Machine-Learning Pioneer Says Stop Calling Everything AI

By Oliver Freeman
Michael I. Jordan, a pioneer in the machine learning (ML) field, explains the critical difference between artificial intelligence (AI) and ML...

One of the leading researchers in the field of artificial intelligence and machine learning recently issued a call to the world of technology: to stop labelling everything as ‘AI’. Michael I. Jordan stated that while AI systems do show some aspects of human intelligence and a human-level of competence in very low-level pattern recognition skills, they are only imitating human intelligence on a cognitive level ─ in essence, AI, in its infancy, is still a far cry from the reality of being human. 

Jordan, a professor in the department of electrical engineering and computer science and the department of statistics at the University of California, Berkeley, is considered by many as one of the foremost authorities on AI and ML. He is credited with transforming unsupervised machine learning from a collection of algorithms to an intellectually coherent field. So this isn’t his first rodeo when it comes to putting down AI. 

Machine Learning’s Superiority

Nowadays, Jordan’s frustration comes from something that many in the field of AI and ML share: their collective irritation at the mislabelling of machine learning. Oftentimes, it seems to be the case that when most people talk about Ai, they actually mean ML ─ they just don’t understand the difference.

“People are getting confused about the meaning of AI in discussions of technology trends – that there is some kind of intelligent thought in computers that is responsible for the progress and which is competing with humans,” Jordan said.

In a previous article on Medium titled “AI – The Revolution Hasn’t Happened Yet”, Jordan said this of ML: “ML is an algorithmic field that blends ideas from statistics, computer science, and many other disciplines to design algorithms that process data, make predictions, and help make decisions.”

The problem with AI is that it’s regularly misconstrued by Hollywood and other filmmaking industries that like to glamourise the technologies’ potential world-conquering capabilities. They continuously portray AI as a competitive force that will overtake humans in a questionable, certainly fictional, race for survival between man and machine. 

“While the science-fiction discussions about AI and superintelligence are fun, they are a distraction,” he says. “There’s not been enough focus on the real problem, which is building planetary-scale machine learning-based systems that actually work, deliver value to humans, and do not amplify inequities.”

In essence, the reality is that ML is the technology that changes our lives on a daily basis; while AI might be present in the workplace, automating previously manual, incredibly mundane tasks, and building links for interconnected devices, it isn’t the be-all and end-all that technologists and companies often portray it as. 

The Future of AI and ML

“For the foreseeable future, computers will not be able to match humans in their ability to reason abstractly about real-world situations,” Jordan writes. “We will need well-thought-out interactions of humans and computers to solve our most pressing problems. We need to understand that the intelligent behaviour of large-scale systems arises as much from the interactions among agents as from the intelligence of individual agents.”

Moreover, he emphasises, human happiness should not be an afterthought when developing technology. “We have a real opportunity to conceive of something historically new: a human-centric engineering discipline,” he writes.

In the most ironic of turns, Jordan’s call-to-reality makes one thing come to mind: if companies and innovators stop focusing on the development of artificial intelligence, we’d probably be better off. Right now, AI is just serving as a distraction and a false saviour when the powers that be could actually make our lives far better through the judicious application of data science and machine learning. 

Share

Featured Articles

Should Tech Leaders be Concerned About the Power of AI?

With insights from Blackstone CEO Steve Schwarzman, we consider if tech leaders are right to be anxious about AI innovation and if regulation is necessary

Andrew Ng Joins Amazon Board to Support Enterprise AI

In the wake of Andrew Ng being appointed Amazon's Board of Directors, we consider his career from education towards artificial general intelligence (AGI)

GPT-4 Turbo: OpenAI Enhances ChatGPT AI Model for Developers

OpenAI announces updates for its GPT-4 Turbo model to improve efficiencies for AI developers and to remain competitive in a changing business landscape

Meta Launches AI Tools to Protect Against Online Image Abuse

AI Applications

Microsoft in Japan: Investing in AI Skills to Boost Future

Cloud & Infrastructure

Microsoft to Open New Hub to Advance State-of-the-Art AI

AI Strategy