Understanding Perceptions of Smart Devices

Hadan, Hilda; Patil, Sameer

doi:10.1007/978-3-030-54455-3_8

Cited by 3 publications

(4 citation statements)

References 16 publications

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“…Some of those who reported owning Smart Speakers mentioned turning the devices off or actively disabling their voice-based capabilities to protect privacy. These findings are in line with the Hadan and Patil's [27] work in which users reported trying to protect their privacy with radical actions such as switching devices off. Yet, the proportion of device owners who reported disabling features or turning the devices off is rather small (36/329, 10.94%) indicating that resignation to ongoing privacy encroachment might be widespread [34,48,49].…”

Section: Use -Smart Home Device Use Is Related To Perceived Regulator...supporting

confidence: 87%

“…For instance, Lau et al [34] found that many users of Smart Speakers report low levels of privacy concerns and do not typically use the available privacy controls because they lack a full understanding of the potential privacy risks. Abdi et al [1] similarly uncovered that users have incomplete mental models of the operation of Smart Speakers, leading to a variety of false perceptions regarding how Smart Speakers handle data storage, processing, and sharing, a point raised also by Hadan and Patil [27] and Haney et al [29].…”

Section: Privacy and Smart Home Devicesmentioning

confidence: 99%

“…Still, if the core functionality is negatively impacted, users of Smart TVs are typically unwilling to employ privacy-protecting measures. More generally, researchers have found that users harbor privacy and security concerns regarding Smart Home Devices, but mostly lack the knowledge to implement the appropriate measures to counter the perceived threats [27,29].…”

Section: Privacy and Smart Home Devicesmentioning

confidence: 99%

See 2 more Smart Citations

A Multi-Region Investigation of the Perceptions and Use of Smart Home Devices

Bombik

Wenzel

Großklags

et al. 2022

PoPETs

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Smart Home Devices are household objects and appliances that are augmented with network connectivity and interactive capabilities. However, the benefits and conveniences of such augmentation are tempered by corresponding increases in privacy and security threats. Studies of user perceptions of these threats and user practices for addressing them are limited mostly to specific devices and/or small samples from a single region. To address this gap, we compared perceptions and practices of people in three geographic regions regarding privacy and security matters related to Smart Home Devices. Across these regions, we found differences in perceived regulatory protection and other regional factors. Our findings suggest that a co-evolution of the design and public policy related to Smart Home Devices could enhance privacy protection and drive increased adoption of these devices.

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Section: Use -Smart Home Device Use Is Related To Perceived Regulator...supporting

confidence: 87%

Section: Privacy and Smart Home Devicesmentioning

confidence: 99%

Section: Privacy and Smart Home Devicesmentioning

confidence: 99%

See 1 more Smart Citation

A Multi-Region Investigation of the Perceptions and Use of Smart Home Devices

Bombik

Wenzel

Großklags

et al. 2022

PoPETs

Self Cite

View full text Add to dashboard Cite

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“…The few studies in the field aim for the assessment of associations and perceptions about AI, referring only to the fifth theme (How do people perceive AI?) of the conceptional AIL-framework mentioned above (e.g., AI in general: Eurobarometer, 2017;Zhang and Dafoe 2019b;Kelley et al, 2019;voice-based conversational agent-specific: Zeng et al, 2017;Lau et al, 2018;Hadan and Patil, 2020). However, an analysis of the items of the instruments revealed that the majority referred to either digitalization in general or specific embodiments such as robots (e.g., Eurobarometer 2017).…”

Section: Measuring Media-related Competencies: From Digital Literacy To Conversation Agent Literacymentioning

confidence: 99%

Development of an Instrument to Measure Conceptualizations and Competencies About Conversational Agents on the Example of Smart Speakers

Wienrich¹,

Carolus

2021

Front. Comput. Sci.

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The concept of digital literacy has been introduced as a new cultural technique, which is regarded as essential for successful participation in a (future) digitized world. Regarding the increasing importance of AI, literacy concepts need to be extended to account for AI-related specifics. The easy handling of the systems results in increased usage, contrasting limited conceptualizations (e.g., imagination of future importance) and competencies (e.g., knowledge about functional principles). In reference to voice-based conversational agents as a concrete application of AI, the present paper aims for the development of a measurement to assess the conceptualizations and competencies about conversational agents. In a first step, a theoretical framework of “AI literacy” is transferred to the context of conversational agent literacy. Second, the “conversational agent literacy scale” (short CALS) is developed, constituting the first attempt to measure interindividual differences in the “(il) literate” usage of conversational agents. 29 items were derived, of which 170 participants answered. An explanatory factor analysis identified five factors leading to five subscales to assess CAL: storage and transfer of the smart speaker’s data input; smart speaker’s functional principles; smart speaker’s intelligent functions, learning abilities; smart speaker’s reach and potential; smart speaker’s technological (surrounding) infrastructure. Preliminary insights into construct validity and reliability of CALS showed satisfying results. Third, using the newly developed instrument, a student sample’s CAL was assessed, revealing intermediated values. Remarkably, owning a smart speaker did not lead to higher CAL scores, confirming our basic assumption that usage of systems does not guarantee enlightened conceptualizations and competencies. In sum, the paper contributes to the first insights into the operationalization and understanding of CAL as a specific subdomain of AI-related competencies.

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