  Background: The COVID-19 pandemic has uncovered the potential of digital
misinformation in shaping the health of nations. The deluge of unverified
information that spreads faster than the epidemic itself is an unprecedented
phenomenon that has put millions of lives in danger. Mitigating this Infodemic
requires strong health messaging systems that are engaging, vernacular,
scalable, effective and continuously learn the new patterns of misinformation.
  Objective: We created WashKaro, a multi-pronged intervention for mitigating
misinformation through conversational AI, machine translation and natural
language processing. WashKaro provides the right information matched against
WHO guidelines through AI, and delivers it in the right format in local
languages.
  Methods: We theorize (i) an NLP based AI engine that could continuously
incorporate user feedback to improve relevance of information, (ii) bite sized
audio in the local language to improve penetrance in a country with skewed
gender literacy ratios, and (iii) conversational but interactive AI engagement
with users towards an increased health awareness in the community. Results: A
total of 5026 people who downloaded the app during the study window, among
those 1545 were active users. Our study shows that 3.4 times more females
engaged with the App in Hindi as compared to males, the relevance of
AI-filtered news content doubled within 45 days of continuous machine learning,
and the prudence of integrated AI chatbot Satya increased thus proving the
usefulness of an mHealth platform to mitigate health misinformation.
  Conclusion: We conclude that a multi-pronged machine learning application
delivering vernacular bite-sized audios and conversational AI is an effective
approach to mitigate health misinformation.
