My Life for A Voice: The Influence of Voice on Health-Care Decisions

Mentovich, Avital; Rhee, Eunho; Tyler, Tom R.

doi:10.1007/s11211-014-0201-y

Cited by 20 publications

(14 citation statements)

References 36 publications

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“…Besides the attitudinal measures, we investigated whether participants will oppose the use of autonomous algorithms leading the decision-making process by displaying behavior that is costly to themselves. Specifically, we investigated to what extent participants were willing to pay to prevent an autonomous algorithm from having the final voice in the decision being made (i.e., measuring their willingness to sacrifice personal resources to ensure influence in the decision-making process by acquiring voice; Mentovich et al, 2014). Measuring such behavior can provide strong evidence to show how far human employees may be willing to go in opposing the adoption of autonomous algorithms in decision-making.…”

Section: Study 1: Validating the Phenomenonmentioning

confidence: 99%

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Human–Algorithm Collaboration Works Best if Humans Lead (Because it is Fair!)

Cremer

McGuire

2021

Soc Just Res

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Autonomous algorithms are increasingly being used by organizations to reach ever increasing heights of organizational efficiency. The emerging business model of today therefore appears to be one where autonomous algorithms are gradually expanding their occupation into becoming a leading decision-maker, and humans by default become increasingly more subordinate to such decisions. We address the question of whether this business perspective is consistent with the sort of collaboration employees want to have with algorithms at work. We explored this question by investigating in what way humans preferred to collaborate with algorithms when making decisions. Using two experimental studies (Study 1, n = 237; Study 2, n = 684), we show that humans consider the collaboration with autonomous algorithms as unfair when the algorithm leads decision-making and will even incur high financial costs in order to avoid this. Our results also show that humans do not want to exclude algorithms entirely but seem to prefer a 60-40% human-algorithm partnership. These findings contrast the position taken by today's emerging business model on the issue of automated organizational decision-making. Our findings also provide support for the existence of an implicit theory-held by both present and future employees-that humans should lead and algorithms follow.

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Section: Study 1: Validating the Phenomenonmentioning

confidence: 99%

“…To do this, two "strategic plan" options were presented to participants for how they can make this decision (cf. Mentovich et al, 2014). 1 The first decision for participants was to choose between these two plans.…”

Section: Design and Proceduresmentioning

confidence: 99%

Human–Algorithm Collaboration Works Best if Humans Lead (Because it is Fair!)

Cremer

McGuire

2021

Soc Just Res

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“…While voice is often is conceptualized as part of procedural fairness (Mentovich, Rhee, & Tyler, 2014;Tyler, 2007Tyler, -2008, listening to and taking the time to understand people's interests also may represent a manner by which care, respect, and concern can be shown to others (Tyler & Lind, 1992) and thus may meet people's needs for connections and belongingness (Baumeister & Leary, 1995;De Cremer & Alberts, 2004).…”

Section: Trust Versus Trustworthinessmentioning

confidence: 99%

The dimensionality of trust-relevant constructs in four institutional domains: results from confirmatory factor analyses

PytlikZillig¹,

Hamm

Shockley

et al. 2016

Journal of Trust Research

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“…Such depoliticization can improve the quality and impartiality of policy implementation, and it should improve political credibility (Batory 2012;Knott and Miller 2006;Majone 2002). Impartiality and fair process are important factors influencing overall satisfaction; some authors argue that process even outweighs outcomes in terms of influence on satisfaction (Braga et al 2014;Mentovich, Rhee, and Tyler 2014).…”

Section: Three Mechanismsmentioning

confidence: 99%

Autonomous Agencies, Happy Citizens? Challenging the Satisfaction Claim

Overman

2016

Governance

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Is the delegation of public services to semi‐autonomous agencies associated with increased citizen satisfaction? This article assesses three theoretical routes that might link the two: responsiveness, credible commitment, and blame deflection. The article draws on data from the European Social Survey and an expert survey about delegation of tax and police services to semi‐autonomous agencies in 15 countries. No supporting evidence was found for the responsiveness and credible commitment theories. Yet semi‐autonomous agencies sometimes can absorb or deflect blame for bad performance. In the tax case, dissatisfied service users blame the agency, rather than the government. The presence of an agency worked as a scapegoat for dissatisfied service users and resulted in less dissatisfaction with the government in countries where tax services were delegated.

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My Life for A Voice: The Influence of Voice on Health-Care Decisions

Cited by 20 publications

References 36 publications

Human–Algorithm Collaboration Works Best if Humans Lead (Because it is Fair!)

Human–Algorithm Collaboration Works Best if Humans Lead (Because it is Fair!)

The dimensionality of trust-relevant constructs in four institutional domains: results from confirmatory factor analyses

Autonomous Agencies, Happy Citizens? Challenging the Satisfaction Claim

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