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He Y, Gu R, Deng G, Lin Y, Gan T, Cui F, Liu C, Luo YJ. Psychological and Brain Responses to Artificial Intelligence's Violation of Community Ethics. CYBERPSYCHOLOGY, BEHAVIOR AND SOCIAL NETWORKING 2024; 27:562-570. [PMID: 38757680 DOI: 10.1089/cyber.2023.0524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2024]
Abstract
Human moral reactions to artificial intelligence (AI) agents' behavior constitute an important aspect of modern-day human-AI relationships. Although previous studies have mainly focused on autonomy ethics, this study investigates how individuals judge AI agents' violations of community ethics (including betrayals and subversions) compared with human violations. Participants' behavioral responses, event-related potentials (ERPs), and individual differences were assessed. Behavioral findings reveal that participants rated AI agents' community-violating actions less morally negative than human transgressions, possibly because AI agents are commonly perceived as having less agency than human adults. The ERP N1 component showed the same pattern with moral rating scores, indicating the modulation effect of human-AI differences on initial moral intuitions. Moreover, the level of social withdrawal correlated with a smaller N1 in the human condition but not in the AI condition. The N2 and P2 components were sensitive to the difference between the loyalty/betrayal and authority/subversion domains but not human/AI differences. Individual levels of moral sense and autistic traits also influenced behavioral data, especially on the loyalty/betrayal domain. In our opinion, these findings offer insights for predicting moral responses to AI agents and guiding ethical AI development aligned with human moral values.
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Affiliation(s)
- Yue He
- School of Psychology, Shenzhen University, Shenzhen, People's Republic of China
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, People's Republic of China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, People's Republic of China
| | - Ruolei Gu
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, People's Republic of China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, People's Republic of China
| | - Guangzhi Deng
- Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (BNU), Faculty of Psychology, Beijing Normal University, Beijing, People's Republic of China
| | - Yongling Lin
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, People's Republic of China
| | - Tian Gan
- Department of Psychology, Zhejiang Sci-Tech University, Hangzhou, People's Republic of China
- Research Institute on Aging, School of Science, Zhejiang Sci-Tech University, Hangzhou, People's Republic of China
| | - Fang Cui
- School of Psychology, Shenzhen University, Shenzhen, People's Republic of China
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Magnetic Resonance Imaging, Center, Center for Brain Disorders and Cognitive Sciences, Shenzhen University, Shenzhen, People's Republic of China
| | - Chao Liu
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, People's Republic of China
- Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, People's Republic of China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, People's Republic of China
- National Demonstration Center for Experimental Psychology Education, Faculty of Psychology, Beijing Normal University, Beijing, People's Republic of China
| | - Yue-Jia Luo
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, People's Republic of China
- Institute for Neuropsychological Rehabilitation, University of Health and Rehabilitation Sciences, Qingdao, People's Republic of China
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Botelho C, Fernandes C, Campos C, Seixas C, Pasion R, Garcez H, Ferreira-Santos F, Barbosa F, Maques-Teixeira J, Paiva TO. Uncertainty deconstructed: conceptual analysis and state-of-the-art review of the ERP correlates of risk and ambiguity in decision-making. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2023:10.3758/s13415-023-01101-8. [PMID: 37173606 DOI: 10.3758/s13415-023-01101-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 04/13/2023] [Indexed: 05/15/2023]
Abstract
Risk and uncertainty are central concepts of decision neuroscience. However, a comprehensive review of the literature shows that most studies define risk and uncertainty in an unclear fashion or use both terms interchangeably, which hinders the integration of the existing findings. We suggest uncertainty as an umbrella term that comprises scenarios characterized by outcome variance where relevant information about the type and likelihood of outcomes may be somewhat unavailable (ambiguity) and scenarios where the likelihood of outcomes is known (risk).These conceptual issues are problematic for studies on the temporal neurodynamics of decision-making under risk and ambiguity, because they lead to heterogeneity in task design and the interpretation of the results. To assess this problem, we conducted a state-of-the-art review of ERP studies on risk and ambiguity in decision-making. By employing the above definitions to 16 reviewed studies, our results suggest that: (a) research has focused more on risk than ambiguity processing; (b) studies assessing decision-making under risk often implemented descriptive-based paradigms, whereas studies assessing ambiguity processing equally implemented descriptive- and experience-based tasks; (c) descriptive-based studies link risk processing to increased frontal negativities (e.g., N2, N400) and both risk and ambiguity to reduced parietal positivities (e.g., P2, P3); (d) experience-based studies link risk to increased P3 amplitudes and ambiguity to increased frontal negativities and the LPC component; (e) both risk and ambiguity processing seem to be related with cognitive control, conflict monitoring, and increased cognitive demand; (f) further research and improved tasks are needed to dissociate risk and ambiguity processing.
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Affiliation(s)
- Catarina Botelho
- Faculty of Psychology and Education Sciences, Laboratory of Neuropsychophysiology, University of Porto, Rua Alfredo Allen, 4200-135, Porto, Portugal.
| | - Carina Fernandes
- Faculty of Psychology and Education Sciences, Laboratory of Neuropsychophysiology, University of Porto, Rua Alfredo Allen, 4200-135, Porto, Portugal
- Faculdade de Ciências Humanas e Sociais, Universidade Fernando Pessoa, Porto, Portugal
- Molecular Oncology and Viral Pathology Group, Research Center of IPO (CI-IPOP) & RISE@CI-IPOP (Health Research Network), Portuguese Oncology Institute of Porto (IPO Porto)/Porto Comprehensive Cancer Center (Porto.CCC), 4200-072, Porto, Portugal
| | - Carlos Campos
- Faculty of Psychology and Education Sciences, Laboratory of Neuropsychophysiology, University of Porto, Rua Alfredo Allen, 4200-135, Porto, Portugal
- Neurocognition Group | LabRP, Center for Rehabilitation Research, School of Health, Polytechnic Institute of Porto, Porto, Portugal
- Digital Human-Environment Interaction Lab (HEI-LAB), Lusófona University, Lisboa, Portugal
| | - Carlos Seixas
- Faculty of Psychology and Education Sciences, Laboratory of Neuropsychophysiology, University of Porto, Rua Alfredo Allen, 4200-135, Porto, Portugal
- Research on Economics, Management and Information Technologies (REMIT), Portucalense University, Porto, Portugal
| | - Rita Pasion
- Faculty of Psychology and Education Sciences, Laboratory of Neuropsychophysiology, University of Porto, Rua Alfredo Allen, 4200-135, Porto, Portugal
- Digital Human-Environment Interaction Lab (HEI-LAB), Lusófona University, Lisboa, Portugal
| | - Helena Garcez
- Faculty of Psychology and Education Sciences, Laboratory of Neuropsychophysiology, University of Porto, Rua Alfredo Allen, 4200-135, Porto, Portugal
| | - Fernando Ferreira-Santos
- Faculty of Psychology and Education Sciences, Laboratory of Neuropsychophysiology, University of Porto, Rua Alfredo Allen, 4200-135, Porto, Portugal
| | - Fernando Barbosa
- Faculty of Psychology and Education Sciences, Laboratory of Neuropsychophysiology, University of Porto, Rua Alfredo Allen, 4200-135, Porto, Portugal
| | - João Maques-Teixeira
- Faculty of Psychology and Education Sciences, Laboratory of Neuropsychophysiology, University of Porto, Rua Alfredo Allen, 4200-135, Porto, Portugal
| | - Tiago O Paiva
- Faculty of Psychology and Education Sciences, Laboratory of Neuropsychophysiology, University of Porto, Rua Alfredo Allen, 4200-135, Porto, Portugal.
- Digital Human-Environment Interaction Lab (HEI-LAB), Lusófona University, Lisboa, Portugal.
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Lin Y, Gu R, Luan S, Hu L, Qin S, Luo YJ. The hierarchical sensitivity to social misalignment during decision-making under uncertainty. Soc Cogn Affect Neurosci 2021; 16:565-575. [PMID: 33615385 PMCID: PMC8138082 DOI: 10.1093/scan/nsab022] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 01/18/2021] [Accepted: 02/19/2021] [Indexed: 12/15/2022] Open
Abstract
Social misalignment occurs when a person’s attitudes and opinions deviate from those of others. We investigated how individuals react to social misalignment in risky (outcome probabilities are known) or ambiguous (outcome probabilities are unknown) decision contexts. During each trial, participants played a forced-choice gamble, and they observed the decisions of four other players after they made a tentative decision, followed by an opportunity to keep or change their initial decision. Behavioral and event-related potential data were collected. Behaviorally, the stronger the participants’ initial preference, the less likely they were to switch their decisions, whereas the more their decisions were misaligned with the majority, the more likely they were to switch. Electrophysiological results showed a hierarchical processing pattern of social misalignment. Misalignment was first detected binarily (i.e. match/mismatch) at an early stage, as indexed by the N1 component. During the second stage, participants became sensitive to low levels of misalignment, which were indexed by the feedback-related negativity. The degree of social misalignment was processed in greater detail, as indexed by the P3 component. Moreover, such hierarchical neural sensitivity is generalizable across different decision contexts (i.e. risky and ambiguous). These findings demonstrate a fine-grained neural sensitivity to social misalignment during decision-making under uncertainty.
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Affiliation(s)
- Yongling Lin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Ruolei Gu
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China.,CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China
| | - Shenghua Luan
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China.,CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China
| | - Li Hu
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China.,CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing 100101, China
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Yue-Jia Luo
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Center for Brain Disorder and Cognitive Science, Shenzhen University, Shenzhen, Guangdong 518061, China.,College of Teacher Education, Qilu Normal University, Jinan, Shandong 250200, China.,The Research Center of Brain Science and Visual Cognition, Kunming University of Science and Technology, Kunming, Yunnan 650504, China
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