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    UnBias-Plus AI tool detects and rewrites bias in text
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    • Alies Maybee
      Alies Maybee last edited by

      Interesting tool developed by the Vector Institute, Canada. Take a read: UnBias-Plus AI tool detects and rewrites bias in text

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      • Debra Turnbull
        Debra Turnbull @Alies Maybee last edited by

        @Alies-Maybee

        Yeah, I read that this morning... !

        Very cool! and there's a free public version!

        Has HUGE implications in training data for AI-Scribes. Hopefully with this we can get the Canadian version of datasets...

        Now, to work on the Consent component. Exciting times!

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        • Debra Turnbull
          Debra Turnbull last edited by

          For those of you that want to test out the free version:

          • UnBias-Plus
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          • Chris Johnston
            Chris Johnston @Debra Turnbull last edited by

            @Debra-Turnbull @Alies-Maybee

            It’s an interesting tool for sure, and I can see it being useful in various ways. But perhaps mostly as a teaching tool to help students tone down at least the more obvious forms of bias in their writing. Again in a teaching context, the concern would be does it weaken the development of critical thinking? If students rely on a tool that identifies a subset of biased language, can they still be taught to recognize more subtle ingrained biases? It’s arguable whether that’s actually happening now, though it should be.

            Deb, I’m interested in your comment about getting the “Canadian version” of datasets using this tool. Can you elaborate on that a little? What kind of datasets in particular and how this tool would be used in that context?

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            • Debra Turnbull
              Debra Turnbull @Chris Johnston last edited by

              @Chris-Johnston

              So, much like the Ethical use of AI project (the one we were both on), bias gets automatically built in to AI systems = because they are fed biased input... especially AI-Scribes. The one example that comes to mind is: "Combative patient refuses to take medication" as opposed to "Patient refuses to take medication". The output decision of an AI gets skewed.

              If Canada is going to produce its own training datasets, it would be good to clean up the clinician notes set that would act as input. Flag the biases and remove or re-classify them (not sure what this would look like). This increases the value of the data.

              So now, I have one for you.
              You mentioned training students - but which students? Med students and writing up physician-notes? How does this benefit high school students? Isn't bias under the guise of "creative writing"?

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