![]() investigate how the acceptance of AI as a replacement for human decision-makers is influenced by perceived impartiality. Based on the perceptions of laypeople, Claudy et al. Leben focuses on the importance of explanations in AI decision-making and explores the role of counterfactuals in fair deliberations. Three papers address the challenges of mitigating bias and promoting fairness in algorithmic decision-making. On the other hand, AI systems reflect and amplify societal biases present in the data on which they are trained. On the one hand, AI algorithms often operate as “black boxes”, making it challenging to understand how decisions are made and whether or how to hold them accountable for potential biases or errors. Two other salient ethical topics for AI use in business refer to transparency and bias. AI can play a crucial role in enhancing ethical decision-making by serving as a mirror that reflects our biases and flaws, ultimately helping humans gain a better understanding of ethical choices and behaviors. In the same vein, De Cremer and Narayanan advocate retaining human responsibility in decision-making despite AI advancements. Thus, they pave the way for a deeper reflection on human and artificial intelligence interaction. They suggest examining moral agency and AI in three critical points, namely: autonomy, right of explanation, and value alignment. Exploring parallels between AI agency and corporate agency from legal, moral, and psychological perspectives could shed light on this complex subject.īertoncini and Serafim argue that as AI becomes more integral to our lives, AI ethics should no longer be viewed as peripheral but rather as an intrinsic requirement. This requires investigations into the extent to which moral attribution applies to AI, and whether recognizing AI agency necessitates a reframing of ethical frameworks. ![]() With self-driving vehicles, robotic caregivers, autonomous weapons, and so forth concerns about loss of control loom large. However, AI systems are designed precisely to make decisions autonomously. Moral agency attribution has traditionally been reserved for humans possessing rationality and freedom. It identifies the main ethical concerns and organizes them into five topic clusters: foundational issues transparency, privacy, and trust bias, preferences, and justice jobs, employment and automation and lastly, social media, participation and democracy.Īmong foundational ethical issues, autonomy in decision-making is one of the most challenging. ![]() Through this selection of papers, we uncover the ethical implications of AI in business and shed light on responsible governance practices to address them.ĭaza and Ilozumba's paper conducts a comprehensive survey of business literature to identify the most influential journals, articles, and authors in AI ethics. And Tesla's autonomous systems have been involved in fatal accidents, leading to calls for greater public scrutiny. ![]() Microsoft's chatbot, Tay, had to be discontinued due to racist and misogynistic remarks. Amazon's AI-driven recruitment tool demonstrated bias against women. Several high-profile incidents have underscored the ethical challenges associated with AI adoption in business. However, this growing reliance on AI raises significant ethical concerns and demands careful attention from managers and researchers alike. These applications employ data-trained algorithms (“machine learning”) with minimal human intervention. Similarly, Tesla's Advanced driver-assistance systems contribute to safer transport. Companies like YouTube, Amazon, Google, and Facebook leverage AI to personalize user experiences, while platforms like Uber and Lyft use it to match passengers with drivers and determine pricing. This Research Topic on Artificial Intelligence in Business delves into the multifaceted ethical dimensions of AI governance, exploring a variety of challenges and opportunities.Īrtificial intelligence (AI) has become increasingly prevalent in businesses, revolutionizing how decisions are made and impacting various sectors such as e-commerce, transportation, and healthcare.
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