Datafied Brains and Digital Twins: Lessons From Industry, Caution For Psychiatry

IF 2.6 0 PHILOSOPHY Philosophy Psychiatry & Psychology Pub Date : 2022-03-01 DOI:10.1353/ppp.2022.0005
Stephen Rainey
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引用次数: 2

Abstract

Abstract:This paper asks what sorts of ethical caution ought to attach to increasingly data-driven approaches to understanding the brain. This is taken to be an important question especially owing to a likely near future of neuromonitoring and neuromodulation devices with applications in psychiatry. The paper explores this by i) sketching the concept of ‘digital twin,’ ii) drawing a schematic picture of ‘brain datafication’ in general, and iii) developing a means of understanding some challenges present in datafication through the lens of digital twins. One central concern arises from the role algorithmic processing of neural recordings plays in terms of neuroscientific objectivity, with knock on effects for psychiatric ethics. Essentially, this is owing to a way in which algorithmic processing in brain data construction appears to be deductive in character, but is in fact based on a particular scheme of inductive inference. The challenges explored urge ethical caution as they concern epistemological gaps in data-centered neuroscientific progress, as well as knock-on effects for psychiatry.
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数据化大脑和数字双胞胎:来自工业的教训,对精神病学的警告
摘要:本文提出,对于越来越多的数据驱动的理解大脑的方法,应该附加什么样的伦理警告。这被认为是一个重要的问题,特别是由于神经监测和神经调节装置可能在不久的将来应用于精神病学。本文通过i)概述“数字双胞胎”的概念,ii)一般绘制“大脑数据化”的示意图,以及iii)通过数字双胞胎的镜头开发一种理解数据化中存在的一些挑战的方法来探讨这一点。一个核心问题来自神经记录的算法处理在神经科学客观性方面所扮演的角色,对精神病学伦理产生了连锁反应。从本质上讲,这是由于大脑数据构建中的算法处理在性质上似乎是演绎的,但实际上是基于归纳推理的特定方案。探索的挑战敦促伦理谨慎,因为它们涉及以数据为中心的神经科学进步的认识论差距,以及对精神病学的连锁反应。
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来源期刊
CiteScore
3.60
自引率
4.30%
发文量
40
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