Oil Giants Are Quietly Funding AI Research at MIT and Oxford—Here’s Why

Carrying laptops and paper coffee cups, students stroll past the glass buildings of the Massachusetts Institute of Technology on a dreary afternoon in Cambridge, Massachusetts. A group of graduate researchers are seated around a screen in one lab that displays whirling geological maps and machine-learning models that forecast subterranean patterns.

The scene appears to be typical AI research. However, the oil industry—which most people associate with offshore rigs and pipelines—provides some of the funding for it.

Several of the biggest fossil fuel corporations in the world have covertly contributed research funds to universities like Oxford and MIT during the last ten years. The collaborations hardly ever make the news. Instead, they can be found in obscure research collaborations, funding acknowledgments, and academic footnotes.

However, the trend has become apparent. It also poses an intriguing query. Why would some of the world’s oldest industrial giants, like oil companies, suddenly become ardent advocates for AI research?

Simple economics is part of the solution. Large volumes of data have always been essential to oil exploration. Millions of data points accumulated over decades include seismic readings, drilling logs, satellite imagery, and reservoir pressure readings. In the past, engineers manually sorted through that data to create models that could take months to perfect.

That process is significantly accelerated by artificial intelligence.

In just a few hours, geological patterns can be analyzed by machine-learning systems, which can then forecast where oil or gas might be concealed beneath rock layers. Algorithms are capable of optimizing pipeline networks, simulating drilling conditions, and even predicting equipment failures before they happen.

It becomes evident why the industry is interested when one is inside a research lab where these models are being developed.

There is a huge potential savings. However, there’s more going on underneath the surface. Not all oil companies are searching for more intelligent drilling methods. They are making a greater effort to adjust to a very different energy landscape than the one they dominated in the 20th century.

Although executives rarely state this directly, there is a perception that AI could aid in their adaptation.

For instance, carbon-capture technology—still-in-experimentation systems intended to capture carbon dioxide before it escapes into the atmosphere—is being improved through the use of AI models. In an effort to find more effective materials and procedures, researchers at a number of universities have been developing algorithms that mimic chemical reactions inside capture facilities.

Some of that work has been funded by oil companies. This arrangement is viewed suspiciously by critics.

Student organizations sometimes wonder if funding for fossil fuels puts subtle pressure on research agendas at universities like MIT and Oxford. Perhaps some issues—like carbon capture—get more attention than others, like the quick phase-out of fossil fuels completely. This dynamic is not wholly novel.

The industries that are being examined have long made an effort to establish connections with academic researchers. It was done decades ago by the tobacco industry. Clinical trials are currently funded by pharmaceutical companies. Oil companies may view universities as locations where scientific legitimacy can be fostered in response to mounting political pressure over climate change. Some researchers are uncomfortable with that interpretation.

It’s difficult to overlook the subtle presence of industry partnerships when strolling through university hallways where corporate logos can be seen on research posters and conference banners. Following a lecture, a representative of Shell or Exxon may attend a seminar and engage in casual conversation with graduate students.

The majority of these encounters seem typical. However, the optics may seem difficult.

The partnerships are frequently defended by researchers themselves. Many contend that knowledge from both academia and industry will be necessary to address the energy and climate issues. From geological modeling to international energy logistics, oil companies have vast technical expertise and infrastructure under their control.

According to some scientists, excluding them completely could actually slow down rather than speed up progress. In discussions on campus, the conflict between those points of view is common.

Teams of engineers and data scientists are investigating AI tools intended to model global energy systems at Oxford’s energy research centers. These models model everything from carbon emissions pathways to renewable power grids. Such initiatives frequently receive funding from a variety of sources, including corporate sponsors, philanthropic foundations, and government grants.

The outcome is an intricate ecosystem. As it develops, it seems like it’s getting more difficult to draw lines between different industries. At the core of this convergence is artificial intelligence, which is of interest to governments, energy companies, and tech companies alike.

The stakes are also very high. Slowly but surely, the world’s energy systems are changing. The use of renewable energy is growing. Transportation markets are changing as a result of electric vehicles. Twenty years ago, it would have seemed politically impossible for governments to enact climate regulations.

These changes are visible to oil companies. Some seem intent on influencing the course of the transition.

They may be able to stay relevant by funding artificial intelligence research, whether that means creating carbon-removal technologies, increasing the efficiency of fossil fuels, or coming up with completely new energy-related ideas.

The effectiveness of that tactic is still unknown. However, it’s difficult to overlook the peculiar alliance that is developing there as you pass whiteboards displaying equations and algorithms in the silent hallways of MIT or Oxford. One of the oldest industries in the world is covertly funding the technology that has the potential to change it.