Data Science in Context: Foundations, Challenges, Opportunities

Data science is the foundation of our modern world, providing new tools, forms of entertainment, economic growth, and potential solutions to complex problems. This book explores the excitement and promise of data science and examines the major challenges in gaining its benefits and mitigating its harms. It offers frameworks for critically evaluating the ingredients and ethical considerations needed to apply data science productively, illustrated by extensive application examples.

Format: Hardback
Length: 335 pages
Publication date: 20 October 2022
Publisher: Cambridge University Press

The cornerstone of our contemporary world is data science, which underpins a wide range of applications that are utilized by billions of people on a daily basis. It offers innovative tools, forms of entertainment, economic growth, and potential solutions to complex and challenging problems. These opportunities come with significant societal implications, raising fundamental questions about data quality, fairness, privacy, and causation.

In this comprehensive book, four renowned experts delve into the excitement and potential of data science while also examining the major challenges in maximizing its benefits and mitigating its harms. They provide frameworks for critically evaluating the ingredients and ethical considerations necessary for applying data science productively, illustrated by extensive application examples. The authors' extensive exploration of these complex issues will inspire data science practitioners, students, humanists, social scientists, scientists, and policy makers to study and debate how data science can be used more effectively and ethically to improve our world.

Data science is a multidisciplinary field that combines mathematics, statistics, computer science, artificial intelligence, and other related disciplines to analyze and extract insights from large datasets. It has the potential to revolutionize various industries, such as healthcare, finance, transportation, and marketing, by providing personalized recommendations, optimizing processes, and making informed decisions.

However, with the increasing reliance on data science, there are also concerns about its ethical implications. For example, the use of data for targeted advertising or surveillance can raise questions about privacy and consent. Additionally, the potential for data bias or discrimination can lead to unfair outcomes and perpetuate social inequalities.

To address these challenges, it is important to develop ethical guidelines and principles for the use of data science. This includes ensuring that data is collected and used in a transparent and responsible manner, with respect for individuals' privacy and rights. It also involves addressing issues of bias and discrimination in data analysis and developing methods to mitigate their effects.

In addition to ethical considerations, there are also technical challenges that need to be addressed in data science. For example, managing large datasets and ensuring their accuracy and reliability can be challenging, especially when dealing with sensitive or confidential information. Additionally, there is a need for more interdisciplinary collaboration and training in data science to ensure that practitioners have the necessary skills and knowledge to work with complex datasets and apply data science effectively.

Despite these challenges, data science has the potential to bring about significant positive changes in our world. By leveraging the power of data and applying it in a responsible and ethical manner, we can improve healthcare outcomes, reduce poverty, promote sustainable development, and address social and environmental challenges.

In conclusion, data science is a powerful tool that has the potential to transform our world for the better. However, its ethical implications and technical challenges need to be carefully considered and addressed. By working together to develop ethical guidelines and principles, and by investing in interdisciplinary collaboration and training, we can maximize the benefits of data science and mitigate its harms.

Weight: 720g
Dimension: 176 x 252 x 24 (mm)
ISBN-13: 9781009272209