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

ary·Artificial IntelligenceI’ve been a thought leader on operationalizing AI for over 35 years and I’m concerned a catastrophe in the makingBy Anand RaoBy Anand Rao Anand Rao is a Distinguished Service fessor of Applied Data Science and AI in the Heinz College of Information Systems and Public Policy at Carnegie Mellon University

He teaches Operationalizing AI, Responsible AI, Applications of LLM, and Agent-Based Models & Agentic nologies.An AI catastrophe is brewing.Getty ImagesIn a speech last month, President Donald J

Trump outlined three executive orders he signed to mote American dominance of AI nology

He mised, in fact, that as America is the country that started the AI race, “I’m here to declare that America is going to win it!” To do so, his executive orders would make it easier for companies to build AI infrastructure, speed up the permitting cess by doing away with any oversight and safeguards he believed to be onerous, and push the exporting of America-manufactured AI ducts

I’ve conducted academic re on responsible AI for over 35 years, I have been at the forefront of operationalizing AI — from pioneering academic re to leading enterprise adoption of analytics and AI across industries

I’m concerned a catastrophe in the making, with giant 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 will become colossal Earlier this year, the four dominant giants — Alphabet, Amazon, Meta and Microsoft — said they planned on spending some $320 billion on AI this year alone

Said Commission President Ursula von der Leyen, “AI will imve our healthcare, spur our re and innovation and boost our competitiveness

We want AI to be a force for good and for growth… ” Then, there’s India

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 tections 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 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

This scarcity of AI skilled workers does not factor the rapid advancements in the nology in relation to the time it takes to train an individual in that nology

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

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, 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 companies — those in so many other sectors that drive world economies — had pledged net zero carbon foots over the next two decades, if not sooner

Sure, at some point, as alternative power sources such as solar, wind and nu become more prevalent, these outputs may diminish

And AI has the potential to play a critical role in reducing carbon foots, optimizing energy efficiency, and accelerating green nology

Indeed, while it seems 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 re and innovation across various scientific disciplines, leading to significant breakthroughs in areas such as drug discovery and materials science

Reers at MIT have developed AI models that imve the accuracy of climate predictions by analyzing vast datasets, aiding in better understanding and mitigation of climate change impacts

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 regulation and more 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 the short-term and long-term impacts of the nology, 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 nologies, leading to many accidents that could have been prevented

But these accidents served as valuable lessons for aviation experts

Rules were established for airways and air traffic

Licensing for pilots and maintenance nicians 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 nology, 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, a plane’s black box

Only then will it be adopted by all sectors and the ROI will have real value

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