An image of the folks as mentioned above via the GAN de jour
First, as usual, i trust everyone is safe. Second, I’ve been “thoughting” a good deal about how the world is being eaten by software and, recently, machine learning. i personally have a tough time with using the words artificial intelligence.
What Would Nash, Shannon, Turing, Wiener, and von Neumann Think of Today’s World?
The modern world is a product of the mathematical and scientific brilliance of a handful of intellectual pioneers who happen to be whom i call the Horsemen of The Digital Future. i consider these humans to be my heroes and persons that i aspire to be whereas most have not accomplished one-quarter of the work product the humans have created for humanity. Among these giants are Dr. John Nash, Dr. Claude Shannon, Dr. Alan Turing, Dr. Norbert Wiener, and Dr. John von Neumann. Each of them, in their own way, laid the groundwork for concepts that now define our digital and technological age: game theory, information theory, artificial intelligence, cybernetics, and computing. But what would they think if they could see how their ideas, theories and creations have shaped the 21st century?
A little context.
John Nash: The Game Theorist
John Nash revolutionized economics, mathematics, and strategic decision-making through his groundbreaking work in game theory. His Nash Equilibrium describes how parties, whether they be countries, companies, or individuals, can find optimal strategies in competitive situations. Today, his work influences fields as diverse as economics, politics, and evolutionary biology. NOTE: Computational Consensus Not So Hard; Carbon (Human) Consensus Nigh Impossible.
The Nash equilibrium is the set of degradation strategies
![\[(E_i^*,E_j^*)\]](https://www.tedtanner.org/wp-content/ql-cache/quicklatex.com-4b7772a3028c53b1f55a34079971f64d_l3.png "Rendered by QuickLaTeX.com")
such that, if both players adopt it, neither player can achieve a higher payoff by changing strategies. Therefore, two rational agents should be expected to pick the Nash equilibrium as their strategy.
If Nash were alive today, he would be amazed at how game theory has permeated decision-making in technology, particularly in algorithms used for machine learning, cryptocurrency trading, and even optimizing social networks. His equilibrium models are at the heart of competitive strategies used by businesses and governments alike. With the rise of AI systems, Nash might ponder the implications of intelligent agents learning to “outplay” human actors and question what ethical boundaries should be set when AI is used in geopolitical or financial arenas.
Claude Shannon: The Father of Information Theory
Claude Shannon’s work on information theory is perhaps the most essential building block of the digital age. His concept of representing and transmitting data efficiently set the stage for everything from telecommunications to the Internet as we know it. Shannon predicted the rise of digital communication and laid the foundations for the compression and encryption algorithms protecting our data. He also is the father of my favorite equation mapping the original entropy equation from thermodynamics to channel capacity:
![\[H=-1/N \sum_{i=1}^{N} P_i\,log_2\,P_i\]](https://www.tedtanner.org/wp-content/ql-cache/quicklatex.com-5a3422c3ff70f85af819c83d0790d495_l3.png "Rendered by QuickLaTeX.com")
The shear elegance and magnitude is unprecedented. If he were here, Shannon would witness the unprecedented explosion of data, quantities, and speeds far beyond what was conceivable in his era. The Internet of Things (IoT), big data analytics, 5G/6G networks, and quantum computing are evolutions directly related to his early ideas. He might also be interested in cybersecurity challenges, where information theory is critical in protecting global communications. Shannon would likely marvel at the sheer volume of information we produce yet be cautious of the potential misuse and the ethical quandaries regarding privacy, surveillance, and data ownership.
Alan Turing: The Architect of Artificial Intelligence
Alan Turing’s vision of machines capable of performing any conceivable task laid the foundation for modern computing and artificial intelligence. His Turing Machine is still a core concept in the theory of computation, and his famous Turing Test continues to be a benchmark in determining machine intelligence.
In today’s world, Turing would see his dream of intelligent machines realized—and then some. From self-driving cars to voice assistants like Siri and Alexa, AI systems are increasingly mimicking human cognition human capabilities in specific tasks like data analysis, pattern recognition, and simple problem-solving. While Turing would likely be excited by this progress, he might also wrestle with the ethical dilemmas arising from AI, such as autonomy, job displacement, and the dangers of creating highly autonomous AI systems as well as calling bluff on the fact that LLM systems do not reason in the same manner as human cognition on basing the results on probabilistic convex optimizations. His work on breaking the Enigma code might inspire him to delve into modern cryptography and cybersecurity challenges as well. His reaction-diffusion model called Turings Metapmorphsis equation, is foundational in explaining biological systems:
Turing’s reaction-diffusion system is typically written as a system of partial differential equations (PDEs):
![\[\frac{\partial u}{\partial t} &= D_u \nabla^2 u + f(u, v),\]](https://www.tedtanner.org/wp-content/ql-cache/quicklatex.com-99147d396c77a8652cc77ac0cab65ffe_l3.png "Rendered by QuickLaTeX.com")
![\[\frac{\partial v}{\partial t} &= D_v \nabla^2 v + g(u, v),\]](https://www.tedtanner.org/wp-content/ql-cache/quicklatex.com-a0acfd5f636e96e9c05ed136c210b906_l3.png "Rendered by QuickLaTeX.com")
![\[\begin{itemize}\item $u$ and $v$ are concentrations of two chemical substances (morphogens),\item $D_u$ and $D_v$ are diffusion coefficients for $u$ and $v$,\item $\nabla^2$ is the Laplacian operator, representing spatial diffusion,\item $f(u, v)$ and $g(u, v)$ are reaction terms representing the interaction between $u$ and $v$.\end{itemize}\]](https://www.tedtanner.org/wp-content/ql-cache/quicklatex.com-3c0fe86ddd76baee1115898f2a4cd86e_l3.png "Rendered by QuickLaTeX.com")
In addition to this, his contributions to cryptography and game theory alone are infathomable.
In his famous paper, “Computing Machinery and Intelligence,” Turing posed the question, “Can machines think?” He proposed the Turing Test as a way to assess whether a machine can exhibit intelligent behavior indistinguishable from a human. This test has been a benchmark in AI for evaluating a machine’s ability to imitate human intelligence.
Given the recent advances made with large language models, I believe he would find it amusing, not that they think or reason.
Norbert Wiener: The Father of Cybernetics
Norbert Wiener’s theory of cybernetics explored the interplay between humans, machines, and systems, particularly how systems could regulate themselves through feedback loops. His ideas greatly influenced robotics, automation, and artificial intelligence. He wrote the books “Cybernetics” and “The Human Use of Humans”. During World War II, his work on the automatic aiming and firing of anti-aircraft guns caused Wiener to investigate information theory independently of Claude Shannon and to invent the Wiener filter. (The now-standard practice of modeling an information source as a random process—in other words, as a variety of noise—is due to Wiener.) Initially, his anti-aircraft work led him to write, with Arturo Rosenblueth and Julian Bigelow, the 1943 article ‘Behavior, Purpose and Teleology. He was also a complete pacifist. What was said about those who can hold two opposing views?
If Wiener were alive today, he would be fascinated by the rise of autonomous systems, from drones to self-regulated automated software, and the increasing role of cybernetic organisms (cyborgs) through advancements in bioengineering and robotic prosthetics. He, I would think, would also be amazed that we could do real-time frequency domain filtering based on his theories. However, Wiener’s warnings about unchecked automation and the need for human control over machines would likely be louder today. He might be deeply concerned about the potential for AI-driven systems to exacerbate inequalities or even spiral out of control without sufficient ethical oversight. The interaction between humans and machines in fields like healthcare, where cybernetics merges with biotechnology, would also be a keen point of interest for him.
John von Neumann: The Architect of Modern Computing
John von Neumann’s contributions span so many disciplines that it’s difficult to pinpoint just one. He’s perhaps most famous for his von Neumann architecture, the foundation of most modern computer systems, and his contributions to quantum mechanics and game theory. His visionary thinking on self-replicating machines even predated discussions of nanotechnology.
Von Neumann would likely be astounded by the ubiquity and power of modern computers. His architectural design is the backbone of nearly every device we use today, from smartphones to supercomputers. He would also find significant developments in quantum computing, aligning with his quantum mechanics work. As someone who worked on the Manhattan Project (also Opphenhiemer), von Neumann might also reflect on the dual-use nature of technology—the incredible potential of AI, nuclear power, and autonomous weapons to both benefit and harm humanity. His early concerns about the potential for mutual destruction could be echoed in today’s discussions on AI governance and existential risks.
What Would They Think Overall?
Together, these visionaries would undoubtedly marvel at how their individual contributions have woven into the very fabric of today’s society. The rapid advancements in AI, data transmission, computing power, and autonomous systems would be thrilling, but they might also feel a collective sense of responsibility to ask:
Where do we go from here?
Once again Oh Dear Reader You pre-empt me….
A colleague sent me this paper, which was the impetus for this blog:
My synopsis of said paper:
“The Tensor as an Informational Resource” discusses the mathematical and computational importance of tensors as resources, particularly in quantum mechanics, AI, and computational complexity. The authors propose new preorders for comparing tensors and explore the notion of tensor rank and transformations, which generalize key problems in these fields. This paper is vital for understanding how the foundational work of Nash, Shannon, Turing, Wiener, and von Neumann has evolved into modern AI and quantum computing. Tensors offer a new frontier in scientific discovery, building on their theories and pushing the boundaries of computational efficiency, information processing, and artificial intelligence. It’s an extension of their legacy, providing a mathematical framework that could revolutionize our interaction with quantum information and complex systems. Fundamental to systems that appear to learn where the information-theoretic transforms are the very rosetta stone of how we perceive the world through perceptual filters of reality.
This shows the continuing relevance in ALL their ideas in today’s rapidly advancing AI and fluid computing technological landscape.
They might question whether today’s technology has outpaced ethical considerations and whether the systems they helped build are being used for the betterment of all humanity. Surveillance, privacy, inequality, and autonomous warfare would likely weigh heavily on their minds. Yet, their boundless curiosity and intellectual rigor would inspire them to continue pushing the boundaries of what’s possible, always seeking new answers to the timeless question of how to create the future we want and live better, more enlightened lives through science and technology.
Their legacy lives on, but so does their challenge to us: to use the tools they gave us wisely for the greater good of all.
Or would they be dismayed that we use all of this technology to make a powerpoint to save time so we can watch tik tok all day?
Until Then,
#iwishyouwater <- click and see folks who got the memo
𝕋𝕖𝕕 ℂ. 𝕋𝕒𝕟𝕟𝕖𝕣 𝕁𝕣. (@tctjr) / X
Music To blog by: Bach: Mass in B Minor, BWV 232. By far my favorite composer. The John Eliot Gardiner and Monterverdi Choir version circa 1985 is astounding.
Nothing to do with the article (which I completely appreciate), but the way you write the C in Ted C. Tanner Jr is always a (complex) marvel to.
Dr LC:
i appreciate the time you took to read the blog. i also appreciate the commentary as well as the history at a certain company in cupertino when the Wyrm Clan had a contest about the letter C. Also thank you for catching the nuance of the (complex) operator. i hope you and your family and doing well.
I concur; this is an excellent thought experiment.
Firstly, all except Nash and Shannon would be astounded by the widespread accessibility and democratization of computation for humanity. This is because they lived long enough to witness its early stages. All would be equally surprised by the current state of AI and its potential influence on humanity due to its ubiquitous nature. Only Shannon and Nash, who witnessed its development, anticipated such massive scaling and commoditization to the point that a poor fisherman in India could afford a cheap Android phone.
Among these titans, I believe Wiener would have the most significant objections and might even advocate for a pause, especially if he were transported to this century with only his previous knowledge. In “The Human Use of Human Beings,” Wiener cautioned that increasing reliance on technology could dehumanize society, as people would prioritize efficiency and productivity over human values and connection. He pondered deeply the potential positive and negative impacts on society. He would be delighted to see advancements like neural interfaces for prosthetics and would be fascinated by neural networks, but he would also be concerned about their lack of explainability and their potential actions.
A distant second to Wiener might be John von Neumann due to his involvement in the Manhattan Project. However, I concede this is speculative, as he would likely also be eager to explore AI to expand on game theory. He would be a child in a candy store, along with Nash.
The biggest unknown in my mind would be Shannon. He once stated, “I do what comes naturally, and usefulness is not my main goal. I like to solve new problems all the time.”
Considering the influence of the modern context, all of them, except perhaps Shannon, might have advocated for a global-level equivalent of an ethical Geneva Convention had they lived today.
However, you’ve accurately portrayed their individual perspectives, and your interpretations seem quite plausible.
Hi Jay:
i truly appreciate you taking the time to read the blog and i truly appreciate the thoughtful commentary. A couple of points herewith:
Thank you for your thoughtful and insightful comment! I really appreciate how you’ve expanded on the perspectives of these intellectual giants and brought Wiener into the conversation with such nuance (yes is said it…) . You’re absolutely right Wiener’s concerns about the dehumanizing effects of technology are more relevant now than ever, and his deep reflections in The Human Use of Human Beings would likely have sparked significant debate in today’s discussions on AI ethics and societal impacts. I agree that he would probably be both fascinated and deeply cautious about the trajectory of AI and technology in general, especially with regard to explainability and unintended consequences.
Your point about von Neumann is intriguing too, especially given his involvement with the Manhattan Project. It’s interesting to speculate how that experience might have influenced his approach to AI. While, as you say, he might have had reservations, I can also imagine him enthusiastically applying his game theory insights to this new frontier (along with Nash).
I love your observation about Shannon as well (plus i am biased). His focus on solving new problems purely for the intellectual challenge, rather than their usefulness, really speaks to the nature of discovery during that era—and perhaps explains why predicting Shannon’s stance on today’s landscape is so difficult. As for Nash, I completely agree that the potential for AI to expand on game theory would have been a fascinating playground for him.
Lastly, your suggestion that many of these thinkers might have advocated for an ethical framework akin to a “Geneva Convention” for AI is engaging yet a slippery slope – yes?
JS again much appreciated, thank you for your time.
//ted
Slippery slope, yes. Something like that would come of a massive catastrophe like WWI. I brought it to the surface due to their era and that perspective. We could go on and on about this, but it would be Turning insights that I would be most interested in since we have little to go on regarding his philosophy.