Behavior by design

Capturing scholarly “impact” often relies on familiar suspects like h-index, JIF, and citations, despite evidence that these indicators are narrow, often misleading, and generally insufficient to capture the full richness of scholarly work. Considering a wider breadth of contributions in assessing the value of academic activities may require a new mental model.

Broadening the definition of scholarly “impact” against two dimensions—the scale of contributions’ influence and new types of audiences—can help institutions recognize and reward a wider variety of academic achievements and outcomes, and also help individuals identify and embrace different goals.

Featured in the UNESCO 2023 report Open science outlook 1: status and trends around the world (available in English and French)

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Schmidt, R. (2022) Rethinking Research Assessment:Building Blocks for Impact. DORA. https://doi.org/10.5281/zenodo.7249187

This is Open Access content distributed in accordance with the Creative Commons Attribution 4.0 International License. This work was sponsored by Arcadia—a charitable fund of Lisbet Rausing and Peter Baldwin.

It is generally recognized that more diverse decision-making panels make better decisions: including more perspectives reduces bias, increases transparency, and exposes more individuals to how decisions are made. But old habits die hard, and increasing the diversity of committees demands behavioral change. Here are some strategies that can help.

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Schmidt, R. (2022) Rethinking Research Assessment: Debiasing Committee Composition and Processes. DORA. https://doi.org/10.5281/zenodo.7249223

This is Open Access content distributed in accordance with the Creative Commons Attribution 4.0 International License. This work was sponsored by Arcadia—a charitable fund of Lisbet Rausing and Peter Baldwin.

Given the increasing interest in sludge and the recognition that nudges can both build on our best qualities and prey on our worst ones, the world of behavior design does fit rather nicely in a world of chaos, lawfulness, good, and evil.

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Judgment and decision-making biases that impact how we weigh options and make choices have been shown to result in inequitable review, promotion, and hiring. While recognizing these biases at a personal level is important, creating new structural and institutional conditions to reduce bias can be even more valuable in helping to promote and support more equitable practices.

Developed in collaboration with DORA

“Rethinking Research Assessment: Ideas for Action” is the result of a collaboration with DORA (Declaration on Research Assessment), based on discussions at the Driving Institutional Change for Research Assessment Reform meeting hosted by DORA and the Howard Hughes Medical Institute (HHMI) in October 2019.

It outlines five common myths about research evaluation to help universities better understand barriers to change, and provides analogous examples to illustrate how these myths exist inside—and outside of—academia, and five design principles to help universities and research institutions improve research assessment policies and practices. #AssessingResearch.

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Entities of all sizes have certain characteristics and conditions that make it more, or less, likely that certain behaviors occur. Highly hierarchical organizations tend toreward adherence to rules; if you get compensated based on meeting specific metrics, it’s a lot more likely that you’ll prioritize activities that satisfy those criteria over others that don’t pay off. Organizations that say they want to innovate but insist on short-term ROI are saying one thing while rewarding another, and should not be surprised when innovation doesn’t happen.

While we can’t design behavior, or culture, we can recognize and design the conditions that support them. This prototype tool, introduced in a workshop at the Institute of Design’s Design Intersections: Design + Networks + Activation May 2019 conference, allows people to explore and reflect on the conditions that work for {and against) network activation — Purpose, Drive, Individualism, Rigidity, Flux, and Flow — by taking on roles in a scenario: how might a crew of thieves organize a jewel heist?

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Designing informed by behavioral insights and designing for behavioral change are not necessarily the same... any design challenge with humans involved can benefit from understanding and integrating principles from behavioral science..

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Nudges typically aim to make things too easy not to do... but efficiency ≠ effectiveness, and sometimes throwing a little sand in the gears can more effectively help us achieve goals in our own best interests. When brakes on the system are useful, positive friction can stall user behavior for powers of good.

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View a presentation on Positive Friction (delivered April 2018)

Uncertainty and Risk are well-known concepts in economics, with widely accepted definitions... yet when it comes to being human, the frequency and significance of decisions can impact how we perceive our options and the actions we choose to take.

Prior exposure to similar situations (frequency) and the level of perceived risk at making a bad decision (significance) impact how people perceive their situation and gauge options. Understanding where situations sit—buying coffee = high frequency/low significance, while going to grad school = low frequency/high significance—provides a valuable lens for problem solving.

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Behavioral economics at work... literally

We're no more rational between 9 and 5 than we are outside of work... and, in fact, the very strategies we use to navigate uncertainty may leave us more prone to blind spots and irrational behavioral tendencies than we'd like to admit. While behavioral solutions exist for specific situations, we must also be aware of more “hidden in plain sight” signals that indicate bias is intruding in our own decision-making and actions.

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View workshop presentation delivered at Design Intersections: Design + Data + Behavior in May 2018

In contexts such as financial advising, or when dealing with managing one’s health, people often struggle due to various deficits in their ability: Competence (their intellectual ability, or level of understanding), Agency (their functional ability to take action on their own), and Confidence (their perceived belief in their ability). Understanding the ways in which a lack—or in some cases, an excess—of these three attributes can help us better design solutions that provide an appropriate balance.

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Designing for behavior often requires a synthetic approach, using strategies that play across personalized messaging that appeals to my sense of self, social norms and interaction-based cues, the mechanics of tools and devices, and systems-level policies that create the rules of the game we play by.

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Seven key behavioral factors emerged from a top-down and bottom-up exploration of Doblin work and real-world examples. These factors ground a set of 30 behavioral tactics to consider when dissecting or creating behavioral aspects of innovation concepts.

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