Abstract
US courts are increasingly using algorithm-based recidivism risk prediction instruments in estimating offenders’ dangerousness and, thus, the warranted severity of the punishment. Some argue that this practice mitigates well-known biases in non-algorithm-based recidivism risk assessments. Whether this is so or not, in the present US context, algorithm-based sentencing is quite likely to be unfairly discriminatory. This claim might have radical implications regarding the US penal system in general (as well as that of all other countries); to wit, that it too is unfairly discriminatory against groups with high base crime rates. If so, we face a dilemma forcing us to revise some of our beliefs about penal justice.
| Originalsprog | Engelsk |
|---|---|
| Titel | Sentencing and Artificial Intelligence |
| Antal sider | 23 |
| Udgivelsessted | New York |
| Forlag | Oxford University Press |
| Publikationsdato | 1 jan. 2023 |
| Sider | 74-96 |
| Kapitel | 5 |
| ISBN (Trykt) | 9780197539538 |
| ISBN (Elektronisk) | 9780197539538 |
| DOI | |
| Status | Udgivet - 1 jan. 2023 |