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Understanding Public Perceptions of AI Use During the COVID-19 Pandemic

This research project addresses the scarcity of interview-based studies in Artificial Intelligence (AI) literature. We conducted 15 semi-structured interviews to delve into participants’ experiences with AI, with a specific focus on their thoughts and opinions regarding AI utilization during the novel coronavirus (COVID-19) pandemic, a global crisis. This study aims to bridge the gap in understanding how individuals perceive the role of AI in the context of a pandemic, providing crucial insights for future research and development. See the full paper here!


Role: Lead User Experience Researcher


Project Goals:

1. To gain in-depth insights into participants' experiences and perceptions of AI use during the COVID-19 pandemic.

2. To identify common themes and patterns in participants' feedback.


Methodologies Utilized:


1. Semi-Structured Interviews:

  • Conducted 15 in-depth interviews to capture nuanced perspectives and experiences related to AI usage during the COVID-19 pandemic.

  • Employed a semi-structured format to allow for flexibility and depth in participants' responses.


2. Thematic Analysis:

  • Applied thematic analysis to systematically identify and analyze recurring patterns, themes, and insights emerging from the interview data.

  • Generated meaningful categories to organize and make sense of the qualitative data.


Key Findings:


1. Positive Feedback on AI's Role in COVID-19 Crisis:

  • Majority of participants expressed positive sentiments towards AI's potential contributions during the pandemic, particularly in areas such as COVID-19 testing and monitoring vital signs.


2. Doubts about Successful Implementation in Healthcare:

  • Two out of 15 participants voiced skepticism about the successful integration of AI in healthcare contexts during the COVID-19 crisis.


3. Notable Concerns and Potential Issues:

  • Four out of 15 participants raised concerns and potential issues related to the application of AI in the context of COVID-19.


Conclusion:


This study addresses a significant gap in the existing literature by providing in-depth insights into public perceptions of AI use during the COVID-19 pandemic. The findings shed light on both the potential benefits and the apprehensions associated with AI deployment in a global health crisis. As one of the pioneering studies in this area, this research lays a solid foundation for future work, guiding the development and implementation of AI-driven solutions in healthcare and crisis response.


The semi-structured interview approach proved instrumental in uncovering rich and diverse perspectives, emphasizing the importance of qualitative research in understanding complex societal attitudes towards emerging technologies like AI. This case study demonstrates the value of user-centered research in shaping the future of AI applications in critical contexts.

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