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Authors, Titles, Abstracts, Presentations

IMPORTANT:
The ASIC speakers and attendees, whether world famous scientists or graduate students, expect to hear, and are used to hearing state-of-the-art leading-edge research. However: ASIC is an interdisciplinary conference and always has a diverse audience, Thus DO NOT give a talk aimed at your co-authors, laboratory colleagues, or even experts in your research domain: GIVE A TALK ACCESSIBLE TO AND UNDERSTANDABLE BY THE DIVERSE ASIC ATTENDEES.

Listing by speaker

[To be added later]

Author 1	Popov, Vencislav University of Zurich
Title	If God Handed Us the Ground-Truth Theory of Memory, How Would We Recognize It?
Abstract	What makes a scientific theory convincing? We have many formal models of human memory, but no agreement about which is the right one. If anything, we agree that they are all wrong. Despite important theoretical milestones, models of human memory are fragmented, most often explaining single paradigms or memory types; they are incompatible with each other; they lack precision in their predictions, and due to our current parameter fitting approach, they are often little more than proof of concept exercises. I fear that our current way of developing and evaluating theoretical models of memory and cognition is getting us nowhere, because we have no clear goal. To address this, I propose the Principle of Completeness: we will be convinced by a theory of memory only when it is able to make precise point predictions for individual people’s behavior in any new memory task, manipulation, or paradigm we could construct, without refitting parameters to do so or only by estimating its parameters for each individual on an independent standardized battery of tests. Such a theory would not only be able to accurately describe lab-based empirical effects but would also be practically useful. I highlight how some of our current model development and evaluation practices might be holding us back and outline some important empirical steps necessary to evaluate theories by this standard. I will conclude with a discussion about the implications for the broader theory crisis in psychology.

Speaker	Allen, Colin
Author 1	Allen, Colin Pittsburgh / UCSB
Title	Suffering: A Neurofunctional Account
Abstract	I argue for a neural systems account of the psychological phenomenon of suffering as distinct from (but related to) strongly negative affective or emotional states. This account potentially explains some psychologically puzzling phenomena, and supports important distinctions among the types of suffering experienced by animals with very different temporal horizons.

Speaker	Aroyehun, Segun
Author 1	Aroyehun, Segun University of Konstanz
Author 2	Simchon, Almog University of Bristol
Author 3	Garcia, David University of Konstanz
Author 4	Carrella, Fabio University of Bristol
Author 5	Lasser, Jana Graz University of Technology
Author 6	Lewandowsky, Stephan University of Bristol
Title	A computational approach to measure “ontology of truth” from text
Abstract	A recent analysis of “ontology of truth” proposed two distinct conceptions of truth. One relying on evidence and the other rejecting the role of evidence (akin to populism). Can we reliably measure this construct from text? We propose to measure these dimensions of the ontology from text using a computational approach. Different from existing approaches that attempt to distinguish populist from non-populist rhetoric with either lexicon or statistical approaches, we present an approach that combines dictionaries with distributed vector representations (embeddings). We posit that evidence-free and evidence-based discourse are on a continuum and derive a score that situates a given sentence on a truth-populism scale. We validate this measure and examine the temporal variations of this score on aggregate across a number of textual sources covering public discourse.

Speaker	Bonnen, Kathryn
Author 1	Bonnen, Kathryn Indiana University
Author 2	Mathis, Jonathan S Northeastern University
Author 3	Muller, Karl University of Texas
Author 4	Hayhoe, Mary University of Texas
Title	Visually guided walking in humans: Natural statistics & Binocular vision
Abstract	Coordination between visual and motor processes druing walking is critical for the selection of stable footholds when walking in rough terrains. In this talk I will: 1) introduce the visuomotor control problem of walking, 2) discuss the natural statistics of retinal motion during walking, and 3) the impact of reduced vision on visuomotor control. Examining the natural statistics of retinal motion during walking, reveals that the gait and eye movement patterns have a huge impact on the pattern of retinal optic flow. Gait introduces vertical translation components to optic flow, while eye movements off of the direction of travel result in rotations. The resulting retinal optic flow patterns are far from the idealized Gibsonian optic flow pattern. Finally, our subsequent work has examined the impact of reduced binocular vision on in the visuomotor control of walking. In the face of increased uncertainty (reduced vision in one eye) they shift their gaze closer to their body, independent of walking speed.

Speaker	Brown, Gordon
Author 1	Huang, Zhihong University of Warwick
Author 2	Quispe-Torreblanca, Edika University of Leeds
Author 3	Brown, Gordon University of Warwick
Title	Nationalism, Income Inequality and Identity: Model and Data
Abstract	Rising nationalism threatens liberal democracy. At the same time, the adverse effects of income inequality on societal well-being are well documented. But what links economic factors such as income inequality, socio-economic factors such as relative deprivation, and intertwined cultural issues such as nationalism and populism? Here, following Shayo and others, we ascribe a central role to identity status. We develop a simple model in which agents maximise their utility by placing more or less weight on their individual and national identities according to circumstances. People with low-ranking incomes are assumed to suffer from increased relative deprivation when income inequality increases, and hence maximise their identity-status utility by increasing their national identification and reducing their individual-level identification. The model predicts that (a) specifically low-income individuals will become more nationalistic as income inequality increases, and (b) preferences for income redistribution can, apparently paradoxically, reduce as income inequality increases. Both of these predictions are consistent with existing data. In a new test using data from more than 451,000 people from 146 countries, we show that increasing income inequality is, as predicted, associated with stronger national affiliation, particularly for people with lower-ranked incomes. We highlight the model’s prediction that wealthy politicians and power-brokers are incentivised to engage in nationalistic rhetoric and to increase perceptions of national standing, as such activity will increase the incentive for low-income people to identify with their nation and reduce their incentive to vote for income-redistributive policies.

Speaker	Carrella, Fabio
Author 1	Carrella, Fabio University of Bristol
Author 2	Aroyehun, Segun Graz University of Technology
Author 3	Lasser, Jana Graz University of Technology
Author 4	Simchon, Almog University of Bristol
Author 5	Garcia, David Graz University of Technology
Author 6	Lewandowsky, Stephan University of bristol
Title	The `Truth Contagion' Effect in the US Political Debate
Abstract	The spread of online misinformation has become a growing concern for society and democracy. Despite politicians making inaccurate and false statements, some segments of the public still perceive them as honest if they appear to "speak their mind" and be "authentic". In the past decade, US politicians have undergone a distinct bifurcation in their conception of truth, with authentic but evidence-free belief-speaking becoming more prominent and differentiated from evidence-based truth-seeking. In this study, the downstream consequences of these conceptions of honesty were examined by analyzing how users engage with truth-seeking and belief-speaking tweets from Democratic and Republican politicians on Twitter. Computational text processing was used to measure the conceptions of honesty of a sample of tweets and replies, and the alignment between the honesty components in the original tweets and replies was checked. The study found that the conceptions of honesty used in replies aligned with those of the original tweets, indicating a "contagion" effect in which politicians determine the tone of subsequent public conversation. In addition, belief-speaking tweets were found to trigger more polarized language in replies than truth-seeking ones, while truth-seeking tweets had the opposite effect of decreasing polarization. This analysis underscores the crucial role of political leaders in shaping online conversation and the potential of evidence-based communication in reducing audience polarization in online political debate.

Speaker	Chandramouli, Suyog
Author 1	Chandramouli, Suyog Aalto University
Author 2	Zhu, Yifan Aalto University
Author 3	Oulasvirta, Antti Aalto University
Title	Interactive Personalization of Classifiers for Explainability using Multi-Objective Bayesian Optimization
Abstract	Explainability is a crucial aspect of models which ensures their reliable use by end-users. However, explainability depends on the user and the model's usage context, making it an important dimension for personalization. In this talk, we discuss an approach for personalizing black-box image classifiers using an interactive hyperparameter tuning approach, in which the user iteratively rates the quality of explanations for a selected set of query images. With the use of a multi-objective Bayesian optimization (MOBO) algorithm, we optimize for both, the classifier's accuracy and the user's perceived explainability. In our user study, we found Pareto-optimal parameters for each participant, that could significantly improve explainability ratings of queried images while minimally impacting classifier accuracy. Furthermore, this improved explainability with tuned hyperparameters generalized to held-out validation images, with the extent of generalization being dependent on the similarity between the query and validation images. This MOBO-based method has the potential to be used in general to jointly optimize any machine learning objective(s) along with any human-centric objective(s). The Pareto front produced after the interactive hyperparameter tuning can be useful during deployment, allowing for desired trade-offs between the objectives to be chosen by selecting the appropriate parameters. Additionally, user studies like ours can assess if commonly assumed trade-offs, such as accuracy versus explainability, exist in a given context.

Speaker	Cruz, Nicole
Author 1	Cruz, Nicole University of Innsbruck
Author 2	Lee, Michael D. University of California, Irvine
Title	What do people mean by “If there is not beer then there is wine”?
Abstract	A central question in reasoning research is what computational level principles, if any, people follow when drawing inferences and when making judgments about how strong or weak a particular inference is. Any measure of inference quality depends on the meaning people ascribe to the statements that make up the inference. The statement types with the most contentiously debated meaning in the literature are conditionals. For example, whether the inference “There is beer or wine. Therefore if there is not beer then there is wine” is deductive or not depends on how the conditional that makes up its conclusion is interpreted. Distinguishing between different interpretations of conditionals requires finding situations in which they lead to non-overlapping behavioral predictions. We present a Bayesian latent-mixture model to distinguish between a material conditional, a probabilistic conditional, and a probabilistic biconditional interpretation of conditionals along with a fourth response to capture guessing. The model correctly classifies the responses expected under each interpretation given premise and conclusion probability judgments for six inference types. We simulate data to illustrate the behavior of the model and discuss characteristics of experiments that would be required to distinguish between interpretations. [Would like to join the group climbing day].

Speaker	Davelaar, Eddy
Author 1	Davelaar, Eddy Birkbeck, University of London
Title	Induced forgetting and optimal criterion placements
Abstract	In the retrieval-induced forgetting paradigm, retrieving studied items impairs memory performance for related-but-not-retrieved items (Rp-) compared to items whose category was not used in retrieval (Nrp). Strong evidence in favour of a memory impairment has come from studies using item recognition. However, the observation of below-baseline recognition performance could be due to decreased memory strength, change in old/new-criterion setting or both. Recently, Megla, Woodman and Maxcey (2021) observed increased frontal negativity for Rp- compared to Nrp (visual) items during a final recognition test. This finding was interpreted as providing evidence in favour of a decreased-strength account of induced forgetting. Here, this interpretation is challenged by highlighting that the initial prediction for the criterion-shift account is incorrect and that the findings with event-related potentials are equally supportive of a criterion-shift account. Using a REM implementation of retrieval-induced forgetting, frontal negativites in recognition memory are reinterpreted as showing comparisons of memory strengths against optimal criterion placements.

Speaker	Dixon, Peter
Author 1	Dixon, Peter University of Alberta
Title	Immediate memory and mind wandering
Abstract	It is intuitive and well established that performance in a variety of tasks is worse when participants report mind wandering and being off task. However, the precise nature of the performance deficit remains elusive. In this talk, I will describe an account in which participants are less focused on the current moment when off task. As a consequence, they may suffer from interference from previous stimuli and responses. I will support this hypothesis with data from task switching, memory scanning, and a short-term recency judgement task. In all cases, there are performance decrements that can be explained in terms of a failure to maintain the current task context. Would like to join the group climbing day

Speaker	Dunn, John
Author 1	Dunn, John University of Western Australia
Author 2	Anderson, Laura Binghamton University
Author 3	Stephens, Rachel University of Adelaide
Title	Measurement of memory
Abstract	For over 70 years, recognition memory has been modeled using signal detection theory. An unsolved problem with this approach is that the shapes of the distributions of memory strength for studied and unstudied items are unknown. Although they are often assumed to be Gaussian, with different location and scale parameters, such models often fail to fit observed data. This has had the effect of sustaining the viability of alternative approaches such as discrete state models, mixture models, and hybrid dual process models. However, it is now possible to estimate the shapes of the proposed memory strength distributions using the monotonic linear regression algorithm developed by Dunn and Anderson (under review). We describe this algorithm, show how it can recover the relevant distribution shapes under the signal detection model, and show that it fails to do so under alternative models. We apply it to data from three item recognition experiments. Each experiment used the same set of stimuli and varied the number of study presentations (1, 2, or 4) and the nature of the study item or the study task: visual vs. auditory presentation (Experiment 1), read vs. generate task (Experiment 2), and focused vs. divided attention task (Experiment 3). While the results confirm the predictions of the signal detection model, the recovered distributions deviate from the Gaussian. Furthermore, we show that the regression weight associated with each condition can be interpreted as a measure of memory strength for that condition, replacing traditional indices such as d-prime.

Speaker	Fasce, Angelo
Author 1	Fasce, Angelo University of Coimbra
Author 2	Holford, Dawn University of Bristol
Author 3	Lewandowsky, Stephan University of Bristol
Author 4	Schmid, Philipp University of Erfurt
Author 5	Bates, Luke Technical University of Darmstadt
Author 6	Costello, Thomas Massachusetts Institute of Technology
Title	Anti-vaccination beliefs: Conceptual taxonomy, psychological profiles, and empathetic rebuttals
Abstract	Effective rebuttal of misinformed arguments against vaccination requires an approach that goes beyond addressing flaws in the arguments, but that also considers the “attitude roots”—that is, the underlying psychological attributes that drives a person’s opposition to vaccines. In this talk, I will present a taxonomy of anti-vaccination arguments developed within the framework of the JITSUVAX research project through a systematic review of 152 scientific articles and thematic analysis of 2,414 contrarian arguments found in the existing academic literature. The taxonomy was further validated on a dataset of 582 instances of COVID-19 anti-vaccine misinformation, using a computational model to derive 11 attitude roots that reflect 62 thematic categories. In two follow-up studies (total sample = 1320), we tested the factor structure, construct validity, and psychological profiles of these attitude roots using a sample from the British general population and well-established measures of characteristics such as individuals’ worldviews and conspiratorial beliefs. Finally, I will present a website developed with the aim of informing clinicians about how to address anti-vaccination arguments from an empathetic perspective.

Speaker	Fröber, Kerstin
Author 1	Fröber, Kerstin University of Regensburg
Author 2	Pastötter, Bernhard University of Trier
Title	The influence of free choice on recognition memory in the face of distraction [Would like to join the group climbing day]
Abstract	Recognition memory is typically better for items learned under free-choice than under forced-choice. In previous studies on the topic, however, the to-be-remembered items were presented in isolation, whereas in everyday situations, the learning material is often embedded within many distractors. Therefore, in the present study, we examined in two experiments the influence of free vs. forced choice on recognition memory in a learning situation with both relevant (to-be-remembered) and irrelevant (to-be-ignored) items. Experiment 1 (N=62) used compound word-picture stimuli, whereas Experiment 2 (N=59) used audio-visual word combinations. Before the presentation of stimuli, participants were either instructed (forced choice) or could decide themselves (free choice) which item of the compound stimuli to remember (Exp. 1: word or picture; Exp. 2: written or spoken word). Receiver operating characteristics were estimated based on the unequal variances signal detection model of recognition memory. In Experiment 1, results showed better recognition memory for relevant than irrelevant items. Free choice had a comparatively small effect, but further boosted recognition memory especially for relevant items. Experiment 2 showed descriptively the same pattern of results, but the interaction was not significant. An analysis across both experiments confirmed that free choice selectively boosted recognition memory for relevant, but not irrelevant items. Taken together, participants were able to learn selectively in the face of irrelevant distractors, and more importantly, having some control about the learning situation seemed to further improve memory specifically for the relevant items. This suggests that self-directed learning is beneficial even in situations with irrelevant distraction.

Speaker	Goldstone, Robert
Author 1	Weitnauer, Erik Indiana University
Author 2	Goldstone, Robert Indiana University
Author 3	Ritter, Helge University of Bielefeld
Title	Perception and Simulation During Concept Learning
Abstract	A key component of humans’ striking creativity in solving problems is our ability to construct novel descriptions to help us characterize novel concepts. Bongard problems, which challenge the problem solver to come up with a rule for distinguishing visual scenes that fall into two categories, provide an elegant test of this ability. Bongard problems are challenging for both human and machine category learners because only a handful of example scenes are presented for each category, and they often require the open-ended creation of new descriptions. A new type of Bongard problem called Physical Bongard Problems (PBPs) is introduced, which requires solvers to perceive and predict the physical spatial dynamics implicit in the depicted scenes. The PATHS (Perceiving And Testing Hypotheses on Structures) computational model which can solve many PBPs is presented, and compared to human performance on the same problems. PATHS and humans are similarly affected by the ordering of scenes within a PBP. Spatially or temporally juxtaposing similar (relative to dissimilar) scenes promotes category learning when the scenes belong to different categories, but hinders learning when the similar scenes belong to the same category. The core theoretical commitments of PATHS, which we believe to also exemplify open-ended human category learning, are a) the continual perception of new scene descriptions over the course of category learning, b) the context-dependent nature of that perceptual process, in which the perceived scenes establish the context for the perception of subsequent scenes, c) hypothesis construction by combining descriptions into explicit rules, and d) bi-directional interactions between perceiving new aspects of scenes and constructing hypotheses for the rule that distinguishes categories.

Speaker	Heathcote, Andrew
Author 1	Gronau, Quentin University of Newcastle, Australia
Author 2	Heathcote, Andrew University of Amsterdam
Title	Chronometic Psychophysics
Abstract	Despite the mapping between objective and subjective magnitudes being central to psychology’s foundational discipline of psychophysics, quantitative characterisations that are stable across different individuals and contexts have remained elusive. We address this problem through a theoretical framework defining subjective magnitudes as the inputs to a dynamic model of perceptual two-alternative forced choice. Three observer-specific parameters—their sensitivity to subjective magnitudes, and differences between magnitudes, and their decision urgency, along with the psychophysical function mapping objective to subjective magnitudes—determine the rate at which evidence for each choice accrues. Responses and response times are a function of the evidence rate, additive stochastic noise, the threshold amount of evidence required to make a choice, and the time for non-decision processes. We develop both non-parametric and parametric methodologies within this framework to measure the psychometric function and apply them to judgements about which of two rectangles has a greater area of one of two colours. In every participant over several experiments varying the decision context (sets of stimuli spanning different ranges), both methodologies converge on an identity mapping between the objective proportional area and the subjective input to the decision process. Ongoing experiments are investigating the application of this methodology to other stimulus dimensions and decision tasks. We discuss how this approach advances the state-of-the-art by providing much-needed constraint that disambiguates the roles of perceptual and individual characteristics in modelling decision processes, and by providing the foundation envisioned by 19th psychophysics for investigating psychological processes.

Speaker	Hemmer, Pernille
Author 1	Hemmer, Pernille Rutgers University
Title	The Memorability of Supernatural Concepts
Abstract	The minimally counterintuitive (MCI) thesis (Boyer 2001) proposes that supernatural concepts recur across cultures because they possess a memorability advantage over other concepts. Specifically, supernatural concepts have characteristics which violate intuitive ontological assumptions, which allow people to easily represent and reason about concepts. These ontological violations make supernatural concepts more memorable than natural concepts. However, the connection between MCI concepts and bizarre (BIZ) but not supernatural concepts, for which memorability advantages are predicted by the von Restorff (VR) effect, has been insufficiently clarified by earlier research. Additionally, the role of inferential potential (IP) in determining MCI concepts’ memorability has remained vague and only rarely controlled for. In a pre-registered experiment, we directly compare memorability for MCI and MXCI concepts (which contain numerous ontological violations), compared to BIZ concepts, while controlling for IP as well as degree of bizarreness. Results indicate that when IP and bizarreness are controlled for, memorability of counterintuitive and BIZ concepts — relative to intuitive control concepts — is similar across concepts with one, two, and three characteristics. Our findings suggest that the MCI and VR effects may be manifestations of the same underlying mechanisms.

Speaker	Holmes, William
Author 1	Holmes, William Indiana University
Author 2	Trueblood, Jennifer
Author 3	Hayes, William
Author 4	Liu, Yanjun
Author 5	Murrow, Matthew
Title	Attentional Dynamics Explain the Elusive Nature of Context Effects
Abstract	Context effects in multi-alternative, multi-attribute choice are pervasive and yet, paradoxically, elusive at the same time. Despite the success of dynamic decision models in explaining the occurrence of context effects, a coherent theory for understanding their elusiveness is currently lacking. We introduce a novel theoretical framework that relies on attention modulated comparisons to explain the elusive nature of context effects. Theoretical results from this model make three testable predictions. 1) Spending more time on comparison of similar alternatives in a choice set promotes standard context effects while comparison of dissimilar alternatives leads to the reversal of those effects. 2) Biasing which alternatives are compared by spatially organizing information (i.e. display layout) alters the observed context effects. 3) Manipulating the comparability of different attributes in a choice further alters choice patterns. Each of these observations is confirmed using choice or choice-RT data from both new experiments and re-analysis of existing data. The contribution of these results are two-fold. First, they illustrate how either subtle (or not so subtle) alterations of attention can manipulate contextual sensitivity, leading to the simultaneous generality and fragility of the classic context effects. Second, this work provides a theoretical framework for explicitly accounting for attention allocation, and various factors that may affect it, as part of the decision process.

Speaker	Ivanova, Iva
Author 1	Ivanova, Iva University of Texas at El Paso
Title	TBD [Language, conversational coordination, multilingualism]
Abstract	TBD [Would like to join the group climbing day; have hotel reservation]

Speaker	Janczyk, Markus
Author 1	Janczyk, Markus University of Bremen
Title	Response-compatibility effects in dual-tasking: (Automatic) response activation in the secondary task and its contribution to response selection
Abstract	When two tasks are performed in close succession, performance in the secondary one typically suffers the more the tasks overlap in time. In addition, response-compatibility effects are observed such as even the response in the first performed task is given faster if the second task requires a compatible response (e.g., the required response is ‘left’ in both tasks), compared to when it is an incompatible response (e.g., first task ‘left’, secondary task ‘right’). This effect, also called backward crosstalk effect (BCE), has been replicated many times. I will first report a series of behavioral experiments that aimed at localizing where in the stream of processing the BCE emerges, and argue that modifications of dual-task models made in response to the BCE are likely not necessary. I will then address the time-course of how the secondary task influences response selection in the first task and whether the gathered response activation in the secondary task is actually used for its response selection or not. As previous experimental approaches were not successful in answering this question, this was done with a computational modelling approach, and its results allow to identify some hypotheses as plausible and others as not.

Speaker	Lewandowsky, Stephan
Author 1	Lewandowsky, Stephan University of Bristol
Title	Technique-based inoculation against misinformation
Abstract	There has been increasing concern about the corroding effects of misinformation on the health of western democracies. In response, much research has addressed ways in which misinformation can be “debunked”, and policy makers have considered regulatory means by which the spread of misinformation can be contained. Although those approaches show considerable promise, one difficulty is that they tend to be tied to the specific content of false messages – for example, one cannot debunk a myth unless one knows what the myth is, by which time the false information may have already spread far and wide. Moreover, disinformers and propagandists can enter the fray by labelling the corrections of misinformation “fake news”, thereby further contributing to confusion and eroding the distinction between evidence-based information and misinformation. An alternative approach is to sidestep debates about specific content but to provide the public with cognitive tools that enable them to differentiate between information of high quality and likely misinformation. This approach is known as inoculation and, similar to a medical inoculation, it involves exposure to a small dose of misleading rhetoric so the person can develop “cognitive antibodies” to be protected against subsequent misinforming rhetoric. Unlike debunking, inoculation does not require knowledge of specific content—only the rhetorical technique by which people are likely to be misled. I review a number of large-scale studies that showed the effectiveness of inoculation in the laboratory and in the field.

Speaker	Nelson Lowe, Angela
Author 1	Nelson Lowe, Angela University of California, San Diego
Author 2	Wixted, John University of California, San Diego
Title	“Now that you’ve had some time to think about it….”: True Recognition of a Familiar Face is Immediate or Not at All
Abstract	In 1979, Kevin Strickland was convicted of murder based on eyewitness testimony. The sole witness, when first questioned, named two of the four perpetrators (neither of which were Strickland), but stated she did not know the other two men. Later, the witness’s sister suggested to her that one of the two unknown men was likely Kevin Strickland, who both knew from their neighborhood. The witness then informed investigators that, after giving it some thought, she “remembered” that one of the perpetrators she initially didn’t recognize was actually Kevin Strickland. He was convicted and spent 42 years in jail. The current experiment simulates the above scenario by presenting subjects with a blurred image of a well-known celebrity and asking for an immediate recognition judgment. Following the initial recognition question, some are given no further information (control), some receive correct suggestive information regarding the identity of the face, and some receive incorrect suggestive information. All subjects are then asked again for the identity of the initial face. Though data collection is ongoing, we hypothesize that subjects in the control condition who failed to identify the face initially will still not be able to identify the face when asked a second time, but subjects in the suggestive conditions will be likely to identify the face with the suggested identity (correct or incorrect) when asked a second time. This finding would support the theory that the eyewitness’s identification of Kevin Strickland was not a delayed true recognition, but a false memory based on suggestion. NOTES: I can speak on any day, and we would like to join the group climbing day: 2 adults + Lucy (11 years old). We have harnesses and shoes but no helmets or ropes.

Speaker	Oberauer, Klaus
Author 1	Oberauer, Klaus University of Zurich
Author 2	Bartsch, Lea M. University of Zurich
Title	The contribution of episodic long-term memory to performance in tests of working memory
Abstract	When participants do a test of working memory (WM), we cannot expect their episodic long-term memory (eLTM) to remain silent. Performance in a WM test could therefore rely in part on eLTM. This creates a problem for WM research, because we don’t know to what extent experimental effects are due to mechanisms of WM or of eLTM, and to what extent individual differences in tests of WM capacity reflect differences in eLTM. We can leverage proactive interference (PI) to diagnose the contribution of eLTM to performance in several WM tests. Episodic memory keeps a record of all events initially encoded into memory, which renders it vulnerable to PI. By contrast, no-longer relevant information is efficiently removed from WM, thereby preventing PI across trials. We will present experiments in which we varied PI between trials in five tests of WM. We found PI specifically for set sizes that challenge WM capacity in two test paradigms: Memory for object-word pairs, and for object-color conjunctions. We found little or no evidence for PI even at large set sizes for three other paradigms: Memory for object-location conjunctions, memory for location-color conjunctions, and memory for lists of verbal items.

Speaker	Olsson, Henrik
Author 1	Olsson, Henrik Complexity Science Hub Vienna
Author 2	Galesic, Mirta Santa Fe Institute
Author 3	Bruine de Bruin, Wändi USC
Author 4	Prelec, Drazen MIT
Title	Relying on human social cognition helps predict elections
Abstract	We show that election forecasts in 2020 and 2018 US elections are improved by adding wisdom-of crowds questions to election polls. Wisdom-of-crowds questions ask poll participants about the percentage of their social contacts (social-circle question) or people in their state (state-winner question) who might vote for different candidates. These questions can be used to forecast elections on their own. They can also be integrated with responses to traditional poll questions that ask participants who they themselves will vote for (own-intention question). We explore a Bayesian method for information integration: that optimally weights private and external signals. We compare different methods on national probabilistic samples (N=4000+) within the USC Understanding America Study panel. The best predictions of the 2020 election results were made by the social-circle question and the integration method. These forecasts outperformed forecasts based on average national polls. They were also better than forecasts based on the own-intention and state-winner questions in the USC poll. Similarly, in 2018, the social-circle and the information integration method outperformed own-intention and state-winner forecasts of national results. In both 2020 and 2018, both wisdom-of-crowds questions and most information integration methods predicted state level results better than the own-intention question. We investigate three reasons why wisdom-of-crowds questions might be more accurate: they might implicitly provide a more diverse sample, decrease social desirability biases, and anticipate social influences on how people will vote. Taken together, our results suggest that election polling can produce accurate results when traditional questions are augmented by wisdom-of-crowds questions.

Speaker	Pedersen, Arthur Paul
Author 1	Pedersen, Arthur Paul The City University of New York
Title	Truth and Obfuscation
Abstract	Individuals and institutions — be they intelligence officers, medical experts, or terrorist cells — collect, analyze, and share information bearing on questions of fact. This talk examines some recent insights from ongoing research on the organizational structure and regimentation of these economies of information exchange. I will focus on two key results. First, creating more channels for information exchange facilitates efficient consensus-building on questions of fact. The price to be paid for this increased speed, however, is the surging risk of getting things wrong. Second, and relatedly, judiciously eliminating channels of information exchange improves effectiveness of consensus-building in reaching correct opinion on questions of fact. I will explain how research findings such as these not only deliver clear, actionable guidance for designing, identifying, understanding, and protecting information sharing economies but also break ground for innovative methods and tools for supporting mission objectives of the US intelligence community. The findings and insights reported in this talk are the product of joint work undertaken for Close Encounters of the Wicked Kind, a multidisciplinary research project in computational epidemiology and information economics carried out under the auspices of the US Intelligence Community Center for Academic Excellence (IC CAE) of Syracuse University.

Speaker	Plancher, Gaën
Author 1	Plancher, Gaën University of Lyon
Author 2	Delem, Maël University of Lyon
Author 3	Turkben, Sema University of Lyon
Author 4	Cavalli, Eddy University of Lyon
Title	Cognitive profile of aphantasics: Exploration of alternative strategies
Abstract	Mental images are a ubiquitous phenomenon for many people. Yet in recent years, attention has focused on a condition defined by the absence of mental images, aphantasia. Aphantasics are said to perform as well as typical imagers in most areas. At the same time, a study has shown that they are more likely to work in scientific occupations: to date, there is no data to explain this over-representation. The present study aims to better understand their cognitive profile by examining the use of alternative strategies based more on semantic and/or abstract processing. Participants completed several questionnaires and behavioral tasks assessing various aspects of cognition: sensory and spatial imagery, verbal strategies, verbal and nonverbal reasoning, and verbal and spatial working memory. While initial results suggested no differences between aphantasics and controls, redefining the groups by clustering revealed three clusters with unique profiles. A mixed cluster of aphantasics and typical imagers who reported using spatial imagery performed very well on all tasks; a cluster of aphantasics who preferred verbal strategy performed slightly worse; and a cluster of non-aphantasics focused on visual imagery performed worse than the other two. These results reveal two very distinct profiles of aphantasics, one focused on spatial representations, the other on verbal representations. The striking contrast between the latter cluster and the other two also suggests that visual imagery may impair abstract reasoning.

Speaker	Ransom, Madeleine
Author 1	Ransom, Madeleine University of British Columbia, Okanagan Campus
Title	The Perceptual Learning of Socially Constructed Kinds
Abstract	Some social kinds are both socially constructed and perceptible, such as MONEY, GENDER and – as I will focus on here – RACE. However, this gives rise to a puzzle: how does culture shape and bias what we perceive? I argue that perceptual learning is the best explanation of our ability to perceive social kinds. Drawing upon known factors that influence perceptual learning, I propose four ways in which culture can shape and bias perception. This account makes clear that the process of enculturation can begin at a very early age, and does not in most cases require background knowledge on the part of the learner: the causal pathways by which perceptual learning occur suffice. In addition – and crucial for understanding the persistence of racism despite a decline in racist attitudes – it can help explain how certain cultural practices become entrenched in a society: by ‘anchoring’ the social kind in perception.

Speaker	Roskies, Adina
Author 1	Roskies, Adina Dartmouth College / UCSB
Title	Does the neuroscience of decision provide evidence of animal awareness?
Abstract	How do we know that nonhuman animals are conscious? Arguments for or against animal consciousness typically rely upon behavior. In the human case, verbal report has traditionally held a privileged evidential position in the justification of claims of awareness and content of phenomenal states. As nonlinguistic animals are unable to verbally report the nature of their internal states, many have denied that they are conscious or have phenomenal states. In this talk I will explore whether metacognitive states are analogous to verbal report for animals. Post decision wagering is a task which prima facie relies upon metacognitive confidence judgments: If subjects effectively opt out when they are uncertain of a choice, it suggests that they are aware of their degree of confidence in their decisions. Monkeys succeed in post-decision wagering tasks, so PDW is a candidate metacognitive task that can serve as a proxy for verbal report of consciousness from nonlinguistic animals. However, computational models of metacognition have shown that animal behavior in these metacognitive tasks can also be modeled with non-metacognitive models. These deflationary models and adherence to Morgan’s Canon caution against taking them as evidence of awareness. Can neural information can provide resolution to these ambiguities? I argue that the neural basis of decision-making in post-decision-wagering tasks corroborates a deflationary view of PDW tasks. However, this deflationary evidence is to be expected and the deflationary view can potentially be defeated. I will suggest how we might look for further evidence of awareness in metacognitive tasks.

Speaker	Schmid, Philipp
Author 1	Schmid, Philipp University of Erfurt
Author 2	Holford, Dawn
Author 3	Fasce, Angelo
Author 4	Lewandowsky, Stephan
Title	An “Empathetic Refutational Interview” to address misconceptions about vaccination
Abstract	Effective corrections of misinformation need to go beyond simply refuting flaws in the misinformation and show an understanding of people’s underlying motivations to believe in it. We examined the effectiveness of a novel, multi-component intervention that addresses vaccine-related misinformation with empathy for people’s own motivations. In 5 experiments, we tested three components of the intervention first individually against active control conditions (Experiments 1-3, total n = 1663) and then as a combined intervention against (i) a single active control (Experiment 4, n = 519) and (ii) two partial interventions and a control (Experiment 5, n = 700). These experiments found that: (1) Asking participants to explain why they supported anti-vaccination arguments was as effective than a control in reducing support for that argument, and did not generate backfire effects. (2) Participants who read a vignette in which a doctor affirmed their patient and used empathetic language to correct misconceptions (compared to a control where the doctor did not do this) were more supportive of this refutation, found it more compelling, and displayed more trust and openness towards the doctor. (3) Giving facts about disease risks and herd immunity increased vaccine acceptance. Overall, the full intervention with all three components performed best at increasing support for the doctor’s refutation, vaccine acceptance, and decreasing support for anti-vaccination arguments. Partial interventions that included some elements of refutation and facts presentation were also more effective than the control at addressing misinformation, but did not receive as much support from participants as the full intervention. NOTE 1: I can only give the talk either Tuesday 04.07., Wednesday 05.07 or Thursday 06.07. NOTE 2: Would like to join the group climbing day

Speaker	Shiffrin, Richard
Author 1	Shiffrin, Richard Indiana University
Title	Lord's Paradox illustrates the chasm between scientific and statistical inference
Abstract	In 1967 Frederic Lord published a two page paper analyzing changes in weight by women and men from the start to the end of a semester. He asked what inferences should be drawn from the data shown. A scientist would surely conclude that the individuals in both groups were fluctuating in weight but not gaining or losing. Yet an analysis of covariance (ANCOVA) produced an inference that both men and women were gaining, with the men gaining more. Lord presented this as an example showing that inappropriate use of ANCOVA leads to absurd conclusions, yet statisticians and causal modelers have been re-examining this paradox ever since, sometimes concluding that one cannot reach a valid conclusion, sometimes concluding that the correct conclusion is more weight gain for the initially heavier group. This is an example showing that what seems to be good, abstract, theory, in this case statistical and causal theory, can lead to interpretations different than those reached by scientists. I use this example to highlight the importance of drawing inference on the basis of models that could produce the observed data that are plausible, simple and coherent. Not one of the many authors since 1969 arguing for what Lord (and I) view as absurd inferences have produced a model capable of producing the data Lord displayed. At heart the differences at stake are those between deduction and induction/abduction.

Speaker	Simchon, Almog
Author 1	Simchon, Almog University of Bristol
Author 2	Sutton, Adam University of Bristol
Author 3	Edwards, Matthew University of Bristol
Author 4	Lewandowsky, Stephan University of Bristol
Title	The Microtargeting Manipulation Machine
Abstract	In recent years, there has been a growing concern over “psychological microtargeting”, in which psychological features that cannot be directly observed, such as personality characteristics, are inferred from online behaviour and personal data, and are used to customize manipulative messages, for example to provoke political action/inaction or to spread misinformation. Such microtargeting is opaque to online users and its effects, to the extent that they are understood, should give rise to concern. Hence, there is an urgent need to “reverse engineer” microtargeting strategies by uncovering the targeting algorithms in action. This paper presents a proof of concept for such algorithmic reverse engineering. We suggest that the detection of personality-congruent language can inform future interventions to alert users when they might be targeted on the basis of their inferred personality * Can speak on July 5-6-7-8 * Would like to join the group climbing day if suitable for young children

Speaker	Sloutsky, Vladimir
Author 1	Sloutsky, Vladimir Thew Ohio State University
Author 2	Blanco, Nate The Ohio State University
Title	Exploration, exploitation, and development
Abstract	Making effective choices requires balancing exploration (seeking information that can be used later) with exploitation (using existing information to make rewarding decisions). Recent work suggests that children are highly exploratory, but little is known about how the exploration-exploitation balance changes across development. We examined the development of decision-making in 3-8-year-old children and adults. Results indicate that mature reward-based choices emerged relatively late in development, with young children tending to over explore. Computational modeling suggests that this exploration was systematic rather than random, with development resulting in increasing exploitation. We discuss how these exploration tendencies may confer benefits in some learning environments.

Speaker	Steyvers, Mark
Author 1	Steyvers, Mark University of California, Irvine
Title	Human-AI Collaboration
Abstract	Artificial intelligence (AI) and machine learning models are being increasingly deployed in real-world applications. In many of these applications, there is strong motivation to develop hybrid systems in which humans and AI algorithms can work together, leveraging their complementary strengths and weaknesses. In this talk, I will discuss the promises and pitfalls of AI-assisted decision-making where a human decision-maker is aided by an AI. I will present empirical research that investigates the effectiveness of AI-assisted decisions and the cognitive decision process in different paradigms for presenting AI advice. I will also discuss the question of “machine theory of mind” and “theory of machine”, how humans and machines can efficiently form mental models of each other to collaborate more effectively. [Would like to join the group climbing day for 2 people]

Speaker	Stremfelj, Andrej
Author 1	Stremfelj, Andrej Slovenia
Author 2	Stremfelj, Marija Slovenia
Title	High Mountain Adventures
Abstract	Strange, unexpected and exciting things sometimes happen in the high mountains of the world.

Speaker	Thalmann, Mirko*
Author 1	Thalmann, Mirko* Max Planck Institute for Biological Cybernetics
Author 2	Witte, Kristin* Max Planck Institute for Biological Cybernetics
Author 3	Schulz, Eric Max Planck Institute for Biological Cybernetics
Title	How to measure exploration strategies in few-armed bandit tasks?
Abstract	The exploration-exploitation dilemma occurs when we have to decide between sticking to options with relatively high immediate rewards and exploring relatively less known, possibly lower-valued options. Several heuristic exploration strategies have been proposed to trade off exploration and exploitation in a favorable manner and were subsequently implemented as parameters in computational cognitive models. These strategies are commonly measured in various options of few-armed bandit tasks. Recent research started relating individual differences in parameter estimates of exploration strategies to individual differences in psychiatric traits. Initial results from a project, in which we are measuring reliability and validity of exploration strategies, show that not all tasks are equally well suited to study certain combinations of exploration strategies a priori, because parameters are not recoverable. Moreover, the results show that measuring exploration strategies may only be achieved under certain boundary conditions.

Speaker	Treiss, Stephan
Author 1	Treiss, Stephan City, University of London
Author 2	Pothos, Emmanuel City, University of London
Author 3	Corr, Philip City, University of London
Author 4	White, Lee C. City, University of London
Title	Influence of incidental emotions on risk and loss aversion
Abstract	In this talk, I will focus on describing how and why incidental emotions influence risk and loss aversion, and if the context of the emotional induction affects the influence or not. Structure: 1. Definitions of incidental emotions using the emotion-imbued choice model, risk and loss aversion according to Prospect Theory 2. Quick overview of ways of measuring risk and loss aversion (Tom et al., 2007; Charpentier et al., 2016) 3. Reasons for why emotions influence decision-making, and, more concretely, risk and loss aversion 4. Description of experimental set-up + results of two recent studies focusing on these effects, control variables (BIS/BAS, personality) 5. Limitations, next steps [ Attending: Monday, Tuesday, Wednesday, Thursday Would like to join the group climbing day w/2 persons and a baby - if possible (!) We can discuss this when we meet on Sunday at the Ramada Resort. ]

Speaker	Trueblood, Jennifer
Author 1	Caplin, Andrew New York University
Author 2	Epping, Gunnar Indiana University
Author 3	Holmes, William Indiana University
Author 4	Martin, Daniel University of California Santa Barbara
Author 5	Trueblood, Jennifer Indiana University
Title	Training Machine Learning Models with Labels obtained via Wisdom of the Crowd
Abstract	One of the bottlenecks in the development of medical artificial intelligence systems is the availability of labeled images. It is often difficult to recruit experts to perform this labeling due to costs and the large volume of labeled images that are required. We investigate the possibility of using minimally trained novices to label images for training AI systems. In our approach, individual novices classify white blood cells as cancerous or not, we then combine the individual classification decisions using wisdom of the crowd techniques, and finally we use the crowd’s labels to train convolutional neural network models. We test different methods for eliciting decisions from individuals and different wisdom of the crowd algorithms. We find that eliciting beliefs as probabilities outperforms binary classification decisions when training neural network models. We also find that using a select crowd of individuals that perform well in initial training also improves model accuracy.

Speaker	Usher, Marius
Author 1	Usher, Marius Tel-Aviv University
Author 2	Rosenbaum, David Tel-Aviv University
Author 3	Glickman, Moshe UCL (London)
Author 4	Fleming, Steve UCL (London)
Title	The Cognition/Metacognition Trade-Off
Abstract	Integration to boundary is an optimal decision algorithm that accumulates evidence until the posterior reaches a decision boundary, resulting in the fastest decisions for a target accuracy. Here, we demonstrate that this advantage incurs a cost in metacognitive accuracy (confidence), generating a cognition/metacognition trade-off. Using computational modeling, we show that integration to a fixed boundary results in less variability in evidence integration and thus reduces metacognitive accuracy, compared with a collapsing-boundary or a random-timer strategy. We examined how decision strategy affects metacognitive accuracy in three cross-domain experiments, in which 102 university students completed a free-response session (evidence terminated by the participant’s response) and an interrogation session (fixed number of evidence samples controlled by the experimenter). In both sessions, participants observed a sequence of evidence and reported their choice and confidence. As predicted, the interrogation protocol (preventing integration to boundary) enhanced metacognitive accuracy. We also found that in the free-response sessions, participants integrated evidence to a collapsing boundary—a strategy that achieves an efficient compromise between optimizing choice and metacognitive accuracy.

Speaker	Volz, Leonhard
Author 1	Volz, Leonhard University of Amsterdam
Author 2	Van Dongen, Noah University of Amsterdam
Author 3	Borsboom, Denny University of Amsterdam
Title	Conceptualising a Database of Formal Models of Psychological Phenomena
Abstract	Formal / computational modelling is increasingly prevalent in psychological research but not greatly accessible to most researchers, for educational and technical reasons. Our research project aims at creating a database that encourages sharing, (re)using, and extending computational implementations of formal models of psychological and cognitive processes. We propose an indexing system that captures relevant aspects of (implementations of) models and present a work-in-progress version of a platform that implements our taxonomy. We hope that our efforts can benefit theoretical and empirical work, aid didactic efforts around modelling, and ease access to computational modelling literature. In that light, we greatly appreciate your input on our development efforts and thought exchange on modelling practices throughout ASIC.

Speaker	Wierzchoń, Michał
Author 1	Wierzchoń, Michał Jagiellonian University
Author 2	Rutiku, Renate Jagiellonian University
Author 3	Hat, Katarzyna Jagiellonian University
Author 4	Sandberg, Kristian Aarhus University
Title	Metacognition and consciousness: a large-scale investigation of the cognitive and neuronal correlates.
Abstract	Metacognition plays a central role in many theories of consciousness. However, little is known about its cognitive and neural underpinnings. Mapping of the behavioural indices of metacognition to neural activation provided mixed results. It is also not clear whether metacognition is a general trait-like ability or whether it applies differentially to specific tasks. We aimed to address those discrepancies by applying the individual differences approach. The reported large-scale study has been realised within the EU COST Action CA18106. Participants completed a set of perceptual discrimination tasks and rated their confidence in response accuracy on every trial. Metacognitive efficiency and metacognitive bias were assessed in two independent samples (N1=301; N2=246). We have also collected a comprehensive set of neuroimaging data probing structural and functional brain organisation. First, we investigated cross-task correlations of both metacognitive bias and metacognitive efficiency between the tasks. Preliminary analyses suggest positive cross-task correlations for metacognitive efficiency (using the meta-d’/d’ ratio) and metacognitive bias (using raw confidence). Second, we tested the relation between behavioural indices and multimodal metrics of individual brain imaging data to explore the neural architecture underlying metacognition. The results are under analysis and will be presented at the meeting. Based on the presented data, we aim to discuss the multidimensional nature of metacognition and demonstrate how interindividual differences in behaviour can be exploited to reveal its underlying neural architecture.

Speaker	Ziegler, Johannes
Author 1	Ziegler, Johannes Aix-Marseille University and Centre National de la Recherche Scientifique, Laboratoire de Psychologie Cognitive, Marseille, France
Author 2	Perry, Conrad Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, Australia
Author 3	Zorzi, Marco Department of General Psychology and Padova Neuroscience Center, University of Padova, Padova, Italy
Title	Learning-to-read and dyslexia: a cross-language computational perspective
Abstract	How do children learn to read in different countries? How do deficits in various components of the reading network affect learning outcomes? What are the consequences of such deficits in different languages? In this talk, we will present a full-blown developmentally plausible computational model of reading acquisition that has been implemented in English, French, Italian and German. The model can simulate individual learning trajectories and intervention outcomes on the basis of three component skills: orthography, phonology, and vocabulary. We will use the model to show how cross-language differences affect the learning-to-read process in different languages and to investigate to what extent similar deficits will produce similar or different manifestations of dyslexia in different languages.

Speaker	Zorzi, Marco
Author 1	Zorzi, Marco University of Padova and IRCC San Camillo Hospital
Author 2	Cinetto, Sebastiano University of Padova
Author 3	Blini, Elvio University of Florence
Author 4	Zangrossi, Andrea University of Padova
Author 5	Corbetta, Maurizio University of Padova
Title	Training free viewing behavior using closed-loop gaze-based biofeedback
Abstract	Eye movements during free viewing of natural scenes are driven not only by image content (e.g., visual saliency) but also by intrinsic dynamics, as shown by our previous work (Zangrossi et al., 2021). We investigated training malleability using a new paradigm in which visual search of invisible targets was directed by real-time auditory biofeedback based on gaze-target distance (as measured by eye-tracking). Participants improved search times and were affected by spatial regularities in the distribution of targets, suggesting the unfolding of statistical learning. Crucially, the spatial bias transferred to subsequent rest and free image viewing conditions, as shown by a shift of fixation density toward the biased hemifield. Finally, we describe how these findings feed into the design of a novel closed-loop rehabilitation protocol for stroke patients based on real-time gaze tracking during visual exploration of real-world images, with the aim to restore normal patterns of eye movements by minimizing the deviation with respect to a “healthy” template.

Contact reberle@indiana.edu with questions.