From Reality to World. A Critical Perspective on AI Fairness

Journal of Business Ethics - Fairness of Artificial Intelligence (AI) decisions has become a big challenge for governments, companies, and societies. We offer a theoretical contribution to consider...     

Do Auditors Accurately Predict Litigation and Reputation Consequences of Inaccurate Accounting Estimates?

To effectively manage audit risk, auditors must correctly predict the potential litigation and reputation consequences associated with inaccurate accounting estimates. Accurate predictions are critical because underestimation of negative consequences leads to excess legal exposure and overestimation leads to overauditing. Our paper examines whether auditors correctly anticipate these litigation and reputation outcomes. We provide manager‐ and partner‐level auditors with case facts from an auditor negligence lawsuit and ask them to predict the proportion of juries that will return verdicts against their firm. We then compare auditors' predictions to the actual verdicts we observe when we provide the same set of case facts to mock jurors who deliberate as part of juries. We find that auditors overestimate the likelihood of negligence verdicts, especially when audit quality is relatively high. Our supplemental measures help explain the reasons for this overestimation: auditors tend to underestimate jurors' perceptions of audit quality and willingness to attribute inaccurate estimates to situational factors. Finally, we examine auditors' predictions about how a news article about the litigation will affect their reputation with the general public. Similar to our litigation results, we find that auditors tend to overestimate the article's negative impact on auditor reputation. Collectively, our findings suggest that auditors overestimate litigation and reputation consequences resulting from inaccurate accounting estimates. This overestimation is consequential as it leads to inefficient allocation of audit resources.     

Examining the Relationship between Labor Law Compliance and Employee Perceptions,Attitudes and Behaviors

Employee Responsibilities and Rights Journal - This study examined the effect of legal compliance in the context of labor laws, and the role of organizational justice in mediating its relationship...     

Corporate climate-related voluntary disclosures: Does potential greenwash exist among Australian high emitters reports?

This study examines the issue of greenwashing among corporate high emitters subject to government scrutiny. To do so, we investigate the relationship between the actual environmental performance, measured as carbon emissions, of companies subject to the Australian National Greenhouse Energy Reporting Act 2007 (NGER) and their climate-related voluntary disclosures. To measure climate-related disclosure, we construct a climate-related disclosure index based on four prominent frameworks and score corporate report content against that Index. Using a sample of 150 companies with NGER emissions data for Years 2016 and 2017, a period that precedes the issuance of recommendations for disclosure by the Task Force on Climate-Related Financial Disclosure (TCFD), our regression results show a disappointingly low level of climate-related disclosure by most companies. We also find a negative relationship between climate-related disclosure and 1-year lagged environmental performance among companies exhibiting a year-on-year rise in carbon emissions. That is, our findings provide evidence of potential greenwashing by poor environmental performers, presumably to change negative perceptions by stakeholders, as predicted by socio-political theories. In contrast, we find no evidence of greenwashing among companies experiencing a year-on-year decrease in emissions.     

Measuring executive personality using machine-learning algorithms: A new approach and audit fee-based validation tests

We present a novel approach for measuring executive personality traits. Relying on recent developments in machine learning and artificial intelligence, we utilize the IBM Watson Personality Insights service to measure executive personalities based on CEOs’ and CFOs’ responses to questions raised by analysts during conference calls. We obtain the Big Five personality traits – openness, conscientiousness, extraversion, agreeableness and neuroticism – based on which we estimate risk tolerance. To validate these traits, we first demonstrate that our risk-tolerance measure varies with existing inherent and behavioural-based measures (gender, age, sensitivity of executive compensation to stock return volatility, and executive unexercised-vested options) in predictable ways. Second, we show that variation in firm-year level personality trait measures, including risk tolerance, is largely explained by manager characteristics, as opposed to firm characteristics and firm performance. Finally, we find that executive inherent risk tolerance helps explain the positive relationship between client risk and audit fees documented in the prior literature. Specifically, the effect of CEO risk-tolerance – as an innate personality trait – on audit fees is incremental to the effect of increased risk appetite from equity risk-taking incentives (Vega). Measuring executive personality using machine-learning algorithms will thus allow researchers to pursue studies that were previously difficult to conduct.