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. The book discusses 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. Taking a computational approach, rather than one dominated by philosophical or legal discussions, this book is geared toward increasing awareness of the immediate moral and legal repercussions of the presence and possibly dominance of AI in our society.
Key Features:
- An investigation of the ethical ramifications of algorithmic decision making
- Methods to ensure fairness in AI algorithms
- Explainability/accountability of the AI algorithms
- Governance of platform companies
- Includes case studies to help the reader understand the importance of each of the topics covered.
表中的内容
Preface
Acknowledgements
Author biography
1 Preamble
2 Discrimination, bias, and fairness
3 Algorithmic decision making
4 Content governance
5 Interpretable versus explainable models
6 Newly emerging paradigms
关于作者
Presently, 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 encyclopaedias 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.
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