94376 - SEM. DATA SCIENCE FOR LEGAL ANALYTIC

Contenuti

1. Open Data and Digital Legal Sources: PSI directive, FAIR principles, FOIA Act – 4 hours (Understand, Sceptical attitude);
2. Legal Knowledge Representation: LegalXML and AI and Law – 4 hours (Understand, Sceptical attitude);
3. Data lifecycle: selection, purge, normalization, filter, aggregation, metadata, visualization, validation, evaluation, curation. – 6 hours (Understand, Sceptical attitude, Make);
4. Textual manipulation: selection, transformation/conversion, extraction, elaboration. – 6 hours (Understand, Sceptical attitude, Make);
5. Quantitative and qualitative analysis, ethics and XAI – 4 hours (Understand, Sceptical attitude).

Testi/Bibliografia

Ashley, Kevin D. Artificial Intelligence and Legal Analytics. Cambridge University Press, 2017.

Livermore, Michael, and Daniel Rockmore, eds. Law as Data: Computation, Text, and the Future of Legal Analysis. SFI Press, 2019.

https://www.datascienceforlawyers.org/

http://www.legalanalyticscourse.com/

https://landers.com.au/legal-insights-news/the-future-of-analytics-in-legal

https://www.knime.com/learning

https://github.com/Liquid-Legal-Institute/Legal-Text-Analytics

https://github.com/echr-od

https://data.europa.eu/euodp/data/dataset/covid-19-documents-on-eur-lex

Metodi didattici

We provide slides, readings, exercises, technical manuals using https://virtuale.unibo.it/ and the TEAMS platform.

Considering the interdisciplinary approach and technical content, including the practice sessions, attendance is key. We consider the frequency limit exceeded at 75% of attendance.

This course requires an aptitude for pro-active participation with co-working skills.

Modalità di verifica e valutazione dell'apprendimento

The exam requires you to design, implement, document (4 pages) a short data-driven project using the competences acquired. The project could be published on TEAMS. The project could be carried out in groups of up to three people. The project must be presented orally with the possibility of discussing the theoretical part as well.

Strumenti a supporto della didattica

The lessons are conducted by prof. Monica Palmirani with the support of Mr. Salvatore Sapienza, Mr. Francesco Sovrano and Mr. Davide Liga. The course is scheduled for the second semester. The course is based on the learning by doing methodology. After the presentation of the theoretical pillars, we use empirical practices to fix the main concepts. Group activities are encouraged to strengthen co-working capacity.

Orario di ricevimento

Consulta il sito web di Monica Palmirani