AI models and the future of genomic research and medicine: True sons of knowledge?: Artificial intelligence needs to be integrated with causal conceptions in biomedicine to harness its societal benefits for the field.

The increasing availability of large-scale, complex data has made research into how human genomes determine physiology in health and disease, as well as its application to drug development and medicine, an attractive field for artificial intelligence (AI) approaches. Looking at recent developments, we explore how such approaches interconnect and may conflict with needs for and notions of causal knowledge in molecular genetics and genomic medicine. We provide reasons to suggest that-while capable of generating predictive knowledge at unprecedented pace and scale-if and how these approaches will be integrated with prevailing causal concepts will not only determine the future of scientific understanding and self-conceptions in these fields. But these questions will also be key to develop differentiated policies, such as for education and regulation, in order to harness societal benefits of AI for genomic research and medicine.

Synthetic biology's self-fulfilling prophecy--dangers of confinement from within and outside.

A too narrow focus on engineering and application may confine the development of synthetic biology: this Forum article provides reasons to suggest that knowledge could remain related to intended functions and applications, and not flow back from application to (deeper biological) understanding. Concurrently, such an engineering/application focus may 'attract' and feed strategic policy schemes, in turn enhancing the need for applicability as a prerequisite of knowledge production. This self-reinforcing loop--driven from within and outside the field--could ultimately restrict future knowledge and benefits from synthetic biology.

Synthetic genomics and synthetic biology applications between hopes and concerns.

New organisms and biological systems designed to satisfy human needs are among the aims of synthetic genomics and synthetic biology. Synthetic biology seeks to model and construct biological components, functions and organisms that do not exist in nature or to redesign existing biological systems to perform new functions. Synthetic genomics, on the other hand, encompasses technologies for the generation of chemically-synthesized whole genomes or larger parts of genomes, allowing to simultaneously engineer a myriad of changes to the genetic material of organisms. Engineering complex functions or new organisms in synthetic biology are thus progressively becoming dependent on and converging with synthetic genomics. While applications from both areas have been predicted to offer great benefits by making possible new drugs, renewable chemicals or clean energy, they have also given rise to concerns about new safety, environmental and socio-economic risks - stirring an increasingly polarizing debate. Here we intend to provide an overview on recent progress in biomedical and biotechnological applications of synthetic genomics and synthetic biology as well as on arguments and evidence related to their possible benefits, risks and governance implications.