Machine Learning and Gene Editing at the Helm of a Societal Evolution.
| Title: | Machine Learning and Gene Editing at the Helm of a Societal Evolution. |
|---|---|
| Authors: | Zakaria S; Marler T; Cabling M; Genc S; Honich A; Virdee M; Stockwell S |
| Source: | Rand health quarterly [Rand Health Q] 2024 Mar 04; Vol. 11 (2), pp. 5. Date of Electronic Publication: 2024 Mar 04 (Print Publication: 2024). |
| Publication Type: | Journal Article |
| Language: | English |
| Journal Info: | Publisher: Rand Corporation Country of Publication: United States NLM ID: 101622976 Publication Model: eCollection Cited Medium: Print ISSN: 2162-8254 (Print) Linking ISSN: 21628254 NLM ISO Abbreviation: Rand Health Q Subsets: PubMed not MEDLINE |
| Imprint Name(s): | Original Publication: Santa Monica, CA : Rand Corporation, [2011]- |
| Abstract: | The integration of artificial intelligence (AI) and biotechnology, whilst in its infancy, presents significant opportunities and risks, and proactive policy is needed to manage these emerging technologies. Whilst AI continues to have significant and broad impact, its relevance and complexity magnify when integrated with other emerging technologies. The confluence of Machine Learning (ML), a subset of AI, with gene editing (GE) in particular can foster substantial benefits as well as daunting risks that range from ethics to national security. These complex technologies have implications for multiple sectors, ranging from agriculture and medicine to economic competition and national security. Consideration of technology advancements and policies in different geographic regions, and involvement of multiple organisations further confound this complexity. As the impact of ML and GE expands, forward looking policy is needed to mitigate risks and leverage opportunities. Thus, this study explores the technological and policy implications of the intersection of ML and GE, with a focus on the United States (US), the United Kingdom (UK), China, and the European Union (EU). Analysis of technical and policy developments over time and an assessment of their current state have informed policy recommendations that can help manage beneficial use of technology advancements and their convergence, which can be applied to other sectors. This study is intended for policymakers to prompt reflection on how to best approach the convergence of the two technologies. Technical practitioners may also find it valuable as a resource to consider the type of information and policy stakeholders engage with.; (Copyright © 2024 RAND Corporation.) |
| Contributed Indexing: | Keywords: Biology and Life Sciences; Biotechnology; Emerging Technologies; Global Security; Machine Learning; Science, Technology, and Innovation Policy |
| Entry Date(s): | Date Created: 20240411 Latest Revision: 20240411 |
| Update Code: | 20260130 |
| PubMed Central ID: | PMC10911753 |
| PMID: | 38601713 |
| Database: | MEDLINE |
Journal Article