Generative AI, Critical Thinking and Social Work Practice
Gillon, Fern and Weaver, Beth and Heron, Gavin and Reid, Fergus and Dong, Feng (2026) Generative AI, Critical Thinking and Social Work Practice. Iriss Insights, 77 . IRISS, Glasgow.
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Abstract
Artificial Intelligence (AI) is a field of computer science focused on creating machines that can perform tasks requiring human-like intelligence, such as learning, problem-solving, decision-making, and understanding language, by processing large amounts of data to recognise patterns and adapt. AI is increasingly becoming embedded in everyday life, particularly generative AI, from the tools we use to communicate, to the systems that support administrative tasks and decision-making. Generative AI creates new content in text, audio or visual form, in response to a prompt (BASW, 2025). It draws from the internet and what people post and say, and is trained on large sets of data using natural language processing (NLP) – to help computers interpret and generate human language – and machine learning (ML) to find patterns, make decisions and predict outcomes without being programmed for every task.
ORCID iDs
Gillon, Fern
ORCID: https://orcid.org/0000-0003-0994-4000, Weaver, Beth
ORCID: https://orcid.org/0000-0003-1711-1068, Heron, Gavin
ORCID: https://orcid.org/0000-0002-2238-1532, Reid, Fergus and Dong, Feng;
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Item type: Book ID code: 95417 Dates: DateEventJanuary 2026PublishedSubjects: Science > Mathematics > Electronic computers. Computer science Department: Faculty of Humanities and Social Sciences (HaSS) > Social Work and Social Policy
Faculty of Humanities and Social Sciences (HaSS) > Social Work and Social Policy > Social Work and Social Policy > Social Policy
Faculty of Humanities and Social Sciences (HaSS) > Social Work and Social Policy > Social Work and Social Policy > Social Work
Faculty of Science > Computer and Information SciencesDepositing user: Pure Administrator Date deposited: 27 Jan 2026 15:45 Last modified: 27 Jan 2026 15:45 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/95417
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