Unit 1
Introduction to Ethics and Artificial Intelligence – Meaning and importance of ethics in business. Introduction to AI ethics and responsible innovation. Difference between legal compliance and ethical responsibility. Why ethics matters in AI-driven decision-making. Role of managers and organizations in ethical AI use. Overview of ethical challenges in AI adoption.
Unit 2
Ethical Issues in AI Systems – Bias and discrimination in AI systems – causes and impact. Fairness and transparency in AI-based decisions – Key concepts and why it matters. Explain ability and accountability in Responsible AI use. Key Ethical issues in automated decision-making – Bias and Discrimination – How does companies address these issues. Real-world examples of ethical failures in AI.
Unit 3
Data Ethics, Privacy, and Consent – Role of data in AI and ethical concerns. Consumer and employee data privacy. Informed consent and data ownership – Interconnection and challenges. Ethical handling of sensitive and personal data – Key practices of handling sensitive data. Impact of data misuse on brand trust and reputation – Financial and operational consequence.
Unit 4
Responsible Innovation and AI Governance – Meaning of responsible innovation. Principles of responsible AI in organizations – how do organizations implement. Role of governance and internal controls in AI use. Best practices of AI Deployment. Balancing innovation, profitability, and responsibility. Key role of leadership in promoting ethical AI culture.
Unit 5
Social Impact and the Future of Responsible AI – Impact of AI on employment, skills, and workforce. AI and social inequality. Human–AI collaboration in the workplace. Responsible AI for sustainable business and society. Emerging global and Indian perspectives on responsible AI. Role of future managers in shaping ethical AI use.