Live Facial Recognition: Trust and Legitimacy as Predictors of Public Support for Police Use of New Technology

Bradford, Ben; Yesberg, Julia A.; Jackson, Jonathan; Dawson, Paul

doi:10.1093/bjc/azaa032

Cited by 26 publications

(33 citation statements)

References 31 publications

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“…While effective, such measures are controversial and spur debate about privacy. A recent study on this subject found that legitimacy and public trust in the police are crucial in this matter, as they influence acceptance of facial recognition technology and may diminish concerns about privacy (Bradford et al 2020).…”

Section: Discussionmentioning

confidence: 99%

Mitigating COVID-19 in a Nationally Representative UK Sample: Personal Abilities and Obligation to Obey the Law Shape Compliance with Mitigation Measures

et al. 2020

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The COVID-19 pandemic has greatly influenced daily life all over the world. The present study assesses what factors influenced inhabitants of the United Kingdom to comply with lockdown and social distancing measures. It analyses data from an online survey, conducted on April 6-8, 2020, amongst a nationally representative sample of 555 participants who currently reside in the UK. The results show that compliance depended mostly on people's capacity to comply with the rules, and the normative obligation they feel to obey the law. As such, compliance was not associated with deterrence or obedience out of fear, but rather with people's practical abilities and intrinsic motivation to comply. The paper discusses policy implications for effective mitigation of the virus. Date: May 11, 2020 Word count (without tables, references, figure captions and endnotes): 6944 Notes: This working paper has not yet been peer reviewed. The authors declare that there is no conflict of interest.

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Section: Discussionmentioning

confidence: 99%

Mitigating COVID-19 in a Nationally Representative UK Sample: Personal Abilities and Obligation to Obey the Law Shape Compliance with Mitigation Measures

et al. 2020

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“…In particular, procedurally fair processes and interactions indicate to people working in an organization that power within it is wielded in a normatively justifiable manner-that managers and supervisors "do the right things for the right reasons" (Suchman, 1995;Jackson & Bradford, 2019). This sense of normative alignment between the power-holder's values and those of subordinates motivates a feeling that the orders and instructions of power-holders within the organization should be obeyed (Jackson et al, 2012;Tyler et al, 2007;Trinkner et al, 2018) and that police are justified in using force and employing new technologies (Tyler & Wakslak, 2004;Bradford et al, 2020). Here, this is a concept of legitimacy within law enforcement agencies that is entirely in accordance with that used in the procedural justice literature, where the concern is between those agencies and the people they police (Huq et al, 2017).…”

Section: Psychological Mechanism Of Promoting Changementioning

confidence: 99%

On the Importance of a Procedurally Fair Organizational Climate for Openness to Change in Law Enforcement

Brimbal¹,

Bradford²,

Jackson³

et al. 2020

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ObjectivesDrawing on recent work in policing and organizational psychology, we examined factors related to openness to organizational change and to adopting evidence-based interview techniques among law enforcement investigators.HypothesesWe hypothesized that a procedurally fair organizational climate would predict support for organizational change, mediated by organizational identification and perceived legitimacy, and that outcome oriented factors (i.e., rewards, sanctions) would predict support for organizational change, but directly and to a lesser extent. MethodsStudy 1 surveyed law enforcement investigators (N = 711) about their attitudes towards and behaviors within their organization (i.e., perceived procedural fairness of one’s organization, identification, legitimacy, compliance, empowerment, and extra-role behavior). Study 2 conceptually extended this survey to interviewers (N = 71) trained in a new, evidence-based interviewing approach adding likelihood of future use of the novel interviewing approach as an outcome. ResultsIn Study 1, the more investigators thought their organization had a procedurally fair climate, the more they identified with the organization and perceived it as legitimate. Framing compliance, empowerment and extra-role behavior as associated with openness to change, we found that legitimacy predicted organizational compliance and tendency toward extra-role behavior (i.e., going “above and beyond”), while level of identification predicted feelings of empowerment and extra-role behavior. Study 2, partially replicated findings from Study 1, and found that motivation to attend the training also predicted likelihood of future use. ConclusionsThese studies highlight the value of a procedurally just organizational climate framework in understanding law enforcement interrogators’ propensity towards implementing new evidence-based interrogation techniques.

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“…Second, will people trust the police to use this technology appropriately? A growing body of research has explored public trust as a critical factor that shapes public attitudes and acceptance towards police uptake of new technology (see among many others Ariel et al, 2018 ; St Louis et al, 2019 ; Meijer & Wessels, 2019 ; Ridgeway, 2019 ; Bradford et al, 2020 ). Such trust is of course not “free-floating” or entirely prior to the development under consideration, but is developed via the direct, vicarious and mediated experiences people have of policing (Jackson et al, 2013 ).…”

Section: Introductionmentioning

confidence: 99%

Artificial fairness? Trust in algorithmic police decision-making

et al. 2021

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Objectives Test whether (1) people view a policing decision made by an algorithm as more or less trustworthy than when an officer makes the same decision; (2) people who are presented with a specific instance of algorithmic policing have greater or lesser support for the general use of algorithmic policing in general; and (3) people use trust as a heuristic through which to make sense of an unfamiliar technology like algorithmic policing. Methods An online experiment tested whether different decision-making methods, outcomes and scenario types affect judgements about the appropriateness and fairness of decision-making and the general acceptability of police use of this particular technology. Results People see a decision as less fair and less appropriate when an algorithm decides, compared to when an officer decides. Yet, perceptions of fairness and appropriateness were strong predictors of support for police use of algorithms, and being exposed to a successful use of an algorithm was linked, via trust in the decision made, to greater support for police use of algorithms. Conclusions Making decisions solely based on algorithms might damage trust, and the more police rely solely on algorithmic decision-making, the less trusting people may be in decisions. However, mere exposure to the successful use of algorithms seems to enhance the general acceptability of this technology.

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Live Facial Recognition: Trust and Legitimacy as Predictors of Public Support for Police Use of New Technology

Cited by 26 publications

References 31 publications

Mitigating COVID-19 in a Nationally Representative UK Sample: Personal Abilities and Obligation to Obey the Law Shape Compliance with Mitigation Measures

Mitigating COVID-19 in a Nationally Representative UK Sample: Personal Abilities and Obligation to Obey the Law Shape Compliance with Mitigation Measures

On the Importance of a Procedurally Fair Organizational Climate for Openness to Change in Law Enforcement

Artificial fairness? Trust in algorithmic police decision-making

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