February GDHN Monthly Meeting: Human versus AI: Pros and Cons of different strategies for providing health information and counseling

Simple item page
dc.date.accessioned2020-06-22T10:57:45Z
dc.date.available2020-06-22T10:57:45Z
dc.description.abstractThe February meeting of the Global Digital Health Network was hosted by FHI 360 and explored how artificial intelligence AI and machine learning ML are being incorporated into client facing digital health applications We had three presentations from Jacaranda Health FHI 360 and Viamo that illustrated a continuum of possible uses of AI and ML in place of and in addition to humans to provide individuals with important health information counseling and support Despite some early technical difficulties we managed to connect to all three presenters and have time to spare for some great Q A Thanks to the approximately 25 folks who participated in person in Washington DC and North Carolina and the 40 people who tuned in remotely Because the presentations were extremely rich and we didn t want anyone to miss out the summary is longer than usual and is therefore included as a separate attachment Please do take a look at the full notes and the presentation deck available as a separate resource To entice you below are our presenters collective considerations for including AI ML in a client facing health intervention AI ML is good for large amounts of data as well as for systems in which questions are asked repeatedly or consistentlyAI ML can be useful for triaging as in the case of Jacaranda Health Weigh what you think the AI ML will do against what a human can do In situations with large amounts of data coming in per first bullet AI ML may be able to handle larger quantities of data more efficiently than a human IN situations where information coming in is nuanced or varied per second bullet a human may be better at sorting analyzing and responding Look to how AI ML can be built into existing programs both Jacaranda and Viamo did this Consider the audience user needs In some instances a user may require a degree of empathy that AI ML cannot provide consideration in FHI 360 s presentation In sum both the content and the context are very important when considering whether to include AI ML Speakers Sathy Rajasekharan Chief Innovation Officer Jacaranda Health LinkedIn Rachel Jones Program Manager LinkedIn Kate Plourde Technical Advisor FHI 360 LinkedIn Melissa Persaud Director of Partnerships Linkedin
dc.identifier.urihttps://lib.digitalsquare.io/handle/123456789/77141
dc.subjectMonthly Meeting Minutes
dc.subjectMonthly Meeting Minutes
dc.subjectAI
dc.subjectML
dc.titleFebruary GDHN Monthly Meeting: Human versus AI: Pros and Cons of different strategies for providing health information and counselingen
dcterms.abstractThe February meeting of the Global Digital Health Network was hosted by FHI 360 and explored how artificial intelligence AI and machine learning ML are being incorporated into client facing digital health applications We had three presentations from Jacaranda Health FHI 360 and Viamo that illustrated a continuum of possible uses of AI and ML in place of and in addition to humans to provide individuals with important health information counseling and support Despite some early technical difficulties we managed to connect to all three presenters and have time to spare for some great Q A Thanks to the approximately 25 folks who participated in person in Washington DC and North Carolina and the 40 people who tuned in remotely Because the presentations were extremely rich and we didn t want anyone to miss out the summary is longer than usual and is therefore included as a separate attachment Please do take a look at the full notes and the presentation deck available as a separate resource To entice you below are our presenters collective considerations for including AI ML in a client facing health intervention AI ML is good for large amounts of data as well as for systems in which questions are asked repeatedly or consistentlyAI ML can be useful for triaging as in the case of Jacaranda Health Weigh what you think the AI ML will do against what a human can do In situations with large amounts of data coming in per first bullet AI ML may be able to handle larger quantities of data more efficiently than a human IN situations where information coming in is nuanced or varied per second bullet a human may be better at sorting analyzing and responding Look to how AI ML can be built into existing programs both Jacaranda and Viamo did this Consider the audience user needs In some instances a user may require a degree of empathy that AI ML cannot provide consideration in FHI 360 s presentation In sum both the content and the context are very important when considering whether to include AI ML Speakers Sathy Rajasekharan Chief Innovation Officer Jacaranda Health LinkedIn Rachel Jones Program Manager LinkedIn Kate Plourde Technical Advisor FHI 360 LinkedIn Melissa Persaud Director of Partnerships Linkedin
dcterms.subjectMonthly Meeting Minutes
dcterms.subjectMonthly Meeting Minutes
dcterms.subjectAI
dcterms.subjectML
dcterms.titleFebruary GDHN Monthly Meeting: Human versus AI: Pros and Cons of different strategies for providing health information and counselingen
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
february_gdhn_monthly_meeting_notes.docx
Size:
22.1 KB
Format:
Microsoft Word XML
Description:
Download
Collections
GDHN Resources