Special issue on Responsible Data Science Issues, Innovations and Interplays

摘要

The rapid development of computer science and information technology in the last couple of decades has generated massive amount of data and fundamentally changed every field in science and engineering. Many disciplines are now rich in data and tend to adopt data science or data-intensive engineering methodologies to do research and development. Scientific approach to process data involving the engineering aspects as well, would lead to major strides in the domains of data, information and knowledge which contribute to the evolving knowledge society. Artificial Intelligence is quickly transforming every perspective of our society, from managing a business, socializing and even playing. AI has magnified our productivity and influenced our preferences. AI systems have now become very pervasive and an integral part of human life. They make decisions every minute, invisible to the users and, interestingly, incomprehensible even to the creators. The opaqueness of these systems is becoming a significant cause of worry, and solutions require an interdisciplinary approach. Data and assumptions made during algorithm design play an essential role in building AI models. This tries to integrate research across diverse topics related to data science, such as fairness, trust, ethics, confidentiality, transparency, and accuracy.