AI: Project Listings and Collaborations

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  • 1.  AI translation

    Posted 14 days ago

    Hi Cori,

    I was searching for regulatory guidance on using AI to translate documents.  I found this pubmed article referring to HHS recommendations:

    https://pmc.ncbi.nlm.nih.gov/articles/PMC12918658/#:~:text=Level%202:%20formal%20regulations,is%20given%20to%20a%20patient.&text='%20This%20creates%20a%20regulatory%20'human,efficiency%20gains%20of%20AI%20deployment.

      Here's the section that was relevant:

      Level 2: formal regulations from HHS:

      At the second level are formal regulations, which implement statutory requirements through detailed rulemaking. The 2024 HHS Final Rule implementing Section 1557 provided the first explicit guidance on machine translation (referred to here as AI translation). This regulation introduced a critical distinction between 'critical' and 'non-critical' documents. For critical documents-a category that includes consent forms, discharge instructions and notices of eligibility18-the regulation mandates that 'a qualified human translator must review and correct the content before it is given to a patient.19' This creates a regulatory 'human-in-the-loop' floor for high-stakes clinical communication. However, this regulation was developed based on the performance capabilities of older model generations and defaults to a manual review process that may negate the efficiency gains of AI deployment.

      Nursing Consultant

      Wolters Kluwer Patient Education



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      Connie Feiler
      Nursing Consultant
      Wolters Kluwer
      Pittsburgh, PA United States
      Connie.Feiler@wolterskluwer.com
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    1. 2.  RE: AI translation

      Posted 14 days ago

      Thank you Connie.  This is great!  Our Manager over Language Services has enforced the need to require a (human) qualified medical translator to review any of the documents you mentioned.  This will be great to have this resource and article to back this up!

      With appreciation,



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      Cori Gibson, MSN, RN, CNL
      Children's Wisconsin
      Program Manager for Health Literacy
      Director of the Health Literacy Task Force
      cgibson@childrenswi.org
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    2. 3.  RE: AI translation

      Posted 6 days ago

      Greetings, Cori, Connie, and colleagues,

       

      Thank you for sharing thoughts.  Here at the New York State Department of Health, there was an opportunity to participate in a pilot for the utilization of Artificial Intelligence  within the workplace. Having a background as a health interpreter and translator, I am writing to share some thoughts on the evolving role of AI  in the workplace, with a particular focus on its implications for language access and the translation of materials. Given my background as a health interpreter and translator,  I've been interested in how these advancements can support our mission.

       

      The NYS Department of Health works closely with the NYS  Office of Language Access to ensure the appropriate and effective use of AI tools and resources, especially when it comes to translating critical materials. The NYS Language Access Law mandates the translation of vital documents into the 12 most prevalent languages spoken in New York State. This is a significant undertaking, and AI holds potential to support these efforts. The nuances of medical terminology, cultural context, and the critical nature of health information necessitate a human-in-the-loop approach to review and validate AI-generated translations.

       

      I believe that by thoughtfully integrating AI while maintaining strong partnerships with the Office of Language Access and prioritizing human review, we can continue to support the ability to serve the diverse linguistic communities of New York State.

       

      Best regards,

      Wilma

       

      Wilma Alvarado-Little, MA MSW

      New York State Department of Health

      Office of Health Equity and Human Rights Executive Team

      p. (518) 474-2180 │ c. (518) 708-4425

       

       

       






    3. 4.  RE: AI translation

      Posted 12 days ago

      Thank you for sharing this resource. At our organization, we also follow a human-in-the-loop-or what I often refer to as a human-at-the-core-approach to translation. This practice supports regulatory requirements, but more importantly, it helps ensure that translated content is accurate, high quality, and truly supports understanding, trust, and positive experiences within the communities we serve.

      AI-powered translation has made meaningful advances, and it can be a useful tool when applied thoughtfully. That said, performance varies widely across languages and subject areas, and for many languages there remain well-documented gaps in accuracy. Without qualified human review and approval, there is a real risk of introducing errors or bias into patient-facing content-risks that can undermine health literacy and, in some cases, cause harm.

      For that reason, we apply the same standards to AI translation that we do to any other drafting tool: if we would not publish AI created English content without review, we should not rely on machine translation outputs without human validation by a trained professional. Ultimately, accountability for patient communication rests with clinicians and organizations, not with the technology itself. Maintaining a human-centered review process is one important way we can uphold both patient safety and trust while responsibly exploring new tools.



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      Sonja Casey Lara
      Translation Program Manager
      Fairview Health Services
      sonja.caseylara@fairview.org
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    4. 5.  RE: AI translation

      Posted 11 days ago

      Sonja: Thank you for sharing your human-at-the-core process at Fairview. You said it wonderfully: "Maintaining a human-centered review process is one important way we can uphold both patient safety and trust while responsibly exploring new tools."

      I'd add that review processes work best when they're grounded in something more structured: a shared, principled human-centered framework for how teams create with AI, use AI, and evaluate what it produces. Where organizations have invested in training their teams on a common approach, I see meaningfully better consistency, fewer errors reaching patients, and standards (both internal and regulatory) being met more reliably. That's because the framework creates shared mental models across teams rather than leaving each person to figure it out individually.

      On AI translation specifically: it has real promise and has improved significantly. But, accuracy varies considerably across languages. Languages like Tagalog, Hindi, and Haitian Creole, all in the top 10 in the US by number of speakers after English and Spanish, are what researchers call "low resource languages" and tend to fare worse in standard LLMs. AI translation is not transcreation.

      A few practical strategies that have worked well for organizations we've supported: identifying which content poses the highest risk if mistranslated, understanding which languages and what kinds of content surface which kinds of errors, and developing human-curated dictionaries of key terms and phrases that can be provided to LLMs at the time of translation to positively influence outputs.

      One area worth paying close attention to: what happens when AI translation moves from static content to the point of care? These are situations where clinicians or staff might use AI translation during a patient interaction or where, for example, IT enables AI translation across your website, including content that was intentionally developed to meet health literacy standards. The human review process that works well for documents doesn't easily transfer to real-time use. That's a different challenge that also requires a human-centered approach to AI. It often involves vendor evaluation, technology decisions, and policy frameworks that may sit outside your team's direct control but that your team should absolutely have a voice in shaping. A shared, structured, human-centered framework for approaching AI makes a real difference in situations like this, not just for static content, but across the organization.

      Thank you, Connie, for sharing the PubMed article. It's an important resource for this conversation.

      If anyone is working through how to build a structured approach to AI for content creation, translation, or evaluation in your organization, I'm always happy to talk through what we're seeing. Feel free to reach out.

      Best,
      Temese



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      Temese Szalai
      Principal
      Subtextive
      temese@subtextive.com
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