Artificial Intelligence Editor Picks Education

Why Predicting The Future Involves Studying The Past

June 27, 2024

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Y2K End of the World Time cover — Futurists in the late 20th century predicted a computer crisis they called Y2K. Mainframe computer software used a two-digit year code which meant the Year 2000 would begin with 00 and cause software in financial institutions and government to crash. Elevators would fail. The sky would fall. Hundreds of millions of dollars were spent on software rewrites. In the end not much happened. (Image credit: https://thenuggetonline.com/y2k-20-years-later/Karlie Mickanuik)

In university, I studied history, notably medieval with a focus on Eurasia and North Africa. I chose the geographical parameters of my studies because I wanted to walk a mile in others’ shoes to appreciate through a larger lens the historic past and the present day for those living in these parts of our planet.

After graduating with the hope of teaching history to reluctant high school students in ways that would make them appreciate the past while striving into the future, I was unable to secure a job. Instead, I joined an educational publishing company and sold textbooks at universities and colleges. Eventually, I became an acquisitions editor, and then with the arrival of the personal computer a software developer and publisher.

The world of computing became my focus. When the first local area networks (LANs) emerged I turned my interest in computing into learning about how networks connected all of us whether streaming data, voice, video or energy. It occurred to me that networks were an avenue of convergence for all of these streams to merge, and when I was asked to be a keynote speaker in 2000 at a Toronto technology conference, I went on stage with a pager, cellphone, CD player, digital camera and electronic organizer all held together by a rubber band (we call them elastics in Canada). I pointed to this awkward bundle and predicted within the decade all of these would be replaced by one device small enough to put in your pocket. When the iPhone launched my prediction had become reality. I had become a futurist.

I am convinced that to be a futurist you need a foundation in history. Analyzing historical data helps you to understand current events and trends. It can help you to make well-informed decisions and even predictions from seeing patterns in the data.

Studying data patterns is how artificial intelligence (AI) works. Today’s large-language-model (LLM) AIs get fed immense quantities of data to make them proficient in predicting word associations. This has led to a proliferation of tools similar to ChatGPT that are being used by people in businesses and students in schools as shortcuts for writing reports, emails, essays, presentations and more.

From recent conversations, I have talked to people in business who use ChatGPT to write emails and reports, and students who are handing in assignments created by AI bots with teachers scrambling to determine whether what is being submitted is human or AI-generated.

Machine learning (ML) and neural network-based artificial general intelligence (AGI) use their pattern recognition capacity on unstructured and structured data fed to them. How good are they at predicting the future?

I asked the AI called Monica to answer that question. This is what it wrote:

“AI is proficient at analyzing data and patterns to make predictions based on historical information. However, predicting the future with absolute certainty is challenging due to the unpredictable nature of many events. AI can provide insights and probabilities based on available data, but it cannot foresee all possible outcomes accurately. The accuracy of AI predictions depends on the quality of data, the algorithms used, and the complexity of the situation being predicted.”

Would an AI have predicted the iPhone? I am not certain because there wasn’t a great deal of published data on multi-stream technological convergence for me to find and read when I first made my prediction about the future iPhone in 2000.

Would an AI have gotten Y2K wrong? If not familiar with Y2K it had to do with mainframe software being written with a two-digit year code. Businesses, financial institutions and governments using mainframes were told they would stop working at midnight on December 31, 1999, as the year code changed to 00. Airplanes were going to drop out of the skies. Trains would stop running, Elevators would plunge to the ground. These were the scenarios being sold by the computer industry at the time that generated hundreds of millions of dollars as old software got rewritten. It turned out to be a highly exaggerated crisis perpetuated by the futurists of the time.

Would an AI have predicted the Russian Revolution or the eventual fall of the U.S.S.R? If the AI had access to the historical, economic and demographic data of the time, remember, there wasn’t an Internet back then or a digitized version of the Encyclopedia Britannica for it to study, I think it would have predicted both results.

The future isn’t written. It will always be uncertain. The psychohistory of Isaac Asimov’s “Foundation” is science fiction. Delving into history, however, does provide context for future possibilities. We are amassing vast amounts of data with it doubling in months today. Historical context and collective experience are equipping us better to tackle current challenges and predict what lies ahead whether it is human futurists making prognostications or AIs acting as our oracles.

When we study the cyclical nature of history and thoughtfully examine and interpret our past, we are more informed and better prepared to be futurists.