Dirk Van Rooy

Australian National University, Research School of Psychology, Faculty Member

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My academic and applied work for industry and government is very much focused on how psychology, tools and technologies can help create positive behaviour change to promote resilience, health and sustainable behaviour.Some of the questions I focus on in my work: How can we promote positive behaviour change using behavioural insights and technology? What are the individual and social biases that shape our thinking, behaviour and decision making? How do organisations, governments and its leaders deal with uncertainty and complexity? Leadership requires the ability to make important decisions independently, but also the capacity to influence others' decisions.I currently work as Chief Behavioural Scientist at ThinkPlace and at the ANU Policy Experiments Lab, a collaborative team of researchers and related resources that work on experimental and quasi-experimental studies with an explicit policy focus. I use a mix of experimental methods and computational modelling techniques to explore behavioural change, social influence, (political) trust, group performance and decision making. I have been known to teach research methods and data science, statistics and social psychology.
Address: Canberra, Australian Capital Territory, Australia

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Papers by Dirk Van Rooy

Harmonizing human-AI synergy: behavioral science in AI-integrated design

Proceedings of the Design Society, May 1, 2024

This paper explores the role of integrating behavioral science to refine human-AI interaction, es... more This paper explores the role of integrating behavioral science to refine human-AI interaction, essential for ensuring safety and efficiency. Advocating for empathetic, user-centric design, the paper illustrates how behavioral insights can effectively inform AI-integrated designs, making AI applications more intuitive and ethically aligned with diverse human needs. This approach can ultimately enrich interaction across systems, fostering a more harmonious human-AI synergy.

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Designing the interaction between humans and autonomous systems: The role of behavioral science

IASDR 2023: Life-Changing Design

In recent years, the use of autonomous systems has grown rapidly in both the industrial and milit... more In recent years, the use of autonomous systems has grown rapidly in both the industrial and military sectors. These systems have the potential to revolutionize the way we live and work, from self-driving cars and drones to automated factories and military equipment. However, it has been argued, for this to happen, researchers and designers need to (re)consider the interaction between humans and machines, as it plays a significant role in ensuring the safe and efficient operation of autonomous systems (De Regt & Gagnon, 2020; Janssen et al., 2019). In this paper, I will argue that a closer integration with applied behavioural science could be beneficial for both researchers and practitioners involved in the design of the Human-machine interaction. To that effect, I will discuss a number of insights from behavioural science and how they could inform the design of human-machine interaction.

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Modeling dynamic, multi-directional influences in social networks

A Connectionist Approach to Causal Attribution

CHAPTER 5 A CONNECTIONIST APPROACH TO CAUSAL ATTRIBUTION Frank Van Overwalle Dirk Van Rooy Vrije ... more

Assessing Social Behaviour Towards Near-Body Product Users in the Wild: A Review of Methods

Proceedings of the Design Society, May 1, 2022

Prior to wide adoption, a product must find social approval, which is especially true for near-bo... more Prior to wide adoption, a product must find social approval, which is especially true for near-body products as they are considered part of the human body. Based on a theoretical foundation, this study aims to provide an overview of methods to assess natural behaviour towards users of visible near-body products in uncontrolled environments, i.e. in the wild. Approaching the matter from a product design perspective, this article is primarily intended for designers of near-body products who wish to gain insights into the social behaviour of people towards users wearing their design proposals.

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The role of shared knowledge in group processes--A recurrent connectionist model

PsycEXTRA Dataset, 2006

Prejudice is about Collective Values, not a Biased Psychological System

New Zealand Journal of Psychology, Mar 1, 2019

Exploring the Origins of Prejudice with Agent-Based Modeling

Agent-based social systems, 2015

Research into the cognitive origins of prejudice has largely focused on individual psychological ... more Research into the cognitive origins of prejudice has largely focused on individual psychological processes. We introduce a novel Agent-based model that simulates both individual-level and inter-personal processes, and that allows exploring how stereotypes are shared and validated through interpersonal processes. At the individual-level, agent processes are simulated by recurrent auto-associative networks. To simulate interpersonal processes, these individual networks are combined into a “community of networks” so that they can exchange their individual information with each other by transmitting information on the same concepts from one network to another. Through simulations, it is shown how the model can account for a number of seminal findings from the empirical literature on illusory correlations, a key cognitive antecedent of prejudice. In addition, novel hypotheses in terms of the impact of interpersonal processes on the dissemination of illusory correlations were supported by the results of a small group experiment. We discuss the results and argue that agent-based models can provide a first step in integrating individual and interpersonal processes underlying stereotype formation and IC.

When are anti‐fat attitudes understood as prejudice versus truth? An experimental study of social influence effects

Obesity science & practice, Jan 13, 2019

Background/Objectives If people who hold anti-fat attitudes believe these attitudes to be true, t... more Background/Objectives If people who hold anti-fat attitudes believe these attitudes to be true, then anti-prejudice appeals are likely to be unsuccessful, if only because the targets will not see their attitudes as in need of change. The current study examined processes that may lead people to see their anti-fat attitudes as 'truth' or as 'prejudice'. Subjects/Methods Participants (N = 482) read anti-fat statements and were then presented with an interpretation of these statements as 'truth' or 'prejudice'. The source of this interpretation was either an (i) in-group or out-group member and (ii) expert or non-expert. Participants' judgements of the statements were expected to vary such that in-group others and experts would exert more influence than would out-group others and non-experts. Results Participants aligned their own interpretations of an anti-fat statement with those of an expert, but not with those of a non-expert, F(1,466) = 8.97, p < 0.05, η p 2 = 0.02. The group membership variable had no effect on judgements of 'truth' or 'prejudice' of the anti-fat statement. Conclusion The expressions that people believe constitute anti-fat prejudice versus truth about people described as overweight are influenced by exposure to expert opinion (in this case, by medical doctors). Implications for the success of weight-based anti-prejudice appeals and for healthcare provision are discussed.

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Analytic thinking predicts accuracy ratings and willingness to share COVID-19 misinformation in Australia

Memory & Cognition, Aug 27, 2021

The classical account of reasoning posits that analytic thinking weakens belief in COVID-19 misin... more The classical account of reasoning posits that analytic thinking weakens belief in COVID-19 misinformation. We tested this account in a demographically representative sample of 742 Australians. Participants completed a performance-based measure of analytic thinking (the Cognitive Reflection Test) and were randomized to groups in which they either rated the perceived accuracy of claims about COVID-19 or indicated whether they would be willing to share these claims. Half of these claims were previously debunked misinformation, and half were statements endorsed by public health agencies. We found that participants with higher analytic thinking levels were less likely to rate COVID-19 misinformation as accurate and were less likely to be willing to share COVID-19 misinformation. These results support the classical account of reasoning for the topic of COVID-19 misinformation and extend it to the Australian context.

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When more observations are better than less: a connectionist account of the acquisition of causal strength

European Journal of Social Psychology, 2001

The statistical law of large numbers prescribes that estimates are more reliable and accurate whe... more The statistical law of large numbers prescribes that estimates are more reliable and accurate when based on a larger sample of observations. This effect of sample size was investigated on causal attributions. Subjects received ®xed levels of consensus and distinctiveness covariation, and attributions were measured after a varying number of trials. Whereas prominent statistical models of causality (e.g. Cheng & Novick, 1990; Fo Èrsterling, 1992) predict no effect of sample size, adaptive connectionist models (McClelland & Rumelhart, 1988) predict that subjects will incrementally adjust causal ratings in the direction of the true covariation the more observations are made. In three experiments, sample size effects were found consistent with the connectionist prediction. Possible extensions of statistical models were considered and simulated, but none of them accommodated the data as well as connectionist models.

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The need for cognitive closure and tolerance for ambiguity in groups

PsycEXTRA Dataset, 2007

Disciplinary differences in the study of the relationship between social variables and mental health: A systematic mapping review

Health, Dec 8, 2021

There has been sustained interest in the intersection between social constructs and mental health... more There has been sustained interest in the intersection between social constructs and mental health from diverse disciplines including psychiatry, sociology, and public health. However, no systematic attempt has been made to catalogue what is meant by "social" by different researchers, how variables deemed "social" constructs are linked to mental health, nor whether these patterns differ by academic discipline. Understanding interdisciplinary differences and commonalities may reveal opportunities for interdisciplinary collaboration to enhance our understanding of how social factors relate to mental health. This article presents a prospectively registered systematic map of social approaches to mental health using an innovative synthesis methodology (coding all sentences from a random selection of N=287 articles). Results indicated that although approaches are diverse, disciplinary overlap is substantial. Psychology and psychiatry led articles tend to focus on social skills or emotions as features of mental (ill-)health, while public health and social sciences led articles tend to focus on social relationships, status, or context as determinants of mental (ill-)health. Medicine led articles were most likely to focus on social outcomes of mental (ill-)health. Potential growth areas are noted, particularly the relative dearth of intervention research drawing upon social approaches. The findings are discussed with a view towards enabling more effective interdisciplinary collaboration.

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Improving Memetic Evolution in Hypertext and the WWW

Résumé/Abstract When memes are communicated from one carrier to another they need to be recoded f... more Résumé/Abstract When memes are communicated from one carrier to another they need to be recoded from the memory&amp;#x27;s coding format into the medium&amp;#x27;s own coding format (books, images, sound). The WWW was explicitly designed to mimic the associative way in which information is stored in human memory and should, in principle, be most compatible with memetic evolution. Unfortunately, most present hypertext systems and the WWW, are passive systems of information storage with fixed network structure, thereby disabling the ...

Gender-based in-group social influence can lead women to view a hostile sexist attitude as less prejudiced and more true

The Journal of Social Psychology

Call for Papers: Social Psychology Section Annual Conference 2006

Social Psychological Review, Apr 1, 2006

Lay perceptions of modern prejudice toward “White” and “Asian” people: It matters who said it, whom it's about, and who's judging

Asian Journal of Social Psychology, 2022

We propose that part of the problem in combatting prejudice lies in people's dynamic understa... more We propose that part of the problem in combatting prejudice lies in people's dynamic understandings of what prejudice is. To examine this, we asked participants to rate the degree to which they perceived specific group‐relevant attitudes as prejudice. In Study 1, White participants perceived the attitudes as more prejudiced when the attitudes were targeted at Asian people than at White people and when expressed by an Anglo‐European speaker than by an Asian speaker. Study 2 was a direct replication but expanded the sample to include Asian participants. The Study 1 results were partially replicated in Study 2, although the target main effect was stronger among White than Asian participants. Together, the data suggest a normative legitimacy process in which injunctive norms dictate appropriate and inappropriate speakers and targets of specific group‐relevant attitudes. The data also confirm the original proposition of dynamic understandings of prejudice. Prejudice is understood by ...

Keynote Paper: Privacy and trust in the Information Society

Springer eBooks, May 29, 2008

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Pandemic and prejudice: Revisiting Bogardus’s social distance concept in a time of COVID-19

Group Processes & Intergroup Relations, Nov 9, 2022

This study examined when the realistic threat of COVID-19 leads to prejudicial social distancing.... more This study examined when the realistic threat of COVID-19 leads to prejudicial social distancing. American participants reported social distancing preferences from Chinese or Italian people (out-group target) after viewing increasing or decreasing COVID-19 case numbers (threat level) in China or Italy (threat relevance). On the Bogardus Social Distance Scale, there was support for a disease avoidance hypothesis: greater social distancing preferences were expressed under higher than under lower relevant threats. Responses on a bespoke COVID-19 Social Distance Scale, however, supported an a priori prejudice hypothesis: greater social distancing preferences were expressed toward a Chinese than toward an Italian out-group. Moreover, responses on a separate bespoke Modern Social Distance Scale supported a complex prejudice hypothesis: greater social distancing preferences were expressed toward Chinese than toward Italian out-groups under higher than under lower threat, regardless of threat relevance. These findings suggest that the threat of COVID-19 may enable prejudice expression accompanied by the rationale of disease avoidance.

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A Connectionist Abm of Social Categorization Processes

Advances in Complex Systems, Aug 1, 2012

This paper introduces a connectionist Agent-Based Model (cABM) that incorporates detailed, microl... more This paper introduces a connectionist Agent-Based Model (cABM) that incorporates detailed, microlevel understanding of social influence processes derived from laboratory studies and that aims to contextualize these processes in such a way that it becomes possible to model multidirectional, dynamic influences in extended social networks. At the micro-level, agent processes are simulated by recurrent auto-associative networks, an architecture that has a proven ability to simulate a variety of individual psychological and memory processes [1]. At the macro-level, these individual networks are combined into a "community of networks" so that they can exchange their individual information with each other by transmitting information on the same concepts from one net to another. This essentially creates a network structure that reflects a social system in which (a collection of) nodes represent individual agents and the links between agents the mutual social influences that connect them [2]. The network structure itself is dynamic and shaped by the interactions between the individual agents through simple processes of social adaptation. Through simulations, the cABM generates a number of novel predictions that broadly address three main issues: (1) the consequences of the interaction between multiple sources and targets of social influence (2) the dynamic development of social influence over time and (3) collective and individual opinion trajectories over time. Some of the predictions regarding individual level processes have been tested and confirmed in laboratory experiments. In a extensive research program, data is currently being collected from real groups that will allow validating the predictions of cABM regarding aggregate outcomes.

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Dirk Van Rooy

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