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An introduction to data : everything you need to know about AI, big data and data science
Corea F., Springer International Publishing, New York, NY, 2019. 131 pp. Type: Book (978-3-030044-67-1)
Date Reviewed: Feb 5 2020

Are you an early practitioner, researcher, business/experience executive, or entrepreneur who uses artificial intelligence (AI), big data, and data sciences in financial services, private investment, or related sectors? This book will help you develop a broader perspective, discover pioneers, and formulate your challenge clearly. It is a recommended reference for beginning research and in-depth study.

Data science and AI are a rapidly expanding body of knowledge. The common theme of the included essays is about helping readers comprehend the possibilities for innovation presented by these emerging technologies. Across the chapters, readers will find pointers to the startup ecosystems and pioneering work of several organizations.

Readers will find a wealth of introductory information concisely presented, along with insights from systematic research and practical experience. Each chapter is focused on one topic, providing a state-of-the-art survey, developing a taxonomy in some cases, presenting the author’s perspective, and concluding with a list of reference materials. The author looks at, and draws patterns from, the biopharma sector to develop his arguments on innovation practices.

The initial chapters provide commentary on big data management, AI, and associated business models. These chapters are useful for those who have a foundation in the subject, but want to apply their knowledge in enterprise contexts. Speech recognition is covered in one chapter. The second half of this short book is dedicated to surveying the application of AI in the insurance, financial services, and private investment management sectors.

The chapters dedicated to the ethical and intellectual property aspects of AI pose unique challenges due to the very nature of the subject matter. The discussion of patenting has less to do with AI itself, but brings up several interesting debates on the topic. The interplay between AI and blockchain can open our minds to interesting research issues about the two extreme ends of the technology spectrum. The chapter on AI accelerators and incubators covers useful information for AI entrepreneurs to choose the right kind of partners.

The highlight of this book is the chapter on AI and venture capital (VC). VC investment decisions are most often intuitive and therefore suffer from a variety of biases. Considering the degree of uncertainty that businesses embed, the author postulates the use of AI in predicting the likelihood of a successful exit. The chapter presents a literature survey for key VC investment considerations: “personal and team characteristics, financial considerations, business features,” and other “signals to predict probability of startup success.” It also includes a list of VC firms that use AI in their private investment process. This chapter opens readers’ minds to the democratization of investment skills using AI platforms.

The book is also a guide to appropriate profile aspects for data scientists, leadership team members, and their personality classifications. It includes a maturity test for organizations to discover their current state and readiness for leveraging data.

Several useful tables (on AI accelerators and incubators, for example) and figures in the book are impossible to read due to the use of small fonts or compressed inclusion. This is not meant to be a textbook for a structured course or a technical reference. Being a set of independent essays, the book is low on cohesion. It is not meant for technologists looking for advanced treatment of AI, big data, and data science. The title of the book may be misleading to many readers.

As a researcher practitioner’s perspective on AI-led innovations in related sectors, this is an invaluable survey of many pointers that the reader can pursue further. It is to the author’s credit that he has managed to cover a vast subject matter in less than 200 pages, densely packed with data, insights, and opinions for readers seeking to formulate a challenge.

Reviewer:  Sundara Nagarajan Review #: CR146876 (2007-0150)
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