This interdisciplinary programme will equip the students with the technical and ethical expertise to drive innovative technological solutions to sustainability challenges using traditional as well as modern AI tools. It will prepare the students for impactful roles in industry, governments, and international organisations. Students will gain hands-on experience and a global perspective of the field that will enable them to address real-world challenges in sustainability, inequality, and governance. The program provides an excellent opportunity for the students interested in pursuing careers as senior executives, policy makers, urban planners, architects, civil and transport engineers, builders and real estate professionals, forecasters, environmental and sustainability managers, social scientists, and data scientists at sustainability-based startups and even corporate ESG groups.

In addition, the master’s projects will boost the research program of KSS.

Program: M. Tech

Subject: Artificial Intelligence for Sustainability

Eligibility Criteria: B. Tech in Civil Engineering, Mechanical Engineering, Chemical Engineering, Environmental Engineering, Sustainable Energy Engineering, Electrical & Electronics Engineering, Computer Science & Engineering, Data Science, MSc. (Physics, Maths & Stats, Atmospheric Sci., Climate Science), Economic Sciences.

Departments from which students may take courses for credits: Sustainable Energy Engineering,

Civil Engineering, Mechanical Engineering, Chemical Engineering, Environmental Engineering,

Electrical & Electronics Engineering, Earth Science, Computer Science & Engineering, Physics, Maths & Stats, Atmospheric Sci., Climate Science, Economic Sciences

Program Structure

1. Tech in Artificial Intelligence for Sustainability

Minimum Credits Required for Graduation: Course Credits – 72 and Thesis Credits – 72

List of Suggested Electives

Note: Existing course details can be found in the IITK website

CORE COURSES

1. Sustainability of AI (KSS 6XX)

   Course Title: Sustainability of AI

   Course No: KSS 6XX

   About the course: The Sustainability of AI theme can encompass a broad range of topics and concerns related to the environmental, social, ethical and economic impacts of Artificial Intelligence (AI).

   Participating Departments for floating the course: KSS, ChE

   Possible Proposers: Ashutosh Sharma (ChE)

   Who can take the course: Ph. D, M. Tech. ,M.Sc. students

   Units: 3-0-0-0-9 [9 credits]

   Prerequisite: None

   Course Contents:

   Some key areas of focus include:

   Environmental Sustainability

   1. Energy consumption: AI systems' significant energy consumption and contributions to greenhouse gas emissions.
   2. E-waste generation: Electronic waste generated by AI-related hardware and infrastructure.
   3. Resource depletion: Potential depletion of rare earth minerals and other resources required for AI development.

   Social Sustainability

   1. Bias and fairness: Ensuring AI systems are fair, unbiased, and respectful of diversity.
   2. Job displacement: Mitigating the impact of AI-driven automation on employment and job markets.
   3. Social manipulation: Preventing AI-powered social manipulation and disinformation.
   4. Privacy and security of data.

   Economic Sustainability

   1. Value creation: Ensuring AI-driven value creation benefits all stakeholders, including workers and local communities.
   2. Wealth concentration: Preventing AI-driven wealth concentration and promoting equitable economic growth.
   3. Regulatory frameworks: Developing regulatory frameworks to promote sustainable AI development and deployment.

   Governance and Accountability

   1. Transparency and explainability: Ensuring AI systems are transparent, explainable, and accountable.
   2. Regulatory oversight: Establishing regulatory oversight mechanisms to ensure AI development and deployment align with sustainability principles.
   3. Public engagement and participation: Fostering public engagement and participation in AI decision-making processes.

   Human-Centered AI

   1. Human-AI collaboration: Designing AI systems that augment human capabilities and promote human-AI collaboration.
   2. Human values and ethics: Ensuring AI systems align with human values and ethics.7
   3. Inclusive design: Developing AI systems that are accessible, usable, and inclusive for diverse populations.

   Research and Development

   1. Sustainable AI research: Encouraging research on sustainable AI development, deployment, and impact assessment.
   2. Artificial Intelligence for sustainability: Exploring AI applications that support sustainability, such as climate change mitigation and environmental monitoring.
   3. AI literacy and education: Promoting AI literacy and education to ensure stakeholders understand AI's potential and limitations.
      In addition, Assessing and Quantifying Sustainability though various accounting and audits and strategies for course corrections.
2. Math & Computation using Python (KSS 6XX)

   Course Title: Math & Computation using Python

   Course No: A 600-level number requested

   About the course: Many scientists and engineers are using computers to solve their research problem.

   In the present course we will cover how to program, and how to solve scientific and engineering problems using computers. Emphasis will be on practical algorithms described in the course contents.

   The instructor(s) may use one of the programming languages: Python, C, C++, Fortran, Matlab, or any other suitable language.

   Participating Departments for floating the course: KSS, CE

   Possible Proposers: Mahendra Verma (PHY), S. N. Tripathi (Math)