I endlessly read people arguing that humans will be to AI as animals or insects are to humans. They envision a future where AI’s relentless advancement transcends every faculty we possess.

The countervailing stance is that human potential is unlimited. We have deliberately and consistently increased our capabilities and knowledge, and now we will use the tools we have created to continue to advance.

The rise of AI has intensified this debate, leading us to question: Are we, as humans, inherently limited or unlimited?

My thinking on this was clarified and crystalized by reading David Deutsch’s seminal work “The Beginning of Infinity”, in which he lays out an extensive and powerful case for human knowledge and abilities being unbounded.

He argues that humans are “universal explainers” who have created and learned to use scientific principles to indefinitely improve our theories, knowledge, and understanding,

At any point our understanding is limited and incorrect, but by continuing to apply the same principles we will consistently and indefinitely advance our knowledge.

He writes:

The astrophysicist Martin Rees has speculated that somewhere in the universe ‘there could be life and intelligence out there in forms we can’t conceive. Just as a chimpanzee can’t understand quantum theory, it could be there are aspects of reality that are beyond the capacity of our brains.’ But that cannot be so. For if the ‘capacity’ in question is mere computational speed and amount of memory, then we can understand the aspects in question with the help of computers – just as we have understood the world for centuries with the help of pencil and paper. As Einstein remarked, ‘My pencil and I are more clever than I.’

In terms of computational repertoire, our computers – and brains – are already universal (see Chapter 6). But if the claim is that we may be qualitatively unable to understand what some other forms of intelligence can – if our disability cannot be remedied by mere automation – then this is just another claim that the world is not explicable. Indeed, it is tantamount to an appeal to the supernatural, with all the arbitrariness that is inherent in such appeals, for if we wanted to incorporate into our world view an imaginary realm explicable only to superhumans, we need never have bothered to abandon the myths of Persephone and her fellow deities.

So human reach is essentially the same as the reach of explanatory knowledge itself.

The track record of humanity, which in just the last few thousand years has grown from superstitions to understanding in great depth our Universe from sub-atomic particles to the structure of the cosmos, sitting on a planet in a far-flung galaxy, is testament to our ability to develop knowledge.

Indeed, the pace of (human) scientific progress and knowledge is not just fast, it is accelerating, by just about any measure you choose.

People compare the exponential technologies underlying AI with our finite cognition and conclude we will be left behind. This is so deeply flawed that I will address this in more detail in another post.

In short, humans are very clearly not static. We co-evolve with the technologies we have created, constantly extending the boundaries of what it means to be human.

It is possible that to keep pace we will need to augment ourselves with brain-computer interfaces and other cognitive amplification technologies. As I wrote in my 2002 book Living Networks,

the real issue is not whether humans will be replaced by machines, because at the same time as computing technology is progressing, people are merging with machines. If machines take over the world, we will be those machines.

Believing we’re doomed to be dwarfed by super-intelligent AI is essentially betting against humanity.

It is giving up. It is lacking faith in humanity. It’s a surrender to superstition, to the idea that there is something undefined and unknowable beyond our capacity to imagine or understand.

The essence of being human is this: We face and solve problems and we progress. The concept of things we cannot understand goes against everything that humans have demonstrated themselves to be.

In an era defined by the rapid rise of AI, it is crucial that we maintain faith in the human capacity for limitless growth and expansion. The unfolding story of our species is not one of succumbing to imagined limits but one of constantly redefining what is possible.

Our future is inevitably one of Humans + AI – our species amplified by the intelligences we have created.

We will not be subsidiary players in this union. Our ability to understand and grow and frame what this incredible pairing can achieve is unlimited.

At this point we have no solid evidence how this will turn out. It is your choice:

Believe humans are intrinsically limited and that we will be as cockroaches to superior intelligences.

Or bet on a species that is intelligent and adaptable enough to have created everything we have so far, and our ability to continue to progress and grow, harnessing the power of our inventions.

In fact the random (as opposed to professional ethicist or MBA student) subjects preferred the AI advice, the paper suggests because AI is generally very agreeable.

The question is what is the role of AI in human ethical decisions?

I have long said that ethics is a distinctly human capability and ever-more important as our actions shape the future of humanity. If AI can provide ethical guidance that is as good as human input, it is extremely valuable.

Yet it is, of course, not a substitute.

Advice is not the same as making choices. Our ethical decision-making can be enhanced through better advice, or access to advice.

Access to a professional ethicist may not always be available, but AI is readily accessible.

The principle of not entirely relying on advice from machines (or humans) remains crucial. Nevertheless, high-quality input is invaluable in shaping our thinking and choices, both as individuals and as a society.

From here we need to work out the role of AI in our ethical decision-making. Do we use it at all? Where do we draw on its input? How do we weight that?

From a bigger frame, given the import of our ethical decisions today, how do we use all available resources – including AI – to shape a better future?

Jose Luis Alvarado, dean of the Fordham Graduate School of Education, has written an excellent counter-narrative to those saying that tertiary education doesn’t matter any more, om the deep inequity of the anti-college movement. He shares how he was told at school he shouldn’t aspire to going to college. Others didn’t see his potential, quite possibly because of his family background.

I have long pointed to the decreasing relevance of higher education.

Employers are finding real-world capabilities and peer esteem are better indicators of performance than exam-assessed degrees.

Educational programs are often out of date while they are taught, let alone when students graduate.

Young entrepreneurs can arguably learn more by doing than by attending any less-than-excellent educational course.

Yet it’s absolutely true that these views come from a position of privilege.

The quality of tertiary education absolutely needs to improve and be more relevant to a rapidly changing world.

But its very existence offers pathways to anyone to achieve anything, not just entrepreneurial, but in every facet of society.

Which leaves us with the challenge of ensuring that everyone, regardless of wealth or background, has clear access to quality tertiary education, and full encouragement to pursue that if they want to.

That is at the heart of a fair society.

As part of the track Main Sequence Ventures partner Phil Morle and I had a conversation on The Next Blur: How To Be Ready for a World of Accelerating Change, essentially how to think strategically about 2050 for entrepreneurs and business leaders.  

Here are some highlights from what we covered:

Framing thinking about 2050

Main Sequence recently ran a 2050 workshop for the leaders of its portfolio companies, focusing on the interactions between different technologies, which generated this chart (click here or on the image for a zoomable image).

To give us context on the path to 2050 Phil ran through some of the massive shifts over the last 30 years, including the interaction of rapid technology development and society.

“There are probably some two way interactions. But you’re starting to see the particles all hit each other, so you can start to think through the world and see all these things affecting each other. 

The beautiful thing that happened in the workshop is when we started joining dots together, creating a noise of ideas and connections. It’s like a neural network. 

All the AI people hadn’t even thought about quantum. So when they understood what quantum computers were about to be and they started thinking about AI they started realizing they could do more. And then all the people making healthcare solutions realized that if AI can do that because of quantum oh my god, I can do all these things. There are going to be all these all these ripple effects. So it became a super interesting conversation.

It just gets really, really interesting. I think these things are colliding so quickly today, they’re making each other go faster and faster and faster.”

Why the world is accelerating 

I followed by discussing some of the forces leading to the acceleration of change in technology, society, and business.

“Everyone’s been saying forever that the world is changing faster and faster. So is it actually going faster and faster, accelerating? The evidence seems to be that it is indeed accelerating.

There are a number of underlying factors. The first and most important one is connectivity. Simply whenever somebody comes up with an idea we can immediately communicate and collaborate around the world, which wasn’t the case not too long ago. Another fundamental shift is preprint and open access journals. There used to be a massive gap from development of scientific research to that being available, whereas now with preprint everything’s immediately available. The acceleration of knowledge is increasing.

Another development which has been absolutely fundamental is open source. Many of the lower levels of the technology stacks are open source, so people can immediately go to higher levels of value creation. Of course another development feeding on itself is AI, machine learning and generative AI are able to design capacities to be able to do things faster and better.

One of the shifts that is often ignored is health care, where when we have longer, healthier lives and better abilities, we’re able to spend more time doing things rather than tending to our diseases, thinking more and better. Better healthcare means more people have more resources and more time to accelerate. There is a whole array of other driving forces, all of which are feeding on themselves.”

Foresight methodologies

I then spoke at a high level about foresight methodologies.

“If you look at every single foresight methodology, essentially it incorporates two key aspects: understanding the trends and the driving forces, and overlaying the uncertainties.

For any trend – which is data from the past pointing to today – possiblities include: will this trend will continue as it is? will it accelerate? will it decelerate and reduce? Or will it stop and reverse? In fact, many trends have reversed for various reasons.

Foresight is a structured approach to thinking about the future. We cannot predict the future. But there’s a whole array of different methodologies we can apply by observing past developments in data patterns, what we can call a trend, thinking about the scope of the uncertainties, and combining those.

[Scenarios] must be multi dimensional worlds. These are the tools we have to do effective planning for building businesses, developing new technologies, creating better societies, and all the other good things everyone here is doing.”

AI as copilot for future thinking

Phil shared the “Forces to 2050” future scenario generator that Main Sequence has created to allow founders to explore possibilities from the intersection of technology, geopolitical, and social forces, and the rationale for it.

“When people try to use AI to write a blog post about the future, we all just know how awful and generic that’s going to be. But it’s not going to be like that forever. It’s going to get better and better and help me to get there. It becomes my job to teach my AI to write good stuff and to do that quicker. I have to work on that with prompt engineering and visual production.

[The generator] is not making great science fiction writing. But as a co pilot for an innovator it’s useful if you’re about to start a company in that space. That’s interesting. What if that did happen? What if I could make that happen?

What if that could be my job in 10 years? Like back testing your career, how could I be that person? What do I need to learn to get there? It’s helping me think.”  

Lessons for long-term thinking and strategy

These were just some highlights of the discussion, there was a lot more, including Phil and I running through some examples of charting long-term company trajectories, the critical challenge of getting timing right. and using backcasting as a strategy tool.

The overarching frame for the conversation is that we not only must think about the long-term in our ventures, we can. There are a whole set of tools, methodologies, frames, and approaches that are incredibly useful for founders, boards, investors, and government leaders. 

Phil and I both have a mission to share this thinking. The SxSW Sydney session was a step on that path.

Creativity was long supposed to be last bastion of human dominion over machines,. Yet over the last 18 months that has been cast into doubt. So what is the future of creativity in a world in which AI is – in some ways at least – becoming creative? It’s best to get it in David’s words. Here are some of most interesting quotes I captured from the session.

“My starting point is I don’t think all creativity needs to survive.”

“I just think that creative is going to thrive and survive no matter what duress or what rears its head.”

“You know what, it’s just going to amplify and enhance.”

“We have to let go of being nostalgic about what creativity is. Success is not nostalgic, neither is creativity.”

“The CEOs and the CTOs and growth officers… are looking for these creative people because clearly these people ask different questions. If you ask different questions, you get different answers.”

“We’ve all probably been lectured by some client or someone’s told us the triangle of speed, quality and cost: pick two. I grew up with that whole thing. Three, you know what you, need all three now. Technology can allow us to do all three, you can do things at pace, you can do things that are high quality, and you can do that at an affordable cost.”

[In the context of selling his agency Droga5 to Accenture to create Accenture Song] “I don’t want people to have to choose between the march of technology and the purity of creativity and only one of them could survive. They both need each other. Creativity needs technology to be real. Technology needs creativity to become to be more relatable and human.”

“AI could write the next version of Fast and Furious, you could plug that in right now and I’ll give you 10, 11, 12, 13 and 14. Gen AI is not going to write Barbie. It’s not doing because that’s that’s a different take on things, that takes a type of mindset that is leaps and irreverence and quirks and all these different things that make us who we are.”

“Look at the sort of industries that disappeared within our industry as it merged typesetters, storyboard artists, all these things that were crucial and part of the ecosystem just evaporated. Many people found new ways to position themselves; technology is irrepressible. So when we accept that it’s irrepressible. Then you start to work out’ “okay, what’s my take on that?’ That’s why I say to the creative people, stop thinking about what’s going to make you redundant, start thinking about how you could shape it and influence it. Because that’s what it needs.”

It was a highly stimulating, rich discussion. Below are slivers of the discussion organized around just two of the major themes of the conversation, focusing on my thoughts but also including insights from the other panelists (distorted through my memory and perception): 

Beyond productivity

Productivity should not be the goal; productivity is a flawed concept that only measures efficiency of tasks and output, not value created. Productivity metrics work well for machines and repetitive tasks but not for knowledge work where goals are less defined. Value often comes from not being busy, by wandering, doing things that seem to have no bearing on work, and coming across different ideas, having conversations. This is not usually achieved by sitting in front of computers at your desk. 

Productivity is based on metrics, so what should companies measure? The only truly useful measures are higher-order objectives such as customer satisfaction, customer happiness, employee personal growth, creativity, and so on. Any lower-level focus on tasks completed will be gamed and is close to meaningless in driving real value creation.

For knowledge workers productivity is only really meaningful over longer periods such as years or possibly months. This means that all exploration and learning along the way has time to flourish and bring unexpected benefits, people have the space they need to flourish, grow, reimagine, and find new pathways. Measuring productivity in short time frames necessarily quashes the ability to develop, grow, and create true value.

The organizations that will prosper in these increasingly wonderful, extraordinary, wild times are the ones that focused on the biggest possible picture of making people happier and better and more fulfilled. If they do, productive outcomes will flow richly.

Amplifying human potential

The starting point is believing in human potential. The question has to be: “who can we be?” Organizations need to move beyond the boxes of job roles and definitions to completely fluid work in which people can apply their talents – recognized and latent – in a multitude of ways. The organizations that enable people’s potential to emerge are the ones that will succeed in the years to come.

Growth has become for some a dirty word, but that’s only if you are focusing on growing revenue and profits to the exclusion of all else. We need to also frame it as the growth of humans and organizations to become who and what they can be. In a word, moving towards their positive potential.    

Growth is a mutual endeavor, an alliance between individuals and organizations. Companies need to shape work for employees to grow as a person in every possible dimension, emotionally, as well as in skills that they can sell in the talent marketplace. Employees should enable organizations to grow, to be more flexible and adaptable, maturing to engaging emotionally with the world and perceiving bigger, more important objectives for what the organization could be. 

Diversity is essential for creativity and learning, Organizations need to increase their “absorptive capacity” for different ideas and perspectives, and manage the “creative abrasion” that comes from this. Psychologically safe environments allow failure to lead to learning and growth, for both the individual and the organization. 

Photo: Amelia Loye