Computers in Human Behavior: Artificial Humans最新文献_第4页

Knowledge cues to human origins facilitate self-disclosure during interactions with chatbots 关于人类起源的知识线索有助于在与聊天机器人的互动中自我披露

Computers in Human Behavior: Artificial Humans Pub Date : 2025-06-20 DOI: 10.1016/j.chbah.2025.100174

Gabriella Warren-Smith , Guy Laban , Emily-Marie Pacheco , Emily S. Cross

{"title":"Knowledge cues to human origins facilitate self-disclosure during interactions with chatbots","authors":"Gabriella Warren-Smith , Guy Laban , Emily-Marie Pacheco , Emily S. Cross","doi":"10.1016/j.chbah.2025.100174","DOIUrl":"10.1016/j.chbah.2025.100174","url":null,"abstract":"<div><div>Chatbots are emerging as a self-management tool for supporting mental health, appearing across commercial and healthcare settings. Whilst chatbots are valued for their perceived lack of judgement, they lack the emotional intelligence and empathy to build trust and rapport with users. A resulting debate questions whether chatbots facilitate or hinder self-disclosure. This study presents a within-subjects experimental design investigating the parameters of self-disclosure in social interactions with chatbots in an open domain. Participants engaged in two short social interactions with two chatbots: one with the knowledge they were conversing with a chatbot and one with the false belief they were conversing with a human. A significant difference was found across both treatments, with participants disclosing more to the chatbot that was introduced as a human, as well as perceiving themselves to do so, perceiving this chatbot as more comforting, and to be demonstrating higher rates of agency and experience compared to the chatbot that was introduced as a chatbot. However, significant findings also indicated participants’ disclosures to the chatbot that was introduced as a chatbot were more sentimental, and they found it to be friendlier compared to the chatbot that was introduced as a human. These results indicate that whilst cues to a chatbot’s human origins enhance self-disclosure and perceptions of mind, when the artificial agent is perceived against one’s social expectations, it may be viewed negatively on social factors that require higher cognitive processing.</div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"5 ","pages":"Article 100174"},"PeriodicalIF":0.0,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144632459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluating the Intelligence of large language models: A comparative study using verbal and visual IQ tests 评估大型语言模型的智力：使用口头和视觉智商测试的比较研究

Computers in Human Behavior: Artificial Humans Pub Date : 2025-06-18 DOI: 10.1016/j.chbah.2025.100170

Sherif Abdelkarim , David Lu , Dora-Luz Flores , Susanne Jaeggi , Pierre Baldi

{"title":"Evaluating the Intelligence of large language models: A comparative study using verbal and visual IQ tests","authors":"Sherif Abdelkarim , David Lu , Dora-Luz Flores , Susanne Jaeggi , Pierre Baldi","doi":"10.1016/j.chbah.2025.100170","DOIUrl":"10.1016/j.chbah.2025.100170","url":null,"abstract":"<div><div>Large language models (LLMs) excel on many specialized benchmarks, yet their general-reasoning ability remains opaque. We therefore test 18 models – including GPT-4, Claude 3 and Gemini Pro – on a 14-section IQ suite spanning verbal, numerical and visual puzzles and add a “multi-agent reflection” variant in which one model answers while others critique and revise. Results replicate known patterns: a strong bias towards verbal vs numerical reasoning (GPT-4: 79% vs 53% accuracy), a pronounced modality gap (text-IQ <span><math><mo>≈</mo></math></span> 125 vs visual-IQ <span><math><mo>≈</mo></math></span> 103), and persistent failure on abstract arithmetic (<span><math><mo>≤</mo></math></span> 20% on missing-number tasks). Scaling lifts mean IQ from 89 (tiny models) to 131 (large models), but gains are non-uniform, and reflection yields only modest extra points for frontier systems. Our contributions include: (1) proposing an evaluation framework for LLM “intelligence” using both verbal and visual IQ tasks, (2) analyzing how multi-agent setups with varying actor and critic sizes affect problem-solving performance; (3) analyzing how model size and multi-modality affect performance across diverse reasoning tasks; and (4) highlighting the value of IQ tests as a standardized, human-referenced benchmark that enables longitudinal comparison of LLMs’ cognitive abilities relative to human norms. We further discuss the limitations of IQ tests as an AI benchmark and outline directions for more comprehensive evaluation of LLM reasoning capabilities.</div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"5 ","pages":"Article 100170"},"PeriodicalIF":0.0,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144470648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development and validation of a short AI literacy test (AILIT-S) for university students 大学生人工智能读写能力短测试（AILIT-S）的开发和验证

Computers in Human Behavior: Artificial Humans Pub Date : 2025-06-16 DOI: 10.1016/j.chbah.2025.100176

Marie Hornberger , Arne Bewersdorff , Daniel S. Schiff , Claudia Nerdel

{"title":"Development and validation of a short AI literacy test (AILIT-S) for university students","authors":"Marie Hornberger , Arne Bewersdorff , Daniel S. Schiff , Claudia Nerdel","doi":"10.1016/j.chbah.2025.100176","DOIUrl":"10.1016/j.chbah.2025.100176","url":null,"abstract":"<div><div>Fostering AI literacy is an important goal in higher education in many disciplines. Assessing AI literacy can inform researchers and educators on current AI literacy levels and provide insights into the effectiveness of learning and teaching in the field of AI. It can also inform decision-makers and policymakers about the successes and gaps with respect to AI literacy within certain institutions, populations, or countries, for example. However, most of the available AI literacy tests are quite long and time-consuming. A short test of AI literacy would instead enable efficient measurement and facilitate better research and understanding. In this study, we develop and validate a short version of an existing validated AI literacy test. Based on a sample of 1,465 university students across three Western countries (Germany, UK, US), we select a subset of items according to content validity, coverage of different difficulty levels, and ability to discriminate between participants. The resulting short version, AILIT-S, consists of 10 items and can be used to assess AI literacy in under 5 minutes. While the shortened test is less reliable than the long version, it maintains high construct validity and has high congruent validity. We offer recommendations for researchers and practitioners on when to use the long or short version.</div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"5 ","pages":"Article 100176"},"PeriodicalIF":0.0,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144470639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Using educational robotics to support motor, cognitive, and social skills in a child with spinal muscular atrophy. A single-case study 使用教育机器人来支持脊髓性肌萎缩症儿童的运动、认知和社交技能。单例研究

Computers in Human Behavior: Artificial Humans Pub Date : 2025-06-13 DOI: 10.1016/j.chbah.2025.100175

Antonella D'Amico , Giuseppina Paci , Laura di Domenico , Alessandro Geraci

{"title":"Using educational robotics to support motor, cognitive, and social skills in a child with spinal muscular atrophy. A single-case study","authors":"Antonella D'Amico , Giuseppina Paci , Laura di Domenico , Alessandro Geraci","doi":"10.1016/j.chbah.2025.100175","DOIUrl":"10.1016/j.chbah.2025.100175","url":null,"abstract":"<div><div>This study reports the results of a single-case intervention involving a child with spinal muscular atrophy. The aim of the study was to promote fine motor skills, visual-motor integration, attentional behaviors, and learning. The treatment was based on the RE4BES protocol, which consists of a set of guidelines for conducting tailored educational robotics activities designed for children with special needs. We employed an experimental single-case ABA design, including Baseline 1 (A1), Treatment (B), and Baseline 2 (A2), with eight sessions per phase. The treatment phase involved activities with Blue-Bot and LEGO® WeDo 2.0. Results showed significant improvements in gross and fine motor skills from baseline to the treatment phase, with these gains maintained after the intervention. Moreover, in alignment with the main goals of school inclusion for people with special needs, results demonstrated that the intervention also improved awareness, flexibility, cooperation, and initiative within the classroom. Despite the study's limitations, the findings support the effectiveness of the RE4BES protocol and suggest that educational robotics can be a valuable tool in special education settings.</div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"5 ","pages":"Article 100175"},"PeriodicalIF":0.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144288715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Gaze-informed signatures of trust and collaboration in human-autonomy teams 人类自主团队中信任和协作的注视信息签名

Computers in Human Behavior: Artificial Humans Pub Date : 2025-06-07 DOI: 10.1016/j.chbah.2025.100171

Anthony J. Ries , Stéphane Aroca-Ouellette , Alessandro Roncone , Ewart J. de Visser

{"title":"Gaze-informed signatures of trust and collaboration in human-autonomy teams","authors":"Anthony J. Ries , Stéphane Aroca-Ouellette , Alessandro Roncone , Ewart J. de Visser","doi":"10.1016/j.chbah.2025.100171","DOIUrl":"10.1016/j.chbah.2025.100171","url":null,"abstract":"<div><div>In the evolving landscape of human-autonomy teaming (HAT), fostering effective collaboration and trust between human and autonomous agents is increasingly important. To explore this, we used the game Overcooked AI to create dynamic teaming scenarios featuring varying agent behaviors (clumsy, rigid, adaptive) and environmental complexities (low, medium, high). Our objectives were to assess the performance of adaptive AI agents designed with hierarchical reinforcement learning for better teamwork and measure eye tracking signals related to changes in trust and collaboration. The results indicate that the adaptive agent was more effective in managing teaming and creating an equitable task distribution across environments compared to the other agents. Working with the adaptive agent resulted in better coordination, reduced collisions, more balanced task contributions, and higher trust ratings. Reduced gaze allocation, across all agents, was associated with higher trust levels, while blink count, scanpath length, agent revisits and trust were predictive of the human's contribution to the team. Notably, fixation revisits on the agent increased with environmental complexity and decreased with agent versatility, offering a unique metric for measuring teammate performance monitoring. This is one of the first studies to use gaze metrics such as revisits, gaze allocation, and scanpath length to predict not only trust, but also human contribution to teaming behavior in a real-time task with cooperative agents. These findings underscore the importance of designing autonomous teammates that not only excel in task performance but also enhance teamwork by being more predictable and reducing the cognitive load on human team members. Additionally, this study highlights the potential of eye-tracking as an unobtrusive measure for evaluating and improving human-autonomy teams, suggesting eye gaze could be used by agents to dynamically adapt their behaviors.</div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"5 ","pages":"Article 100171"},"PeriodicalIF":0.0,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144563946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Increased morality through social communication or decision situation worsens the acceptance of robo-advisors 通过社会沟通或决策情况增加的道德会使机器人顾问的接受程度恶化

Computers in Human Behavior: Artificial Humans Pub Date : 2025-06-06 DOI: 10.1016/j.chbah.2025.100173

Clarissa Sabrina Arlinghaus , Carolin Straßmann , Annika Dix

{"title":"Increased morality through social communication or decision situation worsens the acceptance of robo-advisors","authors":"Clarissa Sabrina Arlinghaus , Carolin Straßmann , Annika Dix","doi":"10.1016/j.chbah.2025.100173","DOIUrl":"10.1016/j.chbah.2025.100173","url":null,"abstract":"<div><div>This German study (<em>N</em> = 317) tests social communication (i.e., self-disclosure, content intimacy, relational continuity units, we-phrases) as a potential compensation strategy for algorithm aversion. Therefore, we explore the acceptance of a robot as an advisor in non-moral, somewhat moral, and very moral decision situations and compare the influence of two verbal communication styles of the robot (functional vs. social).</div><div>Subjects followed the robot's recommendation similarly often for both communication styles (functional vs. social), but more often in the non-moral decision situation than in the moral decision situations. Subjects perceived the robot as more human and more moral during social communication than during functional communication but similarly trustworthy, likable, and intelligent for both communication styles. In moral decision situations, subjects ascribed more anthropomorphism and morality but less trust, likability, and intelligence to the robot compared to the non-moral decision situation.</div><div>Subjects perceive the robot as more moral in social communication. This unexpectedly led to subjects following the robot's recommendation less often. No other mediation effects were found. From this we conclude, that the verbal communication style alone has a rather small influence on the robot's acceptance as an advisor for moral decision-making and does not reduce algorithm aversion. Potential reasons for this (e.g., multimodality, no visual changes), as well as implications (e.g., avoidance of self-disclosure in human-robot interaction) and limitations (e.g., video interaction) of this study, are discussed.</div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"5 ","pages":"Article 100173"},"PeriodicalIF":0.0,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144263624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Of love & lasers: Perceptions of narratives by AI versus human authors 爱与激光：人工智能与人类作者的叙事感知

Computers in Human Behavior: Artificial Humans Pub Date : 2025-06-06 DOI: 10.1016/j.chbah.2025.100168

Gavin Raffloer, Melanie C Green

{"title":"Of love & lasers: Perceptions of narratives by AI versus human authors","authors":"Gavin Raffloer, Melanie C Green","doi":"10.1016/j.chbah.2025.100168","DOIUrl":"10.1016/j.chbah.2025.100168","url":null,"abstract":"<div><div>Artificial Intelligence (AI) programs can produce narratives. However, readers' preconceptions about AI may influence their response to these narratives, and furthermore, AI-generated writing may differ from human writing. Genre may also be relevant for readers’ attitudes regarding AI. This study tests the effects of actual AI versus human authorship, stated (labeled) authorship, and genre on perceptions of narratives and narrative engagement. Participants were randomly assigned within a 2 (actual author: human or AI) X 2 (stated author: human or AI) X 2 (genre: romance or science fiction) design, across two studies. In Study 1, actual AI narratives were perceived as more enjoyable, but human narratives were more appreciated. Furthermore, participants enjoyed actual AI-written sci-fi more than human-written sci-fi. Study 2 found that actual AI stories were rated more highly, particularly in appreciation, transportation, character identification, and future engagement. However, stated human authorship led to higher ratings for romance, but not for sci-fi. An interaction was observed such that for the sci-fi condition, stated human writing was perceived as more likely to be actually AI-written. Future research could expand upon these findings across more genres, as well as examining the determinants of preferences for stated human content.</div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"5 ","pages":"Article 100168"},"PeriodicalIF":0.0,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144263722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

To Be competitive or not to be competitive: How performance goals shape human-AI and human-human collaboration 竞争还是不竞争：绩效目标如何塑造人类-人工智能和人与人之间的合作

Computers in Human Behavior: Artificial Humans Pub Date : 2025-06-05 DOI: 10.1016/j.chbah.2025.100169

Spatola Nicolas

{"title":"To Be competitive or not to be competitive: How performance goals shape human-AI and human-human collaboration","authors":"Spatola Nicolas","doi":"10.1016/j.chbah.2025.100169","DOIUrl":"10.1016/j.chbah.2025.100169","url":null,"abstract":"<div><div>Due to generative AI, and particularly algorithms using large language models, people's use of algorithms as recommendation tools is increasing at an unprecedented pace. While these tools are used in both private and work contexts, less is known about how the motivational context surrounding algorithm use impacts reliance patterns. This research examined how competitive versus non-performance goals affect adherence to algorithmic versus human recommendation. In Experiment 1, participants completed Raven's Matrices with optional algorithm assistance. Framing the task as a competitive test increased reliance on the algorithm compared to a control condition. This effect was mediated by heightened perceived usefulness but not accuracy. Experiment 2 introduced human assistance alongside the algorithm assistance from Experiment 1. Performance (compared to control) goals increased reliance on the algorithm over peer assistance by selectively enhancing the perceived usefulness of the algorithm versus human assistance. These results demonstrate how setting goals may influence the preference to rely on algorithmic or human assistance and particularly how performance goal contexts catalyze a situation in which participants are more prone to rely on algorithms compared to peer recommendation. These results are discussed with regard to social goals and social cognition in competitive settings with the aim of elucidating how motivational framing shapes human-AI collaborative dynamics, informing responsible system design.</div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"5 ","pages":"Article 100169"},"PeriodicalIF":0.0,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144241902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Artificial social influence via human-embodied AI agent interaction in immersive virtual reality (VR): Effects of similarity-matching during health conversations 沉浸式虚拟现实（VR）中人工智能代理交互的人工社会影响：健康对话中的相似性匹配效应

Computers in Human Behavior: Artificial Humans Pub Date : 2025-06-03 DOI: 10.1016/j.chbah.2025.100172

Sue Lim, Ralf Schmälzle, Gary Bente

{"title":"Artificial social influence via human-embodied AI agent interaction in immersive virtual reality (VR): Effects of similarity-matching during health conversations","authors":"Sue Lim, Ralf Schmälzle, Gary Bente","doi":"10.1016/j.chbah.2025.100172","DOIUrl":"10.1016/j.chbah.2025.100172","url":null,"abstract":"<div><div>Interactions with artificial intelligence (AI) based agents can positively influence human behavior and judgment. However, studies to date focus on text-based conversational agents (CA) with limited embodiment, restricting our understanding of how social influence principles, such as physical similarity, apply to AI agents (i.e., artificial social influence). We address this gap by leveraging latest advances in AI (large language models) and combining them with immersive virtual reality (VR). Specifically, we built VR-ECAs, or embodied conversational agents that can engage in turn-taking conversations with humans about health-related topics in a virtual environment. Then we manipulated interpersonal similarity via gender matching and examined its effects on biobehavioral (i.e., gaze), social (e.g., agent likeability), and behavioral outcomes (i.e., healthy snack selection). We observed an interaction effect between agent and participant gender on biobehavioral outcomes: discussing health with opposite-gender agents tended to enhance gaze duration, with the effect stronger for male participants compared to their female counterparts. A similar directional pattern was observed for healthy snack selection. In addition, female participants liked the VR-ECAs more than their male counterparts, regardless of the VR-ECAs’ gender. Finally, participants experienced greater presence while conversing with embodied agents than chatting with text-only agents. Overall, our findings highlight embodiment as a crucial factor of AI's influence on human behavior, and our paradigm enables new experimental research at the intersection of social influence, human-AI communication, and immersive virtual reality (VR).</div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"5 ","pages":"Article 100172"},"PeriodicalIF":0.0,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144270226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Whose mind is it anyway? A systematic review and exploration on agency in cognitive augmentation 这到底是谁的想法？认知增强中能动性的系统回顾与探索

Computers in Human Behavior: Artificial Humans Pub Date : 2025-06-02 DOI: 10.1016/j.chbah.2025.100158

Steeven Villa , Lisa L. Barth , Francesco Chiossi , Robin Welsch , Thomas Kosch

{"title":"Whose mind is it anyway? A systematic review and exploration on agency in cognitive augmentation","authors":"Steeven Villa , Lisa L. Barth , Francesco Chiossi , Robin Welsch , Thomas Kosch","doi":"10.1016/j.chbah.2025.100158","DOIUrl":"10.1016/j.chbah.2025.100158","url":null,"abstract":"<div><div>Technologies for human augmentation aim to enhance sensory, motor, and cognitive abilities. Despite the growing interest in cognitive augmentation, the sense of agency and the feeling of control over one’s actions and outcomes remained underexplored. We conducted a systematic literature review, screening 434 human–computer Interaction articles, and identified 27 papers examining agency in cognitive augmentation. Our analysis revealed a lack of objective methods to measure the sense of agency. We analyzed Electroencephalography (EEG) data of a dataset from 27 participants performing a Columbia Card Task with and without perceived AI assistance to address this research gap. We observed changes in EEG data for alpha and low-beta power, demonstrating EEG as a measure of perceived cognitive agency. These findings demonstrate how EEG can quantify perceived agency, presenting a method to evaluate the impact of cognitive augmentation technologies on the sense of agency. This study not only provides a novel neurophysiological approach for assessing the impact of cognitive augmentation technologies on agency but also leads the way to designing interfaces that create user awareness regarding their sense of agency.</div></div>","PeriodicalId":100324,"journal":{"name":"Computers in Human Behavior: Artificial Humans","volume":"5 ","pages":"Article 100158"},"PeriodicalIF":0.0,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144470649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0