Knew It

Kevin Lewis

August 02, 2022

When linguistic uncertainty spreads across pieces of information: Remembering facts on the news as speculation
Ann-Kathrin Brand et al.
Journal of Experimental Psychology: Applied, forthcoming

Modern media enable rapid reporting that does not refer to facts alone but is often interspersed with unconfirmed speculations. Whereas previous research has concentrated primarily on how unconfirmed contents might propagate, potential memory effects of reporting confirmed facts among speculations have so far been widely disregarded. Across four experiments, we show that the presence of speculative news (indexed by uncertainty cues such as “might”) can reduce the remembered certainty of unrelated facts. The participants read headlines with exclusively speculative news, exclusively factual news, or a mixture of both. Our results indicate that uncertainty cues spread onto one’s recollection of unrelated facts after having read a mixture of facts and speculations. This tendency persisted when both types of news were presented sequentially (e.g., factual news first), suggesting that the presence of speculative news does not specifically affect encoding -- but can overshadow memories of facts in retrospect. Further, the tendency to misremember facts as speculations emerged even when the proportion of speculations among factual news was low (6/24 headlines) but increased linearly with the number of speculations intermingled. Given the widespread dissemination of speculative news, this bias poses a challenge in effectively getting confirmed information across to readers. 

I Share, Therefore I Know? Sharing Online Content -- Even Without Reading It -- Inflates Subjective Knowledge
Adrian Ward, Frank Zheng & Susan Broniarczyk
University of Texas Working Paper, June 2022

Billions of people across the globe use social media to acquire and share information. A large and growing body of research examines how consuming online content affects what people know. The present research investigates a complementary, yet previously unstudied question: how might sharing online content affect what people think they know? We posit that sharing may inflate subjective knowledge through a process of internalized social behavior. Sharing signals expertise; thus, sharers can avoid conflict between their public and private personas by coming to believe that they are as knowledgeable as their posts make them appear. We examine this possibility in the context of “sharing without reading,” a phenomenon that allows us to isolate the effect of sharing on subjective knowledge from any influence of reading or objective knowledge. Six studies provide correlational (study 1) and causal (studies 2, 2a) evidence that sharing -- even without reading -- increases subjective knowledge, and test the internalization mechanism by varying the degree to which sharing publicly commits the sharer to an expert identity (studies 3-5). A seventh study investigates potential consequences of sharing-inflated subjective knowledge on downstream behavior.

Rewarding Numbers: Quantification Premia and Evaluative Convergence
Katariina Mueller-Gastell
Socius: Sociological Research for a Dynamic World, June 2022

The author advances the theory that when evaluation bears high stakes and is subject to high uncertainty of quality, a greater presence of numbers in the evaluated materials positively influences the evaluator’s assessment of the quality of the evaluated object and leads to less variance in the overall assessment of quality by evaluators. The author explores these ideas in a case study of the MacArthur Foundation’s 2016–2017 $100 million winner-take-all grant competition for nonprofit organizations and tests them using judges’ numeric scores and comments together with information from the application materials, tax records, and previous funding histories of the applicant organizations. In this competition, organizations that included more numbers of any kind in their application materials received on average higher scores. Furthermore, the independent judges on the nondeliberative panel were more likely to give the applicants similar scores. Quantification thus both carries a premium — it predicts higher scores — and produces evaluative convergence.

Looming Large or Seeming Small? Attitudes Towards Losses in a Representative Sample
Jonathan Chapman et al.
NBER Working Paper, July 2022

We measure individual-level loss aversion using three incentivized, representative surveys of the U.S. population (combined N=3,000). We find that around 50% of the U.S. population is loss tolerant, with many participants accepting negative-expected-value gambles. This is counter to earlier findings — which mostly come from lab/student samples — and expert predictions that 70-90% of participants are loss averse. Consistent with the difference between our study and the prior literature, loss aversion is more prevalent in people with high cognitive ability. Loss-tolerant individuals are more likely to report recent gambling and to have experienced financial shocks. These results support the general hypothesis that individuals value gains and losses differently, although the tendency in a large proportion of the population to emphasize gains over losses is an overlooked behavioral phenomenon. 

Confidently at your service: Advisors alter their stated confidence to be helpful
Uriel Haran et al.
Organizational Behavior and Human Decision Processes, July 2022

When giving advice, people seek to inform others, but also help them reach a decision. We investigate how the motivation to help affects the confidence people express when advising others. We propose that assuming the role of advisor instigates a desire to help the advisee decide more easily. This desire in turn leads advisors to communicate higher confidence than they actually feel, provided that the environment is sufficiently certain, and thus the risk of misleading the advisee is low. We test our predictions in five studies, using experimental tasks (Studies 1–3), a survey of experienced professionals (Study 4) and an organizational scenario (Study 5). We find that in high-certainty environments, people convey higher confidence when providing advice than private judgments. This effect is driven by the motivation of advisors to facilitate advisees’ decision making: the higher advisors’ desire to help, the more pronounced the effect on their stated confidence.

What is a “likely” amount? Representative (modal) values are considered likely even when their probabilities are low
Karl Halvor Teigen, Marie Juanchich & Erik Løhre
Organizational Behavior and Human Decision Processes, July 2022 

Research on verbal probabilities and standard scales issued by national and international authorities suggest that only events with probabilities above 60% should be labelled “likely”. We find, however, that when people apply this term to continuous variables, like expected costs, it describes the most likely (modal) outcome or interval, regardless of actual probabilities, which may be quite small. This was demonstrated in six studies in which lay participants (N = 2,228) were shown probability distributions from various domains and asked to generate or to select “likely” outcome intervals. Despite having numeric and graphically displayed information available, participants judged central, low-probability segments as “likely” (as opposed to equal or larger segments in the tails) and subsequently overestimated the chances of these outcomes. We conclude that high-probability interpretations of “likely” are only valid for binary outcomes but not for distributions of graded variables or multiple outcomes. 

(Just thinking of) uncertainty increases intolerance of uncertainty
Suzanne Parker & Anthony Ahrens
Journal of Individual Differences, forthcoming

Intolerance of uncertainty is a far-reaching — yet not widely examined — construct with clinical and nonclinical associations. The current study implemented a brief reflection on uncertainty hypothesized to increase tolerance of uncertainty. The group who engaged in the reflection (n = 50) was compared to an active control condition (n = 50). Results demonstrated the opposite of the primary hypothesis: simply reflecting on uncertainty significantly increased intolerance of uncertainty (vs. tolerance of uncertainty). Results also demonstrated that those higher in mindfulness were higher in tolerance of uncertainty, with the “nonreactivity” factor of mindfulness contributing unique variance. These findings suggest multiple factors that might contribute to both tolerance and intolerance of uncertainty. This study indicates that investigations of interventions that include training in mindfulness and its component of nonreactivity might be particularly warranted. 

Democratic Forecast: Small Groups Predict the Future Better Than Individuals and Crowds
Guillaume Dezecache et al.
Journal of Experimental Psychology: Applied, forthcoming 

Predictions pose unique problems. Experts regularly get them wrong, and collective solutions (such as prediction markets and super-forecaster schemes) do better but remain selective and costly. Contrary to the idea that face-to-face discussion hinders collective intelligence, social deliberation improves the resolution of general knowledge problems, with four consensually agreed answers outperforming the aggregate knowledge of 5,000 nondeliberating individuals. Could discussion help predict the future in an efficient, cheap, and inclusive way? We show that smaller groups of lay individuals, when organized, come up with better predictions than those they provide alone. Deliberation and consensus made individual predictions significantly more accurate. Aggregating as few as two consensual predictions did better than classical “wisdom of crowds” aggregation of 100 individual ones. Against the view that discussion can impair decision-making, our results demonstrate that collective intelligence of small groups and consensus-seeking improves accuracy about yet unknown facts, opening the avenue for efficient, inclusive, and inexpensive group forecasting solutions. 

Skew-adjusted extremized-mean: A simple method for identifying and learning from contrarian minorities in groups of forecasters
Ben Powell et al.
Decision, forthcoming

Recent work in forecast aggregation has demonstrated that paying attention to contrarian minorities among larger groups of forecasters can improve aggregated probabilistic forecasts. In those articles, the minorities are identified using “metaquestions” that ask forecasters about their forecasting abilities or those of others. In the present article, we explain how contrarian minorities can be identified without the metaquestions by inspecting the skewness of the distribution of the forecasts. Inspired by this observation, we introduce a new forecast aggregation tool called skew-adjusted extremized-mean and demonstrate its superior predictive power on a large set of geopolitical and general knowledge forecasting data.

On or Off Track: How (Broken) Streaks Affect Consumer Decisions
Jackie Silverman & Alixandra Barasch
Journal of Consumer Research, forthcoming

New technologies increasingly enable consumers to track their behaviors over time, making them more aware of their “streaks” – behaviors performed consecutively three or more times – than ever before. Our research explores how these logged streaks affect consumers’ decisions to engage in the same behavior subsequently. In seven studies, we find that intact streaks highlighted via behavioral logs increase consumers’ subsequent engagement in that behavior, relative to when broken streaks are highlighted. Importantly, this effect is independent of actual past behavior, and depends solely on how that behavior is represented within the log. This is because consumers consider maintaining a logged streak to be a meaningful goal in and of itself. In line with this theory, the effect of intact (vs. broken) logged streaks is amplified when consumers attribute a break in the streak to themselves rather than to external factors, and attenuated when consumers can “repair” a broken streak. Our research provides actionable insights for companies seeking to benefit from highlighting consumers’ streaks in various consequential domains (e.g., fitness, learning) without incurring a cost (e.g., reduced engagement or abandonment) when those streaks are broken. 

Is Psychological Science Self-Correcting? Citations Before and After Successful and Failed Replications
Paul von Hippel
Perspectives on Psychological Science, forthcoming

In principle, successful replications should enhance the credibility of scientific findings, and failed replications should reduce credibility. Yet it is unknown how replication typically affects the influence of research. We analyzed the citation history of 98 articles. Each was published by a selective psychology journal in 2008 and subjected to a replication attempt published in 2015. Relative to successful replications, failed replications reduced citations of replicated studies by only 5% to 9% on average, an amount that did not differ significantly from zero. Less than 3% of articles citing the original studies cited the replication attempt. It does not appear that replication failure much reduced the influence of nonreplicated findings in psychology. To increase the influence of replications, we recommend (a) requiring authors to cite replication studies alongside the individual findings and (b) enhancing reference databases and search engines to give higher priority to replication studies. 

The aesthetic quality model: Complexity and randomness as foundations of visual beauty by signaling quality
Dario Krpan & Wijnand van Tilburg
Psychology of Aesthetics, Creativity, and the Arts, forthcoming

Visual complexity has been identified as a fundamental property that shapes the beauty of visual images. However, its exact influence on beauty judgments, and the mechanism behind this influence, remain a conundrum. In the present article, we developed and empirically evaluated the Aesthetic Quality Model, which proposes that the link between complexity and beauty depends on another key visual property—randomness. According to the model, beauty judgements are determined by an interaction between these two properties, with more beautiful patterns featuring comparatively high complexity and low randomness. The model further posits that this configuration of complexity and randomness leads to higher beauty because it signals quality (i.e., creativity and skill). Study 1 confirmed that black and white binary patterns were judged as more beautiful when they combined high complexity with low randomness. Study 2 replicated these findings using an experimental method and with a more representative set of patterns, and it pointed to quality attribution as a candidate mechanism underlying the beauty judgements. Studies 3 and 4 confirmed these findings using experimental manipulation of the mechanism. Overall, the present research supports the aesthetic quality model, breaking new ground in understanding the fundamentals of beauty judgment.


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