We Will Talk About Our Assigned Text And Articles

We Will Talk About Our Assigned Text And Articlereadings See Syllabus

We will discuss our assigned texts and article readings based on the syllabus, focusing on critical ethical concerns and business situations. The discussion should include the Collins/Kanashiro reading (chapter 6), Ganesan (chapter 4), and articles listed on the syllabus. Specifically, analyze at least one example of Moral Intensity to deepen the discussion. The focus is on understanding ethical decision-making in business contexts and evaluating different ethical theories.

Paper For Above instruction

The purpose of this paper is to analyze ethical decision-making within business environments by examining key texts and articles as outlined in the syllabus. The discussion will synthesize perspectives from Collins and Kanashiro’s chapter on ethical decision-making, Ganesan’s insights on artificial intelligence (AI) and its business implications, and additional related articles. Central to the discussion is the application of at least one example of Moral Intensity, a framework used to evaluate the ethical urgency of business decisions.

Beginning with Collins and Kanashiro’s work, their chapter emphasizes that ethical decision-making involves multiple factors such as moral awareness, moral judgment, and moral motivation. They argue that organizations benefit from fostering an ethical culture that supports transparency, accountability, and ethical reasoning. Their model highlights that decision-making is influenced by individual biases, organizational pressures, and contextual factors, which can either strengthen or weaken moral choices in business settings. Their framework also underscores the importance of leadership in modeling ethical behavior and establishing codes of conduct as preventive measures against unethical practices.

Ganesan’s chapter on AI explores the emerging ethical issues associated with artificial intelligence in business. With AI systems becoming integral to decision-making processes, ethical concerns about transparency, bias, accountability, and the potential for harm become more pronounced. Ganesan advocates for a business case that aligns AI development with moral principles, emphasizing that AI should be designed and deployed to benefit society while safeguarding human rights. Her discussion emphasizes the importance of incorporating ethical considerations into AI strategy—particularly the recognition of AI systems as moral or justice agents, which raises questions about responsibility and moral oversight.

The article by Waser (2012) extends this discussion by emphasizing that safety and morality require recognizing self-improving machines not only as tools but as moral and justice agents that influence organizational and societal outcomes. Rossi’s work (2019), “Building Trust in Artificial Intelligence,” further supports the importance of establishing trustworthiness in AI systems through transparency, fairness, and accountability. These insights suggest that ethical concerns in AI business applications are not merely technical issues but moral challenges that require deliberate ethical reflection and action.

A core component of ethical analysis in business involves evaluating the strengths and weaknesses of different ethical theories. Typically, six prominent theories are considered: utilitarianism, rights-based ethics, justice-based ethics, virtue ethics, care ethics, and the ethical egoism. Each has unique strengths. Utilitarianism emphasizes maximizing overall happiness, which provides a pragmatic framework for decision-making that considers broad societal impacts. Rights-based ethics focus on respecting individual rights, safeguarding personal autonomy in business decisions. Justice-based ethics prioritize fairness, ensuring equitable treatment and resource distribution. Virtue ethics emphasizes moral character, promoting integrity and virtues like honesty and courage. Care ethics centers on relationships and responsibilities, fostering compassion and empathy in organizational decision-making. Ethical egoism advocates for self-interest but can be problematic when it conflicts with societal or organizational well-being.

However, warning signs of approaching unethical decisions are critical markers for early intervention. These include conflicts of interest, pressure to meet unrealistic targets, concealment of information, and rationalizations that justify questionable actions. Recognition of these signs allows organizations to implement corrective measures before decisions result in harm, reputation damage, or legal consequences. For example, excessive focus on profit at the expense of ethical standards often precedes scandals, emphasizing the need for strong ethical oversight.

In conclusion, understanding and applying multiple ethical theories enhances the ability of businesses to navigate complex moral landscapes. By recognizing warning signs, emphasizing ethical culture, and aligning strategic goals with moral principles—particularly in emergent fields like AI—organizations can foster trust, sustainability, and social responsibility. Integrating these perspectives is essential for developing resilient and principled business practices.

References

• Collins, D., & Kanashiro, P. (2021). Business Ethics: Best Practices for Designing & Managing Ethical Organizations (3rd ed.). SAGE Publications.
• Ganesan, K. (2022). The Business Case for AI. Opinosis Analytics Pub.
• Rossi, F. (2019). Building Trust in Artificial Intelligence. Retrieved from [URL]
• Waser, M. R. (2012). Safety and morality require the recognition of self-improving machines as moral/justice patients & agents. OneSearch.
• Rainey, H. G. (2009). Understanding and Managing Public Organizations. Jossey-Bass.
• Beauchamp, T. L., & Childress, J. F. (2019). Principles of Biomedical Ethics. Oxford University Press.
• Shaw, W. H. (2022). Business Ethics: A Text and Cases Approach. Cengage Learning.
• Spinello, R. A. (2019). Cyberethics: Morality and Law in Cyberspace. Jones & Bartlett Learning.
• Freeman, R. E. (2010). Strategic Management: A Stakeholder Approach. Cambridge University Press.
• Benjamin, R. (2019). Race After Technology: Abolitionist Tools for the New Jim Code. Polity Press.