Abstract: 

We hear a variation of this statistic often, ~85% of machine-learning projects fail. This is disheartening to both practitioners and business leaders looking to build high-impact solutions.

The skills involved in bringing AI-powered solutions to life have expanded from data professionals to now include product managers, UX designers, ethicists, and a multitude of domain specialists. As with any multidisciplinary field, the greater the variety of professionals involved, the greater the chance for misunderstandings across domains. It's this growing gap in AI literacy that contributes to the high failure rate.


In this talk, I will share how to leverage design thinking to instill AI literacy and de-risk the development of AI powered solutions. I will cover real-world examples of

· Communication gaps that lead to failure and how to address them

· How to define AI requirements in terms of human-value and trust

· How to manage the fuzzy shift from experimentation to production

· How to build resilience and improve adoption post launch

Bio: 

Cal Al-Dhubaib is a data scientist, entrepreneur, and professional speaker on Artificial Intelligence. He founded Pandata to help organizations plan, design, and scale human-centered AI solutions. Pandata has overseen 80+ transformative projects with leading global brands including Parker Hannifin, the Cleveland Museum of Art, FirstEnergy, and Penn State University.

Cal is especially passionate about orchestrating inclusive teams that are empowered to build Trusted AI solutions. He has been recognized as a Notable Immigrant Entrepreneur, Crain's Cleveland 20 in their 20s, and two-time Cleveland Smart 50 recipient. In addition to becoming the first data science graduate from Case Western Reserve University, Cal is also known for his role in advocating for careers and educational pathways in Data Science through workforce development initiatives.