Experimenting with co-development: A qualitative study of gene drive research for malaria control in Mali

Moving beyond narrow definitions of gene drive: Diverse perspectives and frames enable substantive dialogue among science and humanities teachers in the United States and United Kingdom

Gene drive is an emerging biotechnology with applications in global health, conservation and agriculture. Scientists are preparing for field trials, triggering debate about when and how to release gene-drive organisms. These decisions depend on public understandings of gene drive, which are shaped by language. While some studies on gene drive communication assume the need to persuade publics of expert definitions of gene drive, we highlight the importance of meaning-making in communication and engagement. We conducted focus groups with humanities and science teachers in the United Kingdom and United States to explore how different media framings stimulated discussions of gene drive. We found diversity in the value of these framings for public debate. Interestingly, the definition favoured by gene drive scientists was the least popular among participants. Rather than carefully curating language, we need opportunities for publics to make sense and negotiate the meanings of a technology on their own terms.

Patient and public involvement to build trust in artificial intelligence: A framework, tools, and case studies

Artificial intelligence (AI) is increasingly taking on a greater role in healthcare. However, hype and negative news reports about AI abound. Integrating patient and public involvement (PPI) in healthcare AI projects may help in adoption and acceptance of these technologies.

We argue that AI algorithms should also be co-designed with patients and healthcare workers.

We specifically suggest (1) including patients with lived experience of the disease, and (2) creating a research advisory group (RAG) and using these group meetings to walk patients through the process of AI model building, starting with simple (e.g., linear) models.

We present a framework, case studies, best practices, and tools for applying participative data science to healthcare, enabling data scientists, clinicians, and patients to work together. The strategy of co-designing with patients can help set more realistic expectations for all stakeholders, since conventional narratives of AI revolve around dystopia or limitless optimism.

Hype and negative news reports about artificial intelligence (AI) abound. Involving patients in healthcare AI projects may help in adoption and acceptance of these technologies. We argue that AI algorithms should be co-designed with patients and healthcare workers.

We show examples of how to involve patients in AI research and how patients can build trust in algorithms. We share some best practices, case studies, a framework, and computational tools.

Avenues for future work include guidelines for patient and public involvement in AI healthcare research for funding bodies and regulatory agencies.

An understanding of what AI can and cannot do, and a realistic appraisal of risks and benefits, may help in adoption and democratize access to AI for healthcare.

Gene Drives in the U.K., U.S., and Australian Press (2015-2019): How a New Focus on Responsibility Is Shaping Science Communication

Gene drive is a controversial biotechnology for pest control. Despite a commitment from gene drive researchers to responsibility and the key role of the media in debates about science and technology, little research has been conducted on media reporting of gene drive. We employ metaphor and discourse analysis to explore how responsibility is reflected in the coverage of this technology in the U.S., U.K., and Australian press. The findings reveal a rhetorical strategy of trust-building by evoking the moral attributes of gene drive researchers. We discuss the implications of these findings for the communication of new technologies.