Personal choices and situated data
Privacy negotiations and the acceptance of household Intelligent Personal Assistants
Bibliographic Data
| ID | 5260824 |
|---|---|
| Authors | Jason Pridmore (0000-0001-9159-8623, Erasmus University Rotterdam, corresponding author), Anouk Mols (0000-0003-0355-9849, Erasmus University Rotterdam) |
| Year | 2020 |
| Volume | 7 |
| Issue | 1 |
| Pages | 205395171989174 |
| Publication date | 2020-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Big Data & Society (JOURNAL) |
| Journal identifiers | ISSN: 2053-9517 • E-ISSN: 2053-9517 |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/2053951719891748 |
| OpenAlex | W3003679552 |
| Language | EN |
| Citations received | 13 |
| References cited | 11 |
The emergence of personal assistants in the form of smart speakers has begun to significantly alter people’s everyday experiences with technology. The rate at which household Intelligent Personal Assistants such as Amazon’s Echo and Google Home emerged in household spaces has been rapid. They have begun to move human–computer interaction from text-based to voice-activated input, offering a multiplicity of features through speech. The supporting infrastructure connects with artificial intelligence and the internet of things, allowing digital interfaces with domestic appliances, lighting systems, thermostats, media devices and more. Yet this also constitutes a significant new production of situated and sensitive data. This study focuses on how (potential) users negotiate and make choices about household Intelligent Personal Assistant use in connection with their data. This study is based on empirical research in Europe with early adopters in Germany and potential users in the Netherlands. This examination of users’ early stage technology acceptance considerations highlights particular practices and choices of users to either preserve their privacy or determine what is acceptable use for their data. Drawing on a simplified version of Unified Theory of Acceptance and Use of Technology 2, a quantitative model for technology acceptance, we demonstrate how acceptance of a household Intelligent Personal Assistants does not imply access to all household data, how users see usefulness in relation to a proliferation of devices, and note the recognition by users regarding the efforts needed for full use and acceptance. The study highlights the complexity of data production at a household level and how these devices produce myopic views of users for platforms
Digital divide · Information privacy · Internet privacy · Negotiation · Personal computer · Situated · Sociology · The Internet · World Wide Web · Computer Science · Privacy, Security, and Data Protection · Sharing Economy and Platforms · Technology Adoption and User Behaviour
Interrogating Datafication
Voice assistants in private households
Wieso eigentlich Alexa
Intelligent Personal Assistants in practice. Situational agencies and the multiple forms of cooperation without consensus
Household intelligent personal assistants in the Netherlands
Virtual assistants in the family home. Understanding parents’ motivations to use virtual assistants with their Child(dren)
Towards an experiential ethics of AI and robots
Producing shifting personhood
‘There are some things that I would never ask Alexa’ – privacy work, contextual integrity, and smart speaker assistants
TargetedAds, or memeing dataveillance on TikTok
Critical companionship
Dashboard design and the 'datafied' driving experience
The role of mundane resistance in the spectacular failure of the smart home
Focus Groups
Consumer Acceptance and Use of Information Technology
Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology
How Users Matter
Alexa, Are You Listening
Intelligent Personal Assistants and the Intercultural Negotiations of Dataveillance in Platformed Households
The Social Construction of Facts and Artefacts
Using thematic analysis in psychology
The Platformization of the Web
| Unique citing works | 13 |
|---|---|
| Citations per year | 2,6 |
| Citation span | 2021 - 2025 (5) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 12 |