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Data · dataset · 2026

When should a computer decide? Judicial decision-making in the age of automation, algorithms, and generative artificial intelligence

Listed in ZivaHub and Deakin Research Online and DMU Figshare — shown once because both records carry DOI 10.17034/32639298.v1

This thesis interrogates what it is about the essenLally human activity of judging disputes that cannot be reliably or safely recreated through AI systems.

Description

To conduct this inquiry, two key ‘ingredients’ of the judicial decision-making process that exemplify this innately social practice are selected for analysis. The ability to participate in judicial decision-making, and the exercise of judicial discretion, are manifestations of the law as it exists within a wider social context, which shapes and condiLons it.

Contrary to some analysis, the law is not applied through the mechanical selection of ‘correct’ precedents to cut and dried facts. The quotidian world of legal practice shows us that the law and its application are cultivated iteratively through a variety of legal actors. In this sense, it is malleable, contingent on context, and not necessarily computable in AI systems, including in the context of sophisticated Large Language Models.

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Indeed, it is this interpretation of the judicial role – as it exists within this wider social context – that prompts consideration of the features of judicial decision-making that either: most clearly exhibit the social and dynamic nature of law; and/or cater to it. This leads to the conclusion that the ability to participate effectively, and the exercise of judicial discretion, cannot be reliably or safely captured by AI systems, including Large Language Models.

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Catalogue records · 1

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Provenance · 3 source records, 19 field assertions
SourceKeyLast seenRaw
ZivaHuboai:figshare.com:article/326392989 d agoJSON v1
Deakin Research Onlineoai:figshare.com:article/326392989 d agoJSON v1
DMU Figshareoai:figshare.com:article/326392989 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].anzsrc:group:4602mapping · zivahub uct ac zavocabulary-mapper@1.0.0keywords['Artificial intelligence']
concepts[field].anzsrc:group:4602mapping · dro deakin edu auvocabulary-mapper@1.0.0keywords['Artificial intelligence']
concepts[field].anzsrc:group:4602mapping · figshare dmu ac ukvocabulary-mapper@1.0.0keywords['Artificial intelligence']
concepts[field].local:field:computer-science-aimapping · dro deakin edu auconnector:dro_deakin_edu_au@1.0.0
concepts[field].local:field:computer-science-aimapping · figshare dmu ac ukconnector:figshare_dmu_ac_uk@1.0.0
concepts[field].local:field:computer-science-aimapping · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
concepts[field].local:field:earth-environmentalmapping · dro deakin edu auconnector:dro_deakin_edu_au@1.0.0
concepts[field].local:field:earth-environmentalmapping · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
concepts[field].local:field:earth-environmentalmapping · figshare dmu ac ukconnector:figshare_dmu_ac_uk@1.0.0
concepts[field].local:field:humanitiesmapping · dro deakin edu auconnector:dro_deakin_edu_au@1.0.0
concepts[field].local:field:humanitiesmapping · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
concepts[field].local:field:humanitiesmapping · figshare dmu ac ukconnector:figshare_dmu_ac_uk@1.0.0
concepts[field].local:field:social-sciencemapping · figshare dmu ac ukconnector:figshare_dmu_ac_uk@1.0.0
concepts[field].local:field:social-sciencemapping · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
concepts[field].local:field:social-sciencemapping · dro deakin edu auconnector:dro_deakin_edu_au@1.0.0
descriptionsource · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0/metadata/dc/description
license_textsource · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
publication_datesource · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
titlesource · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0/metadata/dc/title