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Kindly

Kindly aims to end cyberbullying and make students feel safer, by leveraging the latest advances in technology and empowering children to solve this pressing challenge. Kindly is a collaboration between young innovator Gitanjali Rao, who conceived the initial proof of concept, and UNICEF, which is currently leading its development as a digital public good and exploring its implementation at scale.

📚 Documentation

Refer to the Kindly Documentation Site to learn more about the various aspects of this project, including the architecture, doing technical development or the API.

💙 About UNICEF

UNICEF works in over 190 countries and territories to protect the rights of every child. UNICEF has spent more than 70 years working to improve the lives of children and their families. In UNICEF, we believe all children have a right to survive, thrive and fulfill their potential – to the benefit of a better world.

📝 License

This repository contains both software and data, and a different license applies to each.

🙏 Acknowledgements

This project was initially conceived by Gitanjali Rao as a proof of concept that included a Natural Language Processing (NLP) model developed using Microsoft Azure's Language Understanding (LUIS) cloud-based engine, an Application Programing Interface (API), and two front-ends: a Chrome browser extension and a standalone app. All the original materials can be found at https://kindly.godaddysites.com/

UNICEF current work on Kindly is a collaboration between multiple units:

  • UNICEF Division of Communication, which highlighted Gitanjali's work through the Voices of Youth project: The future of internet safety, reimagined in June 2020 and manages communications and outreach or this initiative.
  • UNICEF Office of Innovation that is currently leading the technical development
  • UNICEF Information and Communication Technology Division (ICTD) that is supporting on the IT infrastructure and scale-up strategy
  • UNICEF Child Protection, that is providing guidance on protection of children data