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Frontier Thinking: Designing Next Generation User Experiences

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Current trends in technology emphasize autonomous machines and anthropomorphic robots as team partners. By contrast, this talk promotes an alternative view to guide user experience design towards systems that turn experts into super-experts, enabling higher levels of performance while extending the remarkable human creative capacities by providing control over increasingly powerful tools.

Improved designs depend on understanding the ways that people employ Frontier Thinking, pushing beyond the limits of existing knowledge to deal with tasks and goals that are poorly defined, situations in which context is consequential, and data that is incomplete, inconsistent, or incorrect. Since the goal is to find solutions that are better than previous ones, machine learning and other artificial intelligence methods based on training data from past decisions are a useful starting point, but more is needed.

Physicians will be able to search electronic health records to find patient histories organized by treatment plans to discover unexpected positive outcomes, then adapt treatments based on each patient’s distinct needs. Teachers will be able to find successful lesson plans that they can tailor to include active learning and team project components that fit their students’ skill levels and motivation.

Frontier thinkers do more than find the best matching previous solution, they create solutions, tailored to their context, that have never existed. This is the process of innovation and discovery – building on the past, while creating or finding something new.

Since Frontier Thinking seeks to solve novel problems, create new approaches, and discover new knowledge, the new tools will allow for (1) data exploration, (2) model manipulation, and (3) combining existing ideas to create something new. Frontier Thinking tools will also provide easy access to activity logs and facilitate collaboration with colleagues. People will be at the center of activity, supported by potent tools, as they creatively take on new challenges with appropriate confidence.

BEN SHNEIDERMAN ( is a Distinguished University Professor in the Department of Computer Science, Founding Director (1983-2000) of the Human-Computer Interaction Laboratory (, and a Member of the UM Institute for Advanced Computer Studies (UMIACS) at the University of Maryland. He is a Fellow of the AAAS , ACM, IEEE , and NAI , and a Member of the National Academy of Engineering, in recognition of his pioneering contributions to human-computer interaction and information visualization. His widely-used contributions include the clickable highlighted web-links, high-precision touchscreen keyboards for mobile devices, and tagging for photos. Shneiderman’s information visualization innovations include dynamic query sliders for Spotfire, development of treemaps for viewing hierarchical data, novel network visualizations for NodeXL, and event sequence analysis for electronic health records.

Ben is the co-author with Catherine Plaisant of Designing the User Interface: Strategies for Effective Human-Computer Interaction (6th ed., 2016). With Stu Card and Jock Mackinlay, he co-authored Readings in Information Visualization: Using Vision to Think (1999). His book Leonardo’s Laptop (MIT Press) won the IEEE book award for Distinguished Literary Contribution. He co-authored, Analyzing Social Media Networks with NodeXL (Morgan Kaufmann) with Derek Hansen and Marc Smith. The New ABCs of Research: Achieving Breakthrough Collaborations (Oxford, April 2016) has an accompanying short book Twin-Win Research: Breakthrough Theories and Validated Solutions for Societal Benefit: Second Edition (2019).

Dept of Computer Science & Human-Computer Interaction Lab University of Maryland, College Park, MD, USA @benbendc

This talk is part of the Rainbow Group Seminars series.

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