In this webinar, we will go through the ethical ramifications of the algorithmic decision-making, while talking about some methods to ensure fairness in AI algorithms. We will open a discussion on various aspects, ranging from the effects of proliferation of algorithmic decision-making, autonomous systems, explainability in machine learning, the question of balance between regulation and innovation, the adversarial role of AI in information dissemination, and the questions of individual rights, fairness, and discrimination.

Animesh Mukherjee is a full professor in the Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur. He is also a Distinguished Member of ACM. His main research interests centre around content governance, which includes (i) content moderation (harmful content analysis, detection, and mitigation), (ii) content dissemination (fairness issues in e-commerce platforms and interfaced systems like facial recognition, automatic speech recognition systems etc.), and (iii) content maintenance (quality analysis and improvement of encyclopedias like Wikipedia and large software systems like Ubuntu releases). He regularly publishes in all top CS conferences including AAAI, IJCAI, ACL, NAACL, EMNLP, The Web Conference, CSCW etc. He has received many notable awards and fellowships including the Facebook ethics for AI research award, India, Google course award for the course AI and Ethics, IBM faculty award, Humboldt Fellowship for Experienced Researchers, Simons Associateship, ICTP to name a few.

About this ebook

AI and Ethics. A computational perspective. Developed from a graduate course this book examines some of the deep issues that have become very relevant due to the increasing use of AI in recent times.