September 3, 2026
Perspectives
by William Hooke
“People look at the outward appearance, but the Lord looks at the heart.“—1 Samuel 16:7 (NIV)
“A rose by any other name would smell as sweet.”—William Shakespeare (in Romeo and Juliet)
History buffs in the geosciences crowd might find this vignette interesting. In the early 1980s, the Reagan administration was taking over the reins of government from the Carter administration. President Reagan and his OMB Director David Stockman believed strongly that the federal government’s role was to conduct only basic research. Government should not be in the business of technology development—that was rightly the purview of the private sector. At the time, NOAA’s R&D Line Office (as its title suggested) was heavily engaged in development, as were the Environmental Research Laboratories that comprised the bulk of the R&D Line Office at that time.
The head of the Environmental Research Laboratories pushed back hard against the Reagan guidelines and was quickly sidelined. Meanwhile, his boss, one Joseph O. Fletcher, the newly installed director of the R&D Line Office, simply changed the Line Office name to the Office of Oceanic and Atmospheric Research (OAR). The word “development” was duly scrubbed from mission statements, job descriptions, performance reviews, and reports. Office letterheads and signage were promptly removed and replaced.
All work went ahead unabated. No jobs were lost. Progress continued. The outward appearance was changed, but not the heart.
Fast forward to today. On May 29 of this year, OMB proposed replacing the existing guidelines for federal science grants with a new, strict regulatory framework. The proposal would politicize the grants process, reduce overhead caps while at the same time increasing the compliance burden, expose scientists and their institutions to midway grant cancellations, constrain international collaboration, and more. Scientists and their universities and government agencies saw the proposed changes as an existential threat to U.S. science and its leadership position in the world. The political pushback was massive, coming from every quarter: the U.S. Congress, state-level governments, civil rights groups, and scientists and universities. By the mid-July deadline for comments, almost 500,000 responses had been received, the vast majority expressing degrees of outrage and anger. Any implementation has at least been delayed until after the midterm elections.
However, as discussed in a July 2 LOTRW post, fighting political force with an equal and opposing political force is unsustainable over the long term. Complementary, more enduring approaches should be sought. The July 22 LOTRW post suggested one such possibility: scientists might seek to reduce the scope of conflict, to make science itself less political. The approach suggested was not for science and scientists to withdraw from the larger society, which is increasingly politically polarized, but rather to seek good relationships with all political factions rather than relying on help from any single one.
This post lays out a second such avenue. A survey of the current political damage to science shows one branch of science/technology is surviving relatively unscathed: artificial intelligence. And it doesn’t seem to be unscathed because it is apolitical. Far from it. Battle lines are being drawn. On the one hand, some likely beneficiaries are strong advocates. On the other, people fearing job loss are resisting. (One battleground: the data farm.)
Instead, this branch of technology is being pursued with vigor bordering on frenzy because it is perceived as being paradigm-breaking across the entire human agenda. AI success and primacy are widely seen as of utmost importance to national and economic security and even cultural survival.
The global competition for supremacy is taking place along two distinct lines—a race to achieve cutting-edge advances in AI per se leading to some form of superintelligence, and applications of AI. Nations are pouring in resources in the form of financing, labor, and infrastructure. Two nations are at the forefront, the United States and China. Those tracking this progress tell us the United States holds the lead in development of superintelligence, but perhaps by as little as a few months. Conversely, China appears to be integrating AI into applications more rapidly. (Meanwhile, Europe, Africa, and other regional blocs have been left wringing their hands.)
The dollar investments are immense. In fact, part of the reason for abandoning science funding in other areas (though couched in criticisms the latter are too political) is the need for more dollars to satisfy the insatiable appetite of AI.
To be sustained, the AI superintelligence arms race must build up a stream of economic benefits as it goes along. This requires mastering AI applications across the board. In many U.S. minds, that makes China’s perceived lead in applications especially worrisome.
One piece of the benefits puzzle is the need for better incorporation of environmental science into and across AI applications. For example, AI-enabled electrical utilities will function most efficiently and make best use of grids and networks to the extent they anticipate weather-related fluctuations in both renewable power generation and in energy demand. Similar statements apply to agribusiness, to water resource management, to transportation, to waste disposal, to emergency management, to military tactics and strategy, and more. Longer-term weather and climate outlooks will also be needed, in order to guide long-term AI-aided investment across these economic sectors. Environmental scientists of every flavor will be needed to help train AI systems; to evaluate AI performance during unusual, high-consequence weather and climate events; and so on.
When it comes to any particular application, the incremental benefit might seem small on most days and in most locations. Superficially, it might even seem that understanding of why the AI applications work matters less than the algorithms themselves. But all these economic sectors will pay a price each time weather, water, and climate forecasts go wrong. The why and how of the ways things go wrong will continue to matter. The society that masters the why and how will be the best off in the long run. And the cost of better incorporating that science is also minimal.
Environmental scientists could do worse than hitch their wagon to that star.
This might be off-putting for environmental scientists; it might seem they/we would be playing second fiddle to the technology. And we might mourn the current fragility of what had been robust, sustained, dependable federal funding for environmental science and services.
But that is meteorology’s history and its strength. Much of the progress in our field and its social benefit has come from mastering computing technology and novel observational methods and platforms as they come along and harnessing them to the problem. We’re good at this. And historically, the funding for services and research has come from a variety of federal and private sources.
We need to remain adaptive and embrace new technologies and the associated changes they bring to our task—the way meteorologists have been adaptive for the past two centuries. If we succeed, we’ll help solve world and national global problems in natural resource management, hazards, and pollution along the way. And whether the science and technology in question are labeled AI-supported geosciences and services or geoscience-enabled AI might not matter all that much.
In closing, note that whatever the label, primacy in innovation will be won by the nation able to develop the best professional workforce. Success or failure there will depend in part on a nation’s K-12 and higher education and its ability to attract and hold the best brains from abroad. In this back-to-school season, it’s worth looking at this dimension, in a new era of five R’s: reading, ‘riting, ‘rithmetic, ‘rtificial intelligence, and recruiting.
That’s a subject for the next post.