Algorithms and Authenticity

Jago, Arthur S.

doi:10.5465/ambpp.2017.10853abstract

Cited by 11 publications

(13 citation statements)

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“…While algorithm aversion traditionally refers to the phenomenon of avoiding reliance on algorithmic systems after witnessing their performance or errors [e.g. 8,22,23], other studies have revealed negative attitudes even prior to a confrontation with the system [9,10,24]. Extant research suggests that algorithm aversion specifically manifests itself when algorithmic systems assume tasks that are considered innately human [25], are considered subjective [9,18], and might benefit from human intuition [6].…”

Section: Attitude Toward Algorithmsmentioning

confidence: 99%

“…Second, an original writing style that provides more than what is rationally required, makes an author stand out [37]. In contrast, algorithms are attributed a lack of originality, authenticity, and creativity due to their lack of conscience [22,38]. Furthermore, positive effects of disclosed algorithmic authorship on the perception of content, and hence indications for perceptions of suitable capabilities of algorithms, have only been shown in data-driven domains [1].…”

Section: Hypotheses Developmentmentioning

confidence: 99%

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Human vs. AI: Investigating Consumers’ Context-Dependent Purchase Intentions for Algorithm-Created Content

Rix¹,

Rußell²,

Rühr³

et al. 2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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Increasingly digitalized media consumption is pressuring profitability in the content industry. Technological advancements in the realm of Artificial Intelligence (AI) render the potential to cut costs by applying algorithms to create content. Yet, before implementing algorithm-created content, content providers should be aware of the impact of algorithmic authorship on consumers' intention to purchase said content. Accordingly, this study investigates user attitudes toward algorithmic content creation and their dependence on the underlying utilitarian or hedonic consumption context. In our online experiment (N=298), we find evidence for a positive effect of algorithmic authorship on consumers' purchase intention. Even though the overall purchase intention is context dependent, this algorithm appreciation is independent of the content consumption context. Our study thus suggests that consumers appreciate algorithm-created content. Our results thus provide insights into the benefits of leveraging algorithms in order to maintain content providers' profitability.

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Section: Attitude Toward Algorithmsmentioning

confidence: 99%

Section: Hypotheses Developmentmentioning

confidence: 99%

Human vs. AI: Investigating Consumers’ Context-Dependent Purchase Intentions for Algorithm-Created Content

Rix¹,

Rußell²,

Rühr³

et al. 2022

Proceedings of the Annual Hawaii International Conference on System Sciences

View full text Add to dashboard Cite

show abstract

“…This suggests not only that technologies are patterned by shifting perceptions in fairness in decision-making, but also that the broader trust humans have in algorithms is not stable (Glikson & Woolley, 2020) and is constantly evolving (for some recent empirical explorations, see Jago, 2017;Schafheitle et al, 2020). For instance, the perception of bias in algorithmic decision-making may be weak during the initial introduction of an algorithmic technology, but may become stronger as the system is used (or vice versa).…”

Section: Understanding Algorithms and Organizational Decision-makingmentioning

confidence: 99%

The Biography of an Algorithm: Performing algorithmic technologies in organizations

Glaser

Pollock

D’Adderio

2021

Organization Theory

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Algorithms are ubiquitous in modern organizations. Typically, researchers have viewed algorithms as self-contained computational tools that either magnify organizational capabilities or generate unintended negative consequences. To overcome this limited understanding of algorithms as stable entities, we propose two moves. The first entails building on a performative perspective to theorize algorithms as entangled, relational, emergent, and nested assemblages that use theories—and the sociomaterial networks they invoke—to automate decisions, enact roles and expertise, and perform calculations. The second move entails building on our dynamic perspective on algorithms to theorize how algorithms evolve as they move across contexts and over time. To this end, we introduce a biographical perspective on algorithms which traces their evolution by focusing on key “biographical moments.” We conclude by discussing how our performativity-inspired biographical perspective on algorithms can help management and organization scholars better understand organizational decision-making, the spread of technologies and their logics, and the dynamics of practices and routines.

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“…Large streams of research have looked into how individuals respond to digital technologies [6][7][8][9][10][11], and more recently algorithms [12]. While theses studies offer valuable insights of how users react to algorithms in making relatively "safe" decisionsi.e., those surrounding which either risk is low or technology is better understoodless is known about how clients respond to a service like robo advisory in a real-world setting.…”

Section: Introductionmentioning

confidence: 99%

“…Our study contributes to extant literature in several ways. Besides information systems [13,] [20], there is a growing literature in management [21], [12], [5] and strategy (e.g. [22]) interested in the changes that algorithms and predictive analytics are inducing for firms, particularly in knowledge-intensive contexts.…”

Section: Introductionmentioning

confidence: 99%

Helping or Hindering? How Clients’ Experiences Relate to Their Robo Advisory Use

2021

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Firms are increasingly introducing new business models based on digital technologies in knowledgeintensive, risky contexts that were long immune to them. In the financial industry, banks are opening themselves to robo advisory, an algorithm-based service supporting private clients' investment decisions. Based on our access to a recent data set of 11,302 clients from a leading German robo advisory provider, we have the unique opportunity to analyze how clients react to algorithm-based services in contexts with high uncertainty and risk. Guided by theorical foundations of knowledge and routines, we find clients' personal and business experiences with the focal bank to both, help and hinder their robo advisory use.

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Algorithms and Authenticity

Cited by 11 publications

References 0 publications

Human vs. AI: Investigating Consumers’ Context-Dependent Purchase Intentions for Algorithm-Created Content

Human vs. AI: Investigating Consumers’ Context-Dependent Purchase Intentions for Algorithm-Created Content

The Biography of an Algorithm: Performing algorithmic technologies in organizations

Helping or Hindering? How Clients’ Experiences Relate to Their Robo Advisory Use

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