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Summary
Our team at Gazzetta, a media research lab, is tackling a fundamental challenge in journalism: the disconnect between media output and community needs, particularly in restricted or distorted information environments of autocracies. We have learnt over the past years that traditional audience research has led to quant-heavy, superficial understanding, ineffective content and, ultimately, irrelevance. To address this problem, we have developed a three-stage process using AI knowledge bases to build empathy, map information needs, and analyze information flows. We have used this process to systematically review multiple information sources to build deep community understanding before product development. This methodology has helped us preserve nuance, identify knowledge gaps, and assign confidence levels to findings. Rather than treating AI as a black box solution, a thoughtful process-oriented approach can help us better understand and serve information needs, and gradually rebuild relevance.
Key Insights
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Journalists and UX researchers share the goal of understanding people and situations deeply.
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Structured queries combined with AI can deliver insights beyond traditional methods.
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Empathy and understanding the user context are crucial before identifying information needs.
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Many organizations fail because they misalign their perceptions of user needs and actual needs.
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Measurement often focuses on superficial metrics instead of understanding real user satisfaction.
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Theory of service emphasizes user needs before content creation, shifting from mere delivery to genuine utility.
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AI should enhance human judgment, not replace it; collaboration between humans and AI is key.
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Confidence levels must be assigned to findings to mitigate the risk of false certainty.
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A structured approach to research repositories can make previously unconnected data actionable.
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Iterative learning and building of research repositories can lead to cumulative knowledge beyond expensive one-off studies.
Notable Quotes
"The careful application of structured queries can reveal deeper insights than traditional methods alone."
"How many news organizations fail their users because they don't truly understand their information needs?"
"We need to understand who people are, their context, their lived experience."
"It's not about adding features we think are cool, it's about solving real problems."
"The effectiveness of our research depends on gathering diverse sources and evaluating them critically."
"Making uncertainty explicit is crucial for effective decision-making."
"Never treat AI outputs as facts; they must be critically evaluated for accuracy."
"In UX terms, this means shifting from feature-driven to user-centered design."
"AI excels at processing information, but humans remain essential for evaluation."
"Your research repositories contain treasure troves of insights just waiting to be discovered."
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