The effect of emergent technologies on accountant`s ethical blindness

The accounting field has come under scrutiny after a number of high-profile ethical scandals dealing with organizational fraud has been tied to the profession. While several accounting standards have been established to ensure the integrity, objectivity, and professional competency of accountants; the power of the situation and individual motivations are challenges that may ethically blind accountants and result in fraud. In this paper, we explore the combinative effect of three emergent technologies: Blockchain-based, IoT-enabled and AI-empowered distributed ledger on reducing the risk of accounting ethical blindness. We examine how technical features of emergent technologies present both gains and challenges to ethical decision-making for the accounting profession. While some of these challenges can be overcome by adopting all three emerging technologies, others require social and legal interference to avoid the challenges of these technologies. Keywords: Emergent technology, accounting ethical blindness, blockchain, artificial intelligence, internet of things.

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An Exploration of Ethical Decision Making with Intelligence Augmentation

Social Sciences ◽

10.3390/socsci10020057 ◽

2021 ◽

Vol 10 (2) ◽

pp. 57

Author(s):

Niyi Ogunbiyi ◽

Artie Basukoski ◽

Thierry Chaussalet

Keyword(s):

Decision Making ◽

Ethical Decision ◽

Ethical Decision Making ◽

Future Studies ◽

Ethical Implications ◽

High Profile ◽

Financial Profile ◽

Operational Decision Making ◽

Different Characteristics ◽

Belief Statements

In recent years, the use of Artificial Intelligence agents to augment and enhance the operational decision making of human agents has increased. This has delivered real benefits in terms of improved service quality, delivery of more personalised services, reduction in processing time, and more efficient allocation of resources, amongst others. However, it has also raised issues which have real-world ethical implications such as recommending different credit outcomes for individuals who have an identical financial profile but different characteristics (e.g., gender, race). The popular press has highlighted several high-profile cases of algorithmic discrimination and the issue has gained traction. While both the fields of ethical decision making and Explainable AI (XAI) have been extensively researched, as yet we are not aware of any studies which have examined the process of ethical decision making with Intelligence augmentation (IA). We aim to address that gap with this study. We amalgamate the literature in both fields of research and propose, but not attempt to validate empirically, propositions and belief statements based on the synthesis of the existing literature, observation, logic, and empirical analogy. We aim to test these propositions in future studies.

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Artificial Intelligence in Marketing

Advances in Business Information Systems and Analytics - Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry ◽

10.4018/978-1-7998-6985-6.ch016 ◽

2021 ◽

pp. 342-365

Author(s):

Özge Sığırcı

Keyword(s):

Artificial Intelligence ◽

Decision Making ◽

Consumer Behavior ◽

Literature Review ◽

Ethical Decision ◽

Ethical Decision Making ◽

Previous Literature ◽

Human Interactions ◽

Consumer Vulnerability ◽

Shed Light

The purpose of this chapter is to shed light on the consumer-AI interaction in the marketplace. By this aim, the chapter uses a literature review approach. The previous literature examining AI from a consumer behavior perspective is reviewed, and the findings are compiled in a meaningful flow. According to the review, we see that the traditional marketplace is shaped by AI from only human-to-human interactions to human-to-AI and AI-to-AI interactions. In this new marketplace, while consumers interact with AI, they gain new experiences and feel positive or negative because of these experiences. Also, they build different relationships with AI, such as servant, master, or partner. Besides these relationships, there are still concerns about AI that are related to privacy, algorithmic biases, consumer vulnerability, unemployment, and ethical decision making.

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