Tech History as Prelude
Take for example, the cotton gin. Invented in 1793, the cotton gin used a combination of wire teeth on a rotating cylinder and a grate or screen to pull the cleaned cotton fibers through, significantly increasing the speed and efficiency of cotton processing. This had a major impact on the cotton industry, particularly in the Southern states, where cotton was a major, labor-intensive crop and whose commercial use would force huge percentages of the labor force out of work. In the face of this radically disruptive technology, the cotton gin’s inventor, Eli Whitney, wrote this to his father: “One man and a horse will do more than fifty men with the old machines. ‘Tis generally said by those who know anything about it, that I shall make a Fortune by it.”
And indeed, fortunes were made, and the potential catastrophic implications to society were far overshadowed by the entire industry that was born from this simple invention that fueled regional growth in the South for over a century.
And so, it continues into this century. Andrew Ng, founder and lead of Google Brain and currently an Amazon Board member, recently said the same. “Just as the Industrial Revolution freed up a lot of humanity from physical drudgery, I think AI has the potential to free up humanity from a lot of the mental drudgery.”
The Mother of Invention
From simple stone tools to complex genetic engineering and information technology, the history of technology is the history of the human invention of tools and techniques. The speed at which the invention of these tools and technologies is being delivered now has become exponential as the application of machine learning and AI becomes the ubiquitous open-source ingredient layer to everything and is mutually accelerated by the arms race for processing speed. We now measure success in petaflops (a quadrillion floating-point operations per second) and trillions of parameters (the internal, numerical values that LLMs learns during training to process and generate text).
As knowledge-seeking animals, the potential value of these tools to increase our understanding of the world around us and solve some of our most pressing problems around the quality and quantity of life is as tempting as Pandora’s Box, which, while it contained all the evils of the world, it also contained hope. As Marc Andressen said, “Technology is the glory of human ambition and achievement, the spearhead of progress, and the realization of our potential.”
While decades in the making, with this new computational prowess we are continually (seemingly daily now) seeing breathtaking exponential breakthroughs, none more exciting than in the field of Synthetic Biology, where we can truly see the practical application of the positive outcomes of AI. One powerful example of how this is already being used is being pioneered by Andrew Adams at Eli Lilly and Company. In seeking treatment to the debilitating disease for Alzheimer’s, researchers discovered the Christchurch Mutation: just one copy of the Christchurch variant conferred protection against Alzheimer’s disease, even in individuals with genetic predispositions to the disease. Being able to apply Synthetic Biology to enhance and deliver this modification would transform the field of Alzheimer’s from treatment to prevention.
Add to this the recent open-source release of Google’s Alphafold, their free AI Model to predict the structure of all of life’s molecules and we start to see what’s now possible. The fact that Google just gave away access to over 200 million proteins and provided a free AI tool for scientists to experiment with is in itself exponential.
Admittedly, to the non-scientific community, this seems interesting but arcane until we start to see the practical application of the new technology toolsets being built. Enter Colossal founder Ben Lamm, a protégé of George Church. A self-described ‘serial entrepreneur,’ he started Colossal with $15M in 2019, now worth $10.2B, with the sole purpose of advancing the cause of de-extinction, using advanced gene editing technology to rebuild the DNA of lost megafauna and other creatures. With Earth on track to lose between 30 to 50 percent of its biodiversity by 2050, maintaining this integrity is vital to life on Earth; his work is mission-critical. His most recent accomplishment, the birth of three dire wolves (Romulus, Remus, and Khaleesi) is considered “the world’s first successfully de-extincted animal,” the first of their kind to be alive in over 10,000 years. While Woolly Mammoths and Dodo Birds are also on their roadmap, the work at Colossal is not simply to create novel creatures for 21st-century Jurassic Parks; instead, it is about building the technological capabilities to stop the current waves of extinction in their tracks. Colossal also seeks to use Synthetic Biology in other useful ways, successfully editing the genes of an Amazonian microbe they call ‘X-32’, from a microbe that enjoys eating plastic to a microbe that is voracious for them, digesting polymers in weeks instead of decades or centuries and leaving behind carbon dioxide, water, and biomass. This novel solution could swiftly help us address the problem of plastic pollution on our planet and microplastics in our bodies, all with the enhanced use of data and computational power.
A Synthetic Future
With synthetic data and synthetic biology naturally comes ‘synthetic everything’. Synthetic Humans (Robots), Synthetic Media (Google VEO, Midjourney), Synthetic News and even Synthetic Truth. That there are bad actors and bad intent, we are clear. And the need for us to be diligent and leery, especially in this current era, of dystopias of our own making, is real. The need for the ethical human in the loop couldn’t be more dire and we must all remain diligent to these poor outcomes. We must, and will be, diligent, as these are the human decisions put before us as we build this awesome new AI toolset whose promises far outweigh the perils.
At this year’s World Economic Forum in Davos, Andrew Ng, ever the tech optimist, was asked directly about the perils of AI and Artificial General Intelligence (AGI), and he replied, “Do we think the world is better off with more intelligence? We use, primarily, human intelligence; now we have artificial intelligence. I think that intelligence, net-net, tends to make societies wealthier, make people better off…intelligence can, in some cases, be used for nefarious purposes, but on average, I think it actually makes us all much better off.” But is this a false equivalency? More intelligence may be better intelligence, but is more AI better AI? The answer to this depends wholly on how we use it.
From our daily businesses to our daily feeds, the exponential pace of the practical use cases for the application layers of machine learning, AI, and even Agency is indisputable. It has already become a known-known that AI is the ubiquitous open-source business ingredient for speed, agility, efficiency and profitability. To paraphrase Eli Whitney, ‘From this technology, one can make fortunes.’ However, only by fully understanding the implications beyond the opportunities and using the processes of applied innovation to look at technology breakthroughs outside our industry, we can see more clearly a wider view, ensuring we drive the most desirable outcomes.
As leaders, we must always be deliberate about what we set in motion. In Pandora’s fable, when we are open to every inevitability there can be unintended consequences. But with the right insights, we also know that Hope never left the box.