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Speaker flags intentional or platform‑specific bias in some AI services
Summary
Gadoo discussed cases he characterized as intentional or platform‑driven bias—researchers found Grok and other models surfacing content shaped by particular social media inputs or developer choices, and reports suggested some services generated code biased against disfavored groups.
At the FLCC webinar, Gadoo distinguished unintentional bias from forms that appear to reflect deliberate or platform‑specific sourcing choices. He pointed to reporting on Grok (an X/Twitter‑sourced model) and a China‑based model called Deepseek as examples where the training signals or developer intent produced skewed outputs.
Gadoo said these cases demonstrate that bias can be introduced not only by passive training data artifacts but also by decisions about which sources to emphasize. He recommended scrutiny of the provenance of training data when evaluating model behavior.
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