iiinova — where your digital self keeps evolving

sjdm-tweets @sjdm-tweets.bsky.social · 02/06/2026

Today's SJDM Featured Paper is: Maimone, G., & McKenzie, C. (2026). Whoever is Not With Me is Against Me: The “Moderate as Out-Group” Effect. Journal of Experimental Psychology: General. doi.org/10.31234/osf...

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OSF

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sjdm-tweets @sjdm-tweets.bsky.social · 31/03/2026

The Society for Judgment and Decision Making is pleased to announce that the current newsletter is ready for download: sjdm.org/newsletters/ This issue contains SJDM Featured Research Papers, announcements, jobs, and conferences!

sjdm.org

Society for Judgment and Decision Making: Newsletters

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sjdm-tweets @sjdm-tweets.bsky.social · 16/03/2026

Today's SJDM Featured Paper is: Connolly, D. J., & Loewenstein, G. (2026). How Memory Crystallizes the Past: Memories Become More Consistent Over Time Due to Differential, Nonconstant Change. SSRN. doi.org/10.2139/ssrn...

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How Memory Crystallizes the Past: Memories Become More Consistent Over Time Due to Differential, Nonconstant Change

How do memories of real-life events change over time, and why do some aspects persist while others fade? We propose that two basic properties of memory-nonconst

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sjdm-tweets @sjdm-tweets.bsky.social · 08/03/2026

Today's SJDM Featured Paper is: Strueder, J. D., Looi, T., Clark, P. M., Cockburn, J., & Windschitl, P. D. (2026). Optimistic Predictions Under Uncertainty: Active Information Search Both Supports and Constrains Motivated Bias [Preprint]. PsyArXiv. osf.io/preprints/ps...

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Renato Frey @renatofrey.mstdn.science.ap.brid.gy · 02/03/2026

Which risky choices should (and do) we study as behavioral scientists? In two related articles, we recently examined the current "ecology of risk" (i.e., laypersons' reports on what risky choices they face in real life) and how these choices differ from those […] [Original post on mstdn.science]

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sjdm-tweets @sjdm-tweets.bsky.social · 05/03/2026

Today's SJDM Featured Paper is: Costello, T. H., Pelrine, K., Kowal, M., Arechar, A. A., Godbout, J.-F., Gleave, A., Rand, D., & Pennycook, G. (2026). Large language models can effectively convince people to believe conspiracies. arXiv. doi.org/10.48550/arX...

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Large language models can effectively convince people to believe conspiracies

Large language models (LLMs) have been shown to be persuasive across a variety of contexts. But it remains unclear whether this persuasive power advantages truth over falsehood, or if LLMs can promote...

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sjdm-tweets @sjdm-tweets.bsky.social · 12/01/2026

Today's SJDM Featured Paper is: Hagmann, D., Sajons, G. B., & Tinsley, C. H. (in press). Base rate neglect as a source of inaccurate statistical discrimination. Management Science. files.dhagmann.com/papers/2025_...

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sjdm-tweets @sjdm-tweets.bsky.social · 10/01/2026

Today's SJDM Featured Paper is: Atir S. & Dunning D. A. (in press). Learning more than you can know: Introductory education produces overly expansive self-assessments of knowledge. Management Science. tinyurl.com/AtirDunning-...

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sjdm-tweets @sjdm-tweets.bsky.social · 09/01/2026

Today's SJDM Featured Paper is: DeKay, M. L. (in press). Risky-choice framing effects persist when option descriptions are matched and complete: A replication and extension of DeKay and Dou (2024). Psychonomic Bulletin & Review. osf.io/preprints/ps...

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sjdm-tweets @sjdm-tweets.bsky.social · 08/01/2026

Today's SJDM Featured Paper is: Dietvorst, B. J. (in press). Understanding people's preferences for predictions: People prioritize being right over minimizing how wrong they are in expectation. Management Science. doi.org/10.1287/mnsc...

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sjdm-tweets @sjdm-tweets.bsky.social · 07/01/2026

Today's SJDM Featured Paper is: Vaz, A., Ingendahl, M., Mata, A., & Alves, H. (2025). "Stop the Count!" – How reporting partial election results fuels beliefs in election fraud. Psychological Science, 36(8), 676-688. doi.org/10.1177/0956...

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Gordon Pennycook @gordpennycook.bsky.social · 17/12/2025

The ad collab emerged from a discussion with Don at @sjdm-tweets.bsky.social about this paper: www.cambridge.org/core/journal... In the paper, Jabin & I try to address a longstanding problem for measuring overconfidence: One's level of overconfidence is highly dependent on the task in question.

cambridge.org

Individual differences in overconfidence: A new measurement approach | Judgment and Decision Making | Cambridge Core

Individual differences in overconfidence: A new measurement approach - Volume 19

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sjdm-tweets @sjdm-tweets.bsky.social · 31/12/2025

The Society for Judgment and Decision Making is pleased to announce that the latest newsletter is ready for download: sjdm.org/newsletters/ This issue contains announcements, conferences, and jobs!

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sjdm-tweets @sjdm-tweets.bsky.social · 17/12/2025

Congratulations to Hengchen Dai who is the winner of the 2026 Early Career Impact Award from the Federation of Associations in Behavioral and Brain Sciences! fabbs.org/about/early-...

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Nick Byrd, Ph.D. @byrdnick.com · 23/11/2025

Don also shared his template for declining review requests from journals that try to profit from our taxpayer-funded and volunteer #science: learnmoore.org/hotfresh.html That URL also links to a form to share your #HotFresh preprints, data, reviews, etc. to the @sjdm-tweets.bsky.social newsletter.

The template's text:

I object to providing my free labor to publishers that rely on the volunteer efforts of authors, reviewers, and editors, claim copyright over our work, restrict the dissemination of scientific knowledge, and then charge our own libraries for access to it.

Although I appreciate the valuable role that journal publishers once played, the Internet age has largely eliminated the value of distributing paper journals. I wish I could publish all my work in open-access venues. Yet, perhaps like you, I find myself constrained by the current system while at the same time envisioning a better future. One way to help facilitate change is if individual editors or whole editorial teams move to open-access versions of old-fashioned paper journals. In case you or your editorial team has ever considered such a move, allow me to offer my enthusiastic support.

With apologies for being difficult,
Don Moore

The Drake no/yes meme, except Drake is replaced with an anthropomorphized mouse (a la Stuart little).

This AI-generated mouse appeared throughout the slides as a personification of various points about the challenges scientists face, including the increasing politicization of science funding. The mouse first appeared early in the address when Don reminded us of the "transgender mice" remark from the 47th POTUS.

The QR code for Don Moore's review declination template on the final slide.

The Q&A included pushback:
 Danny Oppenheimer: Would more open publishing allow more misinformation by allowing more junk science to be posted along good science?

- Reply: the status quo is preprints and science reporting is not good. Hard to know if openness actually makes things much worse. 

(I didn't see who asked): How else will early career people get hired and promoted if not by prestigious publications? Wasn't Don's early work on overconfidence made famous by a paywalled, profit-seeking Psychology journal article?  

- Reply: Don still feels uncomfortable about that paper’s home. And there are better forms of prestige, such as the prestige one gets for prioritizing rigorous open science, changing one’s mind in light of better evidence, etc.

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sjdm-tweets @sjdm-tweets.bsky.social · 23/11/2025

If you want to submit your research to HotFresh Research News or find a boilerplate letter to refuse reviewing for closed journals, visit this link learnmoore.org/hotfresh.html

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sjdm-tweets @sjdm-tweets.bsky.social · 23/11/2025

Don Moore kicking off the 2025 Presidential Address at the Society for Judgment and Decision Making conference

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sjdm-tweets @sjdm-tweets.bsky.social · 23/11/2025

For Sunday at the SJDM conference, please note the following changes to the program!

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Nick Byrd, Ph.D. @byrdnick.com · 23/11/2025

Before #MSFT offered "Facilitator" in Teams meetings, @dggoldst.bsky.social et al. developed something similar. People preferred their #statusQuo, but #AI facilitation - made people more open to both human and #LLM facilitation. - didn't seem to impact decisions More via doi.org/10.48550/arX...

Experimental conditions:
- No facilitation
- Human facilitation
- LLM facilitation

Human and LLM facilitators receive the same instructions

1. Guiding message
"People may have different information about what is being discussed in this meeting, so encourage everyone to share all of the relevant information they have.'

2. Information about the facilitator role
"As a facilitator for this meeting, your specific role is help the group make a decision by, first, making sure that everyone is heard from and shares what they know and, second, acting as a scoreboard and keeping track of pros and cons.*

Forecasted and actual decisions were similar across conditions.

See Figure 7 from the preprint (URL/DOI in the post).

Survey question: "You completed this task with a [human, Al, none] facilitator. If you were to repeat this task, which would you prefer?"

"Users seem to prefer what they know, whatever it may be"

"Experiencing LLM facilitation seems to yield interest in both facilitators, in a way that human facilitation doesn't."

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Nick Byrd, Ph.D. @byrdnick.com · 23/11/2025

Agreement can feel nice, but it may discourage reflection and understanding. Agreeing with someone about a policy (vs disagreeing) predicted lower - odds of asking, "Why?"  - accuracy in predicting their preferences Follow Zhiyang (Bella) et al for the pub alert: scholar.google.com/citations?us...

People Who Agreed on a Position Varied in Their Reasons

Position: "We should increase restrictions on foreign ownership of U.S. land and businesses."

Reasons:
- Limits foreign influence 22%
- Protects national sovereignty 30%
- Preserves economic control 25%
- Prevents land exploitation and misuse 20%
- Others 3%

Study 1: Do We Ask Why When We Agree?

Plot of the percentage of people that asked why (y-axis) by agreement (x-axis):

When partner agreed: 25%
When partners disagreed: 70%

Study 3: The Learning Loss Incurred by Not
Asking Why When We Agree

When People Agreed, They Were Worse at Predicting Their Counterpart's Future Preference: 48% versus 37% (p = 0.023).

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Nick Byrd, Ph.D. @byrdnick.com · 22/11/2025

How do people think about using #AI for #writing? Andras Molnar and Jiaqi Zhu found people didn’t suspect #LLM use without cues or reminders, which DID hinder impressions (2 experiments, N = 1301, 8 contexts). Follow for the pub alert: www.researchgate.net/profile/Jiaq... #jobMarket #socialPsych

How Al may erode social signals in writing
Three qualities make an observable signal to be perceived as credible:

1. Costly
Not anymore. Generating content has become trivially easy, and requires less energy: 130-1500 times less CO2/page of text than human writers (Tomlinson et al., 2024)

2. Hard to fake
Not anymore. Generative Al is remarkably effective at creating personalized, context-dependent content

3. Verifiable
Not anymore. We generally lack the tools to reliably detect Al-generated content (Köbis & Mossink, 2021; Kreps et al.,
2022; Sadasivan et al., 2023; Tang et al., 2023; Jakesch et al.,
2023; Gao et al., 2024; Porter & Machery, 2024)

Uncertainty & Limited Attention

What if audiences are aware of potential Al use but remain uncertain about actual Al use? (a classic signaling problem)

What if they don't even think about it? (i.e., default judgments)

Attentional constraints, bounded rationality (Simon, 1955; Slovic, 1972)
- "What you see is all there is": Decision problems are constrained by their presentation and what is most salient in our minds (Kahneman, 2011; Enke, 2020)

Does participants' own use of genAl moderate these effects?

"Al disclosure penalty" (human vs. Al): YES

Default judgments (human vs. no info): NO

The slide shows a plot showing "overall social impression" (y-axis) by message source (x-axis: no info, human-written, uncertain, and AI-generated). The AI-generated source cue had a huge negative impact (d > 1, p < 0.001).

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Nick Byrd, Ph.D. @byrdnick.com · 22/11/2025

Rating scales are vulnerable to biases that reduce predictive power. Can #languageModels do better by analyzing open-ended responses? @adaaka.bsky.social found such #LLM measures were more predictive and less vulnerable to #bias in 7 preregistered studies (N = 2326). #psychometrics #tech #PhilSci

Can open-ended responses, analyzed with LLMs, help overcome these challenges?
→ Open-ended format does not bring certain information to mind. participants generate the content they consider most important
→ This may help minimize order effects and increase predictive power
→ A single open-ended question can contain multiple psychological dimensions
→ LLMs can extract latent structure at scale

(e.g., protocol analyses as discussed by Ericsson & Simon, 1993)

From a within-subject design:
- corr(global life satisfaction rating, GPT inferred life satisfaction) = 0.76
- corr(global life satisfaction rating, relationship satisfaction rating) = 0.46
- corr(global life satisfaction rating, GPT-inferred relationship satisfaction) = 0.58

From a between-subject design:
- corr(global life satisfaction rating, GPT inferred life satisfaction) = 0.63
- corr(global life satisfaction rating, GPT-inferred relationship satisfaction) = 0.52

Other domains show similar effects:

→ Rating life satisfaction and 8 dimensions of life satisfaction (within subjects design with Stanford students)
- Largest effect for: health (r = 0.60 vs r = 0.77) and academic life (r = 0.57 vs. r = 0.74)

→ Future outlook of Al (between subjects design on Prolific)
- Largest effect for: inequality concerns (r= 0.43 vs. r = 0.76)

→ Smartphone satisfaction (between subjects design on Prolific)
- Largest effect for price (r= 0.30 vs. r = 0.64)
- No difference for battery concerns

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Nick Byrd, Ph.D. @byrdnick.com · 22/11/2025

Another way to see inside the black box of #decisionMaking involves recording people thinking aloud during decisions. @aaronlob.bsky.social and @renatofrey.mstdn.science.ap.brid.gy had #AI predict people’s perceptions from their verbalizations (N = 178). The correlations ranged from ≅0.3 to ≅0.6.

Research question 2: Can large language models predict the perceptions people reported about the real-life decisions they verbalized?

An illustration of how a language model can "directly" infer a decision-makers self-reported perceptions based solely on the decision-makers verbalization of the decision (and not the self-reported perception).

The three methods used to have language models infer people's self-reported perceptions from the decision-makers think-aloud recording of the decision: direct, feature extraction, and embeddings.

Visualization of the correlations between model-predicted and self-reported perceptions (left to right) by method (top to bottom). Correlations range from 0.26 to 0.59.

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Nick Byrd, Ph.D. @byrdnick.com · 22/11/2025

Many medical systems remind patients about their #health gaps with text messages. Would adding info about the risks or available benefits increase response rates? Not in the experiments from Jose Arellano Martorellet et al.! Follow to get the publication alert: scholar.google.com/citations?us...

RCTs 2-3: Alerting patients about health gaps

Context: Prompting primary care patients with overdue preventive health gaps.
- Cancer screenings
- Diabetes exams
- Annual physical exam
- Blood pressure control

Impact of reminders on patients who have not opened the letter after the initial notification.

Pre-registrations on ClinicalTrials.gov: NCT05791942, NCT05979987

Conclusions
• Field evidence of information avoidance in response to health messaging.
• Making health messages more attention-grabbing by increasing their importance may come with a psychological cost that unintentionally backfire

Implications
• Practical implications for healthcare systems using health-related outreaches
• Implications for the ongoing debate on nudges in policy

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Nick Byrd, Ph.D. @byrdnick.com · 22/11/2025

Many cognitive scientists change decisions; few look in the black box to see HOW. Steph Smith demoed such #processTracing ...in #Qualtrics! …without any coding! Find everything you need at github.com/QMT-code/QMT Follow her work at www.researchgate.net/profile/Step... #eyeTracking #mouseTracking

Qualtrics Mouse Tracing (QMT) may be the only scalable, code-free way to track mouse activity during experiments, according to Steph Smith (U Chicago).

"If you want complete and total flexibility for your study design, we have a step-by-step version with extensive documentation!" – Steph Smith (U Chicago)

Does the search pattern predict choice? (Yes)
• Outcome: Proportion of choices for higher expected-value option
• Predictor: Payne Index {option-wise transitions - attribute-wise transitions}

Steph Smith's collaborator is David Dolifka. Find their code, Qualtrics files, etc. on GitHub with the QR code or the URL in the post.

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sjdm-tweets @sjdm-tweets.bsky.social · 23/11/2025

Hooray! Katy, we need a megastudy to get people to tag @sjdm-tweets.bsky.social here and @sjdm_tweets on X

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Lucia Savadori @luciasavadori.bsky.social · 23/11/2025

@sjdm-tweets.bsky.social Why does "1-in-X" (e.g., 1 in 50 vs. 20 in 1000) feel riskier? The answer: It's the availability heuristic! We found that the 1-in-X ratio is easier to mentally visualize and recall examples for. Risk Communication Poster at #SJDM2025 in Denver, Colorado!

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sjdm-tweets @sjdm-tweets.bsky.social · 22/11/2025

Repost this to let people know you are at SJDM 2025 in Denver! Tag @sjdm-tweets.bsky.social if you would like us to repost stuff that you post! #SJDM2025

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Margaret Echelbarger @bskybymidge.bsky.social · 19/11/2025

If you're attending @sjdm-tweets.bsky.social or @psychonomicsociety.bsky.social this week, do not print your poster on site at the convention center -- it's $100 more! There's a FedEx a short walking distance away. Please tell your students!!

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Nick Byrd, Ph.D. @byrdnick.com · 22/11/2025

🧠🏔️ Below I'll share mine and others' presentations from the Society for Judgment and Decision Making conference in #Denver. Did you attend a session I missed? Did I fail to tag a presenter? Feel free to add to the thread! Long live #openAccess conferencing. #SJDM #SJDM25 @sjdm-tweets.bsky.social

Byrd, N. (2025, July). Map My Words—Using Waitlist Controlled Trials To Test Whether Argument Mapping Improves Individuals’ Persuasive Writing or Critical Thinking. Experimental Argument Analysis, University of East Anglia. https://www.researchgate.net/publication/390977878

Abstract. Argument mapping is the practice of diagraming the logical relationships between each proposition in an argument, including objections and counter-objections. Some studies find that courses that teach students how to map arguments exhibit better critical thinking and persuasive writing than students in other courses. These promising results are sometimes from surveyors of argument mapping goods and services, and they garner plenty of attention in fields that champion careful thinking and communication. However, the total evidence is mixed, null results are often never published, and many promising studies have not controlled for known confounds. Two waitlist control trials (N = 83) attempted to address these issues; they detected no benefits of argument map training within or between groups (p > 0.13). Rather, variance in outcomes was explained by enrollment in the instructor’s other courses, prior academic achievement, and — most robustly — engagement in flipped classroom activities. These findings raise questions about whether benefits previously attributed to argument mapping in less controlled studies were caused by other factors that were already known to produce such benefits. Implications for pedagogy, course assessment, and the science of learning are discussed.

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sjdm-tweets @sjdm-tweets.bsky.social · 22/11/2025

Jon Kleinberg gave a great keynote at the Society for Judgment and Decision Making 2025 conference in Denver. Tag @sjdm-tweets.bsky.social if you would like us to repost you! #SJDM2025

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sjdm-tweets @sjdm-tweets.bsky.social · 05/11/2025

Today's HotFresh recommended paper is: Yang, A. X., & Teow, J. (2025). Framing affects postdecision preferences through self-preference inferences (and probably not dissonance). Journal of Experimental Psychology: General, 154(2), 574–595. doi.org/10.1037/xge0...

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sjdm-tweets @sjdm-tweets.bsky.social · 03/11/2025

Today's HotFresh recommended paper is: Maier, M., Harris, A. J. L., Kellen, D., & Singmann, H. (2025). Decision making under extinction risk. Cognitive Psychology, 159. doi.org/10.1016/j.co...

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Redirecting

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sjdm-tweets @sjdm-tweets.bsky.social · 03/11/2025

Today's HotFresh recommended paper is: Duckworth et al (2025). A national megastudy shows that email nudges to elementary school teachers boost student math achievement, particularly when personalized. PNAS, 122(13), e2418616122. doi.org/10.1073/pnas...

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sjdm-tweets @sjdm-tweets.bsky.social · 01/11/2025

Today's HotFresh recommended paper is: Naborn, J., & Bogard, J. E. (2025). EXPRESS: The Pick-the-Winner-Picker Heuristic: Preference for Categorically Correct Forecasts. Journal of Marketing Research. doi.org/10.1177/0022...

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sjdm-tweets @sjdm-tweets.bsky.social · 30/10/2025

Today's HotFresh recommended paper is: Sun, C., & LeBoeuf, R. A. (2025). Prediction that conflicts with judgment: The low absolute likelihood effect. Journal of Experimental Psychology: General. psycnet.apa.org/record/2025-...

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APA PsycNet

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sjdm-tweets @sjdm-tweets.bsky.social · 28/10/2025

Today's HotFresh recommended paper is: Heck, P. R., Benjamin, D. J., Simons, D. J., & Chabris, C. F. (2025). Overconfidence Persists Despite Years of Accurate, Precise, Public, and Continuous Feedback: Two Studies of Tournament Chess Players. doi.org/10.1177/0956...

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sjdm-tweets @sjdm-tweets.bsky.social · 22/10/2025

Today's HotFresh recommended paper is: Gaertig, C., & Simmons, J. P. (2025). Why (and When) Are Uncertain Price Promotions More Effective Than Equivalent Sure Discounts? Journal of Consumer Research. doi.org/10.1093/jcr/...

doi.org

Validate User

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sjdm-tweets @sjdm-tweets.bsky.social · 22/10/2025

Today's HotFresh recommended paper is: Pleskac, T. J., Kyung, E. J., Chapman, G. B., & Urminsky, O. (2025). Blinded versus Unblinded Review: A Field Study on the Equity of Peer-Review Processes. Management Science. doi.org/10.1287/mnsc...

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Blinded versus Unblinded Review: A Field Study on the Equity of Peer-Review Processes | Management Science

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sjdm-tweets @sjdm-tweets.bsky.social · 17/10/2025

Today's HotFresh recommended paper is: Dorison, C. A., & Charlesworth, T. E. S. (2025). What Is Rationality, Whom Is It Ascribed To, and Why Does It Matter? Evidence From Internet Text for 66 Social Groups and 101 Occupations. Psychological Science, 36(9), 713-731. doi.org/10.1177/0956...

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sjdm-tweets @sjdm-tweets.bsky.social · 18/07/2025

The sixth HotFresh recommended paper is: Mirny, D. J., & Spiller, S. A. (2025) Source memory is more accurate for opinions than for facts, Journal of Consumer Research. academic.oup.com/jcr/advance-...

academic.oup.com

Source Memory Is More Accurate for Opinions than for Facts

Abstract. Effective communication relies on consumers remembering, sharing, and applying relevant information. Source memory, the ability to link a claim t

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sjdm-tweets @sjdm-tweets.bsky.social · 17/07/2025

The 5th HotFresh recommended paper is: Kirgios, E. L., Silver, I., & Chang, E. H. (2025) Does communicating measurable diversity goals attract or repel historically marginalized job applicants? Evidence from the lab and field, J Experimental Psychology: General psycnet.apa.org/fulltext/202...

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APA PsycNet

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