AI instruments for risk of recidivism prediction and the possibility of criminal adjudication deprived of personal moral recognition standards: sparse notes from a Layman

Pedro Garcia Marques*

*Autor correspondente para este trabalho

Resultado de pesquisarevisão de pares

28 Transferências (Pure)

Resumo

In what follows lies a recount of a concerned criminal lawyer, a layman, as he observes the change foreshadowed by AI in the field of individual risk recidivism assessment for the purposes of criminal penalty imposition on convicted felons. The text will therefore reflect upon the nature of that assessment when promoted by new AI programs based on actuarial-meaning statistically derived-information. It then proceeds to compare that risk recidivism assessment with the one undertaken within the current traditional human paradigm. Identifying the ensuing challenges set by the technological alternatives on the very survival of criminal law’s principiological mainstays. A final note will be drawn on what is lacking in the technological proposal, for all its technical upsides and perceived advantages. The approach here changes. From literature one will bring to the fore the very human account that lies at the center of anything resembling judgment. Both the judgment of the individual being assessed and the one of the court doing the assessment. Human as they both are, one heeds the kind of humanity an entire science—that of law—and its specific approach must acknowledge. Exactly that humanity that seems to be lacking in the technological AI proposals.

Idioma originalEnglish
Título da publicação do anfitriãoMultidisciplinary perspectives on artificial intelligence and the law
EditoresHenrique Sousa Antunes, Arlindo L. Oliveira, Elsa Vaz de Sequeira, Pedro Miguel Freitas, Clara Martins Pereira, Luís Barreto Xavier
EditoraSpringer Nature
Páginas339-350
Número de páginas12
ISBN (eletrónico)9783031412646
ISBN (impresso)9783031412639
DOIs
Estado da publicaçãoPublicado - 2024

Série de publicação

NomeLaw, Governance and Technology Series
Volume58
ISSN (impresso)2352-1902
ISSN (eletrónico)2352-1910

Impressão digital

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