In 1965, Time Magazine made bold projections about the wonders awaiting us from the burgeoning field of technology. While we have seen technological wonders in the last 50 years, almost none of the predictions featured in the magazine came to pass:
"Men such as IBM Economist Joseph Froomkin feel that automation will eventually bring about a 20-hour work week, perhaps within a century, thus creating a mass leisure class. Some of the more radical prophets foresee the time when as little as 2% of the work force will be employed, warn that the whole concept of people as producers of goods and services will become obsolete as automation advances. Even the most moderate estimates of automation's progress show that millions of people will have to adjust to leisurely, 'nonfunctional' lives, a switch that will entail both an economic wrench and a severe test of the deeply ingrained ethic that work is the good and necessary calling of man."
Technology experts continue to overestimate the positive impact of technological advances on the average person. In fact, many recent pronouncements have a very similar ring to the quote above. This line of thought is particularly pervasive in the Artificial Intelligence space today. It's understandable that these sweeping claims are appearing anew – perhaps no other technological advancement has advanced so rapidly since the dawn of the information era. While these accomplishments are remarkable, the fantastical claims that artificial general intelligence (AGI) is just around the corner is incorrect for several reasons.
"The Last Mile"
Nearly every seasoned engineer is familiar with the 90/10 rule, which states that 90% of the work required to finish a project will take roughly 10% of the timeline. The last 10% of work will consumed 90% of the time. While this rule of thumb isn't always a perfect indicator, we see this play out repeatedly.
Five years ago, Tesla appeared poised to deliver a fully autonomous Level 5 vehicle in the next few years; however, the cars manufactured today remain at a humble partial automation (Level 2). Microprocessor design is another example. Transistor size has decreased far more slowly over the last decade than in previous decades. Each successive decade has seen a decrease in speed with which transistors have shrunk. As it turns out, Moore's Law has a limit. This slowed progress mainly stems from significantly more difficult engineering problems as density increases beyond a certain point. Quantum effects such as electron tunneling, where electrons can pass through an extremely thin gate, suddenly become major roadblocks.
Challenge Parity
The trajectory of progress is uncertain and often veers off in unexpected directions. For instance, while the digital age promised enhanced connectivity and access to information, it also gave rise to issues like misinformation, cyberbullying, and digital addiction – challenges that were scarcely anticipated as we heralded the arrival of the internet area. This tendency to overlook potential pitfalls in the face of new technology underscores a common shortfall in our predictive mental models: they often mirror the current zeitgeist and neglect the nuanced complexities of the future.
Systematic Underestimation of Inequality and Corporate Greed
The predominance of Silicon Valley as a hub for technological innovation and prediction can create a skewed perspective on the future of technology. The region's unique ecosystem of venture capital, start-ups, and cutting-edge research tends to foster an echo chamber of ideas and optimism, primarily driven by those who benefit most from technological advances. This demographic, often composed of affluent, technologically savvy individuals, may not fully grasp the broader social and economic challenges faced by less privileged communities worldwide. Consequently, predictions from this vantage point can overlook crucial issues such as digital divides, access to technology, and the varying impacts of automation on different socio-economic groups.
While the advancements in technology we have seen in recent years are impressive, we must approach predictions about the future of technology with caution. The road to AGI is longer than we think, and we must be mindful of the potential pitfalls and challenges that may arise along the way. It is important to consider the impact of technology on all members of society, especially those who may be less privileged. By taking a more nuanced and inclusive approach to technological progress, we can ensure that the benefits of these advancements are more widely shared, and that we are better prepared to address the challenges that lie ahead.
