Responsible AI Leadership
This course explores the ethical, normative, and societal implications of AI and mechanisms to ensure that AI systems remain accountable and advance the social good.
This course has been developed in collaboration with:
What you will learn
- Reflect on the ethical implications of data, AI and algorithms as either tools or agents in modern work and living environments.
- How to manage data, AI and algorithm responsibly in the context of business analytics, especially in light of key legislations such as the GDPR and the EU AI Act.
This course aims to equip you with the necessary knowledge and skills to ensure the ethical, responsible and lawful use of AI. You will be introduced to the global regulatory landscape and ongoing efforts to make AI more accountable and promote its sustainable implementations.
Combining theoretical foundations from data ethics, law and governance with practical insights, the course will enable you to successfully navigate evolving accountability and regulatory demands surrounding the use of AI and related technologies.
After the course, you will be able to identify and assess the ethical impacts of a given course of action in data-driven organisations, identify main concerns associated with AI, and identify and assess compliance with GDPR.
"The course has given me a deeper understanding of the regulations and ethical implications of using artificial intelligence. It is crucial for recognizing the opportunities that lie ahead. I would recommend the course to those working with AI who wish to apply the technology in a responsible way."
Admission requirements
- You are at least 25 years old
- Have completed a bachelors degree
- 4 years of full time work experience (3 years if you already have a masters degree)
Students without a completed bachelors degree can, in some cases, be admitted based on prior learning and work experience.
Read more about the admission requirements at master’s level.
Take a course or build a degree
This course can be integrated in an Executive Master of Management.
The course awards 15 credits, a masters degree consists of 90 credits. Should you choose to take more masters level courses later, you can accumulate a complete masters degree. The combination of courses is up to you, based on your learning goals and career plans.
Modules and course content
This course consists of two physical modules of two days over a semester. All modules takes place on campus in Nydalen, Oslo.
The syllabus is made available as soon as you have been admitted to the course.
Exams consists of a project assignment that counts for 60% of the total grade and an individual 72-hour home exam that counts for 40%. The project assignment can be written individually or in groups of up to three people.
Modules
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- The Nature of Intelligence
- The History and Core Concepts of Artificial Intelligence
- Recent Developments and Impact of Artificial Intelligence
- The AI Life Cycle
- The Nature and Pitfalls of Data
- Navigating the Realities and Tradeoffs in Data Science
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Practices of Responsible AI Leadership
- Al Accountability, Transparency and Explainability
- AI Risk Management
- AI and Global Perspectives
- AI and Public Service Perspectives
- Governance frameworks for AI Implementations
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- Risks and Benefits of Regulation
- Regulations governing AI
- Regulation through AI
- Upcoming regulatory developments
- Participation in Regulation - AI Sandboxes
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AI for Good
- Open-Sourcing and Communities of Practice
- AI Impact Assessment
- Co-Design and Stakeholder Engagement with and around AI
- Tackling Grand Challenges with AI
Faculty
Christian Fieseler is professor at the Department of Communication and Culture at BI Norwegian Business School. Christian’s research interests center on organizational identity, corporate social responsibility and computer-mediated-communication.
Samson Yoseph Esayas is associate Professor at the Department of Law and Governance at BI Norwegian Business School. Samson’s research explores the power dynamics stemming from control over data and mediated communications, with focus on how these evolving power paradigms are addressed by competition and data privacy law.
Time and effort required
All our courses are structured to fit alongside a job and a personal life. Still - you'll need to dedicate some time.
You'll spend a total of four workdays on modules, plus three days for the home exam.
Additionally, you'll need to make time for reading the course material and writing the term paper. How much time this takes varies widely from student to student, and you can adjust this to fit your other commitments.
Tuition
This course is eligible for support from the Norwegian State Educational Loan Fund. Tuition fees are charged in two installments. The first invoice is usually issued on 1 October, and the second invoice on 1 December.
Want to know more?
We regularly host informational webinars that you can join. You can also schedule a personal guidance session with one of our counsellors.
Similar courses
Not quite the course you were looking for? We offer a range of courses in the same subject area - from short courses to part-time master's level studies.