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.
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Christina Ambrose
Director
With a background in interdisciplinary social sciences, Christina has been trained in various qualitative research methods. Her human factors expertise includes consulting on products from early-stage exploratory research through end stage validation studies, and she has supported several successful submissions. She collaborates with clients to design programs of research and decide on optimal methodologies, while supervising individual research projects involving medical devices and digital health management platforms. Christina holds a BA in Comparative Human Development and an MA in the Social Sciences from the University of Chicago.



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Read our team’s latest bold insights
Three things to improve acceptance of AI
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.
Recruiting methods and study logistics for human factors and user research
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.
Singularity and the potential impact on UX design principles
If we are approaching a rapid technology shift as some experts predict, core UX design principles will have to be redefined to adapt to radically different interaction models.