During a recent study, we asked participants how long they thought they would have to speak in order for their voice to be uniquely recognized (i.e., voice print). While their estimates varied widely - from 30 seconds to 30 minutes - most people said about three to...
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Ryan Carney
Partner
Ryan’s background is at the intersection of research and storytelling. This experience allows him to effectively find qualitative and quantitative trends with a product and craft an effective narrative around those trends. With 8 years of experience in the UX field, Ryan executed projects with multiple methods and approaches, spanning multiple industries, including automotive, energy, and consumer technology. Ryan has also worked on medical studies across various stages of development, from early formative to validation, and a wide variety of devices. A member of UXPA, Ryan has an MA in Digital Storytelling and MS in Information and Communication Sciences from Ball State University.
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- Be the student: 4 tips to be a better UX research moderator
- When building next gen fintech, start with research in Africa
- UX principles for robot design: Have we begun to baseline?
- Three things to improve acceptance of AI
- Singularity and the potential impact on UX design principles
- UX project logistics: choosing the right vendors for project success
Read our team’s latest bold insights
UX principles for robot design: Have we begun to baseline?
As the robotics industry continues to find its way into our lives, we can begin to identify UX design principles to apply to this tech to increase the acceptance of robots and improve the human-robot interaction experience.
AI benefits from GPU, not CPU advancements
A quick follow-up to our blog posts about AI… The name of the game is no longer Moore's Law where we see processors getting exponentially faster. AI technology is driven not by computing processes of the past, but from an evolution beyond central processing unit (CPU)...
The critical component missing from AI technology
The first step when developing AI is to understand the user need; but just as critical, is knowing the context in which the data is being collected.