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Anwesha Sen

@anwesha25

Karan Manral

@kmanral Editor

AI and Risk Mitigation Strategies in Key Indian Sectors

Submitted Jun 7, 2024

Abstract:

As AI continues to revolutionize various sectors, it brings both unprecedented opportunities and significant risks. In India, sectors such as Agritech, Fintech, Edtech, public services, and Healthtech are rapidly adopting AI technologies. However, the lack of robust risk mitigation strategies can lead to unintended consequences, including data breaches, algorithmic biases, and systemic vulnerabilities.

Over the past year, we have spoken to practitioners and researchers and collated research on the unique risks in each sector and spicific mitigation strategies. This talk outlines these risks and mitigation strategies as well as best practices for regulatory compliance.

Outline:

The session will be in an open discussion with 4-5 panelists. The structure will broadly cover the following:

  • Introduction: Overview of AI adoption in Agritech, Fintech, Edtech, public services, and Healthtech in India.
  • Risks in AI Deployment: Identification of key risks associated with AI in each sector.
  • Mitigation Strategies: Presentation of effective risk mitigation strategies specific to each sector, with an emphasis on practical implementation.
  • Policy and Compliance: Discussion on the role of policymakers and compliance teams in implementing these strategies.
  • Best Practices: Sharing best practices and guidelines for developers, researchers, and startup founders to mitigate AI risks.

Key participants:

Developers, researchers, policymakers and analysts, startup founders, risk and compliance teams.

Impact:

  • Gain a comprehensive understanding of the risks associated with AI deployment in critical sectors in India.
  • Learn actionable risk mitigation strategies that can be implemented in real-world scenarios.
  • Obtain insights into the policy landscape and how to navigate compliance requirements effectively.
  • Equip participants with knowledge to proactively address potential risks, ensuring sustainable and ethical AI practices.

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