Nature Human Behaviour最新文献_第5页

Risks and protective measures for synthetic relationships 合成关系的风险和保护措施

IF 21.4 1区心理学

Nature Human Behaviour Pub Date : 2024-10-22 DOI: 10.1038/s41562-024-02005-4

Christopher Starke, Alfio Ventura, Clara Bersch, Meeyoung Cha, Claes de Vreese, Philipp Doebler, Mengchen Dong, Nicole Krämer, Margarita Leib, Jochen Peter, Lea Schäfer, Ivan Soraperra, Jessica Szczuka, Erik Tuchtfeld, Rebecca Wald, Nils Köbis

引用次数: 0

Building machines that learn and think with people 制造能与人共同学习和思考的机器

IF 21.4 1区心理学

Nature Human Behaviour Pub Date : 2024-10-22 DOI: 10.1038/s41562-024-01991-9

Katherine M. Collins, Ilia Sucholutsky, Umang Bhatt, Kartik Chandra, Lionel Wong, Mina Lee, Cedegao E. Zhang, Tan Zhi-Xuan, Mark Ho, Vikash Mansinghka, Adrian Weller, Joshua B. Tenenbaum, Thomas L. Griffiths

{"title":"Building machines that learn and think with people","authors":"Katherine M. Collins, Ilia Sucholutsky, Umang Bhatt, Kartik Chandra, Lionel Wong, Mina Lee, Cedegao E. Zhang, Tan Zhi-Xuan, Mark Ho, Vikash Mansinghka, Adrian Weller, Joshua B. Tenenbaum, Thomas L. Griffiths","doi":"10.1038/s41562-024-01991-9","DOIUrl":"10.1038/s41562-024-01991-9","url":null,"abstract":"What do we want from machine intelligence? We envision machines that are not just tools for thought but partners in thought: reasonable, insightful, knowledgeable, reliable and trustworthy systems that think with us. Current artificial intelligence systems satisfy some of these criteria, some of the time. In this Perspective, we show how the science of collaborative cognition can be put to work to engineer systems that really can be called ‘thought partners’, systems built to meet our expectations and complement our limitations. We lay out several modes of collaborative thought in which humans and artificial intelligence thought partners can engage, and we propose desiderata for human-compatible thought partnerships. Drawing on motifs from computational cognitive science, we motivate an alternative scaling path for the design of thought partners and ecosystems around their use through a Bayesian lens, whereby the partners we construct actively build and reason over models of the human and world. In this Perspective, the authors advance a view for the science of collaborative cognition to engineer systems that can be considered thought partners, systems built to meet our expectations and complement our limitations.","PeriodicalId":19074,"journal":{"name":"Nature Human Behaviour","volume":"8 10","pages":"1851-1863"},"PeriodicalIF":21.4,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142486675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Metaverse technologies can foster an inclusive society 元数据技术可促进包容性社会的发展

IF 21.4 1区心理学

Nature Human Behaviour Pub Date : 2024-10-22 DOI: 10.1038/s41562-024-01987-5

Daisuke Sakamoto, Tetsuo Ono

引用次数: 0

Promises and challenges of generative artificial intelligence for human learning 生成式人工智能促进人类学习的前景与挑战

IF 21.4 1区心理学

Nature Human Behaviour Pub Date : 2024-10-22 DOI: 10.1038/s41562-024-02004-5

Lixiang Yan, Samuel Greiff, Ziwen Teuber, Dragan Gašević

{"title":"Promises and challenges of generative artificial intelligence for human learning","authors":"Lixiang Yan, Samuel Greiff, Ziwen Teuber, Dragan Gašević","doi":"10.1038/s41562-024-02004-5","DOIUrl":"10.1038/s41562-024-02004-5","url":null,"abstract":"Generative artificial intelligence (GenAI) holds the potential to transform the delivery, cultivation and evaluation of human learning. Here the authors examine the integration of GenAI as a tool for human learning, addressing its promises and challenges from a holistic viewpoint that integrates insights from learning sciences, educational technology and human–computer interaction. GenAI promises to enhance learning experiences by scaling personalized support, diversifying learning materials, enabling timely feedback and innovating assessment methods. However, it also presents critical issues such as model imperfections, ethical dilemmas and the disruption of traditional assessments. Thus, cultivating AI literacy and adaptive skills is imperative for facilitating informed engagement with GenAI technologies. Rigorous research across learning contexts is essential to evaluate GenAI’s effect on human cognition, metacognition and creativity. Humanity must learn with and about GenAI, ensuring that it becomes a powerful ally in the pursuit of knowledge and innovation, rather than a crutch that undermines our intellectual abilities. This Perspective describes the roles of generative AI in providing personalized support, diversity and innovative assessment in learning. However, it also raises ethical concerns and highlights issues such as model imperfection, underscoring the need for AI literacy and adaptability.","PeriodicalId":19074,"journal":{"name":"Nature Human Behaviour","volume":"8 10","pages":"1839-1850"},"PeriodicalIF":21.4,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142487043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Embracing the ubiquity of machines 拥抱无处不在的机器

IF 21.4 1区心理学

Nature Human Behaviour Pub Date : 2024-10-22 DOI: 10.1038/s41562-024-02049-6

引用次数: 0

How developments in natural language processing help us in understanding human behaviour 自然语言处理的发展如何帮助我们理解人类行为

IF 21.4 1区心理学

Nature Human Behaviour Pub Date : 2024-10-22 DOI: 10.1038/s41562-024-01938-0

Rada Mihalcea, Laura Biester, Ryan L. Boyd, Zhijing Jin, Veronica Perez-Rosas, Steven Wilson, James W. Pennebaker

引用次数: 0

Honesty oaths for rule-following 遵守规则的诚信誓言

IF 29.9 1区心理学

Nature Human Behaviour Pub Date : 2024-10-21 DOI: 10.1038/s41562-024-02018-z

Shaul Shalvi

引用次数: 0

How to design and conduct a megastudy 如何设计和开展大型研究

IF 29.9 1区心理学

Nature Human Behaviour Pub Date : 2024-10-21 DOI: 10.1038/s41562-024-01998-2

Jan G. Voelkel, James Y. Chu, Michael N. Stagnaro, James N. Druckman, Robb Willer

引用次数: 0

A chatbot informed by behavioural science increases vaccination rates more than a simple reminder 基于行为科学的聊天机器人比简单的提醒更能提高疫苗接种率

IF 29.9 1区心理学

Nature Human Behaviour Pub Date : 2024-10-21 DOI: 10.1038/s41562-024-01986-6

引用次数: 0

Effectiveness of ex ante honesty oaths in reducing dishonesty depends on content 事前诚信宣誓能否有效减少不诚信行为取决于宣誓内容

IF 29.9 1区心理学

Nature Human Behaviour Pub Date : 2024-10-21 DOI: 10.1038/s41562-024-02009-0

Janis H. Zickfeld, Karolina A. Ścigała, Christian T. Elbæk, John Michael, Mathilde H. Tønnesen, Gabriel Levy, Shahar Ayal, Isabel Thielmann, Laila Nockur, Eyal Peer, Valerio Capraro, Rachel Barkan, Simen Bø, Štěpán Bahník, Daniele Nosenzo, Ralph Hertwig, Nina Mazar, Alexa Weiss, Ann-Kathrin Koessler, Ronit Montal-Rosenberg, Sebastian Hafenbrädl, Yngwie Asbjørn Nielsen, Patricia Kanngiesser, Simon Schindler, Philipp Gerlach, Nils Köbis, Nicolas Jacquemet, Marek Vranka, Dan Ariely, Jareef Bin Martuza, Yuval Feldman, Michał Białek, Jan K. Woike, Zoe Rahwan, Alicia Seidl, Eileen Chou, Agne Kajackaite, Simeon Schudy, Ulrich Glogowsky, Anna Z. Czarna, Stefan Pfattheicher, Panagiotis Mitkidis

{"title":"Effectiveness of ex ante honesty oaths in reducing dishonesty depends on content","authors":"Janis H. Zickfeld, Karolina A. Ścigała, Christian T. Elbæk, John Michael, Mathilde H. Tønnesen, Gabriel Levy, Shahar Ayal, Isabel Thielmann, Laila Nockur, Eyal Peer, Valerio Capraro, Rachel Barkan, Simen Bø, Štěpán Bahník, Daniele Nosenzo, Ralph Hertwig, Nina Mazar, Alexa Weiss, Ann-Kathrin Koessler, Ronit Montal-Rosenberg, Sebastian Hafenbrädl, Yngwie Asbjørn Nielsen, Patricia Kanngiesser, Simon Schindler, Philipp Gerlach, Nils Köbis, Nicolas Jacquemet, Marek Vranka, Dan Ariely, Jareef Bin Martuza, Yuval Feldman, Michał Białek, Jan K. Woike, Zoe Rahwan, Alicia Seidl, Eileen Chou, Agne Kajackaite, Simeon Schudy, Ulrich Glogowsky, Anna Z. Czarna, Stefan Pfattheicher, Panagiotis Mitkidis","doi":"10.1038/s41562-024-02009-0","DOIUrl":"https://doi.org/10.1038/s41562-024-02009-0","url":null,"abstract":"<p>Dishonest behaviours such as tax evasion impose significant societal costs. Ex ante honesty oaths—commitments to honesty before action—have been proposed as interventions to counteract dishonest behaviour, but the heterogeneity in findings across operationalizations calls their effectiveness into question. We tested 21 honesty oaths (including a baseline oath)—proposed, evaluated and selected by 44 expert researchers—and a no-oath condition in a megastudy involving 21,506 UK and US participants from Prolific.com who played an incentivized tax evasion game online. Of the 21 interventions, 10 significantly improved tax compliance by 4.5 to 8.5 percentage points, with the most successful nearly halving tax evasion. Limited evidence for moderators was found. Experts and laypeople failed to predict the most effective interventions, though experts’ predictions were more accurate. In conclusion, honesty oaths were effective in curbing dishonesty, but their effectiveness varied depending on content. These findings can help design impactful interventions to curb dishonesty.</p>","PeriodicalId":19074,"journal":{"name":"Nature Human Behaviour","volume":"104 1","pages":""},"PeriodicalIF":29.9,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142451809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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