Artificial intelligence (AI) technology continues to advance by leaps and bounds, as it quickly becomes both a potential disruptor and an essential enabler for companies in every industry. At this stage, one of the barriers to widespread AI deployment is no longer the technology itself; rather, it comes down to a set of challenges that, ironically, are far more human: ethics, governance, and equity.

As AI expands into almost every aspect of modern life, the risks of AI misbehaving increase exponentially—to a point where those risks can become a matter of life and death. Real-world examples of AI gone awry include systems that discriminate against people based on their race, age, or gender, as well as social media systems that inadvertently spread rumors and disinformation.

Join us for this 60-minute webinar, Overcoming Terminator Thinking, Enabling a New AI Frontier, where you’ll hear Dr. Jim Webber hosting Dr. Jianshu Weng and Google scholar David Berend on these topics:

  • The past, present, and future of AI
  • How AI leverages the Graph Data Platform
  • When (and how) AI will be trustworthy

Dr. Jim Webber
Chief Scientist, Neo4j

Dr. Jim Webber is Chief Scientist at Neo4j working on next-generation solutions for massively scaling graph data. Prior to joining Neo4j,  Jim was Professional Services Director with ThoughtWorks, where he worked on large-scale computing systems in finance and telecoms. Jim has a Ph.D. in Computing Science from Newcastle University, UK.

Dr. Jianshu Weng
Senior Associate Director of AI Innovation, AI Singapore

Dr. Jianshu Weng acts as Senior Associate Director of AI Innovation at AI Singapore, where he heads the SecureAI team to build processes and tools to make machine learning more robust against potential attacks.

Jianshu has many years of research and consulting experience in both academia and industry. In recent years, he focuses on putting AI/ML into real-world use cases and promoting responsible development and application of AI/ML, e.g., explainability, fairness, robustness, and privacy-preserving AI/ML. 

Before joining AI Singapore, he headed the regional data science team of a leading global reinsurer, where he led his team to deliver a number of data science projects for its key clients in the Asia Pacific region.

David Berend
Google Scholar, Ph.D. Candidate (AI/Computer Science), National University of Singapore

David co-leads the Singapore AI standardisation committee on Secure AI, while being a researcher focusing on quality measures for AI system testing.

His research was one of the first to introduce out-of-distribution detection into AI testing, enabling highly realistic test cases to determine how risky AI systems may actually be when deployed.

The policy approach of the committee is a world-first in quantifying AI quality, providing certification that increases trust in AI, thereby expanding its adoption.

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