Responsibly Feeding a Growing Population with AI

This week in AI and ML news: AI’s role in regenerative agriculture, models for studying the impact of access to electricity, and more.

Both a growing population and the ravages of a changing climate demand novel agricultural strategies to feed the world while doing more with less and avoiding outsize contributions to climate change. Despite advancements in agronomy over the centuries, manual processes and systems are still all too common and all too likely to stymie the industry’s evolution.

On a recent episode of the Business Lab podcast, MIT Technology Review’s Laurel Ruma sat down with Syngenta’s head of IT Research and Development, Thomas Jung, to discuss AI’s role in making regenerative agriculture a reality worldwide. Regenerative agriculture, Jung says, is all about enhancing soil health to build a foundation for more effective and sustainable practices. Chief among the challenges facing agribusinesses and farmers worldwide is the simple fact that a whopping 70% of the world’s increasingly threatened water supply goes toward their industry. Much of Syngenta and its partners’ efforts go toward strategies for growing crops in a world where water is increasingly scarce and excessive water use is increasingly irresponsible.

The study, authored by researchers in Palo Alto and Zurich, focuses on the impact of electrification investments throughout Uganda. The sub-Saharan nation has seen electricity access increase considerably over the last decade, but the impacts of these efforts remain poorly understood. Asset wealth data collected from tens of thousands of towns across the continent combined with digitized maps compiled from satellite imagery helped train a model capable of providing evidence that electrified communities are at a distinct economic advantage over non-electrified communities. The authors note that their findings contrast with some earlier studies, which held that electrification had little household-level impact.

This research ultimately provides a potential framework for future efforts to assess and forecast the impact of infrastructure investment in other data-sparse regions. Similar methods and models may be applied to better understand the livelihood impact of access to roads, cellular service, the internet, and other necessities across entire countries.

Enterprises are much more likely to find the value in AI when individual employees recognize this value themselves and actively embrace AI thanks to solutions that make them feel competent, autonomous, and engaged with broader business goals. This is among the conclusions of a new report co-authored by MIT Sloan Management Review and the Boston Consulting Group, titled “Achieving Individual — and Organizational — Value with AI.”

The report, developed through more than 1,700 manager surveys and 17 executive interviews, also found that a surprisingly large number of people use AI at work without even realizing it. At first, 66% of respondents reported little to no AI use during their average day. Prompted with some illustrative examples, however, nearly half of these respondents changed their answers. This reflects that AI is ubiquitous enough to be taken for granted, but also suggests that awareness of AI’s role and capabilities is often lacking.

About the Author & Plainsight

Bennett Glace is a B2B technology content writer and cinephile from Philadelphia. He helps Plainsight in its mission to make vision AI success repeatable, scalable and traceable for enterprises across industries.

Plainsight provides the unique combination of AI strategy, a visual data science platform, and deep learning expertise to develop, implement, and oversee transformative computer vision solutions for enterprises. From solution-centric strategy, through model deployment, and ongoing monitoring and oversight, Plainsight empowers enterprises to create and operationalize responsible vision AI applications for solving high business challenges.

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