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Marini M, Ansani A, Demichelis A, Mancini G, Paglieri F, Viola M. Real is the new sexy: the influence of perceived realness on self-reported arousal to sexual visual stimuli. Cogn Emot 2024; 38:348-360. [PMID: 38226595 DOI: 10.1080/02699931.2023.2296581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 11/29/2023] [Indexed: 01/17/2024]
Abstract
As state-of-art technology can create artificial images that are indistinguishable from real ones, it is urgent to understand whether believing that a picture is real or not has some import over affective phenomena such as sexual arousal. Thus, in two pre-registered online studies, we tested whether 60 images depicting models in underwear elicited higher self-reported sexual arousal when believed to be (N = 57) or presented as (N = 108) real photographs as opposed to artificially generated. In both cases, Realness correlated with significantly higher scores on self-reported sexual arousal. Consistently with the literature on downregulation of emotional response to fictional works, our result indicates that sexual images that are perceived to be fake are less arousing than those believed to portray real people.
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Affiliation(s)
- Marco Marini
- IMT School for Advanced Studies Lucca, Lucca, Italy
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Alessandro Ansani
- Department of Music, Art and Culture Studies, University of Jyväskylä, Jyväskylä, Finland
- Department of Philosophy, Communication, and Performing Arts, Roma Tre University, Rome, Italy
| | | | | | - Fabio Paglieri
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Marco Viola
- Department of Philosophy, Communication, and Performing Arts, Roma Tre University, Rome, Italy
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2
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Ding J, Zhang C, Li D, Zhan J, Li W, Yao Y. Three-way decisions in generalized intuitionistic fuzzy environments: survey and challenges. Artif Intell Rev 2024; 57:38. [PMID: 38333110 PMCID: PMC10847217 DOI: 10.1007/s10462-023-10647-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2024]
Abstract
Enhancing decision-making under risks is crucial in various fields, and three-way decision (3WD) methods have been extensively utilized and proven to be effective in numerous scenarios. However, traditional methods may not be sufficient when addressing intricate decision-making scenarios characterized by uncertain and ambiguous information. In response to this challenge, the generalized intuitionistic fuzzy set (IFS) theory extends the conventional fuzzy set theory by introducing two pivotal concepts, i.e., membership degrees and non-membership degrees. These concepts offer a more comprehensive means of portraying the relationship between elements and fuzzy concepts, thereby boosting the ability to model complex problems. The generalized IFS theory brings about heightened flexibility and precision in problem-solving, allowing for a more thorough and accurate description of intricate phenomena. Consequently, the generalized IFS theory emerges as a more refined tool for articulating fuzzy phenomena. The paper offers a thorough review of the research advancements made in 3WD methods within the context of generalized intuitionistic fuzzy (IF) environments. First, the paper summarizes fundamental aspects of 3WD methods and the IFS theory. Second, the paper discusses the latest development trends, including the application of these methods in new fields and the development of new hybrid methods. Furthermore, the paper analyzes the strengths and weaknesses of research methods employed in recent years. While these methods have yielded impressive outcomes in decision-making, there are still some limitations and challenges that need to be addressed. Finally, the paper proposes key challenges and future research directions. Overall, the paper offers a comprehensive and insightful review of the latest research progress on 3WD methods in generalized IF environments, which can provide guidance for scholars and engineers in the intelligent decision-making field with situations characterized by various uncertainties.
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Affiliation(s)
- Juanjuan Ding
- School of Computer and Information Technology, Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, 030006 Shanxi China
| | - Chao Zhang
- School of Computer and Information Technology, Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, 030006 Shanxi China
| | - Deyu Li
- School of Computer and Information Technology, Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, 030006 Shanxi China
| | - Jianming Zhan
- School of Mathematics and Statistics, Hubei Minzu University, Enshi, 445000 Hubei China
| | - Wentao Li
- School of Computer and Information Technology, Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, 030006 Shanxi China
- College of Artificial Intelligence, Southwest University, Chongqing, 400715 China
| | - Yiyu Yao
- Department of Computer Science, University of Regina, Regina, Saskatchewan S4S 0A2 Canada
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Zhou Y, Kawabata H. Eyes can tell: Assessment of implicit attitudes toward AI art. Iperception 2023; 14:20416695231209846. [PMID: 38022746 PMCID: PMC10663653 DOI: 10.1177/20416695231209846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 10/10/2023] [Indexed: 12/01/2023] Open
Abstract
Advances in artificial intelligence (AI) have significantly improved the abilities of machines. Human-unique abilities, such as art creation, are now being challenged by AI. Recent studies have investigated and compared people's attitudes toward human-made and AI-generated artworks. These results suggest that a negative bias may exist toward the latter. However, none of these previous studies has examined the extent of this bias. In this study, we investigate whether a bias against AI art can be found at an implicit level. Viewers' attitudes toward AI art were assessed using eye-tracking measures and subjective aesthetic evaluations. Visual attention and aesthetic judgments were compared between artworks categorized as human-made and AI-made. The results showed that although it was difficult for individuals to identify AI-generated artwork, they exhibited an implicit prejudice against AI art. Participants looked longer at paintings that they thought were made by humans. No significant effect of categorization of paintings was found in subjective evaluations. These findings suggest that although human and AI art may be perceived as having similar aesthetic values, an implicit negative bias toward AI art exists. Although AI can now perform creative tasks, artistic creativity is still considered a human prerogative.
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Affiliation(s)
- Yizhen Zhou
- Global Research Institute, Keio University, Tokyo, Japan
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Bellaiche L, Shahi R, Turpin MH, Ragnhildstveit A, Sprockett S, Barr N, Christensen A, Seli P. Humans versus AI: whether and why we prefer human-created compared to AI-created artwork. Cogn Res Princ Implic 2023; 8:42. [PMID: 37401999 DOI: 10.1186/s41235-023-00499-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 06/22/2023] [Indexed: 07/05/2023] Open
Abstract
With the recent proliferation of advanced artificial intelligence (AI) models capable of mimicking human artworks, AI creations might soon replace products of human creativity, although skeptics argue that this outcome is unlikely. One possible reason this may be unlikely is that, independent of the physical properties of art, we place great value on the imbuement of the human experience in art. An interesting question, then, is whether and why people might prefer human-compared to AI-created artworks. To explore these questions, we manipulated the purported creator of pieces of art by randomly assigning a "Human-created" or "AI-created" label to paintings actually created by AI, and then assessed participants' judgements of the artworks across four rating criteria (Liking, Beauty, Profundity, and Worth). Study 1 found increased positive judgements for human- compared to AI-labelled art across all criteria. Study 2 aimed to replicate and extend Study 1 with additional ratings (Emotion, Story, Meaningful, Effort, and Time to create) intended to elucidate why people more-positively appraise Human-labelled artworks. The main findings from Study 1 were replicated, with narrativity (Story) and perceived effort behind artworks (Effort) moderating the label effects ("Human-created" vs. "AI-created"), but only for the sensory-level judgements (Liking, Beauty). Positive personal attitudes toward AI moderated label effects for more-communicative judgements (Profundity, Worth). These studies demonstrate that people tend to be negatively biased against AI-created artworks relative to purportedly human-created artwork, and suggest that knowledge of human engagement in the artistic process contributes positively to appraisals of art.
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Affiliation(s)
- Lucas Bellaiche
- Department of Psychology and Neuroscience, Duke University, 417 Chapel Drive, Durham, NC, 27708, USA.
| | - Rohin Shahi
- Department of Psychology and Neuroscience, Duke University, 417 Chapel Drive, Durham, NC, 27708, USA
| | | | | | - Shawn Sprockett
- MDes in Interaction Design Program, California College of the Arts, San Francisco, CA, USA
| | - Nathaniel Barr
- School of Humanities and Creativity, Sheridan College, Oakville, ON, Canada
| | - Alexander Christensen
- Psychology and Human Development, Peabody College, Vanderbilt University, Nashville, TN, USA
| | - Paul Seli
- Department of Psychology and Neuroscience, Duke University, 417 Chapel Drive, Durham, NC, 27708, USA
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Giorgi A, Menicocci S, Forte M, Ferrara V, Mingione M, Alaimo Di Loro P, Inguscio BMS, Ferrara S, Babiloni F, Vozzi A, Ronca V, Cartocci G. Virtual and Reality: A Neurophysiological Pilot Study of the Sarcophagus of the Spouses. Brain Sci 2023; 13:brainsci13040635. [PMID: 37190600 DOI: 10.3390/brainsci13040635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 03/29/2023] [Accepted: 04/04/2023] [Indexed: 05/17/2023] Open
Abstract
Art experience is not solely the observation of artistic objects, but great relevance is also placed on the environment in which the art experience takes place, often in museums and galleries. Interestingly, in the last few years, the introduction of some forms of virtual reality (VR) in museum contexts has been increasing. This has solicited enormous research interest in investigating any eventual differences between looking at the same artifact either in a real context (e.g. a museum) and in VR. To address such a target, a neuroaesthetic study was performed in which electroencephalography (EEG) and autonomic signals (heart rate and skin conductance) were recorded during the observation of the Etruscan artifact "Sarcophagus of the Spouses", both in the museum and in a VR reproduction. Results from EEG analysis showed a higher level of the Workload Index during observation in the museum compared to VR (p = 0.04), while the Approach-Withdrawal Index highlighted increased levels during the observation in VR compared to the observation in the museum (p = 0.03). Concerning autonomic indices, the museum elicited a higher Emotional Index response than the VR (p = 0.03). Overall, preliminary results suggest a higher engagement potential of the museum compared to VR, although VR could also favour higher embodiment than the museum.
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Affiliation(s)
- Andrea Giorgi
- Unit of Histology and Medical Embryology, SAIMLAL Department, Sapienza University of Rome, 00185 Rome, Italy
- BrainSigns Ltd., 00185 Rome, Italy
| | - Stefano Menicocci
- BrainSigns Ltd., 00185 Rome, Italy
- Department of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy
| | - Maurizio Forte
- Department of Classical Studies, Duke University, Durham, NC 27708, USA
| | - Vincenza Ferrara
- Art and Medical Humanities Lab, Sapienza University of Rome, 00185 Rome, Italy
| | - Marco Mingione
- Department of Political Sciences, Roma Tre University, 00145 Rome, Italy
| | - Pierfrancesco Alaimo Di Loro
- Department of Law, Economics, Politics and Modern Languages, Libera Università Maria SS. Assunta (LUMSA), 00192 Rome, Italy
| | - Bianca Maria Serena Inguscio
- BrainSigns Ltd., 00185 Rome, Italy
- Department of Human Neuroscience, Sapienza University of Rome, 00185 Rome, Italy
| | | | - Fabio Babiloni
- BrainSigns Ltd., 00185 Rome, Italy
- Department of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy
- Department of Computer Science, Hangzhou Dianzi University, Hangzhou 310018, China
| | - Alessia Vozzi
- Unit of Histology and Medical Embryology, SAIMLAL Department, Sapienza University of Rome, 00185 Rome, Italy
- BrainSigns Ltd., 00185 Rome, Italy
| | - Vincenzo Ronca
- BrainSigns Ltd., 00185 Rome, Italy
- Department of Computer, Control and Management Engineering "Antonio Ruberti", Sapienza University of Rome, 00185 Rome, Italy
| | - Giulia Cartocci
- BrainSigns Ltd., 00185 Rome, Italy
- Department of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy
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Abstract
Artificial intelligence (AI) is deemed to increase workers’ productivity by enhancing their creative abilities and acting as a general-purpose tool for innovation. While much is known about AI’s ability to create value through innovation, less is known about how AI’s limitations drive innovative work behaviour (IWB). With AI’s limits in perspective, innovative work behaviour might serve as workarounds to compensate for AI limitations. Therefore, the guiding research question is: How will AI limitations, rather than its apparent transformational strengths, drive workers’ innovative work behaviour in a workplace? A search protocol was employed to identify 65 articles based on relevant keywords and article selection criteria using the Scopus database. The thematic analysis suggests several themes: (i) Robots make mistakes, and such mistakes stimulate workers’ IWB, (ii) AI triggers ‘fear’ in workers, and this ‘fear’ stimulates workers’ IWB, (iii) Workers are reskilled and upskilled to compensate for AI limitations, (iv) AI interface stimulates worker engagement, (v) Algorithmic bias requires IWB, and (vi) AI works as a general-purpose tool for IWB. In contrast to prior reviews, which generally focus on the apparent transformational strengths of AI in the workplace, this review primarily identifies AI limitations before suggesting that the limitations could also drive innovative work behaviour. Propositions are included after each theme to encourage future research.
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Affiliation(s)
- Araz Zirar
- grid.15751.370000 0001 0719 6059Huddersfield Business School, University of Huddersfield, Huddersfield, UK
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Zirar A. Can artificial intelligence’s limitations drive innovative work behaviour? REVIEW OF MANAGERIAL SCIENCE 2023. [PMCID: PMC9910241 DOI: 10.1007/s11846-023-00621-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Abstract
Artificial intelligence (AI) is deemed to increase workers’ productivity by enhancing their creative abilities and acting as a general-purpose tool for innovation. While much is known about AI’s ability to create value through innovation, less is known about how AI’s limitations drive innovative work behaviour (IWB). With AI’s limits in perspective, innovative work behaviour might serve as workarounds to compensate for AI limitations. Therefore, the guiding research question is: How will AI limitations, rather than its apparent transformational strengths, drive workers’ innovative work behaviour in a workplace? A search protocol was employed to identify 65 articles based on relevant keywords and article selection criteria using the Scopus database. The thematic analysis suggests several themes: (i) Robots make mistakes, and such mistakes stimulate workers’ IWB, (ii) AI triggers ‘fear’ in workers, and this ‘fear’ stimulates workers’ IWB, (iii) Workers are reskilled and upskilled to compensate for AI limitations, (iv) AI interface stimulates worker engagement, (v) Algorithmic bias requires IWB, and (vi) AI works as a general-purpose tool for IWB. In contrast to prior reviews, which generally focus on the apparent transformational strengths of AI in the workplace, this review primarily identifies AI limitations before suggesting that the limitations could also drive innovative work behaviour. Propositions are included after each theme to encourage future research.
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Affiliation(s)
- Araz Zirar
- Huddersfield Business School, University of Huddersfield, Huddersfield, UK
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AI-enabled investment advice: Will users buy it? COMPUTERS IN HUMAN BEHAVIOR 2023. [DOI: 10.1016/j.chb.2022.107481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Kim J, Lee SS. Are Two Heads Better Than One?: The Effect of Student-AI Collaboration on Students' Learning Task Performance. TECHTRENDS : FOR LEADERS IN EDUCATION & TRAINING 2022; 67:365-375. [PMID: 36258920 PMCID: PMC9561333 DOI: 10.1007/s11528-022-00788-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 09/19/2022] [Indexed: 06/16/2023]
Abstract
A growing number of educators expect that artificial intelligence (AI) will augment students' capacities and rapidly transform the teaching and learning practice. However, there is a lack of convincing evidence on the effects of Student-AI Collaboration (SAC) on a learning task's performance. A critical examination of the effects on students' learning performance is a crucial step in understanding the potential benefits of SAC on learning. Through a repeated measure experiment participated by 20 undergraduate students in South Korea, this study examined the effects of SAC on a public advertisement drawing task. The findings revealed that SAC significantly affects creativity in content, expressivity in expression, and public utility in effectiveness varied depending on students' attitude toward AI or on the level of drawing skill. Implications for the design of educational AI and AI literacy education are discussed.
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Affiliation(s)
- Jinhee Kim
- School of Future Education, Xi’an Jiatong-Liverpool University, Suzhou, People’s Republic of China
| | - Sang-Soog Lee
- Department of Public Administration, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841 South Korea
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