Artificial Intelligence, Governance and Public Policy

Start Date: Apr 24, 2023 End Date: Apr 28, 2023
Last Date for Application: April 10, 2023 Last Date for Early Bird: April 3, 2023
Programme Fee: 126000 INR

Plus, GST

Early Bird Fee: 117180 INR

Plus, GST

Governments worldwide are ramping up investment in AI and figuring out ways to apply and encourage its applications. In 2020, the Indian government increased the outlay for Digital India to $477 million to boost AI, IoT, big data, cybersecurity, machine learning, and robotics. India’s flagship digital initiative aims to make the internet more accessible, promoting e-governance, e-banking, e-education, and e-health. 

It has become imperative for the government to embrace AI in order to remain competitive, generate new economic growth, drive social progress and improve the health of our environment. Globally, various countries are leveraging data and associated IPs as a strategic asset and for global dominance.  

According to a report by AIMResearch titled “How The Indian Government Is Championing The AI Revolution”, the use cases of AI in the Indian government include facial recognition and hotspot analysis, biometric identification, criminal investigation, traffic and crowd management, wearables to empower women safety, optimizing revenues in the forest, cleaning river, tiger protection, digital agriculture, student progress monitoring and more. 

For more information or any questions, contact Krishna Dhamecha:, +91 70690 29947

The program is structured to take participants through the key frameworks of AI and ML and apply them to real-life policy problems spanning different policy domains. The program will closely focus on the following aspects:

  • Understanding the policy process and how AI/ML can be incorporated into it
  • Understanding the machine learning and AI framework and applying the principles to policymaking
  • Understanding use cases of AI aimed at bringing about behavioral change and improving citizens' life
  • Understanding frameworks that will enable assessment of risks, biases, and uncertainties associated with AI implementation in the policy environment and how policies can be designed to be future-oriented   

Module 1: Understanding AI and ML 

  1. Understanding the various conceptions of AI, machine learning, and deep learning

Module 2: Use cases leveraging AI and Public Policy 

  1. Understanding use cases
  2. AI and Public Policy
  3. AI adoption in the public policy context.

Module 3: Public Private Partnership 

  1. Learning from commercial use cases of AI implementation
  2. Monetizing government data

Module 4: AI-based Public Policy Delivery, Risks, and Social Responsibilities 

  1. Ethical AI
  2. Algorithmic Biases
  3. AI for societal good

Module 5: AI and Regulations 

  1. Privacy-preserving AI and ML algorithms
  2. Algorithmic collusion
  3. Laws and AI

The course will use case studies, in-class exercises, group activities, guest sessions, and field visits to deliver the content. The programme will provide a unique opportunity for the participants to apply their learnings from the course during the “policy design sprint” where groups of participants will design policy solutions to address real-life problems. 

The programme welcomes participants from central and state governments, the public sector, the private sector, and the non-profit sector. The programme is structured to be relevant to participants across policy domains. It would help participants from non-government and non-public sector backgrounds to have a certain level of exposure to or interface with policymaking to grasp and apply the learnings.

  • Middle-to-senior government officials
  • Municipal corporations
  • Public sector organisations
  • Private sector organisations including participants from consulting firms, healthcare, financial services, technology and so on
  • Non-profit organisations
  • International organisations  


Faculty Chair

Anuj Kapoor

Namrata Chindarkar

Programme Faculty