Quantifying the Incremental Impact of an Agri-tech Product with Causal AI
To effectively market a digital product, it's crucial to understand its impact on key user metrics and determine its level of success. In this session, George Giannarakis Data Scientist at National Observatory of Athens and Ilias Tsoumas Research Data Scientist at National Observatory of Athens will discuss the importance of this causal question, the challenges in providing rigorous answers, and introduce causal AI as a powerful tool to address these challenges.

The session will illustrate these concepts through the story of a digital agriculture product developed by the National Observatory of Athens in collaboration with Corteva Agriscience for cotton farmers in Greece. The comprehensive case study covers all aspects of the project, from product development to on-field deployment. We'll specifically focus on how causal AI techniques were used to accurately estimate the incremental impact of the product on the farmers' yield, which served as the primary measure of success.
George Giannakaris
Georgios Giannarakis
Data Scientist, National Observatory of Athens
Ilias Tsoumas
Ilias Tsoumas
Research Data Scientist, National Observatory of Athens
Date
Thursday, November 2, 2023
15:50 -
16:50 EEST
Track
Workshop
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Speaker

Georgios Giannarakis
Data Scientist, National Observatory of Athens

Connect with Georgios Giannarakis on:
George Giannakaris

Speaker

Ilias Tsoumas
Research Data Scientist, National Observatory of Athens

Connect with Ilias Tsoumas on:
Ilias Tsoumas

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