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About this course
Trustworthy AI
Understand the importance, considerations, and impacts of trustworthy AI.
Chapter 1
Trustworthy AI in society and business
SectionExercises
I. The societal impact of AI
II. AI’s ethical implications
III. The dimensions of trustworthy AI
IV. How can (trustworthy) AI transform businesses?
V. The steps in building AI applications
Chapter 2
Fairness and accountability
SectionExercises
I. Challenges in implementing fairness in AI
II. Detecting and mitigating bias and unfairness
Chapter 3
Explainability
SectionExercises
I. The need for explainable AI
II. Types of explainable AI
III. How reliable are XAI explanations?
Chapter 4
Resilience
SectionExercises
I. Challenges in AI performance and data integrity
II. AI security and privacy attacks
III. Mitigating security risks
IV. AI laws and regulations in EU
Chapter 5
Implications
SectionExercises
I. Developing trustworthy AI in your organization
II. Interactive case: Trustworthiness of applicant screening AI
III. Looking to the future of trustworthy AI
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This course has been created with the SPATIAL project, brand name of an EU-funded project that tackles the identified gaps of data issues and black-box AI by designing and developing resilient accountable metrics, privacy-preserving methods, verification tools and system solutions that will serve as critical building blocks for trustworthy AI in ICT systems and cybersecurity.

EU

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 101021808. This communication reflects only the author’s view. It does not represent the view of the European Commission and the EC is not responsible for any use that may be made of the information it contains.