Complex ecologies of trust in data practices and data-driven systems

Abstract

Trust in data practices and data-driven systems is widely seen as both important and elusive. A data trust deficit has been identified, to which proposed solutions are often localised or individualised, focusing either on what institutions can do to increase user trust in their data practices or on data management models that empower the individual user. Scholarship on trust often focuses on typologies of trust. This paper shifts the emphasis to those doing the trusting, by presenting findings from empirical research which explored user perspectives on the data practices of the BBC. These findings challenge the assumption that localised or individualised solutions can be effective. They also suggest that conceptualisations of trust in data practices need to account for the complex range of factors which come into play in relation to trust in data and so move beyond the production of typologies. In this paper, we propose the concept of 'complex ecologiesoftrust'asawayofaddressingalloftheseissues.

Public perceptions of good data management: Findings from a UK-based survey

“…The fact that less knowledgeable respondents were less likely to differentiate amongst approaches might suggest that with good information, more differentiation of approaches might result. But the relationship between information, understanding and perceptions of data practices is complex, and previous research has shown that information and understanding are not necessarily the solution to the data trust deficit (Steedman et al, 2020). Here again, further research is needed to understand the relationship between knowledge about and preference for data management approaches in greater depth.…”

“…Third, we need to think carefully about what respondents' preference for more control over their personal data might look like in practice. In previous qualitative research that we have undertaken, participants expressed concern about the burden of decisionmaking that a PDS approach might impose upon them as individuals (Steedman et al, 2020). Offloading the responsibility for good and informed data management decision-making onto citizens may therefore be problematic.…”

Explanations of news personalisation across countries and media types

“…Research from both the perspective of trust in the media and trust in the use of data suggests a modest relationship between trust and engagement (Curry & Stroud, 2019;Felzmann et al, 2019;Strömbäck et al, 2020). However, emerging research that combines the two perspectives by analysing how trust in the media is affected by its data usage suggests a more complex picture: although indiscriminate data collection may erode the media's trustworthiness, readers' assessment of the media's data collection disclosures is influenced by both their trust in the media organisation and in online data collection more generally (Sørensen & Van den Bulck, 2020;Steedman et al, 2020).…”

Trust for sale

“…Therefore, instead of falling head-first into the notion of increased productivity through deregulation, we would encourage careful consideration of how regulatory measures strengthen and enable different social actors differently, and how this matters to the sustainability of AI policy in the long run. Along these lines, Steedman et al (2020) call for, "collective, ecosystem solutions, for example, better regulation of data-driven systems, in order for them to be perceived as more trustworthy" (829). From their perspective, regulation of AI systems can act as a trust-building mechanism-which, in turn, could help strengthen the public's perception and reception of national AI management.…”

“…Trust is an important theme in AI imaginaries and contemporary critiques of datapowered systems. Steedman et al (2020) have noted a "data trust deficit" amongst the public, as the use and abuse of personal data becomes an ever-pressing topic of debate (818). These issues are also salient in the realm of AI, where data is increasingly brought to life as a very real part of the everyday, with algorithms operating in the background of most of our online interactions.…”