How early environmental data challenges led to today's AI frenzy
Neno Duplan, founder of Locus Technologies, reflects on the data problems of the 1980s that led to today's breakthroughs
By Neno Duplan
(Neno Duplan is the founder and CEO of Locus Technologies, a Silicon Valley-based environmental software company founded in 1997 that pioneered the application of the cloud computing model for data management in the environmental and sustainability industry.)
SAN FRANCISCO (Callaway Climate Insights) — In the late 1980s, as environmental engineers faced an overwhelming data explosion at contaminated sites, collecting millions of data points with little to show in actual cleanups, the seeds of today’s AI tech frenzy began to take shape.
Early environmental engineers such as myself and Gregory Buckle anticipated that emerging technologies — such as artificial intelligence, expert systems, automation, and advanced databases — would be key to transforming this raw data into real-time decision-making tools.
In a 1989 article, “Hazardous Data Explosion,” we predicted that “expert systems… employ methods of artificial intelligence for interpreting and processing large bodies of information,” enabling on-site engineers to make immediate, informed decisions about sampling needs and testing redundancy.
In 1992, in “Taming Environmental Data,” we showcased an early realization of this vision: an integrated environmental database management system that automated data handling from field to lab to report generation.
More than three decades later, many of those predictions have proven remarkably accurate. Environmental data practices have evolved from paper printouts and siloed spreadsheets to cloud-based platforms that handle tens of millions of records in real-time.
Early adoption of AI-like tools and automation in the 1990s — such as the IT Corp.’s ITEMS system — paved the way for today’s sophisticated environmental information management systems.
Modern platforms, exemplified by my company, Locus Technologies’ EIM, (Environmental Information Management, or EIM platform) now harness big data and cloud computing not only to store and visualize environmental data and automate compliance submittals but also to train AI models for predictive analytics. Buckle was our director of EHS Compliance and Data Management until he retired last year.
These models can identify pollution hotspots, forecast the spread of contamination, and even flag potential health risk clusters from anonymized, georeferenced datasets that span numerous sites and years of monitoring.
The human and environmental stakes underscore why getting this right is so important. High-profile environmental tragedies — dramatically depicted in films like “Dark Waters,” “Erin Brockovich” and “A Civil Action” — reveal the cost of mismanaging or ignoring environmental data.
They remind us that behind every dataset of toxins or emissions are real communities and ecosystems at risk. Similarly, the recent film “Oppenheimer” served as a poignant cultural reminder of the immense responsibility scientists and engineers carry, especially when handling data that could determine life-or-death outcomes.
More detailed posts on the Locus Technologies website review the prescient forecasts from 1989 and 1992, examines how environmental data management evolved in the intervening years, and analyzes how those early concepts are manifest in today’s technology. Accessible language and clear examples — from the Rocky Mountain Arsenal and the Fresh Kills Landfill to Los Alamos National Laboratory — illustrate the journey from vision to reality.
We find ourselves in a world where the challenges identified in 1989 are even more pronounced, but the tools at our disposal are exponentially more powerful. Environmental data has truly entered the big data era: Sensors in the field stream readings 24/7, laboratories output electronic results by the thousands, and decades’ worth of monitoring data can be warehoused in the cloud.
Those early predictions about AI, automation, and integrated data systems came true. These early concepts are now in action and paving the way for the AI era.
Read more on Locus Technologies.
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