AI Ethics & Governance for IT Management 

This course equips IT professionals with the knowledge and skills to navigate the ethical and governance considerations surrounding Artificial Intelligence (AI) in IT management. You'll explore core ethical principles, potential biases in AI systems, and best practices for implementing responsible AI practices within your IT department. This empowers you to make informed decisions about AI adoption and ensure its use aligns with ethical and organizational values. 

• Explain the core ethical principles relevant to AI development and deployment, such as fairness, accountability, transparency, and privacy.

• Identify potential biases that can arise in AI systems used for IT management tasks and understand their impact on decision-making.

• Analyze the legal and regulatory landscape surrounding AI, focusing on relevant guidelines and potential compliance considerations for IT operations.

• Develop strategies for mitigating bias in AI models used within IT management and promoting fairness in algorithmic decision-making.

• Design and implement frameworks for responsible AI governance within your IT department, outlining clear roles and responsibilities for ethical AI use.

• Evaluate the potential societal and organizational impacts of AI in IT management and consider strategies for responsible AI adoption.

• Communicate effectively about AI ethics and governance principles to various stakeholders within the IT department and beyond.

1. The Ethical Landscape of AI in IT Management:

• The Ethics of AI: Introducing core ethical principles in AI development and deployment, focusing on fairness, accountability, transparency, and privacy in the context of IT management tasks.

• Understanding Bias in AI: Exploring how bias can creep into AI systems and its potential impact on decision-making within IT (e.g., biased hiring algorithms).

• Case Study 1: Analyzing a real-world scenario of bias in an AI system used for IT resource allocation, highlighting the ethical implications and potential mitigation strategies.

• Interactive Workshop: Identifying potential biases in pre-trained AI models relevant to IT management tasks and exploring techniques for bias detection and mitigation.

• Guest Speaker Session: Inviting an AI ethics expert to discuss the evolving landscape of AI ethics principles and their application within businesses.

2. Governance & Responsible AI Practices in IT:

• The Regulatory Landscape: Understanding the legal and regulatory considerations surrounding AI, focusing on relevant guidelines and potential compliance requirements for IT operations (e.g., GDPR, Algorithmic Justice League principles).

• Governance Frameworks for Responsible AI: Exploring frameworks and best practices for implementing responsible AI governance within your IT department, including risk assessment, human oversight, and auditing processes.

• Designing an AI Ethics Policy: Developing a practical AI ethics policy for your IT department, outlining clear guidelines for ethical AI development, deployment, and use.

• Communicating AI Ethics: Learning strategies for effectively communicating AI ethics principles and governance practices to diverse audiences within the IT department and beyond (e.g., senior management, technical teams).

• Course Wrap-up & Group Project Presentations: Teams develop a plan for implementing responsible AI practices within a specific IT management task. The plan should consider bias mitigation strategies, governance protocols, communication strategies, and potential ethical considerations for the chosen scenario.

• Basic understanding of AI concepts and technologies

• Familiarity with the Healthcare & Life Sciences industries and their operations

• Knowledge of project management and risk assessment principles is beneficial but not required