AI
Free
Singapore (Online)
Wednesday, 27 August, 2025
5:30
–
6:30
am
EDT
An Introduction to AI Risk and Governance
About This Event
AI is being used more widely across industries, and with that comes new types of risk — like bias, lack of transparency, and potential misuse. In this one-hour session, we’ll give a clear overview of what "AI risk" means and how different parts of the world are approaching it.
We’ll look at the AI Risk types like hallucination, overreliance, and see how they are accounted for in major global frameworks, including those from NIST (USA), IMDA (Singapore), ISO, and the OECD. You’ll also hear how AI risk connects to your existing risk, audit, or compliance programs. This session is best for anyone starting to explore AI governance and looking to understand the basics.
Takeaways
Understand key types of AI risk, including bias, lack of explainability, robustness, privacy, and misuse
Get an overview of major global frameworks: NIST, IMDA, ISO 42001, etc.
Learn how AI risk connects to Enterprise Risk Management (ERM) and technology risk processes
See how AI governance relates to legal exposure, audits, and internal controls
About the Instructor
Divya Venkatraman
BE, MSc & PhD (NTU, Singapore)
Divya is a hands-on technologist with a passion for solving real-world problems with an interdisciplinary approach. Currently she switches time between providing data science/AI consulting services to organizations in APAC (mainly startups) and teaching/mentoring adult learners making a shift into the tech industry.
Divya started her career as a Software Engineer developing web-based applications for the US insurance industry while at Infosys, India. She received her masters and doctorate in Digital Signal processing (yester-year data science focussed on feature engineering) from Nanyang Technological University, Singapore. Including her graduate degree, Divya has been an ardent data science/AI practitioner for close to 15 years making the journey from a software engineer to a signal processing engineer to a researcher to an applied machine learning/ AI engineer working on multiple projects across different industry verticals such as Energy (Halliburton), eduTech (CRADLE@NTU), Risk Management (Sense Infosys), MedTech (AiHighway) and HRTech (InterviewerAI.) She specializes in processing sequence data that includes time-series signals like vibration, audio etc and natural language (both text & speech.)
Armed with industry experience, she started teaching the 3-month full time data science immersive bootcamp at General assembly, Singapore. Over the last few years she has tailored many custom curricula and taught various interdisciplinary courses spanning areas of data science, AI, software engineering, cloud architecting and AI for both consumer and enterprise clients. She also sits in the General Assembly Global Data Science Immersive product advisory group.
Currently she is an Adjunct Faculty at the SP Jain School of Global Management, Singapore and teaches the Applied Statistics for Decision Making (ASDM) for the GMBA and MGB cohorts. Her areas of interest include product analytics, natural language processing, and Explainable AI.
Vidyaraman Sankaranarayanan
Chief Product Officer, DeepDive Labs
Vidyaraman Sankaranarayanan is the Chief Product Officer at DeepDive Labs, a Singapore-based AI and data consultancy. He has led product strategy and execution across the company’s GenAI training, regulatory risk management, and compliance automation platforms.
Before DeepDive Labs, Vidyaraman spent over a decade at Microsoft in both Redmond and Singapore, where he held cross-functional roles spanning product design, compliance architecture, and security innovation. He was the Risk Architect for Office 365 in APAC, managing audits for financial services clients. He also spearheaded several product initiatives, including compliant user notifications, Office Mobile user acquisition experiments, and the Social Share plug-in for PowerPoint. Earlier, he was the PM for UX and classification efforts on Data Loss Prevention (DLP) in Outlook and Exchange, implementing features like "Policy Tips" and sensitive content detection using regex, probabilistic models, and fingerprinting. His contributions blended engineering rigor with user-centered design, especially in regulated environments.
He holds a Ph.D. in Computer Science from the University at Buffalo, where he authored a dissertation on game-theoretic approaches to security design, and an M.S. in Computer Engineering from the University of Kansas. His 15+ year career spans enterprise product development, AI-driven regulatory tooling, and risk-aware UX design.
About Our Partners
DeepDive Labs is a consultancy that designs and develops custom SaaS tools and LLM-powered workflows for use cases such as responsible AI, cloud cost engineering, and AI risk management. In addition to tooling, it offers mid-career educational programs as a core part of its services—delivering focused, interactive courses and workshops tailored to teachers, students, and working professionals. Together, these offerings support the practical adoption of emerging technologies and evolving regulatory standards.
Community Code of Conduct
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