Machine Learning vs. AI : Understanding the Difference

IEEE was informed by Professor Jordan from the University of California, Berkeley’s Department of electrical engineering and computer science, as well as the Department of Statistics, that indulging in AI-related conversations from a science-fiction point of view may be enjoyable but it can also become a diversion.

In a piece penned by Kathy Pretz of IEEE Spectrum, Jordan highlighted that the primary issue has been skirted around – constructing AI systems with a global impact that yield positive results for humans, rather than increasing disparities. “We must concentrate on developing these planetary-scale machine learning models to be functional and advantageous to mankind,” said Jordan.

Last year, the IEEE John von Neumann Medal was granted to the renowned machine learning and data science expert, Michael I. Jordan. To put it in perspective, Jeff Bezos was one of several people thanked at the foot of a piece written by him: ‘Artificial Intelligence: The Revolution Hasn’t Happened Yet’. Published in July 2019 and updated early this year, the article cautioned readers that AI technology might need more caution than enthusiasm.

“Just as humans built buildings and bridges before there was civil engineering, humans are proceeding with the building of societal-scale, inference-and-decision-making systems that involve machines, humans, and the environment. “Just as early buildings and bridges sometimes fell to the ground – in unforeseen ways and with tragic consequences – many of our early systems are already exposing serious conceptual flaws.”

Jordan has frequently delved into differentiating AI from machine learning. In a 2019 article, it is highlighted that ‘much of what is publically referred to as AI is in fact, machine learning’.

“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. We don’t have that, but people are talking as if we do.”

Jordan made the important point that the engineering fields have had a significant role in improving overall human happiness. He referenced how there has been a semantic shift between concepts such as social science and social engineering to explain this. As Pretz put it, “The need for human happiness should not be an afterthought when developing technology.’ Jordan explained, “For all of the wonderful things science has done for the human species, it really is engineering – civil, electrical, chemical, and other engineering fields – that has most directly and profoundly increased human happiness.”

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