AI Ethics & Governance for Responsible Customer Experience (CX)
Course Overview:
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.
Learning Objectives:
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.
Course Highlights:
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.
Prerequisites:
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