Why Data Ethics Matters for Every Engineer
Bias in artificial intelligence systems can affect the entire engineering process, from infrastructure to interfaces, making it essential for all engineers—not just data scientists—to address these challenges. Within the Master of Science in Precision Engineering students explore Ethics of Data for a future with fairer technologies.
Bias in artificial intelligence isn’t just a concern for data scientists or machine learning engineers - depending on the application, it may impact all engineers involved in building, deploying, and maintaining systems that integrate artificial intelligence.
Even if you aren’t directly involved in model training, your work on infrastructure, interfaces, or data pipelines can influence how biases are amplified or mitigated. By understanding how discrimination can manifest in AI, you can spot potential issues early, contributing to fairer, more ethical systems.
This is one relevant topic of the field of Data Ethics. Data Ethics problems can also have serious implications for company reputation, regulatory compliance, and public trust. Engineers across all fields can help create more inclusive, responsible technology, preventing costly mistakes that can harm both users and organizations.
Ethics of Data is also part of the Master of Science in Precision Engineering as part of the Complementary Skills Scientific Ethics, Writing and Presentation. Based on examples on general ethical considerations, and on how bias can manifest in AI applications, the students are further investigating the topic in interactive discussions and case studies.
More information about this topic can also be found in a dedicated chapter in Kurpicz-Briki’s recent book, that explains artificial intelligence and large language models for a broad audience: More than a Chatbot