Collective intelligence in fingerprint analysis

When a fingerprint is located at a crime scene, a human examiner is counted upon to manually compare this print to those stored in a database. Several experiments have now shown that these professional analysts are highly accurate, but not infallible, much like other fields that involve high-stakes decision-making. One method to offset mistakes in these safety-critical domains is to distribute these important decisions to groups of raters who independently assess the same information. This redundancy in the system allows it to continue operating effectively even in the face of rare and random errors. Here, we extend this "wisdom of crowds" approach to fingerprint analysis by comparing the performance of individuals to crowds of professional analysts. We replicate the previous findings that individual experts greatly outperform individual novices, particularly in their false-positive rate, but they do make mistakes. When we pool the decisions of small groups of experts by selecting the decision of the majority, however, their false-positive rate decreases by up to 8% and their false-negative rate decreases by up to 12%. Pooling the decisions of novices results in a similar drop in false negatives, but increases their false-positive rate by up to 11%. Aggregating people's judgements by selecting the majority decision performs better than selecting the decision of the most confident or the most experienced rater. Our results show that combining independent judgements from small groups of fingerprint analysts can improve their performance and prevent these mistakes from entering courts.Jason M. Tangen, Kirsty M. Kent and Rachel A. Searsto

The sensorium at work: the sensory phenomenology of the working body

The sociology of the body and the sociology of work and occupations have both neglected to some extent the study of the ‘working body’ in paid employment, particularly with regard to empirical research into the sensory aspects of working practices. This gap is perhaps surprising given how strongly the sensory dimension features in much of working life. This article is very much a first step in calling for a more phenomenological, embodied and ‘fleshy’ perspective on the body in employment, and examines some of the theoretical and conceptual resources available to researchers wishing to focus on the lived working-body experiences of the sensorium. We also consider some possible representational forms for a more evocative, phenomenologically-inspired portrayal of sensory, lived-working-body experiences, and offer suggestions for future avenues of research

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Peer reviewe

A multiple-task reduction approach to measuring perceptual expertise in fingerprint analysis

Presentation - General talks #12Searston R. A., Tangen, J. M., Thompson, M. B

Collective intelligence in perceptual decision making

Program of the 60th Annual Meeting published as part of Abstracts of the Psychonomic SocietyJason Tangen, Rachel A. Searston, Kirsty Ken

Specific versus varied practice in perceptual expertise training

Published December 2022We used a longitudinal randomized control experiment to compare the effect of specific practice (training on one form of a task) and varied practice (training on various forms of a task) on perceptual learning and transfer. Participants practiced a visual search task for 10 hours over 2 to 4 weeks. The specific practice group searched for features only in fingerprints during each session, whereas the varied practice group searched for features in five different image categories. Both groups were tested on a series of tasks at four time points: before training, midway through training, immediately after training ended, and 6 to 8 weeks later. The specific group improved more during training and demonstrated greater pre-post performance gains than the varied group on a visual search task with untrained fingerprint images. Both groups improved equally on a visual search task with an untrained image category, but only the specific group's performance dropped significantly when tested several weeks later. Finally, both groups improved equally on a series of untrained fingerprint tasks. Practice with respect to a single category (versus many) instills better near transfer, but category-specific and category-general visual search training appear equally effective for developing task-general expertise. (PsycInfo Database Record (c) 2022 APA, all rights reserved).Samuel G. Robson, Jason M. Tangen, Rachel A. Searsto

Measuring and simulating human perceptual categorisation performance using Signal Detection Theory

Samuel Robson, Rachel Searston, Matthew Thompson, Brooklyn Corbett, Jason Tange

How low can you go? Detecting style in extremely low resolution images

Humans can see through the complexity of scenes, faces, and objects by quickly extracting their redundant low-spatial and low-dimensional global properties, or their style. It remains unclear, however, whether semantic coding is necessary, or whether visual stylistic information is sufficient, for people to recognize and discriminate complex images and categories. In two experiments, we systematically reduce the resolution of hundreds of unique paintings, birds, and faces, and test people's ability to discriminate and recognize them. We show that the stylistic information retained at extremely low image resolutions is sufficient for visual recognition of images and visual discrimination of categories. Averaging over the 3 domains, people were able to reliably recognize images reduced down to a single pixel, with large differences from chance discriminability across 8 different image resolutions. People were also able to discriminate categories substantially above chance with an image resolution as low as 2 × 2 pixels. We situate our findings in the context of contemporary computational accounts of visual recognition and contend that explicit encoding of the local features in the image, or knowledge of the semantic category, is not necessary for recognizing and distinguishing complex visual stimuli

Getting a grip on insight: real-time and embodied Aha experiences predict correct solutions

© 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.Insight experiences are sudden, persuasive, and can accompany valuable new ideas in science and art. In this preregistered experiment, we aim to validate a novel visceral and continuous measure of insight problem solving and to test whether real-time and embodied feelings of insight can predict correct solutions. We report several findings. Consistent with recent work, we find a strong positive relationship between Aha moments and accuracy for problems that demand implicit processing. We also found that the intensity of the insight experience further predicted the accuracy of solutions and participants naturally embodied the intensity of their insight experiences by squeezing the dynamometer more tightly. Intriguingly, this unintentional embodiment further predicted the accuracy of solutions. We suggest that the dynamometer complements previous measures by (1) simultaneously capturing both process and feeling in real-time, (2) highlights the value of measuring Aha moments on a continuum of intensity, and (3) firmly establishes that the impulsive feeling of Aha can carry information about the veracity of an idea. We discuss the findings in light of a recent theoretical account of how feelings of insight may act as a heuristic to select ideas from the stream of consciousness

Promoting open science: a holistic approach to changing behaviour

In this article, we provide a toolbox of recommendations and resources for those aspiring to promote the uptake of open scientific practices. Open Science encompasses a range of behaviours that aim to improve the transparency of scientific research. This paper is divided into seven sections, each devoted to different groups or institutions in the research ecosystem: colleagues, students, departments and faculties, universities, academic libraries, journals, and funders. We describe the behavioural influences and incentives for each of these stakeholders as well as changes they can make to foster Open Science. Our primary goal, however, is to suggest actions that researchers can take to promote these behaviours, inspired by simple principles of behaviour change: make it easy, social, and attractive. In isolation, a small shift in one person’s behaviour may appear to make little difference, but when combined, many shifts can radically alter shared norms and culture. We offer this toolbox to assist individuals and institutions in cultivating a more open research culture.Samuel G. Robson, Myriam A. Baum, Jennifer L. Beaudry, Julia Beitner, Hilmar Brohmer, Jason M. Chin, Katarzyna Jasko, Chrystyna D. Kouros, Ruben E. Laukkonen, David Moreau, Rachel A. Searston, Heleen A. Slagter, Niklas K. Steffens, Jason M. Tangen, Amberyn Thoma