Remarks on Lydenberg’s “Reason, Rationality and Fiduciary Duty”

Eccles, Neil Stuart

doi:10.1007/s10551-016-3254-z

Cited by 2 publications

(3 citation statements)

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“…Algorithmic decision-making enforcing a formal rationality may imply the end of human (and thus moral) choices, not only through the suppression of substantive rationality but also through the transformation of substantive rationality into formal rationality via formalisation. In other words, the aim of achieving ethical AI poses challenges predominantly to its specific formalisation (Eccles, 2016; Lydenberg, 2013) as in order to “teach” AI-based algorithms human morality, this morality must first be conceptualised (formalised) in a manner that can be learnt, thus processed, by an algorithm (Lindebaum et al ., 2016; Lindebaum et al. , 2020).…”

Section: Discussion: Contributions Implications and Outlookmentioning

confidence: 99%

Artificial intelligence based decision-making in accounting and auditing: ethical challenges and normative thinking

Lehner

Ittonen²,

Silvola³

et al. 2022

AAAJ

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PurposeThis paper aims to identify ethical challenges of using artificial intelligence (AI)-based accounting systems for decision-making and discusses its findings based on Rest's four-component model of antecedents for ethical decision-making. This study derives implications for accounting and auditing scholars and practitioners.Design/methodology/approachThis research is rooted in the hermeneutics tradition of interpretative accounting research, in which the reader and the texts engage in a form of dialogue. To substantiate this dialogue, the authors conduct a theoretically informed, narrative (semi-systematic) literature review spanning the years 2015–2020. This review's narrative is driven by the depicted contexts and the accounting/auditing practices found in selected articles are used as sample instead of the research or methods.FindingsIn the thematic coding of the selected papers the authors identify five major ethical challenges of AI-based decision-making in accounting: objectivity, privacy, transparency, accountability and trustworthiness. Using Rest's component model of antecedents for ethical decision-making as a stable framework for our structure, the authors critically discuss the challenges and their relevance for a future human–machine collaboration within varying agency between humans and AI.Originality/valueThis paper contributes to the literature on accounting as a subjectivising as well as mediating practice in a socio-material context. It does so by providing a solid base of arguments that AI alone, despite its enabling and mediating role in accounting, cannot make ethical accounting decisions because it lacks the necessary preconditions in terms of Rest's model of antecedents. What is more, as AI is bound to pre-set goals and subjected to human made conditions despite its autonomous learning and adaptive practices, it lacks true agency. As a consequence, accountability needs to be shared between humans and AI. The authors suggest that related governance as well as internal and external auditing processes need to be adapted in terms of skills and awareness to ensure an ethical AI-based decision-making.

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Section: Discussion: Contributions Implications and Outlookmentioning

confidence: 99%

Artificial intelligence based decision-making in accounting and auditing: ethical challenges and normative thinking

Lehner

Ittonen²,

Silvola³

et al. 2022

AAAJ

View full text Add to dashboard Cite

show abstract

“…This Hawley described as "more of a potentiality than a completed actuality" (Hawley, 2015:22). And, as I have already argued in a previous article, if one is looking for empirical evidence to support this, it is reasonably safe to assume that the interests of the roughly 750 million people who, according to the World Bank (2016) live on less than $1.90 per day, will never be meaningfully represented by business manager fiduciaries (Eccles, 2018).…”

Section: A Premise From Fiduciary Dutymentioning

confidence: 93%

“…There is, however, a somewhat more implicit perspective. As I have noted previously, to be completely exhaustive in considering this duty of loyalty, one in fact needs to contemplate the interests of three participants or groups of participants (Eccles, 2018). There are the beneficiaries and the fiduciaries, but there are also those outside of the fiduciary relationship.…”

Section: A Premise From Fiduciary Dutymentioning

confidence: 99%

Overcoming constraints imposed by fiduciary duties in terms of justice as a “Leadership Challenge that Matters”

Eccles

2018

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This article focuses on the issue of justice as a challenge facing business and society. I advance a simple deductive argument based on two premises. The first emerges out of theories of justice and holds that fairness, as a foundational basis for justice, demands impartiality or the avoidance of bias. The second emerges out of fiduciary law and holds that the duty of loyalty owed by managers to serve the interests of investors is fundamentally partial or biased. The conclusion is the troubling fact that the fiduciary duty of loyalty owed by managers to serve the interests of investors appears to be incompatible with the demands of justice. Having presented this, I describe the impartiality tools of Rawls' veil of ignorance and Adam Smith's impartial spectator and discuss how these might be applied in this context. I speculate that while Smith's impartial spectator is absolutely incommensurable with managers' fiduciary duty of loyalty, Rawls' veil of ignorance might be used to imagine a synthesis between this duty of loyalty and the impartiality demands of justice-in theory at least. And finally, as a parting shot, I wonder whether the real "Leadership Challenge that Matters" isn't the gap between theory and reality. Justice … is the main pillar that upholds the whole edifice. If it is removed, the great, the immense fabric of human society, the fabric which to raise and support seems in this world, if I may say so, to have been the peculiar darling care of Nature, must in a moment crumble into atoms.

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Remarks on Lydenberg’s “Reason, Rationality and Fiduciary Duty”

Cited by 2 publications

References 24 publications

Artificial intelligence based decision-making in accounting and auditing: ethical challenges and normative thinking

Artificial intelligence based decision-making in accounting and auditing: ethical challenges and normative thinking

Overcoming constraints imposed by fiduciary duties in terms of justice as a “Leadership Challenge that Matters”

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