A Community Event from MKAI
Featuring speakers from Google and IBM, this MKAI Inclusive Forum discusses the big themes around trust of and in AI. The January event focusses on the issue of fairness; touching on data, biases, algorithms, society and inclusivity. As always the MKAI Forums are open to everyone from all walks of life. Our expert speakers make the subject approachable and comprehensible to help all of us improve our AI-fluency and understanding of the domain.
Speaker 1: Jon Thor Sigurleifsson, Corporate Punk & Creative Nerd
Presentation: In Tech We Trust
Jon Thor Sigurleifsson explores how technology interacts with moral and ethical philosophy. Jon Thor is a broadcaster and educator who cares about helping people to explore better questions and search deeper into information.
Speaker 2: Lavina Ramkissoon, African trend influencer & AI strategist
Presentation: Shaping society 5.0 and its leaders
Lavina Ramkissoon is a future technology lover, yoga practitioner, an implementor, trend influencer, strategist, LinkedIn connector, a keynote speaker, mom, partial artist, dancer come writer, technologist and an ai ethics mentor, who speaks worldwide about her love for humanity, technology, economics and businesses.
Speaker 3: Dr. Eva-Marie Muller-Stuler, Chief Data Scientist, Advanced Analytics & AI Practice leader, GBS at IBM
Presentation: Fighting Bias and building trust in AI
Dr. Eva-Marie Muller-Stuler is the Chief Data Scientist and leader of the Centre of Excellence for IBM MEA. She has led ground-breaking Data Science teams and implementations of fully deployed large-scale AI projects globally for over 15 years. Eva-Marie os passionate about advising IBM’s top-tier clients and governments in developing data strategies that show P&L value and to transform them into data-driven organizations that lead the field.
Speaker 4: Tulsee Doshi, Google Product Lead – ML Fairness and Responsible AI
Presentation: ML Fairness in Product: Lessons Learned
Tulsee Doshi is product lead for Google’s efforts in ML Fairness and Responsible AI, driving a deeper understanding of how we can build user experiences that are diverse, inclusive, and ethical.