Summer School on Fairness, Accountability, and Transparency in Artificial Intelligence Hosted by IIT Kharagpur

Sponsored by IBM Research India

Course Cancelled

Course coordinators:

Academic: Manjira Sinha [email protected] and Niloy Ganguly [email protected]
Local (from host institute): Manjira Sinha

Description of school:
In present times, a variety of social sectors and services rely on algorithmic models to perform with optimal efficiency and to ensure maximum good. In a sense, artificial intelligence (AI) based systems have become more cross-disciplinary ; a socio-technical and legal entity. However, algorithms are imperfect and they carry the similar biases and constraints prevalent in tour society and culture. Hence it is important to investigate and comprehend the limitations of the machine learning models and make them more fair, transparent and accountable – in a word, more ethical. This school attempts to address some fundamental and pressing topics in the domains of fairness, accountability and transparency in AI.

List of subtopics:

Introduction and motivation (with case studies)
--Relevance in academic research and industry applications
Algorithmic bias and discrimination
Fairness aware data mining
Rethinking fairness as social choice
Problems with predictive policing
Abuse, hate speech and counterspeech detection
Fake news detection, mis/disinformation online
Media bias
Gender bias in machine learning models, AI applications
Ethics and policy in shaping the course of AI research
Accountability in machine learning and neural network models
Explainability in AI systems
Possibility of end-to-end framework
--How to ensure FAT is preserved in large-scale AI systems deployed in real world, with environmental uncertainties
Hands-on sessions

List of speakers:

Niloy Ganguly, CSE, IIT Kharagpur
Animesh Mukherjee, CSE, IIT Kharagpur
Pawan Goyel, IIT Kharagpur
Saptarshi Ghosh, IIT Kharagpur
Sourangshu Bhattacharya, IIT Kharagpur
Joydeep Chandra, IIT Patna
Abir De, IIT Bombay
Mayank Singh, IIT Gandhinagar
Pranay Lohia, IBM Research India
Vijay Arya, IBM Research India

Background/prior courses recommended:

This school strongly encourages women students to apply and will give special consideration to women applicants during selection process.
Course will be open to UG students from CS/IT stream who are expected to complete their sixth semester by June 2020.
Basic knowledge about algorithms, machine learning and artificial intelligence is required.

Click here to apply for ACM India Summer School 2020