Philosophical Inquiry into Computer Intentionality: Machine Learning and Value Sensitive Design

IF 0.4 Q3 SOCIAL SCIENCES, INTERDISCIPLINARY
Dmytro Mykhailov
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引用次数: 1

Abstract

Abstract Intelligent algorithms together with various machine learning techniques hold a dominant position among major challenges for contemporary value sensitive design. Self-learning capabilities of current AI applications blur the causal link between programmer and computer behavior. This creates a vital challenge for the design, development and implementation of digital technologies nowadays. This paper seeks to provide an account of this challenge. The main question that shapes the current analysis is the following: What conceptual tools can be developed within the value sensitive design school of thought for evaluating machine learning algorithms where the causal relation between designers and the behavior of their computer systems has been eroded? The answer to this question will be provided through two levels of investigation within the value sensitive design methodology. The first level is conceptual. Within the conceptual level, we will introduce the notion of computer intentionality and will show how this term may be used for solving an issue of non-causal relation between designer and computer system. The second level of investigation is technical. At this level the emphasis will be given to machine learning algorithms.
计算机意向性的哲学探究:机器学习和价值敏感设计
智能算法与各种机器学习技术在当代价值敏感设计的主要挑战中占据主导地位。当前人工智能应用的自我学习能力模糊了程序员和计算机行为之间的因果关系。这给当今数字技术的设计、开发和实施带来了重大挑战。本文试图对这一挑战作出解释。形成当前分析的主要问题是:在价值敏感设计思想流派中,可以开发哪些概念性工具来评估机器学习算法,其中设计师与其计算机系统行为之间的因果关系已被侵蚀?这个问题的答案将通过价值敏感设计方法论中的两个层次的调查来提供。第一个层次是概念性的。在概念层面,我们将介绍计算机意向性的概念,并将展示如何使用这个术语来解决设计者和计算机系统之间的非因果关系问题。第二个层面的调查是技术性的。在这个层次上,重点将放在机器学习算法上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.30
自引率
25.00%
发文量
41
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