This podcast works as an introduction course to data ethics and the data ethicists role in today’s working life. It highlights the historical connection between ethics and technology, noting that ancient philosophical questions are relevant to modern data ethics. Deep tech is defined as technology with significant scientific roots and potential for societal disruption, raising ethical concerns about fairness, privacy, and autonomy. The document explores various ethical frameworks like consequentialism, deontology, and virtue ethics, and emphasizes the importance of addressing algorithmic bias and ensuring explainability in automated systems. Privacy and data protection are central themes, with concepts like data minimization and purpose limitation discussed. We also mention the role of stakeholders, the emergence of data ethicists, and the complexities of the global regulatory landscape, particularly the GDPR. Finally, it touches upon the pedagogical approach to teaching data ethics, including the use of science fiction to explore ethical implications. Key ideas include the transformative but ethically complex nature of deep tech, the relevance of ancient ethical principles, the need for multiple ethical lenses, the dangers of algorithmic bias, the importance of privacy, the role of data ethicists, and the evolving nature of global data protection regulations.
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