AI and Privacy Concerns: A Smart Meter Case Study

Carmody, J; Shringarpure, S; Van de Venter, T

AI and Privacy Concerns: A Smart Meter Case Study

Carmody, J Shringarpure, S Van de Venter, T

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Publisher:: Emerald
Publication Type:: Journal Article
Citation:: Journal of Information Communication and Ethics in Society, 2021, 19, (4), pp. 492-505
Issue Date:: 2021

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Field	Value	Language
dc.contributor.author	Carmody, J
dc.contributor.author	Shringarpure, S
dc.contributor.author	Van de Venter, T https://orcid.org/0000-0003-2874-7336
dc.date.accessioned	2021-12-14T01:56:50Z
dc.date.available	2021-12-14T01:56:50Z
dc.date.issued	2021
dc.identifier.citation	Journal of Information Communication and Ethics in Society, 2021, 19, (4), pp. 492-505
dc.identifier.issn	1477-996X
dc.identifier.issn	1758-8871
dc.identifier.uri	http://hdl.handle.net/10453/152300
dc.description.abstract	Purpose: The purpose of this paper is to demonstrate privacy concerns arising from the rapidly increasing advancements and use of artificial intelligence (AI) technology and the challenges of existing privacy regimes to ensure the on-going protection of an individual’s sensitive private information. The authors illustrate this through a case study of energy smart meters and suggest a novel combination of four solutions to strengthen privacy protection. Design/methodology/approach: The authors illustrate how, through smart meter obtained energy data, home energy providers can use AI to reveal private consumer information such as households’ electrical appliances, their time and frequency of usage, including number and model of appliance. The authors show how this data can further be combined with other data to infer sensitive personal information such as lifestyle and household income due to advances in AI technologies. Findings: The authors highlight data protection and privacy concerns which are not immediately obvious to consumers due to the capabilities of advanced AI technology and its ability to extract sensitive personal information when applied to large overlapping granular data sets. Social implications: The authors question the adequacy of existing privacy legislation to protect sensitive inferred consumer data from AI-driven technology. To address this, the authors suggest alternative solutions. Originality/value: The original value of this paper is that it illustrates new privacy issues brought about by advances in AI, failings in current privacy legislation and implementation and opens the dialog between stakeholders to protect vulnerable consumers.
dc.language	en
dc.publisher	Emerald
dc.relation.ispartof	Journal of Information Communication and Ethics in Society
dc.relation.isbasedon	10.1108/JICES-04-2021-0042
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0807 Library and Information Studies, 0899 Other Information and Computing Sciences, 1702 Cognitive Sciences
dc.title	AI and Privacy Concerns: A Smart Meter Case Study
dc.type	Journal Article
utslib.citation.volume	19
utslib.for	0807 Library and Information Studies
utslib.for	0899 Other Information and Computing Sciences
utslib.for	1702 Cognitive Sciences
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Finance Discipline
utslib.copyright.status	closed_access	*
pubs.consider-herdc	true
dc.date.updated	2021-12-14T01:56:48Z
pubs.issue	4
pubs.publication-status	Published
pubs.volume	19
utslib.citation.issue	4

Abstract:

Purpose: The purpose of this paper is to demonstrate privacy concerns arising from the rapidly increasing advancements and use of artificial intelligence (AI) technology and the challenges of existing privacy regimes to ensure the on-going protection of an individual’s sensitive private information. The authors illustrate this through a case study of energy smart meters and suggest a novel combination of four solutions to strengthen privacy protection. Design/methodology/approach: The authors illustrate how, through smart meter obtained energy data, home energy providers can use AI to reveal private consumer information such as households’ electrical appliances, their time and frequency of usage, including number and model of appliance. The authors show how this data can further be combined with other data to infer sensitive personal information such as lifestyle and household income due to advances in AI technologies. Findings: The authors highlight data protection and privacy concerns which are not immediately obvious to consumers due to the capabilities of advanced AI technology and its ability to extract sensitive personal information when applied to large overlapping granular data sets. Social implications: The authors question the adequacy of existing privacy legislation to protect sensitive inferred consumer data from AI-driven technology. To address this, the authors suggest alternative solutions. Originality/value: The original value of this paper is that it illustrates new privacy issues brought about by advances in AI, failings in current privacy legislation and implementation and opens the dialog between stakeholders to protect vulnerable consumers.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/152300