The Future of AI: How Artificial Intelligence Will Change the World

If it feels like the future of AI is a rapidly changing landscape, that’s because the present innovations in the field of artificial intelligence are accelerating at such a blazing-fast pace that it’s tough to keep up.

Indeed, artificial intelligence is shaping the future of humanity across nearly every industry. It is already the main driver of emerging technologies like big data, robotics and IoT — not to mention generative AI, with tools like ChatGPT and AI art generators garnering mainstream attention — and it will continue to act as a technological innovator for the foreseeable future. 

Roughly 44 percent of companies are looking to make serious investments in AI and integrate it into their businesses. And of the 9,130 patents received by IBM inventors in 2021, 2,300 were AI-related.

It seems likely that AI is going to (continue to) change the world. But how, exactly?

The Evolution of AI

AI’s influence on technology is due in part because of how it impacts computing. Through AI, computers have the ability to harness massive amounts of data and use their learned intelligence to make optimal decisions and discoveries in fractions of the time that it would take humans.

AI has come a long way since 1951, when the first documented success of an AI computer program was written by Christopher Strachey, whose checkers program completed a whole game on the Ferranti Mark I computer at the University of Manchester.

Since then, AI has been used to help sequence RNA for vaccines and model human speech, technologies that rely on model- and algorithm-based machine learning and increasingly focus on perception, reasoning and generalization. With innovations like these, AI has re-taken center stage like never before — and it won’t cede the spotlight anytime soon. 

What Industries Will AI Change? 

There’s virtually no major industry that modern AI — more specifically, “narrow AI,” which performs objective functions using data-trained models and often falls into the categories of deep learning or machine learning — hasn’t already affected. That’s especially true in the past few years, as data collection and analysis has ramped up considerably thanks to robust IoT connectivity, the proliferation of connected devices and ever-speedier computer processing.

“I think anybody making assumptions about the capabilities of intelligent software capping out at some point are mistaken,” David Vandegrift, CTO and co-founder of the customer relationship management firm 4Degrees, said.

With companies spending billions of dollars on AI products and services annually, tech giants like Google, Apple, Microsoft and Amazon spending billions to create those products and services, universities making AI a more prominent part of their curricula and the U.S. Department of Defense upping its AI game, big things are bound to happen. 

“Lots of industries go through this pattern of winter, winter, and then an eternal spring,” former Google Brain leader and Baidu chief scientist Andrew Ng told ZDNet. “We may be in the eternal spring of AI.”

THE NEAR FUTURE OF AI

In Mendelson’s view, some of the most intriguing AI research and experimentation that will have near-future ramifications is happening in two areas: “reinforcement” learning, which deals in rewards and punishment rather than labeled data; and generative adversarial networks (GAN for short) that allow computer algorithms to create rather than merely assess by pitting two nets against each other. The former is exemplified by the prowess of Google DeepMind’s AlphaGo Zero, the latter by original image or audio generation that’s based on learning about a certain subject like celebrities or a particular type of music.

On a far grander scale, AI is poised to have a major effect on sustainability, climate change and environmental issues. Ideally and partly through the use of sophisticated sensors, cities will become less congested, less polluted and generally more livable. 

“Once you predict something, you can prescribe certain policies and rules,” Nahrstedt said. Such as sensors on cars that send data about traffic conditions could predict potential problems and optimize the flow of cars. “This is not yet perfected by any means,” she said. “It’s just in its infancy. But years down the road, it will play a really big role.”

AI AND PRIVACY RISKS

Of course, much has been made of the fact that AI’s reliance on big data is already impacting privacy in a major way. Look no further than Cambridge Analytica’s Facebook shenanigans or Amazon’s Alexa eavesdropping, two among many examples of tech gone wild. Without proper regulations and self-imposed limitations, critics argue, the situation will get even worse. In 2015, Apple CEO Tim Cook derided competitors Google and Meta for greed-driven data mining.

“They’re gobbling up everything they can learn about you and trying to monetize it,” he said in a 2015 speech. “We think that’s wrong.”

Later, during a talk in Brussels, Belgium, Cook expounded on his concern.

“Advancing AI by collecting huge personal profiles is laziness, not efficiency,” he said. “For artificial intelligence to be truly smart, it must respect human values, including privacy. If we get this wrong, the dangers are profound.”

Plenty of others agree. In a 2018 paper published by UK-based human rights and privacy groups Article 19 and Privacy International, anxiety about AI is reserved for its everyday functions rather than a cataclysmic shift like the advent of robot overlords.

“If implemented responsibly, AI can benefit society,” the authors wrote. “However, as is the case with most emerging technology, there is a real risk that commercial and state use has a detrimental impact on human rights.”

The authors concede that the collection of large amounts of data can be used for trying to predict future behavior in benign ways, like spam filters and recommendation engines. But there’s also a real threat that it will negatively impact personal privacy and the right to freedom from discrimination.