Although the title sounds like an oxymoron, this short book is entirely in earnest and full of insight into how science is carried out and how scientists think and do their work. If anyone has taken one or more courses in philosophy as a student, the study of this discipline is characterized by a top-down logical protocol of definitions and proofs. Even in the philosophy of science, this approach is frequently followed even though scientific discoveries and theories are part of the foundation of the discipline. For example, in the popular and semi-popular literature on philosophy of science with which most readers are acquainted, there are a handful of prominent scientific topics upon which discussion is based--quantum theory and relativity in physics and evolution and the genetic code in biology. The addition of the history of science and the growth of scientific understanding is often part of the context of the contemporary presentation of the philosophy of science. In fact, history has become sufficiently important that the study of the history of science and the philosophy of science have become a consolidated discipline--the history and philosophy of science (HPS).

This book takes a more expansive approach. Science is what scientists do and is based on their understanding of what science is and how they are to perform their investigations. In this manner, the discussion of the philosophy of science employs the tools and methods of the sciences being studied. This approach is much more inductive and overlaps extensively with the objectives and methods of science education by which students become acculturated into the scientific disciplines they are studying. The “empirical” part of the title of the book applies to the approach used in the study of scientists and their work. Philosophers apply techniques borrowed from sociology and anthropology when they work with scientists in debriefing them as they work through a scientific investigation. These techniques are usually qualitative and involve analysis of transcripts of interviews, discussions, and textual material produced in published papers, research reports, and notes. The premise is that the philosophy of science held by scientists is expressed in what they investigate, how they conduct their investigations, and how they understand their results even if they are not wearing their personal philosophies of science on their lab coats while they work. What they do is based on what they think.

There are only nine chapters in this book. After an introductory chapter by the editors in which they explain the premise of the book, the remaining eight chapters are organized into three parts. The first part is on foundations of an empirical philosophy of science. In this part, the qualitative socio-anthropological methods are described and demonstrated in application to two case studies in infectious disease modeling and in planetary science.

The second part has four papers in which additional case studies are presented. The case studies include financial modeling, reductionism in biology, the nature/nurture debate in biology and psychology, the study of explanations of scientific phenomena and principles in scientific textbooks, and the problem of objectivity in scientific investigations in biomedical research.

The third part of the book has two papers relating the empirical philosophy of science to HPS. The first paper’s thesis is that the two areas are intertwined already since historical studies employ many of the same methods in the study of contemporary problems. The second paper concludes the book with a study of an old scientific disagreement in biochemistry to show how the investigation of anomalies can reveal underlying philosophical issues.

The breadth of case studies selected and the clarity with which they are rendered are the principal strengths of this book. As computational scientists, we do not merely write code. We write code to solve problems in application areas that have scientific bases, often in collaboration with scientists and engineers who have a deeper understanding of the scientific issues underlying the problems. Even in financial and economic modeling, there are principles and theories that need to be sufficiently well understood. Those of us who teach will recognize the challenges faced by students. They not only need to grasp the principles upon which the problem is based; they also have to understand the computational methods they need to use to solve them. The task of the teacher is to lead them through so that they can overcome both barriers.

There are a several typographical errors that eluded editing, but they do not compromise the integrity of the book. This is a book worth reading and reflecting upon.