(AGENPARL) – mer 31 agosto 2022 A new study proposes a straightforward approach for building political consensus and reducing partisan animosity.
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Wednesday, August 31, 2022
Research & Scholarship
[Jazmia Henry](https://stanford.us5.list-manage.com/track/click?u=a8e6569da943904e9ac369cde&id=5ef4857ffc&e=37d6b811e4)
[Building inclusive NLP](https://stanford.us5.list-manage.com/track/click?u=a8e6569da943904e9ac369cde&id=14eeafa266&e=37d6b811e4)
Machine learning specialist Jazmia Henry, a HAI and CCSRE fellow working to incorporate African American Vernacular English into natural language processing models, built an open-source database of more than 141,000 AAVE words to help researchers design models that are less susceptible to bias.
[The secret is cross-party empathy](https://stanford.us5.list-manage.com/track/click?u=a8e6569da943904e9ac369cde&id=258d373d39&e=37d6b811e4)
In this era of strident polarization – and just in time for the midterm elections – a new study proposes a straightforward approach for building political consensus and reducing partisan animosity.
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“Initiatives like this will be challenged in court and will be hard to sustain. That doesn’t mean it’s not a good idea.”
Michelle Mello, professor of law and of health policy, on a California legislative proposal to punish doctors who spread false misinformation. ([The New York Times](https://stanford.us5.list-manage.com/track/click?u=a8e6569da943904e9ac369cde&id=f8c2b9efde&e=37d6b811e4))
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