Examining teachers’ behavioural intention of using generative artificial intelligence tools for teaching and learning based on the extended technology acceptance model DOI Creative Commons
Siu Cheung Kong, Yin Yang,

Chunyu Hou

et al.

Computers and Education Artificial Intelligence, Journal Year: 2024, Volume and Issue: 7, P. 100328 - 100328

Published: Nov. 1, 2024

Language: Английский

Chatbots and AI in Education (AIEd) tools: The good, the bad, and the ugly DOI Open Access
Augustine O. Ifelebuegu,

Peace Kulume,

Perpetua Cherukut

et al.

Journal of Applied Learning & Teaching, Journal Year: 2023, Volume and Issue: 6(2)

Published: Sept. 26, 2023

As the application of Artificial Intelligence (AI) continues to permeate various sectors, educational landscape is no exception. Several AI in education (AIEd) applications, like chatbots, present an intriguing array opportunities and challenges. This paper provides in-depth exploration use role research, focusing on benefits (the good) potential pitfalls bad ugly) associated with deployment chatbots other AIEDs. The explored include personalised learning, facilitation administrative tasks, enriched research capabilities, provision a platform for collaboration. These advantages are balanced against downsides, such as job displacement, misinformation, plagiarism, erosion human connection. Ethical considerations, particularly concerning data privacy, bias reinforcement, digital divide, also examined. Conclusions drawn from this analysis stress importance striking balance between capabilities elements education, well developing comprehensive ethical frameworks contexts.

Language: Английский

Citations

44

Artificial intelligence in healthcare institutions: A systematic literature review on influencing factors DOI Creative Commons
Julia Stefanie Roppelt, Dominik K. Kanbach, Sascha Kraus

et al.

Technology in Society, Journal Year: 2023, Volume and Issue: 76, P. 102443 - 102443

Published: Dec. 9, 2023

The purpose of this review is integrating and contextualizing relevant literature on the factors influencing adoption AI in healthcare industry into a comprehensive framework. Health systems are considered fundamental to creating societal value. However, global health challenged by increasing number patients due population aging growing prevalence chronic diseases cancer. Meanwhile, United Nations calls for equal access healthcare, tackling costs, addressing resource constraints foster sustainable development societies. In context, artificial intelligence (AI) gaining attention as it constitutes promising technology address these burgeoning challenges. Despite opportunities, specifically fragmented across various research fields, lacking overview. It lacks theoretically grounded integrating, example, that influence institutions. Derived from multi-disciplinary systematic review, building 130 studies, we propose Adoption Healthcare Industry Model. This model encompasses five dimensions contextualizes them. We macro-economic, regulatory, technological readiness serve external antecedents whereas organizational individual constitute internal Our has implications acceptance related healthcare. Further, provide hands-on guidance providers, institutions, official bodies such governments leverage

Language: Английский

Citations

43

The knowledge and innovation challenges of ChatGPT: A scoping review DOI
Omar Ali, Peter Murray, Mujtaba M. Momin

et al.

Technology in Society, Journal Year: 2023, Volume and Issue: 75, P. 102402 - 102402

Published: Oct. 21, 2023

Language: Английский

Citations

42

Application of CHATGPT in civil engineering DOI Creative Commons
Martin Aluga

East African Journal of Engineering, Journal Year: 2023, Volume and Issue: 6(1), P. 104 - 112

Published: June 28, 2023

Artificial Intelligence, machine learning, and the Internet of Things (IoT) are changing way tasks accomplished. CHATGPT is a well-known conversational artificial intelligence (AI) system based on generative pre-trained transformer (GPT) architecture, launched by OpenAI. trained through reinforcement learning human feedback. There advantages to use in Civil engineering, including but not limited design planning: structural analysis simulation, code compliance regulations construction management, knowledge repository information retrieval, education, research. The limitation bias datasets used training, requirement sufficient input information, as well risk transparency issues, negative consequences if generating inaccurate content. other language models civil engineering requires careful consideration ensure bypassing expert consultation particular cases. Deep Learning would have positive impact rather than replacing expertise improving infrastructure development world solving challenges facing mankind

Language: Английский

Citations

24

AI in knowledge sharing, which ethical challenges are raised in decision-making processes for organisations? DOI
Mojtaba Rezaei,

Marco Pironti,

Roberto Quaglia

et al.

Management Decision, Journal Year: 2024, Volume and Issue: unknown

Published: April 24, 2024

Purpose This study aims to identify and assess the key ethical challenges associated with integrating artificial intelligence (AI) in knowledge-sharing (KS) practices their implications for decision-making (DM) processes within organisations. Design/methodology/approach The employs a mixed-methods approach, beginning comprehensive literature review extract background information on AI KS potential challenges. Subsequently, confirmatory factor analysis (CFA) is conducted using data collected from individuals employed business settings validate identified impact DM processes. Findings findings reveal that related privacy protection, bias fairness transparency explainability are particularly significant DM. Moreover, accountability responsibility of employment also show relatively high coefficients, highlighting importance process. In contrast, such as intellectual property ownership, algorithmic manipulation global governance regulation found be less central Originality/value research contributes ongoing discourse knowledge management (KM) By providing insights recommendations researchers, managers policymakers, emphasises need holistic collaborative approach harness benefits technologies whilst mitigating risks.

Language: Английский

Citations

13

Applying Artificial Intelligence to Promote Sustainability DOI Open Access

Miriam Du-Phuong Ta,

Stefan Wendt, Þröstur Olaf Sigurjónsson

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(12), P. 4879 - 4879

Published: June 7, 2024

This study reviews the application of artificial intelligence (AI) throughout food value chain and how it can be leveraged to help companies become more sustainable. A literature review across different parts was conducted provide an overview main themes current future AI applications industry. Moreover, paper focuses on benefits challenges change management when integrating AI. documentary Systematic Review using PRISMA research find analyze aforementioned applications. The key insight is that progress varies significantly. Today’s are primarily found within inspection quality assurance due relatively straightforward in chain. Such technology mainly image-based. Companies use interconnectedness sustainability by becoming efficient through simultaneously saving emissions resources optimizing processes.

Language: Английский

Citations

11

A consumer acceptance model in the artificial intelligence era DOI
Paritosh Pramanik, Rabin K. Jana

Management Decision, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 8, 2025

Purpose This paper identifies consumer acceptance criteria of artificial intelligence (AI)-enabled products and services in the business. We first investigate existing three models. They are technology model (TAM), unified theory use (UTAUT) (CAT). then discuss applicability these models for AI-enabled services. Finally, we outline shortcomings propose an product service (AIEPSAM). also validate proposed AIEPSAM with empirical results using primary survey data. Design/methodology/approach To understand customer’s point view on AI applications services, identify some critical factors present a conceptual framework consumers' based literature, prior research prominent management theories. Then, study broadens horizon beyond established principles associated to accommodate AI-specific factors/variables like data privacy, explainability apparent opacity algorithms. In this paper, that Findings argue although TAM, UTAUT CAT generally applicable explain attitudes towards technology, alone insufficient encompass entire spectrum AI-related issues must not be ignored. The model, namely AIEPSAM, accommodates limitations modifies make it suitable technology. Originality/value attempt articulate discover useful insights, leading examination formulating validation through is criticize TAM other but incorporate into those Through study, required modifications considering additional factors. will assist companies building better understanding emergence (TE) opportunities (TO).

Language: Английский

Citations

2

Understanding GAI risk awareness among higher vocational education students: An AI literacy perspective DOI

Helen Wu,

Dantong Li,

Xiaolan Mo

et al.

Education and Information Technologies, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 27, 2025

Language: Английский

Citations

1

Automation and Its Influence on Sustainable Development: Economic, Social, and Environmental Dimensions DOI Open Access
Ahlam Almusharraf

Sustainability, Journal Year: 2025, Volume and Issue: 17(4), P. 1754 - 1754

Published: Feb. 19, 2025

This study investigates the complex duality of automation and its impact on sustainable development, encompassing factors economic growth, social equity, environmental sustainability. Innovations in artificial intelligence, robotics, machine learning are driving transforming industries through improved production, operational efficiency, resource optimization. However, rapid integration has created a paradox. While it offers opportunities for optimization technological advancement, exacerbates challenges such as income inequality, degradation, displacement. These issues underline need balanced inclusive approaches to automation’s implementation. Automation contributes substantively GDP growth because raises labor productivity, yet arguably enhanced inequality by eliminating low-skilled jobs. improves energy efficiency aids renewable but increases overall effectiveness, leading concerns regarding ecological applied quantitative methodology using longitudinal data from 2000 2023 regression models examine sustainability metrics influenced automation. The findings highlight potential reform effective forms manufacturing, encourage innovation, identify systemic governmental policies. Specifically, results indicate that contributed 25% increase productivity across sectors, 15% reduction intensity per unit GDP, 12% rise Gini index, signaling growing inequality. outcomes emphasize both posed By integrating advancements with goals, can act transformative instrument promote conservation, equitable justice. paper concludes recommendations governments industry leaders incorporate into development objectives, ensuring distribution advantages, while alleviating socio-environmental hazards.

Language: Английский

Citations

1

Factors influencing the effects of the Starlink Satellite Project on the internet service provider market in Thailand DOI Creative Commons
Yarnaphat Shaengchart, Tanpat Kraiwanit, Smich Butcharoen

et al.

Technology in Society, Journal Year: 2023, Volume and Issue: 74, P. 102279 - 102279

Published: June 3, 2023

This quantitative study explores the impact of Starlink project on internet service provider market in Thailand. A convenience sampling technique was used to recruit 617 participants, who completed an online questionnaire. The examined several independent variables, including demographic factors, such as gender, age, education, status and income, user behaviour, devices for access, time spent social media platforms used. Binary regression analyse data. results showed that had a significant competitive structure influenced by factors duration, mobile use, Facebook TikTok. recommends businesses develop effective strategies meet needs expectations their customers. Organisations with access have opportunity collect data new products, which can give them edge. It is important maintain environment prevent artificially low collection rates or exorbitant prices due collusion tacit pricing agreements.

Language: Английский

Citations

21