Regular inspirational models are based on stakeholders' perspectives and are limited to their imaginations of the ideal solution. My approach is based on users' reaction to extreme concepts as a tool to discuss tradeoffs, leading to a bolder vision backed by data, not stakeholder bias. In as little as one month, we have a clear view of what is desirable to users, and everyone on the team has ownership of the outcome, with their perspective represented in the design in some balanced form.
Disney wanted to rethink their cast member guest management platform to improve cast member job satisfaction. The notion was to use AI to automate recovery recommendations based on guest data to make their jobs easier. Using my process for defining a design strategy, we found that cast members thought this automation would remove the aspect of their job that provided the most satisfaction, connecting with guests. Through quick ideation of polarizing concepts of AI, we found that the cast members' basic needs were not being met, resulting in the rejection of satisfaction-based features. The best application of AI was to provide insight into park activity and create moments to connect with park guests and celebrate magic moments created by the team.
A large percentage of the work in user experience and interaction design is done in the form of lists and diagrams, but wireframes and prototypes play an important role in exploring how a series of tasks and capabilities will take shape. I believe in creating multiple diverse approaches to a problem to explore the tradeoffs, considering how it matches diverse user and business priorities. Exploration starts loose, focused on assumptions that need to be challenged and high-value features or flows. As the direction solidifies, the system structures take a larger influence to ensure a consistent tone, reuse of components, and a scalable framework.
In 2015, I created the design for a data security system that used AI to identify risks and connected events. The team asked for a design that would "visualize a threat moving through a system." I designed data visualizations to explain risk patterns and focus user attention, distilling the massive amounts of data into a simplified story. This method focused the user's exploration of the data instead of presenting a predetermined conclusion. The visual pictured here illustrates how a threat spreads through an organization, summarizing the triggering events and impacted endpoints that require triage.
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Complex systems require a more rigorous understanding of workflows and interactions between diverse digital and physical systems. It's easy to get caught up in the complexities of the way things are done now, letting existing systems drive workflows. To prevent this influence, I like to separate the human and mechanical elements, breaking existing systems into base functions and breaking existing workflows into decision points that influence behaviors. Once separated, they can be reconstructed to match the users' thought process, resulting in more intuitive and desirable products.
CertScan's global utilization spans crucial operations like cargo ports, parcel inspections, customs and border security, rail and air cargo inspections, and event security. Within each operational domain, a minimum of 5 distinct user roles with varied tasks and needs, coupled with an array of diverse data sources, demanded a design that could adapt and give users confidence when making mission-critical decisions. We tied the system together with a framework centered around visual exploration. The data visualizations were built from a consistent visual language that scaled from analyzing an individual image to tracking the efficiency of multiple sites.
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Emotions are a critical aspect of how users make decisions and behave, making emotions an important part of the design process, especially for products targeting high-stress or vulnerable use cases. I specialize in healthcare products, where emotions run high and users must remain level-headed, understand the content, and make confident decisions. While surgical products focus more on reducing distractions and stressors, patient applications need to foster trust and support while encouraging engagement. When I design for this context, I focus initial research on understanding the emotional reasons driving users' behaviors. Design solutions target the root of the behaviors with a psychology-backed approach to encourage healthy actions and empower users.
Boston Scientific offers an implant to help manage pain by disrupting nerve impulses with an electric current. This implant has been controlled by a remote in the past, but Boston Scientfic reached out to UEGroup to design an app to replace the remote and facilitate the patient journey. One of the app requirements was to collect pain scores, but we learned through patient and caregiver interviews that the act of recording pain daily made patients focus on their pain more instead of positive progress. We changed this feature to incorporate goal setting beyond pain, encouraging small wellness activities to balance the potential negative emotions associated with pain recordings with positive reflection.
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I have been designing products that use AI since 2015, using human-centered principles to create a partnership between AI and the user, helping foster trust, inform decisions, make connections, and direct AI to automate laborious tasks. The technical approach to the AI algorithms determines capabilities and required data structures that we need to embrace as designers as we define the input methods and information communication. It's our responsibility to humanize the AI, considering influences on emotions and behaviors, mirroring human working relationships, and cognition. This approach prioritizes adapting to the user instead of adapting to the technology, resulting in less hesitancy and easier-to-use products.
In 2024, UEGroup took on an experimental project to use AI to tackle dark UX patterns involved in media creation and consumption, contributing to the stress, misinformation, and lack of engagement in politics in the US. The goal of Poli was to make staying up to date on politics more approachable by controlling the emotional triggers used to drive engagement and promoting action, so users feel like they have some control over our collective future. At the start, we knew AI had a major role in summarizing and neutralizing inflammatory articles to the facts, but we found the balance of emotional regulation features and freedom to participate in stress-inducing use patterns through design iteration and research.
See the Awards pageCreating meaningful products is incredibly exciting & rewarding. I want empower more roles to have a voice in the process and feel ownership of the outcome.
