ChatGPT for Social Work Science: Ethical Challenges and Opportunities

Patton, Desmond Upton; Landau, Aviv Y.; Mathiyazhagan, Siva

doi:10.1086/726042

Cited by 5 publications

(1 citation statement)

References 5 publications

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“…For example, OpenAI's ChatGPT explicitly acknowledges its potential to generate inaccurate information about individuals, locations, or facts, underlining the need for researchers to be aware of this limitation and ethical challenges when incorporating ChatGPT in scientific works. This includes essential considerations regarding data privacy, confidentiality, and informed consent [158]. The handling of sensitive data by ChatGPT introduces vulnerabilities that may be exploited for unauthorized access or misuse, thereby posing substantial privacy and security risks [76].…”

Section: Ethical Challengesmentioning

confidence: 99%

Opportunities and Challenges of Generative AI in Construction Industry: Focusing on Adoption of Text-Based Models

Ghimire,

Kim,

Acharya

2024

Buildings

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In the last decade, despite rapid advancements in artificial intelligence (AI) transforming many industry practices, construction largely lags in adoption. Recently, the emergence and rapid adoption of advanced large language models (LLMs) like OpenAI’s GPT, Google’s PaLM, and Meta’s Llama have shown great potential and sparked considerable global interest. However, the current surge lacks a study investigating the opportunities and challenges of implementing Generative AI (GenAI) in the construction sector, creating a critical knowledge gap for researchers and practitioners. This underlines the necessity to explore the prospects and complexities of GenAI integration. Bridging this gap is fundamental to optimizing GenAI’s early stage adoption within the construction sector. Given GenAI’s unprecedented capabilities to generate human-like content based on learning from existing content, we reflect on two guiding questions: What will the future bring for GenAI in the construction industry? What are the potential opportunities and challenges in implementing GenAI in the construction industry? This study delves into reflected perception in literature, analyzes the industry perception using programming-based word cloud and frequency analysis, and integrates authors’ opinions to answer these questions. This paper recommends a conceptual GenAI implementation framework, provides practical recommendations, summarizes future research questions, and builds foundational literature to foster subsequent research expansion in GenAI within the construction and its allied architecture and engineering domains.

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Section: Ethical Challengesmentioning

confidence: 99%

Opportunities and Challenges of Generative AI in Construction Industry: Focusing on Adoption of Text-Based Models

Ghimire,

Kim,

Acharya

2024

Buildings

View full text Add to dashboard Cite

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Introducing Generative Artificial Intelligence Into the MSW Curriculum: A Proposal for the 2029 Educational Policy and Accreditation Standards

Rodriguez,

Goldkind,

Victor

et al. 2024

Journal of Social Work Education

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The NIMH Task Force on Social Work Research Report: Past Accomplishments and Current Challenges

Feldman

2024

Research on Social Work Practice

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Following the publication of the groundbreaking report by the National Institute of Mental Health Task Force on Social Work Research in 1991, major gains have been made in building a potent infrastructure for social work research. Since then, however, progress has faltered in key areas and complex new challenges have emerged. These developments are examined and suggestions are set forth regarding how best to address the most serious challenges.

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ChatGPT for Social Work Science: Ethical Challenges and Opportunities

Cited by 5 publications

References 5 publications

Opportunities and Challenges of Generative AI in Construction Industry: Focusing on Adoption of Text-Based Models

Opportunities and Challenges of Generative AI in Construction Industry: Focusing on Adoption of Text-Based Models

Introducing Generative Artificial Intelligence Into the MSW Curriculum: A Proposal for the 2029 Educational Policy and Accreditation Standards

The NIMH Task Force on Social Work Research Report: Past Accomplishments and Current Challenges

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