preprints.org > computer science and mathematics > artificial intelligence and machine learning > doi: 10.20944/preprints202401.0622.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 8 January 2024 / Approved: 8 January 2024 / Online: 8 January 2024 (10:40:53 CET)

The use of Artificial Intelligence (AI) applications in a growing number of domains in the latest years has put into focus Ethical Legal and Societal Aspects (ELSA) of these technologies and the relevant challenges they pose. In this paper, we propose an ELSA Curriculum for Data Scientists aiming to raise awareness about ELSA challenges in their work, provide them with a common language with the relevant domain experts to cooperate to find appropriate solutions, and finally, incorporate ELSA in the data science workflow and not be seen as an impediment or a superfluous artifact, rather than an integral part of the Data Science Project Lifecycle. The proposed curriculum uses the CRISP-DM model as a backbone to define a vertical partition, expressed in modules corresponding to the CRISP-DM phases. The horizontal partition includes knowledge units belonging to three strands that run through the phases, namely Ethical and Societal, Legal, and Technical Rendering Knowledge Units (KUs). In addition to the detailed description of the aforementioned KUs, we also discuss the implementation, issues such as duration, form, and evaluation of participants, as well as the variance of the knowledge level and needs of the target audience.

AI ethics; Data Science; Artificial Intelligence; ELSA; Education

Computer Science and Mathematics, Artificial Intelligence and Machine Learning

* All users must log in before leaving a comment