UXD 2961 - Human-centered AI

• Demonstrate knowledge of AI history and development and its impact on human life 
• Explain how human-centered design helps create enjoyable, inclusive, responsible, and secure AI applications 
• Analyze case studies of human-centered design in AI applications in professional and social domains 
• Demonstrate awareness of AI activism and its role in shaping AI development today 
• Exercise professional integrity by reflecting on ramifications of algorithmic biases in AI datasets 
• Recognize, explain, and apply fundamental concepts and conventions of data visualization 
• Employ human-centered design and data visualization concepts to assessing and improving AI applications 

• None

• Brief history of AI 
• Algorithms in today’s life (decision-making, prediction markets, ethical, social, economic, human rights, social justice, etc.) 
• Algorithmic biases (e.g., interaction bias, latent bias, selection bias) and their implications   
• AI activism 
• Traditional AI applications (e.g., pattern recognition in images, specials, faces, signals, etc. and natural language) vs. human-centered AI applications (focus on human performance and satisfaction, customer needs, and meaningful human control) 
• Guidelines for human-centered AI systems: reliability, safety, and trustworthiness 
• The importance of data visualization 
• Types of data (factor data, numeric data, and variable data) 
• Types of data visualization (bar, pie, stacked area, and line charts, histograms, scatter plot, etc.) 
• Fundamentals of data visualization (systems and axes, color, emphasis, etc.) 
• Human-centered AI design case studies in professional domains and social structures