If we indulge the part of our brain where metaphors live, we can discover a new dimension for Mao Zedong's "permanent revolution." Artificial Intelligence's (AI) Little Red Book is about the continuous and relentless pursuit of technological advancement and transformation within machine learning (ML) and generative AI, driven by a commitment to constant evolution, knowledge, and improvement. AI's permanent revolution shares a few things with Mao's revolutionary thinking, including:
Continual Innovation Mao advocated for ongoing and sometimes painful revolutionary activity. AI development needs to thrive on and creates constant innovation. Since ML and AI can create new versions of themselves faster than humans, new algorithms, models, and techniques push the boundaries of what AI can achieve. The Internet's Nirvana is faster and faster producing more and more with less and less - the not-so-hidden goal of every website, digital marketing campaign, social media network, and app. Think of a snowball rolling downhill with gravity and momentum pulling snow into an ever-increasing mass. Once the snowball's path down the mountain begins, human effort gets replaced with universal forces (gravity and acceleration) - more mass faster and faster with less and less human action (costs).
Addressing Inequalities Mao's revolution wanted to address social and economic inequalities. There's a growing focus on ethical AI, reducing bias in AI systems, so AI technologies are accessible and beneficial to all, not just a privileged few. The challenge for any system seeking equitable distribution of anything is to feed itself last. Systems capable of imagining or implementing equitable distribution become corrupt when stated values and philosophy become tarnished or diluted. Since inequalities like entropy are inevitable consequences of the impact of time on any system, Mao believed in the need for uninterrupted revolutionary activity to maintain the momentum of his socialist cause. Mao wanted to prevent the return of capitalists like you, me, and everyone we know. Mao should have paid more attention to Adam Smith's The Wealth of Nations (1776). Smith's "invisible hand" converts our self-interest into societal benefits. When demand increases, prices rise, so producers make more. When we've produced too much, prices slide as production slows. Consider generative AI as a HOT product with demand driving the value of everything from startups to GPUs up as people like my boss Eric find new ways AI can rapidly clone the next generation of itself.
Revolutionizing Industries Mao's permanent revolution wanted to transform society. Similarly, AI can revolutionize healthcare, finance, education, marketing, software development, and just about anything and everything we use, think, and do. As AI introduces new capabilities, improves efficiency, and opens new possibilities, everything from the cars we drive to the marketing and tech we create will change faster and faster producing more and more with less and less. AI promises to make more of us (humans) aware of the need for change, from the personal habits we want to improve to societal issues and inequities that must get addressed as awareness gets on faster and faster hamster wheel desire for change, action (implementation of change), persistence, and commitment to adapt to our environment. Since AI needs non-AI sources to learn and avoid the "AI bomb" where machine learning quality gets corrupted by circular logic, we aren't sure if the technological singularity where AI becomes uncontrollable and irreversible will change human civilization for better or worse. What do you think?
Risks of Regression Mao was obsessed with the need for vigilance to prevent a return to old ways. AI can't fall back on outdated methods or models as the field advances. We're on a speeding AI train without a clear idea of our final destination, but regression to the mean could slow progress or tick our "it's all hype" nerve. It is possible to do less and less slower and slower. Extreme data points (far from the mean, in either direction) are less common than those near the mean. Therefore, if a variable is extreme on its first measurement, it will tend to be closer to the average on a second measurement—and, paradoxically, if it is extreme on both the first and second measurements, it will tend to be closer to the average on a third measurement, and on and on. Mao wanted to avoid regression to the mean because "the old ways" were the reasons for his permanent revolution. AI's permanent revolution, the speeding train we are all riding, will get faster and faster doing more, and if we can avoid regressions due to fear, poorly informed regulation or fights over who owns what and why AI systems will avoid the "old ways" as the train speeds forward.
Continued Learning and Adaptation Like Mao's permanent revolution, AI is about continued learning and adaptation. AI models learn and improve over time. Artificial Intelligence continually adapts to discoveries, technologies, and challenges.
Mao's "permanent revolution" was a political concept applied in a specific historical and socio-political context and time. My well-stretched metaphor is an extrapolation and not a direct correlation. I'm more in my fellow Smith's invisible hand camp, as are most of those still reading Mao and AI I bet. Even though the challenges, implications, and ethical considerations in AI development are vastly different from those in a political revolution, it's fun to stretch a metaphor now and again. Please share your thoughts. Here's how you can reach me. martin (at) wte.net Martin Wescott Smith (on LinkedIn) 919.360.1224