In the era of big data, research activity on data science fo-cuses on large datasets to produce knowledge supporting decision-makingprocesses in different application domains and contexts. Data sciencepractices and outputs have a tremendous impact on a variety of fields byraising new ethical issues that become crucial. In this paper, we addressthe ethical issues related to the ethics of data, the ethics of algorithms,and the ethics of practices in the context of our data science approach forcase-law decisions (CLDs) processing called CRIKE (CRIme KnowledgeExtraction). In particular, we discuss the ethical issues that need to befaced when dealing with knowledge extracted from CLDs for descriptiveanalysis purposes and for predictive usage of data extracted from CLDs

Law Data Science and Ethics: the CRIKE Approach / S. Castano, M. Falduti, A. Ferrara, S. Montanelli (CEUR WORKSHOP PROCEEDINGS). - In: Proceedings of the 1st International Workshop on Processing Information Ethically co-located with 31st International Conference on Advanced Information Systems Engineering (CAiSE 2019) / [a cura di] Donatella Firmani, Elena Nieddu, Letizia Tanca, Riccardo Torlone. - [s.l] : CEUR-WS, 2019. - pp. 1-9 (( Intervento presentato al 1. convegno 1st International Workshop on Processing Information Ethically tenutosi a Rome, Italy nel 2019.

Law Data Science and Ethics: the CRIKE Approach

S. Castano;M. Falduti;A. Ferrara;S. Montanelli
2019

Abstract

In the era of big data, research activity on data science fo-cuses on large datasets to produce knowledge supporting decision-makingprocesses in different application domains and contexts. Data sciencepractices and outputs have a tremendous impact on a variety of fields byraising new ethical issues that become crucial. In this paper, we addressthe ethical issues related to the ethics of data, the ethics of algorithms,and the ethics of practices in the context of our data science approach forcase-law decisions (CLDs) processing called CRIKE (CRIme KnowledgeExtraction). In particular, we discuss the ethical issues that need to befaced when dealing with knowledge extracted from CLDs for descriptiveanalysis purposes and for predictive usage of data extracted from CLDs
Settore INF/01 - Informatica
2019
http://ceur-ws.org/Vol-2417/paper3.pdf
Book Part (author)
File in questo prodotto:
File Dimensione Formato  
paper3.pdf

accesso aperto

Tipologia: Publisher's version/PDF
Dimensione 381.6 kB
Formato Adobe PDF
381.6 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/668394
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? ND
social impact