Mechanisms in cognitive science 1

Social machines are a prominent focus of attention for those who work in the field of Web and Internet science. Although a number of online systems have been described as social machines (examples include the likes of Facebook, Twitter, Wikipedia, Reddit, and Galaxy Zoo), there is, as yet, little consensus as to the precise meaning of the term “social machine.” This presents a problem for the scientific study of social machines, especially when it comes to the provision of a theoretical framework that directs, informs, and explicates the scientific and engineering activities of the social machine community. The present paper outlines an approach to understanding social machines that draws on recent work in the philosophy of science, especially work in so-called mechanical philosophy. This is what might be called a mechanistic view of social machines. According to this view, social machines are systems whose phenomena (i.e., events, states, and processes) are explained via an appeal to (online) socio-technical mechanisms. We show how this account is able to accommodate a number of existing attempts to define the social machine concept, thereby yielding an important opportunity for theoretical integration.

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Solving the Black Box Problem: A Normative Framework for Explainable Artificial Intelligence

Zednik

2019

Philos. Technol.

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Many of the computing systems programmed using Machine Learning are opaque: it is difficult to know why they do what they do or how they work. The Explainable Artificial Intelligence research program aims to develop analytic techniques with which to render opaque computing systems transparent, but lacks a normative framework with which to evaluate these techniques' explanatory success. The aim of the present discussion is to develop such a framework, while paying particular attention to different stakeholders' distinct explanatory requirements. Building on an analysis of 'opacity' from philosophy of science, this framework is modeled after David Marr's influential account of explanation in cognitive science. Thus, the framework distinguishes between the different questions that might be asked about an opaque computing system, and specifies the general way in which these questions should be answered. By applying this normative framework to current techniques such as input heatmapping, featuredetector identification, and diagnostic classification, it will be possible to determine whether and to what extent the Black Box Problem can be solved.

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Mechanisms in cognitive science 1

Cited by 6 publications

References 37 publications

The Mechanistic Theory of Human Cognition

The Mechanistic Theory of Human Cognition

Applying mechanical philosophy to web science: The case of social machines

Solving the Black Box Problem: A Normative Framework for Explainable Artificial Intelligence

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