Stephan Lewandowsky

Misinformation and Its Correction Continued Influence and Successful Debiasing

The widespread prevalence and persistence of misinformation in contemporary societies, such as the false belief that there is a link between childhood vaccinations and autism, is a matter of public concern. For example, the myths surrounding vaccinations, which prompted some parents to withhold immunization from their children, have led to a marked increase in vaccine-preventable disease, as well as unnecessary public expenditure on research and public-information campaigns aimed at rectifying the situation. We first examine the mechanisms by which such misinformation is disseminated in society, both inadvertently and purposely. Misinformation can originate from rumors but also from works of fiction, governments and politicians, and vested interests. Moreover, changes in the media landscape, including the arrival of the Internet, have fundamentally influenced the ways in which information is communicated and misinformation is spread. We next move to misinformation at the level of the individual, and review the cognitive factors that often render misinformation resistant to correction. We consider how people assess the truth of statements and what makes people believe certain things but not others. We look at people’s memory for misinformation and answer the questions of why retractions of misinformation are so ineffective in memory updating and why efforts to retract misinformation can even backfire and, ironically, increase misbelief. Though ideology and personal worldviews can be major obstacles for debiasing, there nonetheless are a number of effective techniques for reducing the impact of misinformation, and we pay special attention to these factors that aid in debiasing. We conclude by providing specific recommendations for the debunking of misinformation. These recommendations pertain to the ways in which corrections should be designed, structured, and applied in order to maximize their impact. Grounded in cognitive psychological theory, these recommendations may help practitioners—including journalists, health professionals, educators, and science communicators—design effective misinformation retractions, educational tools, and public-information campaigns.

An endogenous distributed model of ordering in serial recall

We introduce a distributed model of memory for serial order, called SOB, that produces ordered serial recall by relying on encoding and retrieval processes that are endogenous to the model. SOB explains the basic shape of the serial position curve, the pattern of errors during recall (including the balance between transpositions, omissions, intrusions, and erroneous repetitions), the effects of list length on the distribution of errors, the overall level of recall and response latency, and the effects of natural language frequency on recall performance. In addition, contrary to several recent suggestions, SOB demonstrates that distributed representations can support unambiguous recall, selective response suppression, and novelty-sensitive encoding.

NASA Faked the Moon Landing—Therefore, (Climate) Science Is a Hoax: An Anatomy of the Motivated Rejection of Science

Although nearly all domain experts agree that carbon dioxide emissions are altering the world’s climate, segments of the public remain unconvinced by the scientific evidence. Internet blogs have become a platform for denial of climate change, and bloggers have taken a prominent role in questioning climate science. We report a survey of climate-blog visitors to identify the variables underlying acceptance and rejection of climate science. Our findings parallel those of previous work and show that endorsement of free-market economics predicted rejection of climate science. Endorsement of free markets also predicted the rejection of other established scientific findings, such as the facts that HIV causes AIDS and that smoking causes lung cancer. We additionally show that, above and beyond endorsement of free markets, endorsement of a cluster of conspiracy theories (e.g., that the Federal Bureau of Investigation killed Martin Luther King, Jr.) predicted rejection of climate science as well as other scientific findings. Our results provide empirical support for previous suggestions that conspiratorial thinking contributes to the rejection of science. Acceptance of science, by contrast, was strongly associated with the perception of a consensus among scientists.

Forgetting in Immediate Serial Recall : Decay, Temporal Distinctiveness, or Interference?

Three hypotheses of forgetting from immediate memory were tested: time-based decay, decreasing temporal distinctiveness, and interference. The hypotheses were represented by 3 models of serial recall: the primacy model, the SIMPLE (scale-independent memory, perception, and learning) model, and the SOB (serial order in a box) model, respectively. The models were fit to 2 experiments investigating the effect of filled delays between items at encoding or at recall. Short delays between items, filled with articulatory suppression, led to massive impairment of memory relative to a no-delay baseline. Extending the delays had little additional effect, suggesting that the passage of time alone does not cause forgetting. Adding a choice reaction task in the delay periods to block attention-based rehearsal did not change these results. The interference-based SOB fit the data best; the primacy model overpredicted the effect of lengthening delays, and SIMPLE was unable to explain the effect of delays at encoding. The authors conclude that purely temporal views of forgetting are inadequate.

No temporal decay in verbal short-term memory

Many models of short-term memory (STM) ascribe an important role to temporal decay and forgetting because of the passage of time alone. We argue against decay as the primary form of forgetting from STM, and suggest that new experimental methodologies and recent models provide new perspectives on the old issue of the causes of forgetting. We show that several classic sources of evidence for time-based forgetting can be re-interpreted in terms of an interference-based view, and that new experiments provide compelling evidence against decay. We conclude that progress requires moving beyond demonstrations of qualitative effects and focusing instead on testing quantitative predictions of models.

Time does not cause forgetting in short-term serial recall

Time-based theories expect memory performance to decline as the delay between study and recall of an item increases. The assumption of time-based forgetting, central to many models of serial recall, underpins their key behaviors. Here we compare the predictions of time-based and event-based models by simulation and test them in two experiments using a novel manipulation of the delay between study and retrieval. Participants were trained, via corrective feedback, to recall at different speeds, thus varying total recall time from 6 to 10 sec. In the first experiment, participants used the keyboard to enter their responses but had to repeat a word (called thesuppressor) aloud during recall to prevent rehearsal. In the second experiment, articulation was again required, but recall was verbal and was paced by the number of repetitions of the suppressor in between retrieval of items. In both experiments, serial position curves for all retrieval speeds overlapped, and output time had little or no effect. Comparative evaluation of a time-based and an event-based model confirmed that these results present a particular challenge to time-based approaches. We conclude that output interference, rather than output time, is critical in serial recall.

The pivotal role of perceived scientific consensus in acceptance of science

Public concern about anthropogenic global warming has been declining despite the scientific consensus on the issue. It is still unknown whether experts’ consensus determines people’s beliefs, and it is not clear if public perception of consensus overrides worldviews known to foster rejection of anthropogenic climate change. New research shows that information about scientific consensus increases acceptance of anthropogenic global warming and neutralizes the effect of worldviews.

The role of conspiracist ideation and worldviews in predicting rejection of science.

Background Among American Conservatives, but not Liberals, trust in science has been declining since the 1970s. Climate science has become particularly polarized, with Conservatives being more likely than Liberals to reject the notion that greenhouse gas emissions are warming the globe. Conversely, opposition to genetically-modified (GM) foods and vaccinations is often ascribed to the political Left although reliable data are lacking. There are also growing indications that rejection of science is suffused by conspiracist ideation, that is the general tendency to endorse conspiracy theories including the specific beliefs that inconvenient scientific findings constitute a “hoax.” Methodology/Principal findings We conducted a propensity weighted internet-panel survey of the U.S. population and show that conservatism and free-market worldview strongly predict rejection of climate science, in contrast to their weaker and opposing effects on acceptance of vaccinations. The two worldview variables do not predict opposition to GM. Conspiracist ideation, by contrast, predicts rejection of all three scientific propositions, albeit to greatly varying extents. Greater endorsement of a diverse set of conspiracy theories predicts opposition to GM foods, vaccinations, and climate science. Conclusions Free-market worldviews are an important predictor of the rejection of scientific findings that have potential regulatory implications, such as climate science, but not necessarily of other scientific issues. Conspiracist ideation, by contrast, is associated with the rejection of all scientific propositions tested. We highlight the manifold cognitive reasons why conspiracist ideation would stand in opposition to the scientific method. The involvement of conspiracist ideation in the rejection of science has implications for science communicators.

The Components of Working Memory Updating: An Experimental Decomposition and Individual Differences

Working memory updating (WMU) has been identified as a cognitive function of prime importance for everyday tasks and has also been found to be a significant predictor of higher mental abilities. Yet, little is known about the constituent processes of WMU. We suggest that operations required in a typical WMU task can be decomposed into 3 major component processes: retrieval, transformation, and substitution. We report a large-scale experiment that instantiated all possible combinations of those 3 component processes. Results show that the 3 components make independent contributions to updating performance. We additionally present structural equation models that link WMU task performance and working memory capacity (WMC) measures. These feature the methodological advancement of estimating interindividual covariation and experimental effects on mean updating measures simultaneously. The modeling results imply that WMC is a strong predictor of WMU skills in general, although some component processes-in particular, substitution skills-were independent of WMC. Hence, the reported predictive power of WMU measures may rely largely on common WM functions also measured in typical WMC tasks, although substitution skills may make an independent contribution to predicting higher mental abilities. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

Iterated learning: Intergenerational knowledge transmission reveals inductive biases

Cultural transmission of information plays a central role in shaping human knowledge. Some of the most complex knowledge that people acquire, such as languages or cultural norms, can only be learned from other people, who themselves learned from previous generations. The prevalence of this process of “iterated learning” as a mode of cultural transmission raises the question of how it affects the information being transmitted. Analyses of iterated learning utilizing the assumption that the learners are Bayesian agents predict that this process should converge to an equilibrium that reflects the inductive biases of the learners. An experiment in iterated function learning with human participants confirmed this prediction, providing insight into the consequences of intergenerational knowledge transmission and a method for discovering the inductive biases that guide human inferences.