Skip to end of metadata
Go to start of metadata

You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 3 Next »

Andrew Hicks (Unlicensed) scheduling an intro call with the team for Jan 17

"A data infrastructure platform will enable women agricultural workers to use machine learning algorithms to tap into rich data insights, such as tracking supply and demand for produce, predicting production costs, comparing market models and predicting competitive pricing."

https://cifar.ca/ai/ai-society/cifar-solution-networks/data-communities-for-inclusion/

Over the next three years, CIFAR’s first Solution Network will develop an open-access data infrastructure platform that will help women agricultural workers in India gain fair access to a competitive marketplace.

The international, interdisciplinary Network with members from India, Canada, Finland, Switzerland, and the U.K, will work with grassroots organizations to identify and remove technological barriers faced by women workers, including known barriers such as digital literacy and access to mobile phones. A data infrastructure platform will enable women agricultural workers to use machine learning algorithms to tap into rich data insights, such as tracking supply and demand for produce, predicting production costs, comparing market models and predicting competitive pricing. These insights will promote equitable economic opportunities for women agricultural workers in India.

Intro call on January 19:

DG: alesha (Unlicensed) Ashu Sikri (Unlicensed) Andrew Hicks (Unlicensed)

CIFAR:

  • Introductions

  • Why did we want to connect? What are we interested in?

    • Linked by Dan Lussier from EMILI in Manitoba, digital ag initiatives and overlap with what CIFAR is doing

    • We also work with FPOs in India, saw some overlap with the data platform you’re working toward, and thought we should talk

  • Give quick overview of FDN concept, data wallet, consent manager, and / or FarmStack, as applicable

  • Our potential questions:

    • We want to learn more about the platform you’re building – what are the inputs, farmer data, historical data, only from the co-op SEWA or bringing in other data sources?

      • How are they thinking about data sovereignty wrt the farmer input data into the platform?

      • Would they be interested in any of our open-source tools to support it?

    • Are they developing AI / ML algos on their own, will those be open source?

    • Are they developing their own digital literacy curriculum or approach, or applying something from a partner?

    • Geography – are they looking to expand beyond this initial group?


  • No labels