Summary
Data cannot interpret the world. Only humans can. Because of that, the next evolution of AI requires a more collaborative approach to building systems. And UX researchers are uniquely positioned to build the dream team responsible for managing the data collection required for more responsible AI. Anthropology and sociology methodologies provide us the framework to interpret human behavior in a way that telemetry can't. Qualitative research leads to more socially conscious computing decisions that will impact technology companies going forward. Join this fireside conversation to discover... The power of changing one tiny acronym from "Human-Computer Interaction" to "Human-Centered Innovation" Expert recommendations for building more responsible technology What it will take to build a fundamental practice around collecting and analyzing high-quality data Practical steps you can take today to build ethical products in the future
Key Insights
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Mobility platforms in Jakarta co-exist with longstanding informal driver communities called base camps, contrary to expectations.
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Drivers in Jakarta self-organize around physical community spaces with uniforms, badges, and elections, resembling workplaces.
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Drivers developed hacked apps distributed via WhatsApp to solve gaps in official platforms, influencing corporate features.
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Technology impacts vary significantly by cultural and geographic context; assumptions from US scenarios often don’t hold elsewhere.
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Qualitative, grounded research is crucial to uncover unexpected user behaviors and contextual nuances in technology use.
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There is a research gap between what companies expect designers to build and what communities actually need.
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Ethical AI development must incorporate diverse cultural norms and contexts, beyond narrow automated evaluations of outputs.
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Researchers hold power to shape the AI development pipeline through richer, context-aware human feedback design.
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Balancing power dynamics requires building trusted relationships with communities, avoiding parachute research approaches.
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Researchers should create interdisciplinary collaborations and push for more inclusive and responsible technology practices.
Notable Quotes
"Technology impacts are never universal; what happens in New York is very different from Jakarta."
"Drivers in Jakarta built base camps with uniforms and badges, making these spaces more like a workplace."
"Drivers hacked the platform apps and created grey market solutions distributed through WhatsApp groups."
"A lot of the innovation actually comes from users rather than big companies."
"Qualitative researchers have power to unearth rich insights about why and how things happen, not just what."
"Many AI toxicity classifiers have narrow assumptions that only apply to certain communities, especially in the US."
"We need human-in-the-loop evaluations designed with cultural context, not just simple yes/no annotations."
"Researchers often come in with fixed questions and treat users like checkboxes rather than engaging meaningfully."
"Building relationships with local researchers and communities before fieldwork is critical."
"Don't let computer science or STEM dictate power dynamics—you have more power than you think, use it."
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