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Gavin Lew on Muck Rack

Gavin Lew

Chicago, United States
As seen in: UXmatters
UX researcher & designer, Managing Partner at a global UX research consultancy and author of ‘AI and UX’
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Articles by Gavin Lew

How Many Participants Are Enough? Sample Sizes for UX Research

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By Gavin Lew
| skillshare.com
As UX researchers, we are asked tocapture experiencesand the method can vary tremendously and sample size as well. Since this course provides some of thescience behind UX, I ask that you post your project(s) so we can have a sense for the diversity of applications for UX research and accompanying same size. The best way for us to be great researchers is to have confidence in what we do and learn from each other.
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Artificial Intelligence, Supervised Learning, and User Experience

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By Robert Schumacher, Gavin Lew
| UXmatters Verified
By Robert M. Schumacher and Gavin Lew November 4, 2019 AI systems always need training data to ensure their algorithms produce the right outcomes. Such data can frequently be hard to come by. For machine-learning (ML) scientists to train artificial intelligence (AI) systems and algorithms, they need data. They collect many of the datasets they use to build AI systems from human behaviors and people’s interactions with the technology they use in their everyday lives.
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Nov 4 2019: Mobile Dark Patterns | AI, Supervised Learning, & UX | Becoming a Leader | Fintech Design Best Practices | Interactive Prototyping, Pt 3

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By Robert Schumacher, Gavin Lew, Alexey Kutsenko, Apurvo Ghosh
| mailchi.mp
Mobile Matters Mobile Dark Patterns A column by Steven Hoober In addition to the misuse, misunderstanding, and bad implementations of perfectly good UX design patterns, we’ve long understood the concept of anti-patterns. These are things that we know don’t work well for users. We’ve clearly defined and documented them so we can avoid using them.
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Improving User Acceptance of AI: The Bold Future of UX

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By Gavin Lew, Ryan Carney
| UXmatters Verified
By Gavin Lew and Ryan Carney October 22, 2018 As UX professionals, we want to see meaningful advancements in AI that deliver useful functionality to users. This is key to the success of AI. Conversations around artificial intelligence (AI) inevitably lead either to dreams of a world in which computers predict every need one might have or fears of the impending doom of humanity through a SkyNet / Ultron / War Games scenario.
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4 considerations for innovating the automotive industry

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By Gavin Lew
| gfk.com
I recently chaired the World Autonomous Vehicle Summit in Stuttgart, Germany where speakers and attendees peered into their crystal ball to understand what the future holds for the automotive industry. How do manufacturers innovate to embrace the future? What does ‘innovation’ really mean in terms of success? What impact will autonomous driving have on the industry? I reflected on these questions as applied to recent technological announcements and published research.
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