The Artificial Intelligence Revolution : ChatGPT and the Singularity Race

By Andrew Bathgate

Prepare for a profound paradigm shift with 'The Artificial Intelligence Revolution: The Singularity Race.' This book delves deep into the most significant revolution of our time – the imminent explosion of artificial intelligence (AI) that promises to redefine the contours of human life and societal structures.

The author takes you on a riveting journey through the impending transformations AI will catalyze, from human and worker augmentation to the stark reality of 'Jobocalypse' – a seismic shift in the global workforce and employment landscapes.

Yet, amidst the upheaval, the book presents an optimistic perspective – the potential end of scarcity and the ushering in of an era of abundance. We move through a rapidly evolving landscape of super-intelligence, towards a hopeful future where resources might no longer be a constraint.

The narrative doesn't stop at socio-economic upheavals. It delves into the speculative endgame of this revolution, bravely tackling the prospects of a post-capitalist world and the redefinition of societal purpose in an AI-dominated reality.

This book challenges us to grapple with audacious concepts – from human mind augmentation, the notion of the 'Singulariton', to a future where nanites could be the norm. It explores a reality where the lines between the 'experience engine' and real life are blurred, forcing us to reconsider our perception of consciousness and existence.

'The Artificial Intelligence Revolution: The Singularity Race' is a must-read for anyone who wishes to understand the imminent future. It's a comprehensive guidebook for navigating the moral, ethical, and societal challenges that the AI revolution presents. It insists that we question, comprehend and prepare for our evolving roles in this extraordinary narrative.

The future isn't far off. It's here, and it's time we understood it. Are you ready?

• Language: English
• Publisher: Andrew Bathgate
• Release date: Sep 11, 2023
• ISBN: 9798890480064

Book preview

Preface

In 1981, in the physics lab after class, I soldered together a computer kit I had ordered from an electronics magazine. I hooked it up to a TV and began a forty-year love affair with all things technical. It was uncommon to have a career in computing in 1981, so my teachers tried to persuade me to give up my obsession and focus on something practical. One evening, while trying to choose a real career, I realized I was fascinated not only with computers but by the human mind. So, as working with computers was seen as impractical, I decided I would be a psychologist and kept computing as a hobby.

In 1984, I started my undergraduate degree in psychology. There was rampant unemployment at the time, and I often wondered whether I would be able to get a job after graduation. Concerned, I went to the library and looked up the post-graduate employment rates for psychology majors—it was 50 percent. I did not like those odds, so I looked up post-graduate employment rates for computer majors, and it was 98 percent.

With great joy, I then switched majors. In the first year of my computer science degree, we were presented with electives, and I was immediately drawn to artificial intelligence (AI). I thought with that elective, I could understand the mind and the magic that is the computer.

I loved university; I loved studying computers, programming, and AI. I also won a grant by solving a problem for the British Ministry of Defense using neural nets to recognize sonar targets. I coded expert systems and a natural language parser written in C using neural nets. It was extraordinarily accurate for its day. The only problem was the processing took ten minutes per word, so it wasn’t very practical.

Few people thought AI was real and set constantly moving goalposts that would prove the existence of AI. When a computer can beat a human at chess, then I’ll be impressed, people used to say. Then, in the late 1950s, computers started playing chess, and people still didn’t believe in it.

New goals were constantly set for AI, and AI kept achieving them. AI could recognize faces. It could sort fruit. It could diagnose illness. It could prescribe the right antibiotics. It could beat grandmasters in chess. It could play and win Jeopardy against its all-time human champions. It beat Go masters. Still, people said it was all shabby little tricks and a lot of processing power. But is that really so different from the human mind?

The father of computers, Alan Turing, posited a test for AI in a 1950 paper called Computing Machinery and Intelligence. The Turing test involves a human evaluator engaging in natural language conversations with both a human and a machine without knowing which is which. If the evaluator cannot reliably determine which is the human and which is the machine based on the responses to their questions, then the machine is said to have passed the Turing test.

In the 1990s, I decided to try my hand at coding a chatbot to pass the Turing test on a system called Compuserve. The bot never came close to being mistaken for a person. However, it was an intriguing experiment, and made me keep my eye on the chatbot industry. I was involved as an advisor to a company that was developing AI algorithms to detect influence bots farming (or pharming) on Facebook in the run up to the 2016 presidential election. Getting bots to generate and disseminate information was a money-making endeavor and was no easy task. The technology had advanced to the point that most people mistakenly believed that chat bots were human. I have long understood that information is a valuable commodity, but that experience made me realize that misinformation is just as valuable. The truth is just the truth but a lie can be tailored to serve a purpose.

Philosopher John Searle's 1980 Chinese Room argument is an analogy to critique the idea that a computer program could have true intelligence and understanding.

The analogy goes like this: Imagine a person who does not speak or understand Chinese but is placed in a room with a large book of instructions in English on how to manipulate Chinese symbols. People outside the room hand them written questions in Chinese, and the person inside the room follows the instructions to manipulate the symbols in response. The person inside the room has no actual understanding of Chinese but can give the appearance of understanding by following the instructions.

Searle's point is that a computer program, like the person in the room, could manipulate symbols without understanding the meaning behind them. According to Searle, understanding language requires more than just manipulating symbols—it requires actual cognitive processes and consciousness.

Searle's argument is intended to challenge the idea of strong AI, which holds that machines can exhibit true intelligence and consciousness. Searle's Chinese Room analogy suggests that even if a machine can give the appearance of understanding language, it may not actually possess true intelligence or consciousness.

John Searle explained his analogy to me over dinner in 1987, and I thought he had proved that it simply does not matter what the medium of information processing is—what matters is the processing itself. Intelligence and consciousness are emergent not in the material but in the abstract. The physical merely correlates with phenomena of intelligence and consciousness. It does not matter if that information is processed in the sodium and potassium