Columbia University's Amit Arora on AI Risks

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Introduction:

Chuck Martin: 
Hi, this is Chuck Martin with AI Business TV in New York City. I'm happy to be here with Amit Arora, Professor of AI and Applied Risk Analysis at Columbia University. Thank you for joining us. You just got off the keynote stage. Tell us what your talk was about. 

Amit Arora: 
It was a fun and highly relevant topic in today's world—cyber insurability in the insurance industry. It’s a topic that intersects AI, cybersecurity, and insurance. Essentially, we discussed how to quantify cyber risks for companies and how that determines their insurability for cyber insurance 

State of Cyber Risk Quantification 

Chuck Martin: 
How advanced is the current technology in this space? 

Amit Arora: 
It’s not so much a question of technology. It’s about using an ensemble of existing techniques—statistical models, machine learning, and known frameworks—combining them in a way that produces relevant and reliable outcomes. 

Teaching AI and Risk Mitigation at Columbia 

Chuck Martin: 
What are students interested in learning when it comes to AI and risk management? 

Amit Arora: 
I teach AI and Applied Risk Analytics with a focus on risk mitigation. We cover various risk scenarios, from supply chain risk to credit market risk, using case studies and AI techniques. Students are eager to learn predictive analytics for risk quantification across industries. 

Interest in Risk Analytics Among Students 

Chuck Martin: 
How interested are students in risk management? 

Amit Arora: 
There’s a growing focus on risk awareness and containment, whether students come from engineering, healthcare, or MBA programs. Recent global events like the Russia-Ukraine conflict, the Israel-Palestine issue, and COVID-19 have made businesses more conscious of quantifying and managing risks. 

The Role of AI in Insurance 

Chuck Martin: 
You've been in the insurance industry for a long time. How has AI shaped the industry? 

Amit Arora: 
Insurance is a conservative industry focused on risk management. Different companies have different appetites for AI adoption, but AI integration often requires support from top leadership. Without that, innovation can stagnate. Additionally, the industry is heavily regulated, which slows down innovation because of concerns about auditability, bias, and customer impact. 

Challenges in AI Adoption for Insurance Companies 

Amit Arora: 
Insurance companies are cautious due to regulations and the need to ensure AI is safe for customers. Legal and compliance teams are often hesitant about adopting generative AI without considering its impact first 

Predictions for AI in 2024 

Chuck Martin: 
What do you expect to see in AI in the coming year? 

Amit Arora: 
I foresee two major trends. First, cyber risk quantification will continue to explode in relevance. Second, we’ll see a growing emphasis on AI audits—ensuring that companies using AI are compliant and free from algorithmic discrimination. Many large organizations are already working on developing frameworks for algorithmic risk management. 

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