| Students develop the ability to critically evaluate and apply principles of fairness, explainability, privacy, sustainability, and accessibility in the design and deployment of AI systems. They are equipped to address the ethical and regulatory challenges in AI, balancing the drive for innovation with adherence to fundamental human rights, ethical standards, and European values.
|
- Assessing Ethical and Social Implications of AI (k5)
Students can critically analyze the ethical and social implications of AI technologies, identifying potential risks and conflicts with principles of fairness, privacy, and human rights.
- Designing Human-Centric AI Solutions (k6)
Students are able to conceptualize and design AI systems that are aligned with responsible AI practices, focusing on human-centric approaches and balancing innovation with ethical considerations.
- Applying Frameworks for Responsible AI (k4)
Students can apply existing frameworks and best practices for responsible AI development to real-world scenarios, ensuring AI solutions are ethical, transparent, and accountable.
- Engaging in Discussions on Regulation and Innovation Tensions (k5)
Students can discuss and evaluate the challenges and tensions between AI innovation and regulatory constraints, considering perspectives on policy-making, ethical standards, and societal impacts.
- Analyzing Practical Case Studies in Responsible AI (k4)
Students can analyze and reflect upon practical examples of responsible AI implementation, identifying both the successes and shortcomings of current approaches.
|
Students understand key concepts and principles related to responsible AI, including fairness, explainability, privacy, sustainability, and accessibility. They are familiar with the ethical frameworks, guidelines, and best practices for developing AI systems that are human-centric and compliant with societal values and regulations, especially within a European context.
|
