koed Madsen. In his recent paper, "Behavioral science should start by assuming people are reasonable," Dr. Madsen and colleagues challenge the age-old assumption that humans are irrational decision-makers and highlight the need for a more nuanced perspective on human rationality in policy design. Let's dive into their insights.
Until next time,
Gabrielle & Charlotte and the 100% irrational humans at TDL
Disclaimer: We can’t touch on everything regarding the study of human rationality (or lack thereof) in one newsletter. After all, it’s just a newsletter! Instead of approaching this as a metanalysis, think of it as a launching point for your own explorations.
📧 If you are truly a rational human being, then you will subscribe to our newsletter here. Just saying…
Today’s topics 👀
đź’ But first: Ready to think clearly?
🤔 Deep Dive: Homo irrationalis?
🌏 Field Notes: A new (political) climate
đź’ˇ Viewpoints: From rational to reasonable
đź’ But first: Ready to think clearly?
Looking for ways to think more clearly and to make better decisions?
ClearerThinking.org is a treasure trove of free, interactive tools to help you do just that. With over 80 free research-backed tools, you'll find evidence-based resources to help you make better decisions, hone your critical thinking, and achieve your goals. For example: learn what kind of thinker you are with the Rationality Test, check your reasoning skills with the Faulty Reasoning Quiz, or test your knowledge of AI concepts and risks with the Artificial Intelligence Quiz.
Explore ClearerThinking.org today and start sharpening your critical thinking skills.
DEEP DIVE
🤔 Homo irrationalis?
What does it mean to be irrational? ​​When it comes to decision-making, there is a common belief that humans deviate from logical reasoning or optimal choices, influenced by emotions, cognitive biases, and less-than-perfect information.
Measuring rationality. But if we’re calling ourselves “irrational,” we need to identify what rational decision-making looks like in the first place. Oftentimes, this is defined bymaximizing utility and logical evaluation of all the relevant information. This, coupled with the illusive idea of “objectivity,” sets the benchmark against which our behaviors are judged.
The illusion of the “all-seeing-eye.” Our perception guides our decision-making and, therefore, plays a central role in theories of rationality. However, our perception isn’t always an accurate reflection of reality. In this review, Felin et al. argue that we shouldn’t assume that humans are “all-seeing” but instead focus on understanding rationality as shaped by our context and environmental constraints.
Bias in biases? Cognitive biases have long been behavioral science’s claim to fame in showcasing human irrationality. But as you may have observed, biases can contradict one another. Think about it: how do we know when the recency effect will take hold in lieu of the primacy effect? What about negativity bias versus optimism bias? Though there has been progress in bringing together different frameworks, these biases often describeobserved behaviors rather than revealing underlying universal cognitive processes.
Why does it matter? Well, as Madsen et al. point out, how we think about decision-making directly influences the solutions that are proposed to large issues like climate change or global pandemics. To develop effective and well-informed policies, we must move away from the assumption that we are “predictably irritational” and toward the idea that we are reasonable.
Field Notes: 🌏 A new (political) climate
Up until this point, behavioral science has advocated that climate inaction is rooted in our irrational minds. Thanks to hyperbolic discounting, we may prioritize immediate convenience (such as plastic bags or disposable coffee cups) over later rewards (such as a waste-free future).
However, there is a new movement in the field suggesting that we might be putting too much blame on cognitive biases. Instead, it seems like our environmental views might have much more to do with our political alignment — which, in itself, is not necessarily irrational. (Relying on social norms can, in fact, be adaptive!)
To get everyone on board working toward a green future, we need to focus on reducing polarization. This means trying to understand the rationale behind climate denial, rather than dismissing it as irrational right off the bat.
To find out more, read Dr. Madsen and colleagues’ original paper here.
According to a survey conducted by the Pew Research Center in 2022, 78% of Democrats saw climate change as a major threat compared to 23% of Republicans.
Viewpoints
đź’ˇFrom rational to reasonable
Perhaps our goal shouldn’t be determining if humans are rational — that is, making the optimal choice according to the rules of perfect logic. Perhaps our goal should instead be determining if humans are reasonable — that is, making the optimal choice given the personal, social, and environmental conditions in place.
This switch can help us start to understand why humans make seemingly “irrational” decisions using perfectly reasonable thought processes. We can be one step closer to designing experiments that capture the tradeoffs humans make, as well as interventions to help humans optimize these tradeoffs.
For behavioral scientists, this means treating participants as partners rather than just the targets of interventions. By actively involving participants in the design, implementation, and interpretation of research, we can better understand why humans do what they do. Capturing the cultural context here is key — especially when studying non-WEIRD populations, where Western standards might be wrongly assumed as the status quo.
Here are three experimental methods that Dr. Madsen and colleagues propose to turn participants into partners:
Citizens’ assemblies. This form of “deliberative research” encourages conversations among a diverse group about their stance on a specific issue. By conducting an assembly before designing an intervention, researchers can get a better sense of what the “general population” thinks — and, more importantly, why.
Co-design interventions. Researchers can collaborate with potential participants in designing interventions rooted in social learning and culturally specific knowledge. This may even involve making key community members agents in the intervention, such as encouraging participation from their peers.
Nudge plus. A “nudge plus” is just like a normal nudge, but goes one step further in encouraging participants to reflect upon whether the suggested behavioral change aligns with their values or goals. This provides policymakers with feedback about the way choice environments should shape behavior in a way that actually helps its inhabitants.
Bounded Rationality
According to bounded rationality, we often settle on decisions that are “good enough” rather than striving for the best possible outcome. The point here is that humans can still be rational — however, we “bind” our rationality to save time and mental resources for other tasks. (That sounds pretty fair to me!)
Read more on our website here to learn where bounded rationality works — and, unfortunately, where it doesn’t.
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