I’ve been a thought leader on operationalizing AI for over 35 years and I’m concerned about a catastrophe in the making

To do so, his executive orders would make it easier for companies to build AI infrastructure, speed up the permitting process by doing away with any oversight and safeguards he believed to be onerous, and push the exporting of America-manufactured AI products.  

This is just the latest salvo in what is now a global AI arms race, backed by billions of dollars in investment by tech companies and venture capital firms big and small here in the U.S. and across the globe. I’ve conducted academic research on responsible AI for over 35 years, I have been at the forefront of operationalizing AI — from pioneering academic research to leading enterprise adoption of analytics and AI across industries. I’m concerned about a catastrophe in the making, with giant tech firms winning the battle of the current AI arms race but most assuredly losing the war in terms of creating an utterly destructive impact on society.  

Big tech will become colossal tech

Earlier this year, the four dominant tech giants — Alphabet, Amazon, Meta and Microsoft — said they planned on spending some $320 billion on AI this year alone.  

Not to be left behind, the EU recently mobilized billions of euros to finance and build AI gigafactories, with the goal of becoming a global leader in the field. Said Commission President Ursula von der Leyen, “AI will improve our healthcare, spur our research and innovation and boost our competitiveness. We want AI to be a force for good and for growth… ”

Then, there’s India. The national IndiaAI Mission, launched last year, has a budget outlay of approximately $1.3 billion over the next five years directed toward AI infrastructure and financing startups, with a smaller portion allocated to research and development and centers of excellence, focusing on sustainability, healthcare, and agriculture as priority areas. 

And we can’t ignore the once “sleeping giant,” China, which has the singular goal of achieving global AI leadership by 2030, when its vast investments would value its AI market at some $1.4 trillion!

The return on investment on all this money is hard to predict, other than the fact that Big Tech will become Colossal Tech the world over. Ultimately, though, success will be measured not by how much money companies and countries invest and earn but how all this AI is used and what protections will be enacted to ensure that its myriad uses are constructive rather than destructive.  

For now, there are so many unanswered questions to ponder, questions that few have ventured to honestly and thoroughly answer because there is both too much unknown and for the most part the industry is totally unfettered.

Employment crisis brewing

Consider as but one example, the employment factor. In other words, who are all the people who will work on the plethora of AI initiatives present and future.  A shortage of trained personnel is already acute in the tech industry, with a study by Randstad, the international human resources consulting firm, finding that just over a third of employees at the companies examined saying they have received any AI training in the past year.  Only one in five Baby Boomers have had access to AI upskilling opportunities. And quite alarming, more than seven out of 10 workers who say they are skilled in AI are men, while only 29% are women.

This scarcity of AI skilled workers does not factor the rapid advancements in the technology in relation to the time it takes to train an individual in that technology. While it can vary significantly, depending on the complexity of the AI model, training one person can take many months. Workers don’t just have to learn new AI concepts and models, they must “learn how to learn” in a world where AI innovations are coming fast and furious. For companies, this is another significant financial investment in education and training — a totally wasteful one  because there is no predictable ROI.

Then there’s the perception that AI will displace humans in the workforce because it is faster, cheaper, and more efficient and effective. Companies that even consider such a mindset are headed towards oblivion. In fact, to companies that are striving to do more with less manpower by using AI assistants to develop code, I say good luck. You still need skilled software engineers and always will. Yet, a recent report shows that there has been an alarming 34% drop in the demand for software engineers since a 2021 peak. 

So, rather than focusing so much on embracing autonomy, companies must look at AI as augmentation, a collaboration between machine and human. If not, they may win the battle in the current AI arms race but they will most assuredly lose the war because the impact on society will be nothing short of catastrophic.   

The matter of emissions

There is also another catastrophe in the making. According to the World Economic Forum, tech companies are spewing out more emissions from running the massive data centers necessary to power the AI systems. Microsoft announced recently that its emissions from carbon dioxide had surged nearly 30% since 2020 due to the expansion of its data centers, which are powered by oil and gas. Energy consumption is blowing up and there doesn’t seem to be an end in sight. It’s a toxic equation: more power, more air pollution. Ironically, it comes at the same time these tech companies — like those in so many other sectors that drive world economies — had pledged net zero carbon footprints over the next two decades, if not sooner.   

Sure, at some point, as alternative power sources such as solar, wind and nuclear become more prevalent, these outputs may diminish. And AI has the potential to play a critical role in reducing carbon footprints, optimizing energy efficiency, and accelerating green technology. Indeed, while it seems like only a fractional amount, AI has the potential to cut global carbon dioxide emissions by 4% by 2030, according to a report from the World Economic Forum. 

Moreover, AI has other societal benefits. It is accelerating research and innovation across various scientific disciplines, leading to significant breakthroughs in areas such as drug discovery and materials science. Researchers at MIT have developed AI models that improve the accuracy of climate predictions by analyzing vast datasets, aiding in better understanding and mitigation of climate change impacts. Further, the integration of AI in climate science has led to a 30% improvement in the accuracy of weather forecasting models, enhancing the ability to predict and respond to extreme weather events.

With such conflict between the potential for societal good and that for great harm, many wonder if there is a middle ground, and does it lay with unified global regulation of the entire AI industry. The fact is the cat is already out of the bag — every country has AI. So, I would argue that it is less about regulation and more about using AI responsibly while earning the trust of users. In other words, there still needs to be some regulation but it must be combined with common sense. It must be advanced at a pace that society finds acceptable and earns the trust of individuals and the collective whole about the short-term and long-term impacts of the technology, rather than having it shoved down their throats.  

The air safety model that was adopted after World War I and that has evolved in the years since serves as an ideal corollary. Back then, as commercial air travel became a transportation option, safety measures were limited by the existing technologies, leading to many accidents that could have been prevented. But these accidents served as valuable lessons for aviation experts. In 1926 came the establishment of the Federal Aviation Administration, which was charged with improving flights both domestically and internationally. Rules were established for airways and air traffic. Licensing for pilots and maintenance technicians became mandatory, as did certification of repair stations and their crews. Manufacturing standards for air worthiness were developed. And the designs of the planes themselves were greatly enhanced with innovations such as radar systems, cabin pressurization, communication technology, and even AI itself. Today, airline travel is the safest mode of transportation.

AI could eventually be the safest mode of innovation on multiple levels and in industries across the board. But it does need to be really safe and it needs to be secure, like a plane’s black box. Only then will it be adopted by all sectors and the ROI will have real value.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.