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Model Bias in AI

We often trust intelligent systems blindly, because of the faith that we've put in their rationality, impartial objectivity and technical reliability.

However, the reality cannot be further from the truth. Not only that there are very few genuinely unbiased systems, but also the multiple sources for that bias that we should consider. According to a recent TechCrunch article: “These sources include the data we use to train systems, our interactions with them in the “wild,” emergent bias, similarity bias and the bias of conflicting goals”.

You're invited to City.AI's third event in Singapore, where the importance, implications and handling strategies for Model Bias in AI will be discussed. A panel of esteemed speakers will share their thoughts and experiences from a practical perspective and answer any questions that you may have. The floor will then be open to sharing opinions from the crowd, wrapping up the evening with an open networking session.


Speakers include: 

Wan Ting Poh - Manager Data Science at Allianz APAC

Zane Lim - Senior Data Scientist at Go-Jek

Simon See - Director and Chief Solution Architect, Nvidia AI Technology Centre

Jan Daniel Semrau - MIT Catalyst and Founder/CEO at Tenqyu

Jason T. Wajaja - Associate Director Global Data Science Competency at MSD



Victor Alexiev - City.AI Lead for Singapore, Founder & Chairman of 



Event Plan:

  • 1700 - 17:30 - Registration
  • 17:30 - 19:00 - Speaker Presentations
  • 19:00 - 20:00 - Open Networking