Specializations: Making Artificial Intelligence Real Specializations: Making Artificial Intelligence Real
Beyond the AI buzz: learn to lead, manage, and implement impactful AI projects via a truly interdisciplinary approach.
ABOUT THE SPECIALIZATION:
The Specialization follows the four I’s: Ideation, Implementation, Integration, and Iteration. After having learned about the fundamentals of AI, participants—in groups—will ideate on their own AI project. Leveraging our networks, they will receive extensive support from Creative Destructive Lab and learn from promising AI ventures as well as deep tech venture capitalists. In close collaboration with Hi!Paris, we then will turn to implementation where participants will lead data and computer scientists (a key competence) to implement hands-on tools.
The second week, in Canada, will be dedicated to Integration and Iteration—and again highlight the necessity of embracing an interdisciplinary and holistic approach to leverage AI’s potential.
There, we will extensively discuss essential topics such as technology acceptance, consumers’ and stakeholders’ reactions to AI and automation, responsible AI, AI for good, and AI regulations, among others. Generally, the focus will be on market validation of AI.
These insights are supposed to be integrated in the group work via continuous iteration.
KEY EXPERIENCES
Some themes explored:
- The big picture: developing an AI strategy
- Leading teams of data and computer scientists to shape AI projects.
- Psychology of Technology: Considering and managing stakeholders’ reactions to AI
- Responsible AI and regulations
Why should you join this specialization?
- Executives need to have a solid understanding of the possibilities (and limitations) of AI
- Executives should not leave AI do data and computer scientists, but foster and lead collaboration with a clear vision in mind.
- Executive need to have a solid understanding of the consequences of AI for their businesses (i.e., business model innovation) and beyond have to take responsibility for societal consequences.
Sample Courses
AI Fundamentals; AI & Business Model Innovation; Leading Tech Teams to Make Artificial Intelligence Real Intelligence; Creating Meaningful Human-Machine Interactions; Responsible AI and Building Trust in AI