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AI Changes Everything

I spoke at the Front End of Innovation (FEI) Conference in Boston this week about AI, innovation and the future. This post is part one of a distillation of my thoughts.

The very first thing we need to understand is, to misquote Churchill, is that the stage of the development, implementation and monetisation of artificial intelligence that we are at is not even the end of the beginning of the age of AI. We are in the earliest of times. We are in the times when folks are running around and making bold (and largely unfounded) either utopian or dystopian pronouncements. We are in the times where businesses are trying to work out if this is a real thing they can make money from or with, or another flash in the pan like NFTs.

I believe that AI will have a profound impact on the world in the long run. But, as I usually do, I will cite that we must remain mindful of Amara’s Law:

“We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.”

Roy Amara

AI will make profound changes in the way humans operate, interact with each other and machines, manufacture things, fight wars, educate the young, grow food, work and collaborate together as humans and machines, and live our lives.

But we need to understand just how early we are in this process, or in this journey. In any case, it is no longer possible to put the AI genie back into its bottle.

We are in the proto-AI stage

We are in the earliest of stages of our AI journey as human beings. Let’s just recap on how young this technology really is:

  • 1956 Artificial Intelligence: field of computer science that seeks to create intelligent machines that can replicate or exceed human intelligence
  • 1997 Machine Learning: subset of AI that enables machines to learn from existing data and improve upon that data to make decisions or predictions
  • 2012 Deep Learning: a machine learning technique in which layers of neural networks are used to process data and make decisions
  • 2021 Generative AI: create new written, visual, video, and auditory content given prompts or existing data

Firstly, let’s go back to the grandfather of AI, John McCarthy where he outlined what he was thinking of back in 1956 when they first had the idea of artificial intelligence:

“It is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable.”

This notion of “intelligence” is one that I am pretty sure the computer scientists and engineers who invented this idea did not really attempt to deconstruct, nor did they seem to have any scientists or philosophers or ethicists on hand to help them to unpack this idea of “intelligence” and machines and what it all might mean.

Aside: I want to note here that I am pretty sure that AI is going to make us question what we actually mean by intelligence. What we have always seen as intelligence seems to have merely been a kind of glibness and facility with languaage. And we are seeing with Gen AI how hollow that "intelligence" can actually be.

What are some analogues in the world of technology that will help us to get a sense of where we are in the AI journey? Well let us use the time honoured technique of consulting Gartner and their famous hype cycle diagrams:

generic Gartner hype cycle diagram
generic Gartner hype cycle diagram

Now the most recent Gartner hype cycle for AI that I could find was this one from July 2023 in which one can see that Generative AI (Gen AI) is about to tip over into the Trough of Disillusionment (or as I often like to call it the Slough of Despond).

Gartner hype cycle AI July 2023
Gartner hype cycle AI July 2023

Now I do not disagree with this assessment as we are starting to see news articles like this from the BBC emerge: AI products like Chat GPT much hyped but not much used, study says. And perhaps the best illustration of where we are in terms of our AI journey is this splendid diagram by Michael Burtov in Surviving the 2024 AI Hype Cycle (as slightly annotated by me). So before we can achieve the Plateau of Productivity there is a fair journey ahead in sorting out the business models, the technology, privacy, security and operational models in the use of AI.

Surviving the 2024 AI Hype Cycle, Michael Burtov, November 28, 2023

Where are we now?

To put this into a more familiar concept, in terms of the development of the web, I believe that in terms of the development of the internet and Web 2.0 and the development of the social web we are the Netscape stage. So if we can start to position ourselves as if we are in a similar state of knowledge and understanding about AI as if we are the Netscape stage I think it will make everything a bit easier.

Brief Social Media Timeline

Stay tuned for my next instalment on innovation and the age of AI.