The Unique and Practical Advantages of Applying A Capability Approach to Brain Computer Interface

Author:

Jecker Nancy S.ORCID,Ko AndrewORCID

Abstract

AbstractIntelligent neurotechnology is an emerging field that combines neurotechnologies like brain-computer interface (BCI) with artificial intelligence. This paper introduces a capability framework to assess the responsible use of intelligent BCI systems and provide practical ethical guidance. It proposes two tests, the threshold and flourishing tests, that BCI applications must meet, and illustrates them in a series of cases. After a brief introduction (Section 1), Section 2 sets forth the capability view and the two tests. It illustrates the threshold test using examples from clinical medicine of BCI applications that enable patients with profound disabilities to function at a threshold level through computer mediation. Section 3 illustrates the flourishing test by exploring possible future applications of BCI involving neuroenhancements for healthy people, using examples adapted from research currently underway in the US military. Section 3 applies a capability lens to a complex case involving dual effects, both therapeutic and non-therapeutic, showing how the threshold and flourishing tests resolve the case. Section 4 replies to three objections: neurorights are the best tool for assessing BCI; the two tests are moving targets; and the analysis utilizes a capability view to do work it is not designed for. The paper concludes that a capability view offers unique advantages and gives practical guidance for evaluating the responsible use of present and future BCI applications. Extrapolating from our analysis may help guide other emerging technologies, such as germline gene editing, expected to impact central human capabilities.

Publisher

Springer Science and Business Media LLC

Subject

History and Philosophy of Science,Philosophy

Reference70 articles.

1. Abiri, R., Borhani, S., Sellers, E. W., Jiang, Y., & Zhao, X. (2019). A comprehensive review of EEG-based brain-computer interface paradigms. Journal of Neural Engineering, 16(1), 011001. https://doi.org/10.1088/1741-2552/aaf12e

2. Abecassis, I. J., & Ko, A. L. (2018). Brain-computer interface (BCI). In A. M. Raslan & K. J. Burchiel (Eds.), Functional Neurosurgery and Neuromodulation (pp. 143–152). Elsevier.

3. Battelle Media Relations (2019). Battelle-led team wins DARPA award to develop injectable, bi-directional brain computer interface, 20 May. https://www.battelle.org/insights/newsroom/press-release-details/battelle-led-team-wins-darpa-award-to-develop-injectable-bi-directional-brain-computer-interface

4. Blankertz, B., Tangermann, M., & Müller, K. R. (2012). BCI applications for the general population. In J. Wolpaw & E. W. Wolpaw (Eds.), Brain Computer Interfaces: Principles and Practice (pp. 363–392). Oxford University Press.

5. Bostrom, N. (2003). Human genetic enhancements: A transhumanist perspective. Journal of Value Inquiry, 37(4), 493–506.

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3