Machine Learning and the Work of the User

dc.contributor.authorHarper, Richard
dc.contributor.authorRandall, Dave
dc.date45444
dc.date.accessioned2024-08-02T05:23:23Z
dc.date.available2024-08-02T05:23:23Z
dc.date.issued2024
dc.description.abstractThis paper introduces the collection of the Journal on Machine Learning (ML) and the user. It provides a brief history of ML from the 1950’s through to the current time, sketching the nature of the kinds of precursor AI techniques used in such things as expert systems right the way through to the emergence of ML and its tool sets, including deep learning. It concludes with the ‘generative AI’ used in such ML technologies as PaLM and GPT-3. The history highlights key changes and developments in ML, the especial importance and limitations of deep learning, and the changing attitudes and expectations of users in an environment when ML can and often is oversold. The paper then explores the ways CSCW research has addressed the social context of organisational systems and how the same can apply for ML tools and techniques. It urges research that focuses on the particular ways that ML comes to fit into ‘real world’ collaborative work sites and hence speaks to the CSCW cannon.de
dc.identifier.doi10.1007/s10606-023-09483-6
dc.identifier.issn1573-7551
dc.identifier.urihttp://dx.doi.org/10.1007/s10606-023-09483-6
dc.identifier.urihttps://dl.eusset.eu/handle/20.500.12015/5153
dc.publisherSpringer
dc.relation.ispartofComputer Supported Cooperative Work (CSCW): Vol. 33, No. 2
dc.relation.ispartofseriesComputer Supported Cooperative Work (CSCW)
dc.titleMachine Learning and the Work of the Userde
dc.typeText/Journal Article
mci.reference.pages103-136

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