FEATURE
AI is also excellent for modifying the tone of a message or altering the language for different audiences ... This could be helpful for technical documentation or reports from the public health laboratory that need to be translated into a brief summary — minus scientific jargon — to update executive leadership .
can adjust , link and find relationships among various data sets .
APHL has been partnering with CDC on a project called DETOR : The New Direction in Electronic Test Orders and Results . The project recognizes the problem of public health laboratories and health care organizations using incompatible data systems . This makes it hard to exchange critical test orders and results quickly , accurately and securely .
DETOR enables real-time electronic test orders and results to be shared between public health laboratories and providers . It is built on the AIMS Platform and transmits and translates data between disparate systems . The platform was created by APHL and fully funded by CDC . It ’ s available free to public health laboratories and their partners through APHL .
After data quality and management improves , Calzada said the next step is to focus on machine learning operations . He said CDC has been successful at creating sophisticated computer models , but the agency needs to get better at deploying and operationalizing these models across public health .
“ Can you build a factory floor that lets you produce machine learning at scale and in a reliable way , or are you going to leave it as an artisanal craft where , if you want to run a model , you call the person who built it to do it ,” he said . “ I think we can have much more impact on public health with a factory floor approach .”
Calzada encourages public health laboratories and individuals to reach out to him to discuss high-value models that CDC could build to address current public health challenges .
Generative AI has the power right now to improve efficiencies in the workplace , including in public health laboratories , said Jade Wang , a senior bioinformatics scientist at the New York City Public Health Laboratory . GenAI tools include ChatGPT , Google Gemini ( now built into the Google search engine ) and Microsoft CoPilot ( an add-on to Microsoft 365 , formerly Microsoft Office ).
Wang ’ s laboratory has not used GenAI , but she has personally used it for brainstorming and other tasks that don ’ t use data , don ’ t need to be factchecked and don ’ t involve any privacy concerns . For example , she might have trouble thinking of a certain phrase or word . Instead of turning to a dictionary or thesaurus , she uses GenAI , asking something like , “ I ’ m looking for the word that means XYZ .”
Wang outlined other use cases that could speed up and streamline tasks : You might prompt or instruct a GenAI tool to draft an email you ’ ve had difficulty writing , though you will want to edit it . Or you may need to write a new standard operating procedure ( SOP ). You could input the template and the SOP ’ s basic steps and then GenAI would turn that into complete sentences and finish writing the SOP .
“ That would save so much time . You wouldn ’ t have to sit there and manually describe every single step of what you ’ re trying to do ,” Wang said .
Challenges and Concerns
Current public GenAI tools do not follow data privacy or patient privacy guidelines . The models also store and learn from the text you type in , whether it is patient identification details , confidential documents , or drafts of reports that haven ’ t been fact-checked or published yet .
Other concerns include inaccuracies and bias . GenAI is pulling information from the data sets it has been given . That data might include inaccuracies , biases , racist and bigoted language , and outdated guidelines or materials . These biases and falsehoods can be perpetuated as the tool continues to use them . In addition ,
20 LAB MATTERS Fall 2023
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