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Elizabeth has a background in academic research and training in developmental psychology, social psychology, and cognitive psychology. She has over 10 years of research experience and loves to analyze data. Elizabeth is passionate about accessibility and inclusive design. She has a bachelor’s degree in psychology and mathematics from Ripon College and a PhD in Psychology from the University of Washington.
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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 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.
To truly deliver on the promise of AI, developers need to keep the end users in mind. By integrating three components of context, interaction, and trust, AI can be the runaway success that futurists predict it will be.
A stronger recruiting strategy that includes relationships with patient support groups and clinical treatment centers can provide better access to difficult-to-reach patient populations. Being intentional about how you plan the logistics of your human factors and user research can mitigate risks to validity introduced by biases.