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Human-AI Interaction, 7.5 Higher education credits

Människa-AI interaktion, 7,5 Högskolepoäng

Established: 2023-04-12

Established by: Department of Engineering Science

Applies from: H23

Learning outcomes

After completing the course, the student should be able to:

Knowledge and understanding

• explain the fundamental limitations of human perception, cognition, and (re-)action and give examples of how they affect user interface design.
• explain key differences (w.r.t. how they can support different kinds of human activities) between some established and emerging interaction paradigms.
• show some insight and ability to provide examples of challenges in using AI algorithms and human agents together for controlling complex digital processes and systems, from a software engineering, ethical, and legal perspective.
• demonstrate understanding of the key strengths and weaknesses of various methods used in the iterative design of interactive systems.

Skills and abilities

• systematically develop, evaluate, and document a user interface component towards an AI-based interactive system intended to split control of time-and-space critical processes between human agents and the system in an the best possible way.
• research and argue for decisions on the potential use of emerging sensor and interaction technology for reaching communication efficiency and safety goals of an interactive system, taking human factors into consideration.
• read and understand the basics of international and national rules and regulations in relation to autonomous systems.
• choose suitable research and development methods for addressing open questions when driving iterative human-centered system development processes.

Judgement and approach

• reflect on the need for understandable AI-based interactive systems and on the ethical aspects of automating all or parts of potentially hazardous processes.
• look beyond partial, technical, and functional requirements when designing complex AI-based interactive systems, including user experience (UX) factors, and acknowledging the serendipity and unpredictability of human behaviour.

Entry requirements

General entry requirements and approved result from the following course/courses:

STB600-Sensor Technology and Image Analysis and

IAI600-Introduction to Artificial Intelligence and Machine Learning and

BSD600-Big Data Processing and Analysis or the equivalent.

The forms of assessment of student performance

Project including oral group presentation and individually written report. Mandatory seminars.

Course contents

The course introduces the student to the challenges involved, and methods for overcoming those challenges, when designing and developing usable, efficient, and safe interfaces for human users of interactive systems. The focus is on systems that exhibit at least partial autonomous behavior based on Artificial Intelligence.

Theoretical part

• Research methodology: research questions, hypothesis, user experience (UX) goals; evaluation methods (formative, final; quantitative, qualitative; simulation); experimental design, analysis; documentation
• Human factors: limitations of human perception, cognition, and (re-)action; multimodal, peripheral, and implicit human-computer interaction
• Established and emerging interaction paradigms, e.g. PC WIMP interaction paradigm (Windows, Icons, Menus, Pointing device); smartphone touch interaction paradigm; intervention user interfaces
• Emerging interaction technologies, e.g. Augmented Reality; biometric sensor technologies incl. eye tracking
• Human-centered AI: explainable AI; the complexity of human-AI co-decision making incl. system-level risks; ethical aspects; legal aspects
• The iterative design process of interactive systems: conceptualization/requirements gathering, prototyping, evaluation

Practical part

• Group project including conceptualizing, prototyping, and evaluating a user interface to a (semi-)autonomous process. Individually performed exercises (labs). Active participation in discussion seminars.

Other regulations

Course grading: F/Fx/E/D/C/B/A - Insufficient, Insufficient- more work required before the credit can be awarded, Sufficient, Satisfactory, Good, Very Good, Excellent

Course language: The teaching is conducted in English.

General rules pertaining to examination at University West are available at www.hv.se.

If the student has a decision/recommendation on special support due to disability, the examiner has the right to examine the student in a customized examination form.

Cycle

Second cycle

Progressive specialization

A1F - second cycle, has second-cycle course/s as entry requirements

Main field of study

Automation, Computer Engineering, Computer Engineering