Amanda L. Wilford

ChatGPT, a language-learning model chatbot, has garnered considerable attention for its ability to respond to users’ questions. Using data from 14 countries and 186 institutions, we compare ChatGPT and student performance for 28,085 questions from accounting assessments and textbook test banks. As of January 2023, ChatGPT provides correct answers for 56.5 percent of questions and partially correct answers for an additional 9.4 percent of questions. When considering point values for questions, students significantly outperform ChatGPT with a 76.7 percent average on assessments compared to 47.5 percent for ChatGPT if no partial credit is awarded and 56.5 percent if partial credit is awarded. Still, ChatGPT performs better than the student average for 15.8 percent of assessments when we include partial credit. We provide evidence of how ChatGPT performs on different question types, accounting topics, class levels, open/closed assessments, and test bank questions. We also discuss implications for accounting education and research.

We adopt a historical perspective to understand the current landscape of accountability and governance mechanisms. In adopting assurance as the umbrella concept for audit and internal control, we explore how the notion of accountability ("accountability for what") and the beneficiaries of corporate accountability ("accountability to whom") have changed over time, leading to the re-definition of "old" mechanisms of accountability and governance and the development of new mechanisms ("accountability through"). We then provide an overview of recent studies examining how these mechanisms contribute to accountability and governance. We show that the recent trend of combining traditional financial reporting with other reporting activities in an integrated report is questioning the traditional boundaries among the three mechanisms, challenging the attempts to compartmentalize them ("combined assurance"). The chapter concludes by proposing a taxonomy as a tool to help conceptually organize the recent debates on assurance, audit, and internal control practices.

We examine the internal and external benefits associated with the remediation, or correction, of material weaknesses in internal controls over financial reporting. We document that firms that remediate material weaknesses exhibit higher performance and reporting quality than firms that never reported any weaknesses. These results suggest that the remediation of material weaknesses, an indication of an improved internal control system, is associated with internal benefits. Moreover, we find that remediating firms experience significantly lower audit fees and betas (i.e. external costs) than non-material weakness firms. However, these lower external costs are contingent on a firm's level of performance and information quality. These results suggest that remediation offers firms a chance to re-examine and correct their internal controls and this leads to better performance and information quality. Furthermore, external stakeholders are not necessarily swayed by remediation alone but need to observe tangible evidence of the corrected internal control system before reassessing a firm's risk downward.

The primary objective of the current study is to empirically reexamine the relation between material weaknesses in internal control (MW) and cost of equity (CE). We direct particular emphasis to the way non-remediation, as well as remediation, of MW affects a firm's CE. This study utilizes a dataset that contains a large sample of second-year MW non-remediation cases, as well as third-, fourth-, and fifth-year non-remediation cases. The findings provide evidence that reporting MW, absent any remediation, in multiple consecutive years has a significant negative impact on CE. However, the current study also shows that the market views favorably a reduction in the number of MW (i.e., partial remediation). Our study helps to reconcile conflicting results in the literature devoted to the relation between MW and CE. JEL Classifications: M41; M42. Data Availability: Available from sources identified within the article.