
Entanglement
Author(s) -
Maya Indira Ganesh
Publication year - 2017
Publication title -
a peer-reviewed journal about --
Language(s) - English
Resource type - Journals
ISSN - 2245-7755
DOI - 10.7146/aprja.v6i1.116013
Subject(s) - accountability , transparency (behavior) , big data , context (archaeology) , valuation (finance) , computer science , narrative , epistemology , engineering ethics , sociology , political science , computer security , business , engineering , law , accounting , philosophy , data mining , paleontology , biology , linguistics
This paper is based on driver-less car technology as currently being developed by Google and Tesla, two companies that amplify their work in the media. More specifically, I focus on the moment of real and imagined crashes involving driver-less cars, and argue that the narrative of ‘ethics of driver-less cars’ indicates a shift in the construction of ethics, as an outcome of machine learning rather than a framework of values. Through applications of the ‘Trolley Problem’, among other tests, ethics has been transformed into a valuation based on processing of big data. Thus ethics-as-software enables what I refer to as big data-driven accountability. In this formulation, ‘accountability’ is distinguished from ‘responsibility’; responsibility implies intentionality and can only be assigned to humans, whereas accountability includes a wide net of actors and interactions (in Simon). ‘Transparency’ is one of the more established, widely acknowledged mechanisms for accountability; based on the belief that seeing into a system delivers the truth of that system and thereby a means to govern it. There are however limitations to this mechanism in the context of algorithmic transparency (Ananny and Crawford).