为合成生物学的伦理、法律和社会影响开发基于NLP的推荐系统
Developing an NLP-based Recommender System for the Ethical, Legal, and Social Implications of Synthetic Biology
摘要：
合成生物学是一个新兴领域，涉及生物体的工程和重新设计，用于食品安全，健康和环境保护等目的。因此，它对研究人员和政策制定者提出了许多伦理，法律和社会影响（ELSI）。正在进行各种努力，以确保对社会负责的合成生物学。政策制定是一种监管途径，其他举措也试图将社会科学家和伦理学家纳入合成生物学项目。然而，考虑到合成生物学的新生，它跨越的异质领域的数量，以及许多伦理问题的开放性，建立广泛的具体政策已被证明具有挑战性，并且将社会科学家和伦理学家纳入合成生物学团队已经取得了好坏参半的成功。本文提出了一种不同的方法，而是问是否有可能开发一个性能良好的推荐模型的基础上自然语言处理（NLP）连接合成生物学家与信息的ELSI他们的具体研究？这个推荐器是作为一个更大的项目的一部分开发的，该项目建立了一个合成生物学知识系统（SBKS），以加速合成生物学设计空间的发现和探索。我们的方法旨在为合成生物学家提取相关的伦理和社会科学信息，并将其嵌入合成生物学研究工作流程中。
英文摘要：
Synthetic biology is an emerging field that involves the engineering and re-design of organisms for purposes such as food security, health, and environmental protection. As such, it poses numerous ethical, legal, and social implications (ELSI) for researchers and policy makers. Various efforts to ensure socially responsible synthetic biology are underway. Policy making is one regulatory avenue, and other initiatives have sought to embed social scientists and ethicists on synthetic biology projects. However, given the nascency of synthetic biology, the number of heterogeneous domains it spans, and the open nature of many ethical questions, it has proven challenging to establish widespread concrete policies, and including social scientists and ethicists on synthetic biology teams has met with mixed success. This text proposes a different approach, asking instead is it possible to develop a well-performing recommender model based upon natural language processing (NLP) to connect synthetic biologists with information on the ELSI of their specific research? This recommender was developed as part of a larger project building a Synthetic Biology Knowledge System (SBKS) to accelerate discovery and exploration of the synthetic biology design space. Our approach aims to distill for synthetic biologists relevant ethical and social scientific information and embed it into synthetic biology research workflows.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
