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Biology can be misused, and the risk of this causing widespread harm increases in step with the rapid march of technological progress. A key security challenge involves attribution: determining, in the wake of a human-caused biological event, who was responsible. Recent scientific developments have demonstrated a capability for detecting whether an organism involved in such an event has been genetically modified and, if modified, to infer from its genetic sequence its likely lab of origin. We believe this technique could be developed into powerful forensic tools to aid the attribution of outbreaks caused by genetically engineered pathogens, and thus protect against the potential misuse of synthetic biology., A key security challenge with biosecurity threats is determining the responsible actor. In this Perspective, the authors review recent developments in using genetic sequence to assign a lab-of-origin and the potential protection it provides against misuse of synthetic biology.

As the transformative potential of AI has become increasingly salient as a matter of public and political interest, there has been growing discussion about the need to ensure that AI broadly benefits humanity. This in turn has spurred debate on the social responsibilities of large technology companies to serve the interests of society at large. In response, ethical principles and codes of conduct have been proposed to meet the escalating demand for this responsibility to be taken seriously. As yet, however, few institutional innovations have been suggested to translate this responsibility into legal commitments which apply to companies positioned to reap large financial gains from the development and use of AI. This paper offers one potentially attractive tool for addressing such issues: the Windfall Clause, which is an ex ante commitment by AI firms to donate a significant amount of any eventual extremely large profits. By this we mean an early commitment that profits that a firm could not earn without achieving fundamental, economically transformative breakthroughs in AI capabilities will be donated to benefit humanity broadly, with particular attention towards mitigating any downsides from deployment of windfall-generating AI., Short version to be published in proceedings of AIES

The article by Fink and Houston in this special issue of Journal of Sport and Health Science provides an excellent example of implementing an evidence-based fall prevention program in real communities with diverse cultures of elderly populations. Although preliminary, the project revealed a number of interconnected barriers and facilitators that shed light on practical implications (“lessons learned”) for policymakers and program providers regarding implementation of any evidence-based intervention. While applauding Fink and Houston’s effort, in this commentary we share our experiences with Tai Ji Quan: Moving for Better Balance (TJQMBB) in the state of Maryland, with a discussion of our own set of lessons learned in terms of successes and challenges.