Ethical AI Design: Principles and Implementation
Learn to incorporate ethical considerations into AI system development and implementation, focusing on responsible design practices.
Learn to incorporate ethical considerations into AI system development and implementation, focusing on responsible design practices.
Dive into the critical intersection of ethics and artificial intelligence with this comprehensive course from DelftX. Explore how to design and implement AI systems responsibly, addressing key ethical challenges such as discrimination, loss of human control, and lack of explainability. Using the Delft Design for Values methodology, you'll learn to identify ethical values and translate them into concrete design requirements. The course covers crucial topics including bias, transparency, accountability, and trust in AI. With a focus on healthcare AI applications and other real-world scenarios, you'll gain practical skills in making AI ethics actionable across various sectors. Ideal for AI developers and managers overseeing AI projects, this course equips you with the tools to navigate the ethical landscape of AI development.
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What you'll learn
Identify and explain potential ethical issues in AI design and development
Analyze ethical challenges in various AI applications across different sectors
Apply the Delft Design for Values methodology to AI system development
Translate ethical values into concrete design requirements for AI systems
Evaluate AI systems for trustworthiness, accuracy, and explainability
Address bias and fairness issues in AI data and algorithms
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
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There are 5 modules in this course
This course offers a comprehensive exploration of ethical considerations in AI design and development. Students will learn to identify and address potential ethical issues in AI applications using the Delft Design for Values methodology. The curriculum covers key topics such as trustworthiness, accuracy, and explainability of AI systems, as well as bias in data and algorithmic fairness. Participants will explore concepts of accountability and human oversight in AI, including the notion of meaningful human control. The course also addresses value conflicts in AI design and provides practical tools for translating ethical values into concrete design requirements. Throughout the course, students will apply their learning to real-world scenarios, with a particular focus on AI applications in healthcare. By the end of the course, participants will be equipped to implement responsible AI design practices and navigate the complex ethical landscape of AI development across various sectors.
Introduction to the Ethical challenges with AI
Module 1
Trustworthiness of AI systems, accuracy and explainability
Module 2
Bias in data and algorithmic fairness
Module 3
Accountability and human oversight
Module 4
Value conflicts: what to do when different ethical values are difficult to realise at the same time?
Module 5
Fee Structure
Instructors
1 Course
Pioneering Philosopher in AI Ethics and Mathematics
Stefan Buijsman is an Associate Professor in Philosophy at TU Delft and managing director of the TU Delft Digital Ethics Centre. A prodigy in academia, he completed his PhD in philosophy of mathematics at Stockholm University at age 20, after studying computer science and philosophy at Leiden University. His research bridges philosophy, mathematics, and artificial intelligence, with a current focus on AI explainability and ethics. As co-founder of the Delft Digital Ethics Centre, he works on translating ethical values into practical design requirements for engineers and policymakers. His expertise extends beyond academia through three popular science books on mathematics and AI, with one published in over 20 countries. His interdisciplinary approach combines epistemology and philosophy of science to develop practical tools for improving AI transparency and responsible implementation. He collaborates with computer scientists to create new tools enhancing algorithm explainability while working with external stakeholders on broader ethical challenges in technology.
1 Course
Expert in Philosophy of Technology and Computer Science Ethics
Juan M. Durán serves as an Assistant Professor in Ethics of Technology at TU Delft's Faculty of Technology, Policy and Management. His academic journey began with studies in computer science and philosophy at the National University of Córdoba, Argentina, followed by work at the National Space Activities Commission. After earning his PhD from the University of Stuttgart, he established himself as a leading voice in the philosophy of science and technology. His research spans computer simulations, Big Data, scientific modeling, and the ethics of technology, with particular focus on AI algorithms and medical applications. He received the prestigious Herbert A. Simon Award in 2019 for his groundbreaking work in computing and philosophy. His publications include influential works on black box algorithms in medical AI, computational reliability, and scientific explanation in computer simulations. He has authored several books, including a comprehensive Springer monograph on computer simulations in science and engineering. His current work examines the intersection of ethics and technology, particularly focusing on algorithmic explanation and understanding in medical contexts.
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