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AI models and the future of genomic research and medicine: True sons of knowledge?
BioEssays ( IF 3.2 ) Pub Date : 2021-08-11 , DOI: 10.1002/bies.202100025 Harald König 1 , Daniel Frank 2 , Martina Baumann 1 , Reinhard Heil 1
BioEssays ( IF 3.2 ) Pub Date : 2021-08-11 , DOI: 10.1002/bies.202100025 Harald König 1 , Daniel Frank 2 , Martina Baumann 1 , Reinhard Heil 1
Affiliation
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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.
中文翻译：
AI 模型和基因组研究和医学的未来：真正的知识之子？
随着大规模复杂数据的日益普及，人们开始研究人类基因组如何决定健康和疾病的生理机能，以及其在药物开发和医学中的应用，这是人工智能 (AI) 方法的一个有吸引力的领域。着眼于最近的发展，我们探讨了这些方法如何相互关联，并可能与分子遗传学和基因组医学中因果知识的需求和概念发生冲突。我们提供理由表明，虽然能够以前所未有的速度和规模产生预测性知识，但这些方法是否以及如何与流行的因果概念相结合，不仅将决定这些领域科学理解和自我概念的未来。但这些问题也将是制定差异化政策的关键，例如教育和监管、
更新日期：2021-09-27
中文翻译：
AI 模型和基因组研究和医学的未来：真正的知识之子？
随着大规模复杂数据的日益普及，人们开始研究人类基因组如何决定健康和疾病的生理机能，以及其在药物开发和医学中的应用，这是人工智能 (AI) 方法的一个有吸引力的领域。着眼于最近的发展，我们探讨了这些方法如何相互关联，并可能与分子遗传学和基因组医学中因果知识的需求和概念发生冲突。我们提供理由表明，虽然能够以前所未有的速度和规模产生预测性知识，但这些方法是否以及如何与流行的因果概念相结合，不仅将决定这些领域科学理解和自我概念的未来。但这些问题也将是制定差异化政策的关键，例如教育和监管、
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