Responsible & Safe AI Systems

By Prof. Ponnurangam Kumaraguru, Prof. Balaraman Ravindran, Prof. Arun Rajkumar | IIIT Hyderabad, IIT Madras

Learners enrolled: 11880 | Exam registration: 5114

ABOUT THE COURSE:
There has been an exponential increase in the use of platforms / technologies like ChatGPT, Gemini, Llama, Sora, DALL-E, etc. in our day-to-day lives. There Language & Vision models have changed our way of living, and way we seek & create information. This course provides students with a comprehensive understanding of the ethical, social, and safety considerations essential for developing and deploying artificial intelligence (AI) systems. Uncover the intricacies of algorithmic transparency, fairness in machine (un)learning, interpretability, consistency and many more. The course encourages critical thinking and fosters a deep appreciation for the impact of AI on individuals and communities. Students who complete the course can: recognize possible harms that can be caused by modern AI capabilities; learn to reason about various perspectives on the trajectory of AI development and proliferation; learn about latest research agendas towards making AI systems safer.

INTENDED AUDIENCE: Anybody interested in the area of AI, Machine Learning, including industry professionals and students

PREREQUISITES: Any level of machine learning / AI course would help, it is not mandatory though

INDUSTRY SUPPORT: TCS, Wipro, Microsoft, Infosys, Amazon, Uber, to name a few, any company involved in AI & ML will be interested

Summary

Course Status :	Ongoing
Course Type :	Elective
Language for course content :	English
Duration :	12 weeks
Category :	Computer Science and Engineering Artificial Intelligence
Credit Points :	3
Level :	Undergraduate/Postgraduate
Start Date :	22 Jul 2024
End Date :	11 Oct 2024
Enrollment Ends :	05 Aug 2024
Exam Registration Ends :	16 Aug 2024
Exam Date :	02 Nov 2024 IST

Note: This exam date is subject to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

Course layout

Week 1 & 2:

AI Capabilities Improvement in last 5-10 years
Imminent risks from AI Models: Toxicity, bias, goal misspecification, adversarial examples etc.
Long-term risks from AI Models: Misuse, Misgeneralization, Rogue AGI
Principles of RAI - Transparency; Accountability; Safety, Robustness and Reliability;Privacy and Security; Fairness and non-discrimination; Human-Centred Values; Inclusive
and Sustainable development, Interpretability
Recap of Deep Learning Techniques, Language/Vision Models
AI Risks for Gen models
Adversarial Attacks – Vision, NLP, Superhuman Go agents

Week 3 & 4:

ML Poisoning Attacks like Trojans
Implications for current and future AI safety
Explainability
Imminent and Long-term potential for transparency techniques
Mechanistic Interpretability
Representation Engineering, model editing and probing
Critiques of Transparency for AI Safety

Week 5 & 6:

Privacy & Fairness in AI

Week 7 & 8:

Metrics and Tools for RAI - measuring bias/fairness, adversarial testing, explanations (Lime/SHAP/GradCam), audit mechanisms
Regulation landscape - DPDP act (India), GDPR (EU), EU AI act, US presidential declaration, Ethical approvals, informed consent, participatory design, future of work, Indian context
What is AGI? When could it be achieved?
Instrumental Convergence: Power Seeking, Deception etc.

Week 9 & 10:

RAI in Legal domain
RAI in Health care domain
RAI in Education domain
A few other domains
Policy issues in RAI

Week 11 & 12:

Couple of panel discussion with industry practitioners, academic, government (possibly), and others.
Fireside chat with eminent personalities
Recorded Paper reading discussion

Books and references

All necessary materials will be shared with students on slides, online materials

Instructor bio

Prof. Ponnurangam Kumaraguru

IIIT Hyderabad

Prof. Ponnurangam Kumaraguru “PK” is a Professor of Computer Science at IIIT Hyderabad, Associate Faculty Fellow at Centre for Responsible AI at IIT Madras, and Adjunct faculty at IIIT Delhi. PK chaired the ACM India Council's Publicity and Research Facilitation Committee for two years each from 2020 to 2024. He leads initiatives like PhDClinic, Anveshan Setu Fellowship, ROCS, and ARCS to improve PhD student quality. PK is a TEDx, ACM Distinguished and ACM India Eminent Speaker. PK received his Ph.D. from Carnegie Mellon University. His Ph.D. research on anti-phishing contributed in creating Wombat Security Technologies which was acquired for $225 Million.

Prof. Balaraman Ravindran

IIT Madras

Professor B. Ravindran heads the Department of Data Science and Artificial Intelligence (DSAI), the Wadhwani School of Data Science and Artificial Intelligence (WSAI) the Robert Bosch Centre for Data Science & Artificial Intelligence (RBCDSAI) and the Centre for Responsible AI (CeRAI) at IIT Madras. Along with that, he is also the Mindtree Faculty Fellow at IIT Madras. Currently, his research interests are centred on learning from and through interactions and span the areas of geometric deep learning and reinforcement learning. He received his PhD from the University of Massachusetts, Amherst and his Master’s degree from the Indian Institute of Science, Bangalore. He is a senior member of the Association for Advancement of AI (AAAI) and an ACM Distinguished Member.

Prof. Arun Rajkumar

Prof. Arun Rajkumar is currently an Assistant Professor at the Computer Science and Engineering department of IIT Madras. Prior to joining IIT Madras, he was a research scientist at the Xerox Research Center (now Conduent Labs), Bangalore for three years. He earned his Ph.D from the Indian Institute of Science where he worked on ‘Ranking from Pairwise Comparisons’.

Course certificate

The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.
The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).
Date and Time of Exams: 02 November 2024 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.
Registration url: Announcements will be made when the registration form is open for registrations.
The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.
Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.

CRITERIA TO GET A CERTIFICATE

Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Madras .It will be e-verifiable at nptel.ac.in/noc.

Only the e-certificate will be made available. Hard copies will not be dispatched.

Once again, thanks for your interest in our online courses and certification. Happy learning.

- NPTEL team