User Experience Now Includes Machine Experience

User experience now includes a new user segment, machines and software. This “machine experience” occurs when algorithms engage with human structures, designs and content. However, machine users do not act, engage or think like human ones. UX for machine intelligence is an experience that is calculated, not observed. It is predicted based on past behavior rather than informed by human understanding. It is determined by machine intelligence rather than guided by empathetic, collaborative design thinking. As artificial intelligence and machine learning increase in power and prevalence, how can we ensure that it serves human needs as well as fulfill its instructions? In this session, we will explore the intersections between AI, information architecture, design, user experience and content strategy.
Who is this presentation for?
Developers, data scientists and computer scientists that want a deeper understanding of human information behavior and human engagement factors. Business leaders and managers who want a more complete understanding of the design and development of AI systems.
Prerequisite knowledge:
none
What you'll learn?
How AI systems use information architecture, user engagement and content structures to satisfy programmed requirements. How to accommodate machine users to achieve shared outcomes.

Marianne Sweeny considers herself a Search Information Architect (IA), that would be an IA with deep experience in UX, search engine optimization (SEO) and content strategy. Marianne first started advocating the relationship between information architecture, user experience and search engines in 2007. Google converted her seeming heresy to dogma with its Panda update in 2011. She is passionate about dissolving the silos between information architecture, content strategy and Web development to create a more unified approach to solving user needs for an optimal user experience. Spring quarter finds Marianne teaching INFX 544 Introduction to Information Retrieval at the University of Washington Information school. She is past president of the Information Architecture Institute and a frequent speaker at UX and digital marketing conferences to further understanding and awareness of AI history and development. She is determined to get more IA, UX and content professionals aware of their influence over the development and performance of AI systems so that they can contribute to the development of these key technologies.