Dual Citizen LLC

Sometimes a book is so good it deserves a post. And Kate Crawford's "Atlas of AI" is one of those books. The book dispels the binary conventional wisdom that AI systems present some kind of "algorithmic exceptionalism" or are a threat to humanity's survival. Instead, it shows how AI systems are subject to design tradeoffs, biases, resource use, and labor tensions - just like most economic or technological systems. How they evolve & the extent to which they improve or degrade society depends on us: educating ourselves on how AI works and how we want it to operate in our lives. Some historical parallels in the book I found interesting: * Lithium from Nevada fuels Silicon Valley today much like the goldfields of the 19th century built the city of San Francisco * Like manufacturing, the majority of "labor" behind AI is unseen, including thousands of workers who label the content that makes AI systems work * Similar to defense contractors like Lockheed Martin, newer technology companies like Palantir Technologies are deeply integrated into core government functions Learn much more & buy this fantastic book here: https://a.co/d/g9qyQ40

Some news: the full data file from the Global Green Economy Index (GGEI) is now accessible in the public domain for the very first time. Read more & download it here: https://bit.ly/3Wy4i5v Why this change? The relationship between data & sustainability management has evolved significantly. A decade ago when the GGEI was first published, datasets existed in silos. But today, data usage in the sustainability space has become much more of a system, whereby myriad data sources are synthesized into increasingly sophisticated models, often enhanced by artificial intelligence, satellite-based data, remote sensing, and other advanced methods. Making the GGEI more accessible in the public domain will accelerate its impact. Researchers, academics, and analysts can more readily integrate the novel perspective it provides on how countries are progressing against global sustainability targets to their own work. Let us know what you think! This work is licensed under CC BY-SA 4.0.

There is an AI elephant in the room: AI is rapidly expanding but so is its negative environmental impact. Recent projections from Alex de Vries @ Vrije Universiteit Amsterdam (VU Amsterdam) suggest that by 2027, global AI energy consumption will exceed that of the Netherlands. Sustainability best practices are being articulated for AI development, and the regulatory environment is changing rapidly with pending legislation in the US & EU. But will it be enough? Catch up on this emerging debate in our latest insight: https://bit.ly/3TH8DAC

Last year, 1,050 global sustainability experts from our network responded to a simple question: how can we unlock a 2020s green breakthrough? The question should have a simple answer (phase out fossil fuels). But in the contorted times we live in, the survey responses were anything but clear cut. Take a read of the results for yourself, and let me know what you think: https://bit.ly/49X0dv9 Photo credit: Kevin Cooley

Since early 2022, hundreds of academics & research institutions globally have leveraged GGEI data in their work. A few months ago, I highlighted one such collaboration w/Alona Korohod based in Kyiv, Ukraine at the State University of Trade & Economics. This year, the hope is to further expand the integration of GGEI data to these academic & research projects. The short video below explains the novel GGEI methodology introduced in 2022, and why it is valuable by tracking all indicators according to both *progress* over time and *distance* from globally established hashtag #sustainability targets. Please be in touch with interest or referrals here or through the GGEI data platform: https://bit.ly/3mnnAXy