I really love this idea of data as soil. It also raises the question of who owns our data. If it becomes communal as opposed to something that belongs to corporate interests, then it’s less likely to be extracted for profit.
"Data as soil, not oil" — this framing captures something I've long believed but never expressed so precisely.
As President of KIC (Kobe Institute of Computing), where students from over 100 countries build AI-powered systems and applications to address real-world social challenges, I encourage them to go to Gemba first. To sit with people at the frontline (e.g. nurses) and ask: what information do they actually need to better serve their clients (patients)?
The answers never come from the algorithm. They come from people at Gemba.
As a small farmer who practices agroecological methods, I would add that the logic too often applied to soil is also extractive. Soil isn't just a growing medium that can be crudely manipulated (tilled, chemically supplemented) or easily substituted for (hydroponics) without dire long term consequences. Soil is relational. Soil is a web of organic lifeforms and inorganic compounds in a community dance. Enter into that relationship respectfully and it returns abundance.
In the long litany of data metaphors, soil definitely beats oil— second only perhaps to data is the new bacon 😂seriously though the need for proper cultivation of data is very needed for these models. I wrote about similar themes here
I really love this idea of data as soil. It also raises the question of who owns our data. If it becomes communal as opposed to something that belongs to corporate interests, then it’s less likely to be extracted for profit.
Timely wisdom for contemporary applications via Timeless Regenerative Metaphor.
So grateful for your insights!
"Data as soil, not oil" — this framing captures something I've long believed but never expressed so precisely.
As President of KIC (Kobe Institute of Computing), where students from over 100 countries build AI-powered systems and applications to address real-world social challenges, I encourage them to go to Gemba first. To sit with people at the frontline (e.g. nurses) and ask: what information do they actually need to better serve their clients (patients)?
The answers never come from the algorithm. They come from people at Gemba.
AIを一部の巨大プラットフォーマーによる「搾取（石油）」ではなく、現場の知恵を育む「土壌（soil）」として捉える視点、非常に腑に落ちました。台湾の事例が挙げられていますが、日本の町工場が抱える「職人の暗黙知の継承」という課題にもそのまま刺さりますね。「機械の弟子（machine apprentice）」という概念こそ、これからのAIと人間の最も美しい共存の形なのかもしれません。深く考えさせられる記事をありがとうございます。
As a small farmer who practices agroecological methods, I would add that the logic too often applied to soil is also extractive. Soil isn't just a growing medium that can be crudely manipulated (tilled, chemically supplemented) or easily substituted for (hydroponics) without dire long term consequences. Soil is relational. Soil is a web of organic lifeforms and inorganic compounds in a community dance. Enter into that relationship respectfully and it returns abundance.
In the long litany of data metaphors, soil definitely beats oil— second only perhaps to data is the new bacon 😂seriously though the need for proper cultivation of data is very needed for these models. I wrote about similar themes here
https://pioneeringspirit.xyz/3web-the-frontier-where-digital-meets-dirt