Cyberbiosecurity: An Emerging Field that has Ethical Implications for Clinical Neuroscience.

Cyberbiosecurity is an emerging field that relates to the intersection of cybersecurity and the clinical and research practice in the biosciences. Beyond the concerns that usually arise in the areas of genomics, this paper highlights ethical concerns raised by cyberbiosecurity in clinical neuroscience. These concerns relate not only to the privacy of the data collected by imaging devices, but also the concern that patients using various stimulatory devices can be harmed by a hacker who either obfuscates the outputs or who interferes with the stimulatory process. The paper offers some suggestions as to how to rectify these increasingly dire concerns.

Under the influenceRevenge of the Tipping Point: Overstories, Superspreaders, and the Rise of Social Engineering Malcolm Gladwell Little, Brown, 2024. 368 pp.

A journalist revisits his popular theory of social contagions.

Bold decisions in uncertain timesOn the Edge: The Art of Risking Everything Nate Silver Penguin, 2024. 576 pp.

A celebrated election forecaster proposes a framework for confronting risk.

The Key Features of a Genetic Nondiscrimination Policy: A Delphi Consensus Statement.

Importance: Governments worldwide have become increasingly cognizant of the spread of genetic discrimination (negative treatment or harm on the basis of actual or presumed genetic characteristics). Despite efforts by a number of governments to establish regulations addressing this phenomenon, public concern about genetic discrimination persists. Objective: To identify key elements of an optimal genetic nondiscrimination policy and inform policymakers as they seek to allay genetic nondiscrimination and related public anxieties. Evidence Review: Sixty multidisciplinary experts from 20 jurisdictions worldwide were consulted to understand their views on effective genetic nondiscrimination policies. Following standard requirements of the Delphi method, 3 rounds of surveys over the course of 1.5 years were conducted. Round 1 focused on assessing participants' understanding of the intricacies of existing genetic nondiscrimination policies, while rounds 2 and 3 invited participants to reflect on specific means of implementing a more effective regime. A total of 60 respondents participated in the first round, 53 participated in round 2, and 43 participated in round 3. Findings: While responses varied across disciplines, there was consensus that binding regulations that reach across various sectors are most useful in preventing genetic discrimination. Overall, experts agreed that human rights-based approaches are well suited to preventing genetic discrimination. Experts also agreed that explicit prohibition of genetic discrimination within nondiscrimination policies can highlight the importance of genetic nondiscrimination as a fundamental right and ensure robust protection at a national level. While most participants believed the international harmonization of genetic nondiscrimination laws would facilitate data sharing worldwide, they also recognized that regulations must reflect the sociocultural differences that exist among regions. Conclusions and Relevance: As the reach of genetic discrimination continues to evolve alongside developments in genomics, strategic policy responses that are harmonious at the international and state levels will be critical to address this phenomenon. In seeking to establish comprehensive frameworks, policymakers will need to be mindful of regional and local circumstances that influence the need for and efficacy of unique genetic nondiscrimination approaches across diverse contexts.

Resisting efficiency's overreachOptimal Illusions: The False Promise of Optimization Coco Krumme Riverhead Books, 2023. 256 pp.

Society's obsession with optimization has a cost, argues a mathematical modeler.

Calculating the futureQuantum Supremacy: How the Quantum Computer Revolution Will Change Everything Michio Kaku Doubleday, 2023. 352 pp.

A quantum computing primer offers insights into the technology's most promising potential applications.

Genomics and privacy: implications of the new reality of closed data for the field.

Open source and open data have been driving forces in bioinformatics in the past. However, privacy concerns may soon change the landscape, limiting future access to important data sets, including personal genomics data. Here we survey this situation in some detail, describing, in particular, how the large scale of the data from personal genomic sequencing makes it especially hard to share data, exacerbating the privacy problem. We also go over various aspects of genomic privacy: first, there is basic identifiability of subjects having their genome sequenced. However, even for individuals who have consented to be identified, there is the prospect of very detailed future characterization of their genotype, which, unanticipated at the time of their consent, may be more personal and invasive than the release of their medical records. We go over various computational strategies for dealing with the issue of genomic privacy. One can "slice" and reformat datasets to allow them to be partially shared while securing the most private variants. This is particularly applicable to functional genomics information, which can be largely processed without variant information. For handling the most private data there are a number of legal and technological approaches-for example, modifying the informed consent procedure to acknowledge that privacy cannot be guaranteed, and/or employing a secure cloud computing environment. Cloud computing in particular may allow access to the data in a more controlled fashion than the current practice of downloading and computing on large datasets. Furthermore, it may be particularly advantageous for small labs, given that the burden of many privacy issues falls disproportionately on them in comparison to large corporations and genome centers. Finally, we discuss how education of future genetics researchers will be important, with curriculums emphasizing privacy and data security. However, teaching personal genomics with identifiable subjects in the university setting will, in turn, create additional privacy issues and social conundrums.