- Area tematica Ingegneria
- Sede Palazzo della Carovana, Scuola Normale Superiore, Pisa, Italia
- Scadenza iscrizione 02.02.2023
- Periodo di svolgimento -
- Crediti CFU 2
- Ore formazione 32
- Numero massimo di partecipanti 30
In fulfilment of the EELISA Board Declaration, this spring school aims to align technical excellence with social impact in the upcoming generation of AI researchers and developers, by combining their tekhnè with ethos.
This Seasonal School has received funding from the EELISA project under the European Union's Erasmus+ programme Grant Agreement N. 101004081 and from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme. Grant agreement № 835294.
On site, the school targets early-career researchers (e.g. research assistants, PhD students, post-docs, exceptional master students) in AI or in computational sciences more broadly.
The course can also be followed remotely, with no academic requirement, but no ECTS will be awarded.
To receive the link for online auditing, simply fill out this form.
The main goal is to provide AI researchers with a broader view of the impact of the development of their field, through plural perspectives (from AI academics to big-tech leaders, economists, journalists, lawyers, members of the EU parliament, philosophers and citizens).
More specifically, the course will teach and set a discussion on how to implement key notions of the Ethics Guidelines for Trustworthy AI, drafted by the AI High-Level Expert Group appointed by the European Commission.
Lectures, panel discussions, tutorials, workshops, moot court competition, open discussion.
The school program will unfold over a week of thematic days around key chapters of the Ethics Guidelines for Trustworthy AI. Each day will address a specific question, thanks to lectures in the morning and practical activities in the afternoon. The five topics will be:
1) the socioeconomic impact of AI
2) EU regulations for a fair and private AI
3) explainable AI (XAI)
4) AI decision-making biases identification and AI trustworthiness assessment
5) legal liability in AI
You can find more details about speakers and draft programme by downloading the attachment from the "Download attachment" button, from the EELISA community website.