Auditing the Information Quality of News-Related Queries on the Alexa Voice Assistant

Dambanemuya, Henry K.; Diakopoulos, Nicholas

doi:10.1145/3449157

Cited by 8 publications

(15 citation statements)

References 36 publications

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“…It could also be that people with higher involvement only skimmed the information since they thought they already knew it. Considering all findings, the stakes for the quality of the single response of smart speakers are even higher than expected (Dambanemuya & Diakopoulos, 2021). This can have multiple implications for users and the companies behind the devices.…”

Section: Discussionmentioning

confidence: 80%

“…Providing no sponsor information results in the same credibility ratings as naming a highly credible sponsor. That no-sponsor attribution does not negatively affect credibility ratings is important because smart speakers often do not give the provenance of information (Dambanemuya & Diakopoulos, 2021). Consequently, people could perceive information from less credible sources to be as credible as information from highly credible sources without a source attribution, which could be problematic for adequate credibility judgments.…”

Section: Discussionmentioning

confidence: 99%

“…Smart speakers usually provide one result read by an artificial voice, making users more dependent on the search algorithm; the other results are invisible (Gruber et al, 2021). The quality of this single response thus becomes more important (Dambanemuya & Diakopoulos, 2021). The New York Times recently compared search results for conspiracy theories on Google and Bing and found that Bing displayed more untrustworthy websites (Thompson, 2022).…”

mentioning

confidence: 99%

“…Moreover, smart speakers often do not mention the source of information. In a study on information quality of Amazon Alexa, Dambanemuya and Diakopoulos (2021) found that most responses were of unknown provenance, which makes it more difficult to determine their trustworthiness (Metzger et al, 2003).…”

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confidence: 99%

See 3 more Smart Citations

Is Hearing Really Believing?

Gaiser

Utz

2024

Journal of Media Psychology

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Smart speakers are becoming popular all over the world and offer an alternative to conventional web search. We conducted two experiments to investigate whether different message modalities affect credibility perceptions, which role sponsor credibility and message accuracy play, and if this role differs in the two modalities. Based on the MAIN Model by Sundar (2008) , we assumed that modality, that is, whether the information is given textually or aurally, can affect credibility assessments. To investigate this, two online experiments with a 2 (modality: smart speaker/search engine) × 2 (message accuracy: high/low) ×3 (sponsor credibility: high/low/none) mixed factorial design were conducted ( n = 399 and 398). Information presented by the voice of a smart speaker was generally perceived as more credible. Results further showed that no source attribution and low message accuracy affected message credibility less in the auditive than in the textual modality, especially for participants with less topic involvement. With this, we gained valuable insights into the role of smart speakers for information search and potential downsides of this usage.

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Section: Discussionmentioning

confidence: 80%

Section: Discussionmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Is Hearing Really Believing?

Gaiser

Utz

2024

Journal of Media Psychology

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“…Furthermore, as one of the main VA's functions is providing information to its owner (McCaffrey et al, 2018), it is imperative to pay attention to their potential role in influencing opinion‐forming in the public sphere. By understanding user's characteristics, preferences, and moods, the VA is uniquely positioned to recommend news and content that seamlessly steers the user into a political preference (political consequences); the same type of content may indirectly contribute to inciting hatred and violence toward specific groups (social consequences); or make her question whether coronavirus pandemic is a hoax (private consequences) (Stucke & Ezrachi, 2017; Turow, 2021; on limitations of VAs: Dambanemuya & Diakopoulos, 2020).…”

Section: Hypernudging As a Policymaker's Problem: “Unknown (Un)knowns”mentioning

confidence: 99%

Hypernudging in the changing European regulatory landscape for digital markets

Morozovaite

2022

Policy & Internet

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The European regulatory landscape for digital markets is undergoing a transformative change. There is an observed shift toward the protection of public values and fundamental rights, as the market mechanism and market values that traditionally led regulatory processes in digital markets seem to have fallen short. In the context of the user‐centric digital economy, a clear commitment to safeguarding citizens' interests is ever‐more salient. This article provides a comprehensive account of hypernudging—dynamically personalized user steering, which represents the next generation user influencing techniques online, with the potential to lead to multifaceted individual and collective harms. However, problematizing the phenomenon for digital policy purposes is not a straightforward task. Due to the complexity and opaqueness of its underlying mechanisms and effects, policymakers are operating under conditions of uncertainty, necessitating a shared understanding of what impact hypernudging has on users as well as crafting a shared vision of values that ought to be embedded and safeguarded in digital choice architectures. To highlight the developing European approach in relation to hypernudging, the assessment of the recent legislative initiatives—the Artificial Intelligence Act, the Digital Markets Act, and the Digital Services Act—showcases underlying learning opportunities for addressing emergent challenges.

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The right to audit and power asymmetries in algorithm auditing

Urman,

Smirnov,

Lasser

2024

EPJ Data Sci.

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In this paper, we engage with and expand on the keynote talk about the “Right to Audit” given by Prof. Christian Sandvig at the International Conference on Computational Social Science 2021 through a critical reflection on power asymmetries in the algorithm auditing field. We elaborate on the challenges and asymmetries mentioned by Sandvig — such as those related to legal issues and the disparity between early-career and senior researchers. We also contribute a discussion of the asymmetries that were not covered by Sandvig but that we find critically important: those related to other disparities between researchers, incentive structures related to the access to data from companies, targets of auditing and users and their rights. We also discuss the implications these asymmetries have for algorithm auditing research such as the Western-centrism and the lack of the diversity of perspectives. While we focus on the field of algorithm auditing specifically, we suggest some of the discussed asymmetries affect Computational Social Science more generally and need to be reflected on and addressed.

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Auditing the Information Quality of News-Related Queries on the Alexa Voice Assistant

Cited by 8 publications

References 36 publications

Is Hearing Really Believing?

Is Hearing Really Believing?

Hypernudging in the changing European regulatory landscape for digital markets

The right to audit and power asymmetries in algorithm auditing

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