Perspectives on Psychological Science最新文献

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Social Drivers and Algorithmic Mechanisms on Digital Media. 数字媒体的社会驱动力和算法机制。
IF 10.5 1区 心理学
Perspectives on Psychological Science Pub Date : 2024-09-01 Epub Date: 2023-07-19 DOI: 10.1177/17456916231185057
Hannah Metzler, David Garcia
{"title":"Social Drivers and Algorithmic Mechanisms on Digital Media.","authors":"Hannah Metzler, David Garcia","doi":"10.1177/17456916231185057","DOIUrl":"10.1177/17456916231185057","url":null,"abstract":"<p><p>On digital media, algorithms that process data and recommend content have become ubiquitous. Their fast and barely regulated adoption has raised concerns about their role in well-being both at the individual and collective levels. Algorithmic mechanisms on digital media are powered by social drivers, creating a feedback loop that complicates research to disentangle the role of algorithms and already existing social phenomena. Our brief overview of the current evidence on how algorithms affect well-being, misinformation, and polarization suggests that the role of algorithms in these phenomena is far from straightforward and that substantial further empirical research is needed. Existing evidence suggests that algorithms mostly reinforce existing social drivers, a finding that stresses the importance of reflecting on algorithms in the larger societal context that encompasses individualism, populist politics, and climate change. We present concrete ideas and research questions to improve algorithms on digital platforms and to investigate their role in current problems and potential solutions. Finally, we discuss how the current shift from social media to more algorithmically curated media brings both risks and opportunities if algorithms are designed for individual and societal flourishing rather than short-term profit.</p>","PeriodicalId":19757,"journal":{"name":"Perspectives on Psychological Science","volume":" ","pages":"735-748"},"PeriodicalIF":10.5,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11373151/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9822531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
People Think That Social Media Platforms Do (but Should Not) Amplify Divisive Content. 人们认为社交媒体平台确实(但不应该)放大了分裂性的内容。
IF 10.5 1区 心理学
Perspectives on Psychological Science Pub Date : 2024-09-01 Epub Date: 2023-09-26 DOI: 10.1177/17456916231190392
Steve Rathje, Claire Robertson, William J Brady, Jay J Van Bavel
{"title":"People Think That Social Media Platforms Do (but Should Not) Amplify Divisive Content.","authors":"Steve Rathje, Claire Robertson, William J Brady, Jay J Van Bavel","doi":"10.1177/17456916231190392","DOIUrl":"10.1177/17456916231190392","url":null,"abstract":"<p><p>Recent studies have documented the type of content that is most likely to spread widely, or go \"viral,\" on social media, yet little is known about people's perceptions of what goes viral or what should go viral. This is critical to understand because there is widespread debate about how to improve or regulate social media algorithms. We recruited a sample of participants that is nationally representative of the U.S. population (according to age, gender, and race/ethnicity) and surveyed them about their perceptions of social media virality (<i>n</i> = 511). In line with prior research, people believe that divisive content, moral outrage, negative content, high-arousal content, and misinformation are all likely to go viral online. However, they reported that this type of content should not go viral on social media. Instead, people reported that many forms of positive content-such as accurate content, nuanced content, and educational content-are not likely to go viral even though they think this content should go viral. These perceptions were shared among most participants and were only weakly related to political orientation, social media usage, and demographic variables. In sum, there is broad consensus around the type of content people think social media platforms should and should not amplify, which can help inform solutions for improving social media.</p>","PeriodicalId":19757,"journal":{"name":"Perspectives on Psychological Science","volume":" ","pages":"781-795"},"PeriodicalIF":10.5,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41109994","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
The Inversion Problem: Why Algorithms Should Infer Mental State and Not Just Predict Behavior. 反转问题 为什么算法应该推断心理状态,而不仅仅是预测行为?
IF 10.5 1区 心理学
Perspectives on Psychological Science Pub Date : 2024-09-01 Epub Date: 2023-12-12 DOI: 10.1177/17456916231212138
Jon Kleinberg, Jens Ludwig, Sendhil Mullainathan, Manish Raghavan
{"title":"The Inversion Problem: Why Algorithms Should Infer Mental State and Not Just Predict Behavior.","authors":"Jon Kleinberg, Jens Ludwig, Sendhil Mullainathan, Manish Raghavan","doi":"10.1177/17456916231212138","DOIUrl":"10.1177/17456916231212138","url":null,"abstract":"<p><p>More and more machine learning is applied to human behavior. Increasingly these algorithms suffer from a hidden-but serious-problem. It arises because they often predict one thing while hoping for another. Take a recommender system: It predicts clicks but hopes to identify preferences. Or take an algorithm that automates a radiologist: It predicts in-the-moment diagnoses while hoping to identify their reflective judgments. Psychology shows us the gaps between the objectives of such prediction tasks and the goals we hope to achieve: People can click mindlessly; experts can get tired and make systematic errors. We argue such situations are ubiquitous and call them \"inversion problems\": The real goal requires understanding a mental state that is not directly measured in behavioral data but must instead be inverted from the behavior. Identifying and solving these problems require new tools that draw on both behavioral and computational science.</p>","PeriodicalId":19757,"journal":{"name":"Perspectives on Psychological Science","volume":" ","pages":"827-838"},"PeriodicalIF":10.5,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138808387","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
Blinding to Circumvent Human Biases: Deliberate Ignorance in Humans, Institutions, and Machines. 蒙蔽以规避人类偏见:人类、机构和机器的故意无知。
IF 10.5 1区 心理学
Perspectives on Psychological Science Pub Date : 2024-09-01 Epub Date: 2023-09-05 DOI: 10.1177/17456916231188052
Ralph Hertwig, Stefan M Herzog, Anastasia Kozyreva
{"title":"Blinding to Circumvent Human Biases: Deliberate Ignorance in Humans, Institutions, and Machines.","authors":"Ralph Hertwig, Stefan M Herzog, Anastasia Kozyreva","doi":"10.1177/17456916231188052","DOIUrl":"10.1177/17456916231188052","url":null,"abstract":"<p><p>Inequalities and injustices are thorny issues in liberal societies, manifesting in forms such as the gender-pay gap; sentencing discrepancies among Black, Hispanic, and White defendants; and unequal medical-resource distribution across ethnicities. One cause of these inequalities is <i>implicit social bias</i>-unconsciously formed associations between social groups and attributions such as \"nurturing,\" \"lazy,\" or \"uneducated.\" One strategy to counteract implicit and explicit human biases is delegating crucial decisions, such as how to allocate benefits, resources, or opportunities, to algorithms. Algorithms, however, are not necessarily impartial and objective. Although they can detect and mitigate human biases, they can also perpetuate and even amplify existing inequalities and injustices. We explore how a philosophical thought experiment, Rawls's \"veil of ignorance,\" and a psychological phenomenon, deliberate ignorance, can help shield individuals, institutions, and algorithms from biases. We discuss the benefits and drawbacks of methods for shielding human and artificial decision makers from potentially biasing information. We then broaden our discussion beyond the issues of bias and fairness and turn to a research agenda aimed at improving human judgment accuracy with the assistance of algorithms that conceal information that has the potential to undermine performance. Finally, we propose interdisciplinary research questions.</p>","PeriodicalId":19757,"journal":{"name":"Perspectives on Psychological Science","volume":" ","pages":"849-859"},"PeriodicalIF":10.5,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11373160/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10157746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
A Normative Framework for Assessing the Information Curation Algorithms of the Internet. 评估互联网信息管理算法的规范框架。
IF 10.5 1区 心理学
Perspectives on Psychological Science Pub Date : 2024-09-01 Epub Date: 2023-11-27 DOI: 10.1177/17456916231186779
David Lazer, Briony Swire-Thompson, Christo Wilson
{"title":"A Normative Framework for Assessing the Information Curation Algorithms of the Internet.","authors":"David Lazer, Briony Swire-Thompson, Christo Wilson","doi":"10.1177/17456916231186779","DOIUrl":"10.1177/17456916231186779","url":null,"abstract":"<p><p>It is critical to understand how algorithms structure the information people see and how those algorithms support or undermine society's core values. We offer a normative framework for the assessment of the information curation algorithms that determine much of what people see on the internet. The framework presents two levels of assessment: one for individual-level effects and another for systemic effects. With regard to individual-level effects we discuss whether (a) the information is aligned with the user's interests, (b) the information is accurate, and (c) the information is so appealing that it is difficult for a person's self-regulatory resources to ignore (\"agency hacking\"). At the systemic level we discuss whether (a) there are adverse civic-level effects on a system-level variable, such as political polarization; (b) there are negative distributional or discriminatory effects; and (c) there are anticompetitive effects, with the information providing an advantage to the platform. The objective of this framework is both to inform the direction of future scholarship as well as to offer tools for intervention for policymakers.</p>","PeriodicalId":19757,"journal":{"name":"Perspectives on Psychological Science","volume":" ","pages":"749-757"},"PeriodicalIF":10.5,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138445669","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
AI Psychometrics: Assessing the Psychological Profiles of Large Language Models Through Psychometric Inventories. 人工智能心理测量学:通过心理测量问卷评估大型语言模型的心理特征。
IF 10.5 1区 心理学
Perspectives on Psychological Science Pub Date : 2024-09-01 Epub Date: 2024-01-02 DOI: 10.1177/17456916231214460
Max Pellert, Clemens M Lechner, Claudia Wagner, Beatrice Rammstedt, Markus Strohmaier
{"title":"AI Psychometrics: Assessing the Psychological Profiles of Large Language Models Through Psychometric Inventories.","authors":"Max Pellert, Clemens M Lechner, Claudia Wagner, Beatrice Rammstedt, Markus Strohmaier","doi":"10.1177/17456916231214460","DOIUrl":"10.1177/17456916231214460","url":null,"abstract":"<p><p>We illustrate how standard psychometric inventories originally designed for assessing noncognitive human traits can be repurposed as diagnostic tools to evaluate analogous traits in large language models (LLMs). We start from the assumption that LLMs, inadvertently yet inevitably, acquire psychological traits (metaphorically speaking) from the vast text corpora on which they are trained. Such corpora contain sediments of the personalities, values, beliefs, and biases of the countless human authors of these texts, which LLMs learn through a complex training process. The traits that LLMs acquire in such a way can potentially influence their behavior, that is, their outputs in downstream tasks and applications in which they are employed, which in turn may have real-world consequences for individuals and social groups. By eliciting LLMs' responses to language-based psychometric inventories, we can bring their traits to light. Psychometric profiling enables researchers to study and compare LLMs in terms of noncognitive characteristics, thereby providing a window into the personalities, values, beliefs, and biases these models exhibit (or mimic). We discuss the history of similar ideas and outline possible psychometric approaches for LLMs. We demonstrate one promising approach, zero-shot classification, for several LLMs and psychometric inventories. We conclude by highlighting open challenges and future avenues of research for AI Psychometrics.</p>","PeriodicalId":19757,"journal":{"name":"Perspectives on Psychological Science","volume":" ","pages":"808-826"},"PeriodicalIF":10.5,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11373167/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139080662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
Human and Algorithmic Predictions in Geopolitical Forecasting: Quantifying Uncertainty in Hard-to-Quantify Domains. 地缘政治预测中的人工和算法预测:量化难以量化领域的不确定性。
IF 10.5 1区 心理学
Perspectives on Psychological Science Pub Date : 2024-09-01 Epub Date: 2023-08-29 DOI: 10.1177/17456916231185339
Barbara A Mellers, John P McCoy, Louise Lu, Philip E Tetlock
{"title":"Human and Algorithmic Predictions in Geopolitical Forecasting: Quantifying Uncertainty in Hard-to-Quantify Domains.","authors":"Barbara A Mellers, John P McCoy, Louise Lu, Philip E Tetlock","doi":"10.1177/17456916231185339","DOIUrl":"10.1177/17456916231185339","url":null,"abstract":"<p><p>Research on clinical versus statistical prediction has demonstrated that algorithms make more accurate predictions than humans in many domains. Geopolitical forecasting is an algorithm-unfriendly domain, with hard-to-quantify data and elusive reference classes that make predictive model-building difficult. Furthermore, the stakes can be high, with missed forecasts leading to mass-casualty consequences. For these reasons, geopolitical forecasting is typically done by humans, even though algorithms play important roles. They are essential as aggregators of crowd wisdom, as frameworks to partition human forecasting variance, and as inputs to hybrid forecasting models. Algorithms are extremely important in this domain. We doubt that humans will relinquish control to algorithms anytime soon-nor do we think they should. However, the accuracy of forecasts will greatly improve if humans are aided by algorithms.</p>","PeriodicalId":19757,"journal":{"name":"Perspectives on Psychological Science","volume":" ","pages":"711-721"},"PeriodicalIF":10.5,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11373164/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10109373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
Building Human-Like Artificial Agents: A General Cognitive Algorithm for Emulating Human Decision-Making in Dynamic Environments. 构建类人人工智能体:一种在动态环境中模拟人类决策的通用认知算法。
IF 10.5 1区 心理学
Perspectives on Psychological Science Pub Date : 2024-09-01 Epub Date: 2023-10-31 DOI: 10.1177/17456916231196766
Cleotilde Gonzalez
{"title":"Building Human-Like Artificial Agents: A General Cognitive Algorithm for Emulating Human Decision-Making in Dynamic Environments.","authors":"Cleotilde Gonzalez","doi":"10.1177/17456916231196766","DOIUrl":"10.1177/17456916231196766","url":null,"abstract":"<p><p>One of the early goals of artificial intelligence (AI) was to create algorithms that exhibited behavior indistinguishable from human behavior (i.e., human-like behavior). Today, AI has diverged, often aiming to excel in tasks inspired by human capabilities and outperform humans, rather than replicating human cogntion and action. In this paper, I explore the overarching question of whether computational algorithms have achieved this initial goal of AI. I focus on dynamic decision-making, approaching the question from the perspective of computational cognitive science. I present a general cognitive algorithm that intends to emulate human decision-making in dynamic environments, as defined in instance-based learning theory (IBLT). I use the cognitive steps proposed in IBLT to organize and discuss current evidence that supports some of the human-likeness of the decision-making mechanisms. I also highlight the significant gaps in research that are required to improve current models and to create higher fidelity in computational algorithms to represent human decision processes. I conclude with concrete steps toward advancing the construction of algorithms that exhibit human-like behavior with the ultimate goal of supporting human dynamic decision-making.</p>","PeriodicalId":19757,"journal":{"name":"Perspectives on Psychological Science","volume":" ","pages":"860-873"},"PeriodicalIF":10.5,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71413406","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
Editorial for the Special Issue on Algorithms in Our Lives. 为 "我们生活中的算法 "特刊撰写社论。
IF 10.5 1区 心理学
Perspectives on Psychological Science Pub Date : 2024-09-01 Epub Date: 2024-01-02 DOI: 10.1177/17456916231214452
Sudeep Bhatia, Mirta Galesic, Melanie Mitchell
{"title":"Editorial for the Special Issue on Algorithms in Our Lives.","authors":"Sudeep Bhatia, Mirta Galesic, Melanie Mitchell","doi":"10.1177/17456916231214452","DOIUrl":"10.1177/17456916231214452","url":null,"abstract":"","PeriodicalId":19757,"journal":{"name":"Perspectives on Psychological Science","volume":" ","pages":"707-710"},"PeriodicalIF":10.5,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139080663","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
The Cognitive Architecture of Infant Attachment. 婴儿依恋的认知结构。
IF 10.5 1区 心理学
Perspectives on Psychological Science Pub Date : 2024-08-26 DOI: 10.1177/17456916241262693
Yuyan Luo, Kristy vanMarle, Ashley M Groh
{"title":"The Cognitive Architecture of Infant Attachment.","authors":"Yuyan Luo, Kristy vanMarle, Ashley M Groh","doi":"10.1177/17456916241262693","DOIUrl":"10.1177/17456916241262693","url":null,"abstract":"<p><p>Meta-analytic evidence indicates that the quality of the attachment relationship that infants establish with their primary caregiver has enduring significance for socioemotional and cognitive outcomes. However, the mechanisms by which early attachment experiences contribute to subsequent development remain underspecified. According to attachment theory, early attachment experiences become embodied in the form of cognitive-affective representations, referred to as internal working models (IWMs), that guide future behavior. Little is known, however, about the cognitive architecture of IWMs in infancy. In this article, we discuss significant advances made in the field of infant cognitive development and propose that leveraging insights from this research has the potential to fundamentally shape our understanding of the cognitive architecture of attachment representations in infancy. We also propose that the integration of attachment research into cognitive research can shed light on the role of early experiences, individual differences, and stability and change in infant cognition, as well as open new routes of investigation in cognitive studies, which will further our understanding of human knowledge. We provide recommendations for future research throughout the article and conclude by using our collaborative research as an example.</p>","PeriodicalId":19757,"journal":{"name":"Perspectives on Psychological Science","volume":" ","pages":"17456916241262693"},"PeriodicalIF":10.5,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11861394/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142056235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
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