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Advancing AI Ethics in Engineering Curricula in Europe: A Case Study Approach

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21460%2F25%3A00387115" target="_blank" >RIV/68407700:21460/25:00387115 - isvavai.cz</a>

  • Alternative codes found

    RIV/68407700:21730/25:00387115

  • Result on the web

    <a href="https://doi.org/10.1109/EAEEIE65428.2025.11136781" target="_blank" >https://doi.org/10.1109/EAEEIE65428.2025.11136781</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/EAEEIE65428.2025.11136781" target="_blank" >10.1109/EAEEIE65428.2025.11136781</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Advancing AI Ethics in Engineering Curricula in Europe: A Case Study Approach

  • Original language description

    The Erasmus+ Ethical Engineer project aims to enhance AI education by integrating ethical, social, and legal aspects into engineering training, promoting truthful AI in Europe. In the paper, we present the explored case studies and the methodology for their development. AI ethics is explored through the following case studies. AI in healthcare is examined through fall detection systems for vulnerable populations, the potential for data bias in personalized medical devices, and the ethical implications of off-label device use, such as continuous artificial hearts. The use of AI in witness testimonies is considered through the example of the AIWitness chatbot designed to automate witness statements. Ethical considerations surrounding facial recognition are explored in the context of airport boarding, using a hypothetical scenario based on Brighton International Airport's pilot program, FaceBoard. The project also considers self-driving taxis' ethical and practical implications, using a hypothetical scenario in San Francisco. The ecological impact of generative AI is analyzed, referencing studies from Stanford University on energy consumption and water usage for cooling systems. The ethical challenges of AI in marketing processes are addressed, including the generation of content like text, images, and voice, along with concerns about job displacement, fake content creation, and authorship issues. The use of AI in assessing historic photos is examined, focusing on selection bias, the potential for surfacing insulting content, the need for transparency, and the potential prioritization of profit over ethical considerations. Finally, the paper addresses the pervasive issue of bias in data, particularly within the field of data science. The main contribution of the paper is the development of a structured template for creating AI ethics case studies, which we already tested with smaller groups of teachers and students and refined based on their feedback.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    R - Projekt Ramcoveho programu EK

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    2025 34th Annual Conference of the European Association for Education in Electrical and Information Engineering (EAEEIE)

  • ISBN

    979-8-3315-0290-4

  • ISSN

    2472-7687

  • e-ISSN

    2472-7687

  • Number of pages

    6

  • Pages from-to

  • Publisher name

    IEEE

  • Place of publication

    Piscataway

  • Event location

    Cluj-Napoca

  • Event date

    Jun 18, 2025

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article