Gregory J. Morgan

After the Double Helix

Rosalind Franklin is best known for her informative X-ray diffraction patterns of DNA that provided vital clues for James Watson and Francis Cricks double-stranded helical model. Her scientific career did not end when she left the DNA work at Kings College, however. In 1953 Franklin moved to J. D. Bernals crystallography laboratory at Birkbeck College, where she shifted her focus to the three-dimensional structure of viruses, obtaining diffraction patterns of Tobacco mosaic virus (TMV) of unprecedented detail and clarity. During the next five years, while making significant headway on the structural determination of TMV, Franklin maintained an active correspondence with both Watson and Crick, who were also studying aspects of virus structure. Developments in TMV research during the 1950s illustrate the connections in the emerging field of molecular biology between structural studies of nucleic acids and of proteins and viruses. They also reveal how the protagonists of the “race for the double helix” continued to interact personally and professionally during the years when Watson and Cricks model for the double-helical structure of DNA was debated and confirmed.

Using Ethical Reasoning to Amplify the Reach and Resonance of Professional Codes of Conduct in Training Big Data Scientists

The use of Big Data—however the term is defined—involves a wide array of issues and stakeholders, thereby increasing numbers of complex decisions around issues including data acquisition, use, and sharing. Big Data is becoming a significant component of practice in an ever-increasing range of disciplines; however, since it is not a coherent “discipline” itself, specific codes of conduct for Big Data users and researchers do not exist. While many institutions have created, or will create, training opportunities (e.g., degree programs, workshops) to prepare people to work in and around Big Data, insufficient time, space, and thought have been dedicated to training these people to engage with the ethical, legal, and social issues in this new domain. Since Big Data practitioners come from, and work in, diverse contexts, neither a relevant professional code of conduct nor specific formal ethics training are likely to be readily available. This normative paper describes an approach to conceptualizing ethical reasoning and integrating it into training for Big Data use and research. Our approach is based on a published framework that emphasizes ethical reasoning rather than topical knowledge. We describe the formation of professional community norms from two key disciplines that contribute to the emergent field of Big Data: computer science and statistics. Historical analogies from these professions suggest strategies for introducing trainees and orienting practitioners both to ethical reasoning and to a code of professional conduct itself. We include two semester course syllabi to strengthen our thesis that codes of conduct (including and beyond those we describe) can be harnessed to support the development of ethical reasoning in, and a sense of professional identity among, Big Data practitioners.

Embedding Privacy and Ethical Values in Big Data Technology

The phenomenon now commonly referred to as “Big Data” holds great promise and opportunity as a potential source of solutions to many societal ills ranging from cancer to terrorism; but it might also end up as “…a troubling manifestation of Big Brother, enabling invasions of privacy, decreased civil freedoms (and) increased state and corporate control” (Boyd & Crawford, 2012, p. 664). Discussions about the use of Big Data are widespread as “(d)iverse groups argue about the potential benefits and costs of analyzing genetic sequences, social media interactions, health records, phone logs, government records, and other digital traces left by people” (Boyd & Crawford, 2012, p. 662). This chapter attempts to establish guidelines for the discussion and analysis of ethical issues related to Big Data in research, particularly with respect to privacy. In doing so, it adds new dimensions to the agenda setting goal of this volume. It is intended to help researchers in all fields, as well as policy-makers, to articulate their concerns in an organized way, and to specify relevant issues for discussion, policy-making and action with respect to the ethics of Big Data. On the basis of our review of scholarly literature and our own investigations with big and small data, we have come to recognize that privacy and the great potential for privacy violations constitute major concerns in the debate about Big Data. Furthermore, our approach and our recommendations are generalizable to other ethical considerations inherent in Big Data as we illustrate in the final section of the chapter.

Does Evolutionary Theory Offer Insight into Epistemology, Consciousness, Sex, Race, Religion, Ethics, and the Meaning of Life?

This relatively thin but provocative volume discusses whether evolutionary explanations (often from evolutionary psychology) are useful in understanding some of life’s deepest issues, including the foundations of ethics and religion. Each chapter considers a new “Big Question.” At the end of each chapter, David Stamos supplies his analysis, which often attempts to overturn pre-Darwinian thinking. The book’s strength is its breadth, and its weakness is its lack of depth on some rather thorny issues. It is a stimulating book for students to read and with supplementary additional readings serves successfully as a text for an upper-level philosophy of biology class.