https://www.googleforeducommunity.com/t5/Social-Sciences-GFG/AI-as-a-quot-Non-Canonical-quot-Historian/m-p/212103#M1 <P><SPAN>Can AI help us recover "lost" history, or does it just reinforce existing biases?</SPAN></P><P><SPAN>The</SPAN><A href="https://dhnb.eu/conferences/dhnb2026/" target="_blank" rel="noopener"> <SPAN>Digital Humanities in the Nordic and Baltic Countries (DHNB) 2026</SPAN></A><SPAN> theme is "Lost in Abundance." As we digitize millions of records, we risk focusing only on the "canonical" (the famous people and events). Scholars are now using AI agents to find "non-canonical" trends—the stories of everyday people, fringe political movements, and under-resourced languages.</SPAN></P><UL><LI><STRONG>Challenge:</STRONG><SPAN> If an AI is trained on historical data that is already biased toward the powerful, can it actually help us find the marginalized voices? Or are we just building a faster way to confirm our own prejudices?</SPAN></LI><LI><STRONG>Case Study:</STRONG><SPAN> Look into the</SPAN><A href="https://clariah.at/en/news/call-for-contributions-digital-history-tagung-2026/" target="_blank" rel="noopener"> <SPAN>University of Salzburg’s 2026 Digital History Conference</SPAN></A><SPAN> focus on "Doing Cultural Heritage" through digital mediation.</SPAN></LI></UL> Thu, 12 Mar 2026 14:27:32 GMT dlaufenberg 2026-03-12T14:27:32Z https://www.googleforeducommunity.com/t5/Social-Sciences-GFG/AI-as-a-quot-Non-Canonical-quot-Historian/m-p/212103#M1 <P><SPAN>Can AI help us recover "lost" history, or does it just reinforce existing biases?</SPAN></P><P><SPAN>The</SPAN><A href="https://dhnb.eu/conferences/dhnb2026/" target="_blank" rel="noopener"> <SPAN>Digital Humanities in the Nordic and Baltic Countries (DHNB) 2026</SPAN></A><SPAN> theme is "Lost in Abundance." As we digitize millions of records, we risk focusing only on the "canonical" (the famous people and events). Scholars are now using AI agents to find "non-canonical" trends—the stories of everyday people, fringe political movements, and under-resourced languages.</SPAN></P><UL><LI><STRONG>Challenge:</STRONG><SPAN> If an AI is trained on historical data that is already biased toward the powerful, can it actually help us find the marginalized voices? Or are we just building a faster way to confirm our own prejudices?</SPAN></LI><LI><STRONG>Case Study:</STRONG><SPAN> Look into the</SPAN><A href="https://clariah.at/en/news/call-for-contributions-digital-history-tagung-2026/" target="_blank" rel="noopener"> <SPAN>University of Salzburg’s 2026 Digital History Conference</SPAN></A><SPAN> focus on "Doing Cultural Heritage" through digital mediation.</SPAN></LI></UL> Thu, 12 Mar 2026 14:27:32 GMT https://www.googleforeducommunity.com/t5/Social-Sciences-GFG/AI-as-a-quot-Non-Canonical-quot-Historian/m-p/212103#M1 dlaufenberg 2026-03-12T14:27:32Z