British journal of psychology最新文献_第3页

Generative neural networks for experimental manipulation: Examining dominance-trustworthiness face impressions with data-efficient models 用于实验操作的生成神经网络：用数据高效模型检验支配力-可信度面部印象。

IF 3.3 2区心理学

British journal of psychology Pub Date : 2026-04-05 Epub Date: 2024-09-23 DOI: 10.1111/bjop.12732

Adam Sobieszek, Maciej Siemiątkowski, Kamil K. Imbir

{"title":"Generative neural networks for experimental manipulation: Examining dominance-trustworthiness face impressions with data-efficient models","authors":"Adam Sobieszek, Maciej Siemiątkowski, Kamil K. Imbir","doi":"10.1111/bjop.12732","DOIUrl":"10.1111/bjop.12732","url":null,"abstract":"An important development in the study of face impressions was the introduction of dominance and trustworthiness as the primary and potentially orthogonal traits judged from faces. We test competing predictions of recent accounts that address evidence against the independence of these judgements. To this end we develop a version of recent ‘deep models of face impressions’ better suited for data-efficient experimental manipulation. In Study 1 (N = 128) we build impression models using 15 times less ratings per dimension than previously assumed necessary. In Study 2 (N = 234) we show how our method can precisely manipulate dominance and trustworthiness impressions of face photographs and observe how the effects' pattern of the cues of one trait on impressions of the other differs from previous accounts. We propose an altered account that stresses how a successful execution of the two judgements' functional roles requires impressions of trustworthiness and dominance to be based on cues of both traits. Finally we show our manipulation resulted in larger effect sizes using a broader array of features than previous methods. Our approach lets researchers manipulate face stimuli for various face perception studies and investigate new dimensions with minimal data collection.","PeriodicalId":9300,"journal":{"name":"British journal of psychology","volume":"117 2","pages":"636-655"},"PeriodicalIF":3.3,"publicationDate":"2026-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13051002/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142280540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The state of modelling face processing in humans with deep learning 基于深度学习的人脸处理模型的研究现状。

IF 3.3 2区心理学

British journal of psychology Pub Date : 2026-04-05 Epub Date: 2025-05-14 DOI: 10.1111/bjop.12794

P. Jonathon Phillips, David White

{"title":"The state of modelling face processing in humans with deep learning","authors":"P. Jonathon Phillips, David White","doi":"10.1111/bjop.12794","DOIUrl":"10.1111/bjop.12794","url":null,"abstract":"Deep learning models trained for facial recognition now surpass the highest performing human participants. Recent evidence suggests that they also model some qualitative aspects of face processing in humans. This review compares the current understanding of deep learning models with psychological models of the face processing system. Psychological models consist of two components that operate on the information encoded when people perceive a face, which we refer to here as ‘face codes’. The first component, the core system, extracts face codes from retinal input that encode invariant and changeable properties. The second component, the extended system, links face codes to personal information about a person and their social context. Studies of face codes in existing deep learning models reveal some surprising results. For example, face codes in networks designed for identity recognition also encode expression information, which contrasts with psychological models that separate invariant and changeable properties. Deep learning can also be used to implement candidate models of the face processing system, for example to compare alternative cognitive architectures and codes that might support interchange between core and extended face processing systems. We conclude by summarizing seven key lessons from this research and outlining three open questions for future study.","PeriodicalId":9300,"journal":{"name":"British journal of psychology","volume":"117 2","pages":"656-676"},"PeriodicalIF":3.3,"publicationDate":"2026-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13051013/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144060950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Scoping review on natural language processing applications in counselling and psychotherapy 关于咨询和心理治疗中自然语言处理应用的范围审查。

IF 3.3 2区心理学

British journal of psychology Pub Date : 2026-04-05 Epub Date: 2024-08-02 DOI: 10.1111/bjop.12721

Maria Laricheva, Yan Liu, Edward Shi, Amery Wu

引用次数: 0

How AI can advance psychological science 人工智能如何推动心理科学的发展。

IF 3.3 2区心理学

British journal of psychology Pub Date : 2026-04-05 Epub Date: 2025-12-09 DOI: 10.1111/bjop.70047

Galit Yovel

引用次数: 0

Comparability between AI and human cognition and its role in psychological research and AI ethics 人工智能与人类认知的可比性及其在心理学研究和人工智能伦理中的作用。

IF 3.3 2区心理学

British journal of psychology Pub Date : 2026-04-05 Epub Date: 2026-01-18 DOI: 10.1111/bjop.70056

Janet H. Hsiao

引用次数: 0

People have different expectations for their own versus others' use of AI-mediated communication tools 人们对自己和他人使用以人工智能为媒介的通信工具有着不同的期望。

IF 3.3 2区心理学

British journal of psychology Pub Date : 2026-04-05 Epub Date: 2024-09-04 DOI: 10.1111/bjop.12727

Zoe A. Purcell, Mengchen Dong, Anne-Marie Nussberger, Nils Köbis, Maurice Jakesch

{"title":"People have different expectations for their own versus others' use of AI-mediated communication tools","authors":"Zoe A. Purcell, Mengchen Dong, Anne-Marie Nussberger, Nils Köbis, Maurice Jakesch","doi":"10.1111/bjop.12727","DOIUrl":"10.1111/bjop.12727","url":null,"abstract":"Artificial intelligence (AI) can enhance human communication, for example, by improving the quality of our writing, voice or appearance. However, AI mediated communication also has risks—it may increase deception, compromise authenticity or yield widespread mistrust. As a result, both policymakers and technology firms are developing approaches to prevent and reduce potentially unacceptable uses of AI communication technologies. However, we do not yet know what people believe is acceptable or what their expectations are regarding usage. Drawing on normative psychology theories, we examine people's judgements of the acceptability of open and secret AI use, as well as people's expectations of their own and others' use. In two studies with representative samples (Study 1: N = 477; Study 2: N = 765), we find that people are less accepting of secret than open AI use in communication, but only when directly compared. Our results also suggest that people believe others will use AI communication tools more than they would themselves and that people do not expect others' use to align with their expectations of what is acceptable. While much attention has been focused on transparency measures, our results suggest that self-other differences are a central factor for understanding people's attitudes and expectations for AI-mediated communication.","PeriodicalId":9300,"journal":{"name":"British journal of psychology","volume":"117 2","pages":"548-566"},"PeriodicalIF":3.3,"publicationDate":"2026-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13051031/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142124883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing novelty, feasibility and value of creative ideas with an unsupervised approach using GPT-4 使用 GPT-4 无监督方法评估创意的新颖性、可行性和价值。

IF 3.3 2区心理学

British journal of psychology Pub Date : 2026-04-05 Epub Date: 2024-07-22 DOI: 10.1111/bjop.12720

Felix B. Kern, Chien-Te Wu, Zenas C. Chao

{"title":"Assessing novelty, feasibility and value of creative ideas with an unsupervised approach using GPT-4","authors":"Felix B. Kern, Chien-Te Wu, Zenas C. Chao","doi":"10.1111/bjop.12720","DOIUrl":"10.1111/bjop.12720","url":null,"abstract":"Creativity is defined by three key factors: novelty, feasibility and value. While many creativity tests focus primarily on novelty, they often neglect feasibility and value, thereby limiting their reflection of real-world creativity. In this study, we employ GPT-4, a large language model, to assess these three dimensions in a Japanese-language Alternative Uses Test (AUT). Using a crowdsourced evaluation method, we acquire ground truth data for 30 question items and test various GPT prompt designs. Our findings show that asking for multiple responses in a single prompt, using an ‘explain first, rate later’ design, is both cost-effective and accurate (r = .62, .59 and .33 for novelty, feasibility and value, respectively). Moreover, our method offers comparable accuracy to existing methods in assessing novelty, without the need for training data. We also evaluate additional models such as GPT-4 Turbo, GPT-4 Omni and Claude 3.5 Sonnet. Comparable performance across these models demonstrates the universal applicability of our prompt design. Our results contribute a straightforward platform for instant AUT evaluation and provide valuable ground truth data for future methodological research.","PeriodicalId":9300,"journal":{"name":"British journal of psychology","volume":"117 2","pages":"741-760"},"PeriodicalIF":3.3,"publicationDate":"2026-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13051022/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141733636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Decoding the language of first impressions: Comparing models of first impressions of faces derived from free-text descriptions and trait ratings 解码第一印象语言：比较从自由文本描述和特质评分中得出的面孔第一印象模型。

IF 3.3 2区心理学

British journal of psychology Pub Date : 2026-04-05 Epub Date: 2024-06-17 DOI: 10.1111/bjop.12717

Alex L. Jones, Victor Shiramizu, Benedict C. Jones

{"title":"Decoding the language of first impressions: Comparing models of first impressions of faces derived from free-text descriptions and trait ratings","authors":"Alex L. Jones, Victor Shiramizu, Benedict C. Jones","doi":"10.1111/bjop.12717","DOIUrl":"10.1111/bjop.12717","url":null,"abstract":"First impressions formed from facial appearance predict important social outcomes. Existing models of these impressions indicate they are underpinned by dimensions of Valence and Dominance, and are typically derived by applying data reduction methods to explicit ratings of faces for a range of traits. However, this approach is potentially problematic because the trait ratings may not fully capture the dimensions on which people spontaneously assess faces. Here, we used natural language processing to extract ‘topics’ directly from participants' free-text descriptions (i.e., their first impressions) of 2222 face images. Two topics emerged, reflecting first impressions related to positive emotional valence and warmth (Topic 1) and negative emotional valence and potential threat (Topic 2). Next, we investigated how these topics were related to Valence and Dominance components derived from explicit trait ratings. Collectively, these components explained only ~44% of the variance in the topics extracted from free-text descriptions and suggested that first impressions are underpinned by correlated valence dimensions that subsume the content of existing trait-rating-based models. Natural language offers a promising new avenue for understanding social cognition, and future work can examine the predictive utility of natural language and traditional data-driven models for impressions in varying social contexts.","PeriodicalId":9300,"journal":{"name":"British journal of psychology","volume":"117 2","pages":"725-740"},"PeriodicalIF":3.3,"publicationDate":"2026-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13051011/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141417870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unveiling the factors of aesthetic preferences with explainable AI 用可解释的人工智能揭示审美偏好的因素。

IF 3.3 2区心理学

British journal of psychology Pub Date : 2026-04-05 Epub Date: 2024-05-17 DOI: 10.1111/bjop.12707

Derya Soydaner, Johan Wagemans

{"title":"Unveiling the factors of aesthetic preferences with explainable AI","authors":"Derya Soydaner, Johan Wagemans","doi":"10.1111/bjop.12707","DOIUrl":"10.1111/bjop.12707","url":null,"abstract":"The allure of aesthetic appeal in images captivates our senses, yet the underlying intricacies of aesthetic preferences remain elusive. In this study, we pioneer a novel perspective by utilizing several different machine learning (ML) models that focus on aesthetic attributes known to influence preferences. Our models process these attributes as inputs to predict the aesthetic scores of images. Moreover, to delve deeper and obtain interpretable explanations regarding the factors driving aesthetic preferences, we utilize the popular Explainable AI (XAI) technique known as SHapley Additive exPlanations (SHAP). Our methodology compares the performance of various ML models, including Random Forest, XGBoost, Support Vector Regression, and Multilayer Perceptron, in accurately predicting aesthetic scores, and consistently observing results in conjunction with SHAP. We conduct experiments on three image aesthetic benchmarks, namely Aesthetics with Attributes Database (AADB), Explainable Visual Aesthetics (EVA), and Personalized image Aesthetics database with Rich Attributes (PARA), providing insights into the roles of attributes and their interactions. Finally, our study presents ML models for aesthetics research, alongside the introduction of XAI. Our aim is to shed light on the complex nature of aesthetic preferences in images through ML and to provide a deeper understanding of the attributes that influence aesthetic judgements.","PeriodicalId":9300,"journal":{"name":"British journal of psychology","volume":"117 2","pages":"444-478"},"PeriodicalIF":3.3,"publicationDate":"2026-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13051012/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140961481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Serial dependence in time perception requires consistent motor responses, not shared memory alone. 时间感知的序列依赖需要一致的运动反应，而不仅仅是共享记忆。

IF 3.3 2区心理学

British journal of psychology Pub Date : 2026-04-03 DOI: 10.1111/bjop.70070

Jiao Wu, Halid Oğuz Serçe, Zhuanghua Shi

{"title":"Serial dependence in time perception requires consistent motor responses, not shared memory alone.","authors":"Jiao Wu, Halid Oğuz Serçe, Zhuanghua Shi","doi":"10.1111/bjop.70070","DOIUrl":"https://doi.org/10.1111/bjop.70070","url":null,"abstract":"Serial dependence-the bias from recent experience on present response-has been attributed to shared memory representations, yet previous studies yielded contradictory findings about whether consistent motor responses are required. To address this debate in time perception, we tested whether serial dependence emerges when tasks share identical stimulus features but differ only in response modes. We interleaved temporal reproduction and bisection tasks using a post-cue design that held duration encoding constant while varying motor output across trials. Grounded in binding and retrieval in action control (BRAC) theory, we hypothesized that response-feature binding retrieval drives serial dependence. Using structural equation modelling (SEM), we dissociated perceptual (stimulus-driven) and decisional (response-driven) components. With the same task, we replicated repulsive perceptual serial dependence and attractive decisional carryover. Critically, both effects vanished across tasks despite identical stimulus processing-demonstrating that response-mode consistency, not shared memory alone, drives sequential biases in temporal judgements. Our SEM approach uncovered repulsive perceptual influences that standard regression missed, highlighting its power to isolate overlapping effects. These findings reveal that response-specific reactivation of event files underpins serial dependence in temporal decision-making.","PeriodicalId":9300,"journal":{"name":"British journal of psychology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147615720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0