Journal of Medical Internet Research, Год журнала: 2024, Номер unknown
Опубликована: Дек. 5, 2024
Язык: Английский
ACM Journal on Responsible Computing, Год журнала: 2024, Номер 1(4), С. 1 - 45
Опубликована: Сен. 21, 2024
Appropriate trust in Artificial Intelligence (AI) systems has rapidly become an important area of focus for both researchers and practitioners. Various approaches have been used to achieve it, such as confidence scores, explanations, trustworthiness cues, uncertainty communication. However, a comprehensive understanding the field is lacking due diversity perspectives arising from various backgrounds that influence it lack single definition appropriate trust. To investigate this topic, article presents systematic review identify current practices building trust, different ways measure types tasks used, potential challenges associated with it. We also propose Belief, Intentions, Actions mapping study commonalities differences concepts related by (a) describing existing disagreements on defining (b) providing overview definitions AI literature. Finally, identified studying are discussed, observations summarized trends, gaps, research opportunities future work. Overall, provides insights into complex concept human-AI interaction advance our topic.
Язык: Английский
Процитировано
11
International Journal of Human-Computer Interaction, Год журнала: 2024, Номер unknown, С. 1 - 15
Опубликована: Май 28, 2024
Trust is critical in humans' interactions with artificial intelligence (AI). In this large-scale survey study (N = 2187), we examined the effects of 19 factors on people's trust AI. Across three dimensions (i.e., trustor, trustee, and their interacting context), related to trustee AI) were found affect AI most. Among category, warmth competence, two also human relationships, emerged as most pivotal ones, they partially mediated other We further show that influenced participants' intentions collaborate use both directly mediator between warmth, intentions. These findings indicate shares much common ground humans, provide practical suggestions how promote effectively.
Язык: Английский
Процитировано
3
Philosophy & Technology, Год журнала: 2025, Номер 38(1)
Опубликована: Фев. 12, 2025
Язык: Английский
Процитировано
0
Опубликована: Март 28, 2025
Abstract Artificial intelligence (AI) is reshaping healthcare, promising improved diagnostics, personalized treatments, and streamlined operations. Yet a lack of trust remains persistent barrier to widespread adoption. This Perspective examines the web in AI-assisted healthcare systems, exploring relationships it shapes, systemic inequalities can reinforce, technical challenges poses. We highlight bidirectional nature trust, which both patients providers must AI while these systems rely on quality human input function effectively. Using models care-seeking behavior, we explore potential affect patients’ decisions seek care, influence institutions, diverse demographic clinical settings. argue that addressing trust-related requires rigorous empirical research, equitable algorithm design, shared accountability frameworks. Ultimately, AI’s impact hinges not just progress but sustaining may erode if biases persist, transparency falters, or incentives misalign.
Язык: Английский
Процитировано
0
Frontiers in Communication, Год журнала: 2025, Номер 10
Опубликована: Май 26, 2025
Introduction This paper investigates how 33 Turkish and 38 Russian university students perceive experience artificial intelligence (AI) in scholarly communication. study students’ perspectives, experiences, concerns regarding AI use educational settings. Three main areas of inquiry are addressed: general views experiences with technology, effects on academic communication teamwork, evaluation AI-generated work terms integrity plagiarism. Methods The participants were 71 students, consisting students. Data was collected through open-ended questionnaires. Qualitative material examined using six-stage theme analysis system. Results Our findings reveal both shared divergent perspectives among AI’s role their environment. Students from countries recognize significant potential to streamline tasks enhance access information. However, they also voice apprehensions over its influence critical thinking abilities honesty. exhibited a predominantly favorable outlook toward the collaborative capabilities AI, but placed greater emphasis privacy data security. Discussion highlights complex interplay between benefits challenges environments. encounter ethical issues, namely plagiarism authenticity content. research importance clearly defined institutional regulations initiatives offer guidelines for academia. comparative offers fascinating cultural factors influencing applications higher education. It adds ongoing worldwide conversation about technology impacts future plans.
Язык: Английский
Процитировано
0
European Journal of Management Issues, Год журнала: 2024, Номер 32(3), С. 174 - 182
Опубликована: Сен. 15, 2024
Purpose: The aim of this study is to examine how the integration Emotional Intelligence (EI) and Artificial (AI) in leadership can enhance effectiveness influence development future leaders. Design / Method Approach: research employs a mixed-methods approach, combining qualitative quantitative analyses. utilizes secondary data sources, including scholarly articles, industry reports, empirical studies, analyze interaction between EI AI settings. Findings: findings reveal that significantly improves decision-making, strategic planning, talent management, communication within organizations. Leaders who leverage both experience higher employee satisfaction, improved team performance, enhanced organizational outcomes. Theoretical Implications: This contributes theory by introducing novel framework demonstrates complementary roles leadership. Practical offers practical guidelines for development, emphasizing need leaders integrate skills order navigate complex business environments successfully. Originality Value: paper provides an original leadership, offering new insights into these two elements work together improve effectiveness. Research Limitations Future Research: should further explore impact various industries levels generalize across broader contexts. Paper Type: Conceptual JEL Classification: D83, M12, M15, L21, O33
Язык: Английский
Процитировано
2
Computers & Education, Год журнала: 2024, Номер unknown, С. 105230 - 105230
Опубликована: Дек. 1, 2024
Язык: Английский
Процитировано
2
Frontiers in Psychology, Год журнала: 2024, Номер 15
Опубликована: Дек. 19, 2024
On the technical side, both traditional, shallow feature-based methods (e.g., Support Vector Machines and Random Forest) deep neural network models LSTM CNN types) have been utilized (Khare et al., 2024;Pepa 2023). A key focus has development of multimodal systems that integrate diverse data sources, such as facial expressions, voice tone, dialogue sentiment, physiological signals (Geetha 2024). Multiple enable aggregation complementary information, leveraging strengths various measurement techniques to enhance robustness accuracy.Technology is only effective with users; thus, beyond developing methods, fostering adoption among professionals citizens essential. Alongside advancements, researchers explored psychological social factors influencing acceptance trust AI systems, particularly in healthcare education. Trust proven pivotal for adoption, studies investigating how build it what system attributes ensure trustworthiness (Li Key include explainability, transparency processes usage, credibility institutions behind development.This Research Topic explores novel theories, methodologies, applications Emotion The published works address aspects, models, literacy. Burgess al. (2023) evaluated automated coding software parent-infant interactions across five fathers mothers. Automated detection rates were low (~25%) compared manual naturalistic settings but strongly correlated assessments, positive when successful. challenges included poor lighting, occlusion, rapid movements, highlighting need greater real-world conditions. Despite these limitations, study demonstrated potential analyzing authentic emotional expressions parent-child interactions. 2023) introduced an innovative semi-supervised learning approach stress monitoring. Using from 14 participants experiments, they achieved 77% accuracy label propagation 76% autoencoders despite utilizing 17% labeled data. Their method matched performance fully supervised approaches while substantially reducing annotation requirements, offering a practical solution continuous monitoring applications. Žvanut Mihelič (2024) identified four distinct attitudes older adults toward domestic robots: Cautious Optimists, Skeptical Traditionalists, Positive Technophiles. Through interviews 24 participants, highlighted influence like technology familiarity, privacy concerns, perceived utility on acceptance. findings offer valuable insights designing emotionally intelligent robotic assistants tailored user needs concerns. Shen Cui investigated link between satisfaction literacy 445 university students. revealed teacher support positively impacted students' autonomy competence, subsequently improving Notably, satisfying proved more critical than direct enhancing These guidance AI-enhanced educational environments foster better engagement. Gong examined patients' AI-powered pharmacy intravenous admixture services studies. They found patients generally trusted PIVAS less human services, primarily due limited subjective understanding systems. However, informed consent significantly improved by understanding. This underscores role transparent communication adopting healthcare.The articles this advance datasets explore can be effectively integrated into education, addressing related trust, privacy, While shows promise, its use fields raises ethical including surveillance, misuse personal information. Clinical are further constrained small sample sizes, lack control groups, testing, methodological variability, which hinder reproducibility reliability (Pepa tackle model-training noisy identifying trust.Future research should prioritize emotion recognition settings, efficient reduce dependence data, considerations AI. Emphasis cross-cultural validation long-term evaluation crucial. Recent generative (GenAI) foundation GPT-4, significant advancing their versatility (Cheng GenAI already shown promise recognizing indicators (Elyoseph 2024) could help alleviate scarcity specialized model development. Additionally, there growing interest analysis groups crowds, broadening field's scope (Veltmeijer 2023;Li
Язык: Английский
Процитировано
1
Frontiers in Psychology, Год журнала: 2024, Номер 15
Опубликована: Сен. 5, 2024
Medical services are getting automated and intelligent. An emerging medical service is the AI pharmacy intravenous admixture (PIVAS) that prepares infusions through robots. However, patients may distrust these Therefore, this study aims to investigate psychological mechanism of patients' trust in PIVAS.
Язык: Английский
Процитировано
0
Опубликована: Сен. 5, 2024
Язык: Английский
Процитировано
0