The Use of Artificial Intelligence Systems in Tourism and Hospitality: The Tourists’ Perspective DOI Creative Commons
Ana Elisa Sousa, Paula Cardoso, Francisco Dias

et al.

Administrative Sciences, Journal Year: 2024, Volume and Issue: 14(8), P. 165 - 165

Published: Aug. 2, 2024

A myriad of types artificial intelligence (AI) systems—namely AI-powered site search, augmented reality, biometric data recognition, booking systems, chatbots, drones, kiosks/self-service screens, machine translation, QR codes, robots, virtual and voice assistants—are being used by companies in the tourism hospitality industry. How are consumers reacting to these profound changes? This study aims address this issue identifying AI systems that tourists, purposes they for present, how likely be future. also identify emotions (positive vs. negative) tourists associate with use as well advantages disadvantages attribute them. Considering exploratory nature research, were collected through an online survey shared on social media, which was available from September December 2023. Results show most respondents have already several assign more than their use, significantly positive. Moreover, compared small number (13.7%) who negative claim feel positive when using evaluate them positively terms usefulness hospitality. They advantages, a greater diversity admit would diverse range contexts

Language: Английский

Understanding tourist barriers and personality influences in embracing generative AI for travel planning and decision-making DOI Creative Commons
Siamak Seyfi, Myung Ja Kim, Amin Nazifi

et al.

International Journal of Hospitality Management, Journal Year: 2025, Volume and Issue: 126, P. 104105 - 104105

Published: Jan. 15, 2025

Language: Английский

Citations

3
Third-party evaluators perceive AI as more compassionate than expert humans DOI Creative Commons

Dariya Ovsyannikova,

Victoria Oldemburgo de Mello, Michael Inzlicht

et al.

Communications Psychology, Journal Year: 2025, Volume and Issue: 3(1)

Published: Jan. 10, 2025

Abstract Empathy connects us but strains under demanding settings. This study explored how third parties evaluated AI-generated empathetic responses versus human in terms of compassion, responsiveness, and overall preference across four preregistered experiments. Participants ( N = 556) read empathy prompts describing valenced personal experiences compared the AI to select non-expert or expert humans. Results revealed that were preferred rated as more compassionate responders (Study 1). pattern results remained when author identity was made transparent 2), crisis 3), disclosed all participants 4). Third perceived being responsive—conveying understanding, validation, care—which partially explained AI’s higher compassion ratings Study 4. These findings suggest has robust utility contexts requiring interaction, with potential address increasing need for supportive communication contexts.

Language: Английский

Citations

2
A Cross-National Assessment of Artificial Intelligence (AI) Chatbot User Perceptions in Collegiate Physics Education. DOI Creative Commons

Benjamin Osafo Agyare,

Joseph Asare, A. F. Kraishan

et al.

Computers and Education Artificial Intelligence, Journal Year: 2025, Volume and Issue: unknown, P. 100365 - 100365

Published: Jan. 1, 2025

Language: Английский

Citations

2
CONTRADICTORY ATTITUDES TOWARD ACADEMIC AI TOOLS: THE EFFECT OF AWE-PRONENESS AND CORRESPONDING SELF-REGULATION DOI Creative Commons
Jiajin Tong,

Yangmingxi Zhang,

Yutong Li

et al.

Computers in Human Behavior Artificial Humans, Journal Year: 2025, Volume and Issue: unknown, P. 100123 - 100123

Published: Jan. 1, 2025

Language: Английский

Citations

1
Validating the AI-assisted second language (L2) learning attitude scale for Chinese college students and its correlation with L2 proficiency DOI Creative Commons

Hanwei Wu,

Wentao Liu,

Yonghong Zeng

et al.

Acta Psychologica, Journal Year: 2024, Volume and Issue: 248, P. 104376 - 104376

Published: July 1, 2024

The positive impact of Artificial Intelligence (AI) on second language (L2) learning is well-documented. An individual's attitude toward AI significantly influences its adoption. Despite this, no specific scale has been designed to measure this attitude, particularly in the Chinese context. To address gap, our study aims construct AI-Assisted L2 Learning Attitude Scale for College Students (AL2AS-CCS) and evaluate reliability, validity, relationship with proficiency. Our research comprises two phases, each involving separate samples. In Phase One (Sample 1: n = 379), we conducted exploratory factor analysis (EFA) determine structure AL2AS-CCS. resulting two-factor consists 12 items, categorized into cognitive behavioral components. Two 2: 429), performed confirmatory (CFA) validate assess model fit. CFA Sample 2 confirmed demonstrated a good Additionally, AL2AS-CCS exhibited high criterion internal consistency, cross-gender invariance. findings suggest that valid measurement tool assessing college students' AI-assisted learning. Moreover, students were discovered maintain moderately correlation was identified between their

Language: Английский

Citations

7
The relationships of personality traits on perceptions and attitudes of dentistry students towards AI DOI Creative Commons
Furkan Özbey, Yasin Yaşa

BMC Medical Education, Journal Year: 2025, Volume and Issue: 25(1)

Published: Jan. 6, 2025

Artificial intelligence (AI) has gained significant attention in dentistry due to its potential revolutionize practice and improve patient outcomes. However, dentists' views attitudes toward technology can affect the application of AI. This perception attitude be affected by personality traits individuals. study aims evaluate perceptions students cross-sectional was conducted on dental at Ordu University Faculty Dentistry, involving a sample 83 students. The utilized Big Five 50 Test 5-point Likert scale gather data 20 statements regarding AI dentistry. Data were analyzed using IBM SPSS Statistics software, chi-square test employed assess relationship between their towards artificial intelligence, as well gender intelligence. Statistical significance set P < 0.05. involved participants, with 29 male 54 female participants. most common Openness Agreeableness, whereas least Extraversion. Participants found useful believed it could help dentists radiographs. agreed statement that they would trust more than dentist evaluating radiograph results. A statistically difference personal expressions comparing Males familiar females. vary based traits. Developing educational strategies tailored these foster positive integration into practice.

Language: Английский

Citations

0
AI Performer Bias: Listeners Like Music Less When They Think it was Performed by an AI DOI Creative Commons
Alessandro Ansani, Friederike Koehler, Lisa Giombini

et al.

Empirical Studies of the Arts, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 15, 2025

Contextual information can shape the aesthetic judgements of music compositions. Recently, a study proposed existence an AI composer bias; namely, listeners tend to like less when they think (or are told) that it was composed by AI. In this online ( N = 120), we used cross-over experimental design verify whether such bias extends audiovisual performance. The participants rated three videos classic piano performances in two versions with identical audio: one professional pianist who pretended play, and playing automatically, allegedly thanks As hypothesised, as more likeable, engaging, higher emotional valence, quality pieces were “performed” pianist. Notably, these effects insensitive participants’ musical expertise but moderated their attitudes toward Interestingly, asked what differences had found between renditions, confabulated about rhythm, tempo variations, dynamics, dissonances, pointing underlying psychological processes, expectations beliefs humanness. Implications for Aesthetics Psychology Art discussed.

Language: Английский

Citations

0
Unveiling the role of honesty-humility in shaping attitudes towards artificial intelligence DOI Creative Commons

Sarah Zabel,

Pamela Pensini, Siegmar Otto

et al.

Personality and Individual Differences, Journal Year: 2025, Volume and Issue: 238, P. 113072 - 113072

Published: Jan. 30, 2025

Language: Английский

Citations

0
Trust and Acceptance Challenges in the Adoption of AI Applications in Health Care: Quantitative Survey Analysis DOI Creative Commons
Janne Kauttonen, Rebekah Rousi, Ari Alamäki

et al.

Journal of Medical Internet Research, Journal Year: 2025, Volume and Issue: 27, P. e65567 - e65567

Published: March 21, 2025

Background Artificial intelligence (AI) has potential to transform health care, but its successful implementation depends on the trust and acceptance of consumers patients. Understanding factors that influence attitudes toward AI is crucial for effective adoption. Despite AI’s growing integration into consumer patient remains a critical challenge. Research largely focused applications or attitudes, lacking comprehensive analysis how factors, such as demographics, personality traits, technology knowledge, affect interact across different care contexts. Objective We aimed investigate people’s in use cases determine context perceived risk individuals’ propensity accept specific scenarios. Methods collected analyzed web-based survey data from 1100 Finnish participants, presenting them with 8 care: 5 (62%) noninvasive (eg, activity monitoring mental support) 3 (38%) physical interventions AI-controlled robotic surgery). Respondents evaluated intention use, trust, willingness trade off personal these cases. Gradient boosted tree regression models were trained predict responses based 33 demographic-, personality-, technology-related variables. To interpret results our predictive models, we used Shapley additive explanations method, game theory–based approach explaining output machine learning models. It quantifies contribution each feature individual predictions, allowing us relative importance various their interactions shaping participants’ care. Results Consumer technology, traits primary drivers Use ranked by acceptance, monitors being most preferred. However, case had less impact general than expected. Nonlinear dependencies observed, including an inverted U-shaped pattern positivity self-reported knowledge. Certain more disorganized careless, associated positive Women seemed cautious about men. Conclusions The findings highlight complex interplay influencing are driven rather service providers should consider demographic when designing implementing systems study demonstrates using decision-making tools interacting clients applications.

Language: Английский

Citations

0
Suspicious of AI? Perceived autonomy and interdependence predict AI‐related conspiracy beliefs DOI Creative Commons
Q Zhao, Jan‐Willem van Prooijen, Xinying Jiang

et al.

British Journal of Social Psychology, Journal Year: 2025, Volume and Issue: 64(2)

Published: April 1, 2025

Abstract As artificial intelligence (AI) evolves, conspiracy theories have emerged that authorities will use AI to oppress humanity, or itself will. We propose perceived high autonomy and low interdependence of increase AI‐related beliefs. Four studies (total N = 1897) examined this line reasoning. Study 1 ( 300) supported the hypotheses in a correlational survey. Studies 2 400) 3 (pre‐registered; manipulated experiments. Both found higher lower increased beliefs, while threat society mediated these effects most cases. 4 (pre‐registered) replicated findings from United States China 397) cultural differences These illuminate how properties contribute

Language: Английский

Citations

0