The LJDM seminar series is supported by
University College London
City University London
Originally established at UCL in the early 1970’s as a weekly Cognition and Reasoning seminar, it later became an intercollegiate seminar on Language and Cognition in the early 1980’s.
The name LJDM was finally coined in 1990, and the group has been running seminars under this name ever since, with lecturers and researchers in and around the UK meeting on a regular basis to discuss judgment and decision making, judgments of likelihood, reasoning, thinking, problem solving, forecasting, risk perception and communication, and other related topics.
If you would like to present your research to the group or to suggest a speaker, please contact the organizers:
Unless specified otherwise, all seminars take place on Wednesdays at 5pm, in Room 313 at the Psychology Department, University College London (on the corner of Bedford Way, Gordon Square and Torrington Place, London WC1H 0AP). Map.
To get updates on the current schedule and weekly reminders of the seminars, please subscribe to the Risk and Decision mailing list.
All are welcome to attend.
Term 1 Seminar Schedule
September – December 2019
Perceptual routes to social understanding
Understanding the thoughts and feelings of those around us is crucial for building social bonds. However, people lack direct access to others’ minds and regularly use perceptual cues to infer others’ mental states. In this talk, I outline how perceptual cues are analyzed for social meaning and explore how this process impacts the way we judge others’ mental states. In the first part of the talk, I will present behavioral and neural evidence in the domain of face perception to demonstrate that translating visual cues into social meaning occurs in two stages: a rapid, indiscriminate pattern-matching process that detects face configurations, followed by a slower more sustained stage wherein faces are scrutinized for mind detection. In the second part of the talk, I explore the consequences of relying on perceptual cues to understand others’ minds. In particular, I will present data on self-other biases in the evaluation of physical and mental experiences. Together these results suggest people rely on perceptual cues to understand others’ minds, but doing so subverts their ability to understand those minds accurately.
Kings College London
Causality, responsibility, blame, and interventions - how can we use them in software engineering?
There is a number of challenges in software engineering that can be roughly classified as “explanations challenges”: why is this system correct? why is this a buggy trace of a program? I am getting an error - where is the fault? why did my neural network classify this image as a racoon?
Not understanding why a certain decision has been made by an automated tool is not only worry-inducing for the users, but is also counter-productive for fixing errors. Indeed, if our automated tool says that the program contains an error and brings an erroneous execution as an example, we need more information in order to localise the problem and fix it. Similarly, if our neural network keeps misclassifying the inputs, we need to understand why this is happening in order to fix the problem. And even if our automated tool says that the program is correct, how can we be confident that the tool worked correctly?
In this talk I will survey these questions, which serve as a motivation for the talk. I will then introduce the notions of actual causality (introduced by Halpern and Pearl), and its quantitative measures responsibility and blame, as well as the more recent notion of interventions in causal models. I will demonstrate that these notions can be useful to answer the questions above, and that the computation of causality can be integrated into software engineering tools to produce helpful information that increases the user’s confidence and aids in locating and fixing errors.
I will conclude the talk with outlining some interesting future directions.
University of Warwick
Cognitive Selection in Information Evolution
There are well-understood psychological limits on our capacity to process information. As information proliferation— the consumption and sharing of information—increases through social media and other communications technology, these limits create an attentional bottleneck, favoring information that is more likely to be searched for, attended to, comprehended, encoded, and later reproduced. In information-rich environments, this bottleneck influences the evolution of information via four forces of cognitive selection, selecting for information that is belief-consistent, negative, social, and predictive. Selection for belief-consistent information leads balanced information to support increasingly polarized views. Selection for negative information amplifies information about downside risks and crowds out potential benefits. Selection for social information drives herding, impairs objective assessments, and reduces exploration for solutions to hard problems. Selection for predictive patterns drives overfitting, the replication crisis, and risk seeking. This article summarizes the negative implications of these forces of cognitive selection and presents eight warnings that represent severe pitfalls for the naive “informavore,” accelerating extremism, hysteria, herding, and the proliferation of misinformation.Paper: Hills, T. T. (2019). The dark side of information proliferation. Perspectives on Psychological Science, 14(3), 323-330.
University of Essex
How does processing of valenced information shape age differences in risk taking?
A wealth of research has shown that people are less inclined to take risks as they approach older age. Yet relatively little is known about the psychological mechanisms that underlie adult age differences in risk taking. In this talk, I will propose that age differences in the processing of positive and negative information play an important role in shaping age differences in risk taking. Recent findings will be discussed that suggest age differences in the processing of valenced information influences risk perceptions and behavioural intentions that inform decision-making. I will speculate that goal selection and prioritization across adulthood is adaptive for enhancing decision-making goals.
University of Edinburgh
Function learning, shared tasks, and computational models
I will describe a project to understand and evaluate computational cognitive models - or theories about human cogntion described in precise quantitative terms - using a "shared task" based on a large open data set and a set of simple, pre-defined criteria. I will argue that this approach has several advantages over the traditional model in which labs collect their own data sets and conduct in-house evaluations. It achieves many of the same goals as experiment and analysis pre-registration while avoiding some important downsides. This task focuses on function learning, or the human ability to observe evidence involving continuous variables and to learn the relationships underlying that evidence. In describing the data I have collected, the evaluation framework, and a few concrete experiments, I will touch on some issues that are relevant to a broad range of judgment and decision-making tasks. These include revealing individual differences in high-dimensional data (e.g., associative versus rule-based strategies and different ways that participants might disengage from an experiment), order effects, and different kinds of variability or noise.
(Not) Eating for the environment: The impact of vegetarian food category framing on vegetarian food choice
Eating less meat and farmed fish and more vegetarian foods is one of the key lifestyle changes that could help reverse the alarming climate trends. Relative to other green behaviours such as energy conservation, transforming dietary habits to tackle climate change has received little attention to date from both policy makers and psychologists. Previous research showed that changing the names of vegetarian dishes can influence their choice. However, can simply altering the name of the vegetarian food category but without changing the names of dishes belonging to this category impact the choice? In this talk, I will discuss the impact of framing on vegetarian food choice and present the findings from my recent line of studies where I tested how different types of framing (e.g. "pro-environmental" or "socialization") as well as different intervention strategies (e.g. combining vegetarian and non-vegetarian items in the same category) influence the choice of these foods compared to the label "vegetarian".
No seminar this week
University of Exeter
The Moral Machine Experiment
I describe the Moral Machine, an internet-based serious game exploring the many-dimensional ethical dilemmas faced by autonomous vehicles. The game enabled us to gather 40 million decisions from 3 million people in 200 countries/territories. I report the various preferences estimated from this data, and document interpersonal differences in the strength of these preferences. I also report cross-cultural ethical variation and uncover major clusters of countries exhibiting substantial differences along key moral preferences. These differences correlate with modern institutions, but also with deep cultural traits. I discuss how these three layers of preferences can help progress toward global, harmonious, and socially acceptable principles for machine ethics. Finally, I describe other follow up work that build on this project.
University of Kent
Moral actions and moral persons
A growing body of research has suggested that morality dominates person perception. Yet little is known about how the different kinds of moral judgments people make, the values they hold, and the behaviours they perform impact person perception. What should one do, for example, if the only way to prevent a major terrorist attack is to torture the child of the suspected terrorist until she releases the information of where her father is? Different ethical traditions give different answers: drawing on consequentialist theories one might say that you should torture the child because it will maximise overall welfare, but drawing on deontological ethical theories one might say that one should not torture the child because even if this helps bring about the best consequences overall, some things are just wrong. Different ethical traditions give different answers, and drawing on these different traditions might have different implications for person perception. In this talk I will I discuss some of my recent research on how deontological and consequentialist decision makers are perceived, and the implications this might have for why we hold the moral intuitions we do. I will highlight that that person perception is not just sensitive to whether someone has moral qualities, but the kinds of moral judgments they make.
University of New South Wales
Elucidating the differential impact of extreme-outcomes in perceptual and preferential choice
hen making decisions in complex environments we must selectively sample and process information with respect to task demands. Previous studies have shown that this requirement can manifest in the influence that extreme outcomes (i.e. values at the edges of a distribution) have on judgment and choice. We elucidate this influence via a task in which participants are presented, briefly, with an array of numbers and have to make one of two judgments. In ‘preferential’ judgments where the participants’ goal was to choose between a safe, known outcome, and an unknown outcome drawn from the array, extreme-outcomes had a greater influence on choice than mid-range outcomes, especially under shorter time-limits. In ‘perceptual’ judgments where the participants' goal was to estimate the arrays’ average, the influence of the extremes was less pronounced. In a follow-up study, we attempted to disentangle task goal and items' saliency as two independent factors that drive the selective mechanism. Findings show a replication of previous effects along with a new influence of salient items on choice. A novel cognitive process model captures these patterns via a two-step selective-sampling and integration mechanism. Together our results shed light on how task goals and items' saliency modulate sampling from complex environments, show how sampling determines choice, and highlight the conflicting conclusions that arise from applying statistical and cognitive models to data.
University of Leeds
A decision sciences approach for studying communications about uncertain climate projections to non-expert audiences
Policy makers and practitioners face decisions about climate change adaptation, which are often complex and long-term. At the same time, they often lack a background in climate science. Bodies such as the Intergovernmental Panel on Climate Change or The Met Office UK are tasked with communicating uncertain climate projections about the future to these audiences. In this seminar, I will present outcomes from an experiment, semi-structured interviews, as well as a systematic literature review on communications of such information. This will include the challenges these audiences face when trying to understand such information, as well as a set of recommendations on how findings from cognitive sciences and psychology can inform the design of such climate information, including different types of risk and uncertainty.
University of Essex
Improving uncertainty and risk communication. Review of recent findings with applications in health, climate change and weather forecasting
In most aspects of our life, uncertainty communication is critical for making informed decisions. The main problem, however, is that it comes in many forms and has a great scope for misunderstandings and biases. In my talk, I will provide an overview of my recent studies and argue that although there is no single best way to communicate uncertainty there might be a set of questions that can guide effective uncertainty communication.
(1) Is it beneficial to recipients to convey this uncertainty? People tend to prefer being certain to being uncertain, but as uncertainty can trigger indecision there is a trade-off between certainty, the precision of the event predicted, and the accuracy of the prediction. (2) What do you really want to say? Uncertainty quantifiers are not always used to convey uncertainty; they can also be used to smooth social relationships. Knowing our level of uncertainty and the kind of uncertainty we want to communicate may help to choose the right words. (3) Words or numbers (and their implications)? If your uncertainty is not rooted in frequencies of past events or models, it could be better communicated in words which better accounts for subjective uncertainty. Words are vague but they have some useful pragmatic functions such as to influence decision or “leak” extra information. On average, people consistently interpret the meaning of uncertainty words, but the same person interprets uncertainty differently depending on whether they formulate a prediction or receive it. If your uncertainty is precise enough, you could use numbers, but choose which numerical format with care, because some formats lead to specific biases (e.g., ratios) and misperceptions (e.g., trend effects).
I will close by discussing the next steps forward in the area of uncertainty communication by focusing on under-researched areas of uncertainty communication and new methodologies.