PhD Program in Computer Science and Mathematics of the University of Bari - Italy
Course: Human-Computer Interaction for AI (HCI4AI)
Credits: 3 (24 hours of lectures)
Teachers: Rosa Lanzilotti (1 credit), Berardina Nadja Decarolis (1 credit), Giuseppe Desolda (1 credit)
Teaching period: Jan-Feb 2021
Short description:Compared with traditional technologies, AI-based technologies pose different challenges from a user’s perspective. Besides the established principles of user-centered design, there are further important aspects that are peculiar to this type of system and that need to be considered during design.
AI-based systems typically have a probabilistic behavior that can confuse users, erode their confidence, and lead to the abandonment of AI technology. High-profile reports of failures, ranging from humorous and embarrassing (e.g., auto-completion errors) to more serious situations in which users cannot effectively understand or control an AI system (e.g., collaboration with semi-autonomous cars), might harm users. These factors, among others, show that designers and developers need proper knowledge as well as proper methodologies and techniques to create effective intelligent systems that may better satisfy the users. It also highlights the need for the end users to have control over the system: this can be achieved on one side by granting transparency of the system behaviour, and on the other side by empowering the end users to configure the system behaviour.
Given this scenario, it is important that future AI specialists become aware of the potential ethical and practical issues of this type of system, as well as acquire theoretical competences and methodological skills to properly design them. This requires adopting a perspective that considers the users and their needs to let them understand and control AI-based technologies.
The emphasis should not only be on specific interaction techniques (such as gestures or voice), rather on understanding how HCI methods and principles can help design “human-in-the-loop” AI systems, which implies considering who AI systems are built for and evaluating how well those systems are working.
The course aims to guide the student from the basics of Human-AI Interaction, exploring principles, challenges and methods to design AI-based systems. Then the course will focus on emerging aspects of HCI for AI, for example, the Explainability for AI systems, design of and interaction with conversational agents and more general principles for designing Human-AI Interaction. Students will be stimulated to include some topics related to their research activities.
- Introduction to Human-AI Interaction - 3h
- User-Centered Design, Usability and User eXperience (short introduction) - 4h
- Designing Human-AI Interaction: substitution vs. augmentation - 4h
- Explainability for AI systems: Data, bias, and trust - 4h
- Paradigms for Human-AI Interaction: smart interface vs. conversational (with or without anthropomorphism and its effect: uncanny valley) - 4h
- Hands-on sessions: design and prototyping of conversational agents - 5h