Fairness & Explainable AI

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From the news we consume to our suggested Netflix content, algorithms are becoming increasingly influential on our day-to-day existence. But as more sectors recognise the economic potential of machines at large-scale application, the impact of technology is becoming far greater.

Today, machine learning models are frequently applied to guide decisions in areas such as assessing candidate risk in loan applications. However, we often find that increasingly complex machine learning models lack ‘explainability’ — the professionals depending on them can’t interpret them.

At this meetup, we will discuss the important intertwined themes of fairness & explainable AI.

After the talks, there will be opportunity to network and enjoy free pizza & beer!


6:30pm - 6:45pm Meet, greet & welcome

6:45pm - 7:45pm

- Prof Yair Zick, Assistant Professor at NUS School of Computing; expert in game theory, fair division, strategic collaborative behaviour, algorithmic transparency, and ethics in AI/ML

- Zech Yap Jia Qing, Founder of the Emerging Technologies Policy Forum and researcher at NUS Faculty of Law; author of recent Strait Times article "How to train AI to be fair to humans"

- More TBC - please get in touch if you are/know an expert in this area interested to speak!

7:45pm - Networking


This event is sponsored by QuantumBlack

QuantumBlack is an advanced analytics firm operating at the intersection of strategy, technology and design to improve performance outcomes for organisations.


By participating in the meetup you agree that McKinsey & Company may (i) videotape, audiotape, photograph, or otherwise record your name, voice, or image, and (ii) use and distribute such videotapes, audiotapes, photographs or recordings of your name, voice or image in any texts, videos, and other materials that McKinsey may make available through websites and social media to its employees or any third parties.

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