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Scott’s background is in qualitative research and human behavior. He has been working in research for eight years, with a particular interest in human factors research. He has conducted research in a variety of industries, including health care, automotive, and financial services, with experience in focus groups, in-lab usability testing, summative medical testing, and in-car research. Scott has an MA in global politics from Illinois State University.
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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.