AI Ethics & Governance for Responsible Customer Experience (CX) 

This course equips Customer Experience (CX) and Customer Service Management (CSM) professionals with a foundational understanding of AI Ethics and Governance. You'll explore the ethical considerations surrounding AI use in CX initiatives and governance frameworks that ensure responsible and trustworthy implementation. 

• Explain the core principles of AI Ethics and their importance in ensuring responsible AI development and deployment for CX applications.

• Identify potential ethical challenges associated with AI in CX, such as bias, fairness, and privacy concerns.

• Understand different AI Governance frameworks and their role in promoting responsible and accountable AI use within organizations.

• Apply ethical considerations to evaluate and implement AI solutions for enhancing customer experiences.

• Develop strategies for mitigating potential risks and promoting transparency in AI-powered CX initiatives.

1. The Ethical Landscape of AI in CX:
   
   

• Introduction to AI Ethics: Exploring the core principles of AI Ethics like fairness, accountability, and transparency, emphasizing their importance in CX applications.

• Potential Biases in AI: Understanding how bias can creep into AI models and its potential consequences for customer experience (e.g., unfair treatment, inaccurate recommendations).

• Case Study 1: Analyzing a case study of biased AI in a customer loan approval process, highlighting the importance of mitigating bias for fair treatment.

• Guest Speaker Session: Inviting an AI ethicist or legal expert to discuss the evolving landscape of AI Ethics and its implications for CX professionals.

• Group Discussion: Identifying potential ethical concerns related to AI within your department and brainstorming strategies for mitigating those concerns.

2. Frameworks for Responsible AI Governance:

• Introduction to AI Governance Frameworks: Exploring different AI Governance frameworks (e.g., EU AI Act) and their guidelines for responsible development, deployment, and use of AI.

• Implementing AI Governance Practices in CX: Learning about practical steps for implementing AI governance within your department, including risk assessment, bias detection, and explainability techniques.

• Case Study 2: Examining how a large company implemented an AI governance framework to ensure responsible use of AI in their customer service chatbots.

• Interactive Workshop: Working on a mock scenario to develop an AI governance plan for a specific CX application, considering ethical risks and mitigation strategies.

• Introduction to Explainable AI (XAI): Understanding the concept of XAI and its role in promoting transparency and trust in AI decisions impacting customer experiences.

3. Building Trustworthy AI for CX:

• Ensuring Transparency & User Control in AI-Powered CX: Discussing the importance of transparency in AI models and enabling user control over data collection and AI decision making in CX applications.

• Privacy Considerations in AI-Driven Customer Interactions: Understanding privacy concerns associated with AI and exploring strategies for protecting customer data and privacy in CX initiatives.

• Case Study 3: Analyzing a case study of a company that successfully implemented transparent and user-centric AI in their personalized product recommendation system.

• Course Wrap-up & Group Project Presentations: Teams present their chosen CX application and outline a plan for implementing AI ethically and responsibly. Their plan should consider ethical principles, governance frameworks, risk mitigation strategies, and promoting trust with customers.

• Resource Sharing: Discussing ongoing resources for staying up-to-date with AI Ethics and Governance best practices specifically for Customer Experience professionals.

• 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