The Many, Many Positive Possibilities of Generative AI
The positive counter-narrative that eventually will supersede the gloom & doom stories that are currently clouding the take off of this amazing new technology
We need a positive reframe of what's really going on with the arrival of Generative AI and the opening up of a new age of Artificial Intelligence.
We need to interrupt the negative screeds that seem to be proliferating throughout the media and gaining a lot of the initial attention of the public, and the political class, and the powers that be in various legacy industries and fields.
Instead, we need to open up our minds to the cornucopia of positive possibilities that this new general purpose technology could open up in the economy and society of America and the world in the next 25 years.
Like the arrival of widely accessible Artificial Intelligence via Generative AI could provide humans with exactly the tool we all need to deal with the complexity of our most daunting challenges like climate change.
Like AI giving all workers a cheap, effective personal assistant could quickly lead to boosts in productivity rates and ultimately economic growth rates that we have not seen in the developed world since the great economic boom coming off World War II and rolling through the 1960s.
Like AI giving all students a cheap, dedicated personal tutor could transform the academic performance of those in the bottom half of schools as well as the entire K through 12 educational system still stuck in old industrial age models.
Like AI accelerating scientific discovery and our understanding of the incredibly complex biology of all living things, and so leading to unprecedented breakthroughs in human healthcare like personalized medicine.
And that list of positive possibilities that Generative AI is now opening up just goes on and on and on…
I know because last month we gathered about 200 top AI experts, Gen AI founders, investors, academics from Stanford and UC Berkeley, and innovators representing a wide range of networks from Silicon Valley and the San Francisco Bay Area for a conversation on the Positive Potential of Generative AI.
We selected a dozen of the most remarkable people to stretch our thinking in short talks about what’s possible in the next 25 years as this super-tool augments human capabilities and allows us to do things that humans could not do before. Then we opened up the conversation to everyone gathered in the Shack15 Club in the Ferry Building, which is a good proxy for ground zero in this Generative AI revolution that has broken out in the last six months.
I co-hosted the event with my partner Joe Boggio via our company Reinvent Futures, along with our partners Shack15 who provided the fantastic space and Cerebral Valley who connected us with the next wave of Gen AI founders and builders. We also had the support of a terrific group of sponsors who brought the necessary resources, along with their networks: Autodesk, Slalom, Capgemini and White & Case.
I drove the conversation that night and now I’m going to report some of the best insights about what we learned about the many positive possibilities along the way, like the following one from Greg Corrado, the cofounder of Google Brain, and one of a handful of people most responsible for developing this new approach to AI starting about a decade ago.
“I feel like there hasn't been a moment that I've been alive where there was a larger space of possibilities that had just come up over the horizon than have come up in the last year or so,” said Corrado, in opening up his talk, which kicked off the event.
“And I do think that there's reason for optimism,” he added. “There's also reason for concern, but the optimism for me is that I believe that we're on the precipice of an explosive expansion in human capabilities that these technologies are going to bring to individuals in a very democratized way — capabilities and powers that seem unimaginable.”
The Big Bang of Generative AI
Corrado was the perfect person to kick off this gathering since he has been closely involved in the development of what had been an alternative approach to AI through neural networks and Large Language Model (LLMs) that led to what we now call Generative AI. He joined Google in 2010 and was a cofounder of the Google Brain team, and has risen through the ranks ever since. He’s now a Distinguished Scientist and Senior Research Director at Google.
We were lucky to have Corrado explain how the Gen AI revolution boils down to two key phases. The first phase was about teaching computers to recognize patterns, whether that was images like cats, or eventually words. The second phase, which is just beginning now, is about pattern completion. If the computers have enough data about how humans finish their sentences, then the computer can finish that sentence too.
“I think it's good for us to understand, to be humble, that so much of what we think of as human intelligence and human capabilities is pattern recognition and pattern completion,” Corrado said.
What this essentially means is that computers can now talk to people, which means that the growing powers of Artificial Intelligence that have so far needed the great resources and technical expertise of corporations or governments can now be accessed and leveraged by all. That’s essentially what Generative AI has done in the last 6 months.
Crossing that threshold of giving everyone access to increasingly powerful AI is what has unleashed the Pandora's Box of speculation about the consequences, whether bad or good.
“The reason why there's lots of very, very smart people with all kinds of strong opinions about AI that are contradictory, is because it's so, so uncertain,” said Kevin Kelly, the Founding Executive Editor of WIRED magazine who still writes for them as their Senior Maverick. “I think the shape of the next several decades is going to be hugely increasing uncertainty in all dimensions. And part of it is because AI is an enabling technology and it's going to enable uncertainty in almost all other realms.”
In other words, AI has now arrived in a form that can be applied as a general purpose technology that can make a difference, and in many cases a very positive difference, in a wide range of industries and fields.
When Every Worker Gets an Assistant
Peter Schwartz, the Chief Futures Officer of Salesforce, one of the top advisors to Salesforce CEO Marc Benioff, has not one but two executive assistants.
“And what do they do?,” Schwartz said to open his talk. “They handle complexity for me. They take complexity out of my life. The world has become very, very complex, managing many, many tasks simultaneously. And a very good executive assistant solves all of that so you can focus on the things that really matter and that's what you will all have very shortly. And by very shortly, I mean weeks. I don't mean years, I mean now.”
What happens in the next few years when every knowledge worker, and with time every worker period, gets a very capable AI assistant that is very inexpensive if not free? How much will the average productivity of the average worker increase, if not leap ahead?
One indication of the answer came from Anton Troynikov, the Founder of the Gen AI startup Chroma, and a former Research Engineer at Facebook, who spoke shortly after Schwartz. Troynikov estimated that his early adoption of these new Gen AI tools has already increased his personal productivity as a programmer somewhere between two to five times.
Stop and think about that for a moment: Here’s a top computer programmer saying that he can now do the amount of coding in one day that would have taken him an entire 5-day work week to do just a year ago. A five-fold increase. At the very least a doubling of his work. (This is a rough estimate that I have heard numerous times from skilled computer coders within my circles.)
Everyone in Troynikov’s startup is similarly using these productivity enhancers and so his entire company is able to punch well above their weight in ways that they could not have done even a year before.
“Consider how many more businesses can now be started, how many more companies can be founded because you no longer need a team of dozens of people to build all these internal systems for your company,” he said. “How many more people will have access to that capability now who never would've had access to it before without raising millions of dollars of venture capital?”
The closest analogy that the relatively young Troynikov could make was to how the early web opened up the internet to everyone in the mid-1990s and provided a step-change in capability almost overnight. “Gen AI is at least on par with the web and the PC where ordinary people had the ability to publish to millions of people around the world,” he said.
We then had an economic historian speculate on how this new capability might affect the productivity rates of the entire economy, and through that, boost the economic growth rates for the GDP for a developed economy like that of the United States. Brad DeLong is a professor of economic history and the author of Slouching Towards Utopia, an economic history of what he calls “the long 20th century” from 1870 to 2010.
DeLong described for us the productivity enhancers that came through four technological developments that he himself has lived through since the 1970s, from the mainframe to the personal computer to the internet to the mobile phone. All of those technological waves, he estimated, have made him about 4 times more productive since he became an adult.
“And this AI wave is certainly a fifth and maybe the biggest of the five,” DeLong said. “Genuinely useful machine learning is a huge deal.” He said that individuals in the American economy will soon see “a huge productivity bonanza.” He estimated that the 20 percent of the American workforce who are knowledge workers will “come close to doubling what they can do individually.”
When Every Student Gets a Tutor
Then what happens when that GenAI capability migrates from the economy into the world of learning and our educational systems? What happens when teachers get 30 teaching assistants for all 30 kids in their class? Or, flip that around, what happens when every student gets a personal tutor?
Peter Schwartz, the master of strategic foresight, played out the probable scenario that will start rolling out shortly. The same technology that will make for cheap, ubiquitous personal assistants for adults will almost certainly be used to create cheap ubiquitous personal tutors for kids. Then the secondary effects kick in.
Wealthy elites have always been able to afford private schools and personal tutors when their children need them. So the people at the very top of society might not see a huge difference in the education of their kids. But people in the average middle classes and those who are poor in America might see a big difference in their educational experiences with the arrival of AI. For that matter, we should be able to scale this globally.
But the potential positive impact goes beyond the social class a child grows up in and goes to natural ability. Less gifted kids who have a hard time learning and fall to the lower half of students in tests have been shown to get tremendous benefit from a personal tutor. They almost always dramatically improve their scores.
“Every kid will now have a personal tutor from the beginning of their learning. Every kid,” said Schwartz. “The lower half of the class will now have the ability to learn math, history, geography, all of that. And every kid will now be above average just like in Lake Wobegon.”
“And so we're going to see a remarkable transformation of education as the experience in education is highly personalized and unique to every single child going through school,” he added.
We happened to have a bonafide expert in education at our gathering in the form of Daphne Koller, co-founder of Coursera, the storied online education platform, who also was the first machine learning hire into the Computer Science Department of Stanford University, and who taught OpenAI Cofounder and CEO Sam Altman, among many others.
Koller confirmed that the academic research absolutely shows that a personal tutor for a child in elementary or high school makes a huge difference in learning outcomes. She cited the groundbreaking work of educational psychologist Benjamin Bloom who demonstrated in the 1980s that a child who initially fell in the lower half of the distribution of test scores in a class yet then received one-on-one personal tutoring would dramatically improve his or her test scores by two standard deviations.
“For those of you who don't remember your Gaussian distributions, the two standard deviations means you're in the top 5%, not the top half, but the top 5% of the distribution,” Koller said. “So imagine what if everyone was actually at the top 5% of distribution because we could offer them a personalized learning experience.”
When Every Human Gets Truly Personalized Medicine
The narrative keeps getting better. A much more productive economy. A much more effective educational system. What about doing something with our healthcare system, the one that’s currently both overwhelmed and extremely expensive? Turns out the arrival of Generative AI could have a very big impact on that system too. And it turns out that Greg Corrado, who currently leads Google’s Health Research & Innovations division, is in a good position to explain why.
“I've been working in this space of applying artificial intelligence in healthcare and in biology,” he said in a second 5-minute talk he gave on the impact on biology. “And the reason that I do that is because I think that's the greatest opportunity that these technologies have to provide tangible human benefit in the near-term.”
One reason has to do with the promise of personalized healthcare. Our healthcare system has a lot of similarities to our educational systems. Both are heavily dependent on human labor, both are extremely costly to run, both are very bureaucratic, both are stuck in models that were innovative in the 20th century but need a big upgrade to meet the challenges of the 21st century.
Just as cheap, ubiquitous personal tutoring through AI could provide a new way forward for our educational systems, similar uses of AI could finally bring about personalized medicine. That could bring us much better care of individuals in the developed and even the developing worlds, and maybe even bring needed cost reductions.
“We need AI if we're going to realize personalized medicine, if we're going to have the capability to provide care for people,” Corrado said. “I don't think that we can provide humane healthcare to the global population or that we can keep up with the rate of change in our environment, the rate of evolution in pathogens without AI.”
The second reason has to do with the complexity of understanding the human body and all human biological systems, let alone of all living things. Humans are still just beginning to understand the biological world like how genes work, or proteins work, or cells work. We need the powers of AI to augment our abilities to understand these fields as well as leverage what we learn into practical applications like new drugs.
Turns out Gen AI is already on the case and making a practical impact on drug development too. Linda Avey, the co-founder of 23andMe, which democratized genetic sequencing and pioneered one aspect of personalized medicine, gave a short talk on what she’s seeing today as a Founding Partner of Humain Ventures, an AI Fund focused on healthcare.
Avey gave the example of a traditional biotech company that developed a drug that could increase or decrease your cholesterol levels that were affected by the gene PCSK9. That company leveraged a large team of medicinal chemists over the course of 10 years to find 1 key molecule, which technically received the Molecule of the Year award in 2021.
Yet she said her AI Fund is about to invest in an AI bio startup in the San Francisco Bay Area that has been working on a similar concept with a small team for just the last two years and they have already come up with 5,000 molecules.
“AI is going to be game-changing, and we're just beyond excited about just this one first company that we're looking at,” Avey said. “I think the companies are going to be coming forward fast and furious.”
A Super Tool for the Complexity of Climate Change
The theme that keeps coming up over and over again when talking about AI is complexity. AI is a general purpose tool that will boost humanity’s ability to deal with complexity. And not just a kind of boost, but a dramatic boost in our ability to deal with complexity.
AI will allow humans to do things that we never could have possibly done on human brain power alone. Take one example that everyone has experienced - searching for a piece of information in Google search and getting the right answer in a second. You can think of the Google search engine as an early example of AI that did something that no number of librarians with human brains could have possibly done.
Generative AI is now opening up the updated powers of AI to be applied to all kinds of situations that up until now needed human intelligence. And since AI is a general purpose tool like electricity, which can be applied in many different industries or fields, then this super tool can deal with understanding and mastering our complex world in almost every direction.
The timing could not be better because humans in the 2020s are heading into an extremely complex set of challenges capped by the mother of all complexities - the rapidly changing climate of the planet.
“The most pressing problem probably facing the world right now is climate change. And solving climate change is non-trivial, right?,” said Mike Haley, Senior Vice President leading a research team of more than 100 at Autodesk. “When you're designing buildings, when you're building products, when you're building power systems, when you're building anything in the world, that has an effect on climate in some way, shape or form.”
Autodesk is like the Microsoft of the built world. They provide the core software that creates three-dimensional modeling that is used by a very large share of architects and engineers, and those in the construction and manufacturing industries around the world. Autodesk has spent years researching and prototyping what they call “Generative Design,” which is a way to apply AI to the design process when humans are building anything.
Haley talked about how AI could be used to ultimately help optimize all the myriad design choices that an architect would need to make to have a new building make the least possible carbon impact over its entire life cycle. And those choices are mind-bogglingly complex for a handful of human minds. Every choice of building material and where it was sourced. Every scenario of energy efficiency from sunlight and changing weather outside the building. AI could dramatically narrow down to the most sustainable options that humans could then choose from.
Generative AI will also now accelerate the design process as well. The design software that companies like Autodesk created for the last 40 years were only able to be mastered by professionals who had serious training. And the only way to manipulate that software was through the constrained tools of a keyboard, mouse, and maybe an electronic pencil.
“That's going to change with Generative AI, the ability for the systems to understand us at language level, at gesture level, at image level, at sketch level, at idea level,” Haley said. “This is going to allow designers and creatives to start working at a pace and an ease that we've never seen before.”
So Generative AI is going to simplify the design process and so make it much more accessible to everyone without the professional training of architects and engineers. In other words, GenAI is going to democratize design beyond a cadre of elites.
“This is super exciting,” Haley said. “We need more good design in the world. We need people to be able to think of the complexity that sits in the world and create designs that respond to that.”
But what about those professional elites? (Excuse me for a moment while I shift from the positive tone of this piece to one of the typical negative worries that are so prevalent in the media.) Won’t AI take away all the design jobs?
“There's an infinite number of design jobs out there,” Haley said. “These problems are so hard that this is going to allow us to solve them. So I'm super excited about the ability of this kind of technology to solve problems.”
So Why Would We Shut Down this Technology?
So let me get this straight. With the arrival of Generative AI we now have access to a new general purpose technology of AI that potentially can boost the productivity of almost all workers and increase the growth of all economies, which could bring new wealth and prosperity into the world. Check.
We have a new super tool that potentially could give every student in the world a dedicated tutor and transform how we ultimately educate everyone more effectively. Check.
That same tool potentially could be used to bring personalized medicine to our healthcare systems with probable cost reductions because of the widespread application of cheap automation. Check.
And then that Artificial Intelligence potentially could augment all of humanity’s efforts to deal with our most complex challenges like global pandemics or intractable climate change. Ok, another check.
Why aren’t we all jumping up and down with excitement about what we all could do with this mind-boggling new capability? Joy would seem to be at least as reasonable a response to this new development as the fear that seems to be spreading.
I get that there are reasonable concerns about the actual risks of AI that need to be addressed. There are always reasonable concerns with any new technology, and humans always figure out a reasonable way to deal with those risks. In fact, our next Meeting of the Minds gathering will focus on the question: What are the Actual Risks of Generative AI? And you will get my write-up of what we learn on that topic next month.
But what the world needs now is more people looking at the many, many positive possibilities of AI that now are within reach. Let’s get everyone a much better understanding of the positive potential that’s within reach before we get too scared to move forward.
I’ll end this piece with the closing thoughts from Greg Corrado, the cofounder of the Google Brain team, who knows more about the potential of this technology that just about anyone, including the 200 other experts and innovators in the room that evening.
“I think that the Generative AI revolution is going to add a whole new layer in terms of what's possible in terms of drug discovery, in terms of protein design, in terms of understanding how we interact with our environment, how we mitigate climate change, how we adapt to climate change,” Corrado said.
“We have to try. It would be insane to look at this kind of technology, this kind of opportunity and say, ‘Well, I'm too scared,’” he said, looking around the room. “So please try.”
I want to recognize those whose support makes this ambitious project by Reinvent Futures possible, including this essay. Our partners Shack15 club in the Ferry Building in San Francisco and Cerebral Valley, the community of founders and builders in Generative AI. And our sponsors Autodesk, Slalom, Capgemini, and White & Case who help with the resources and the networks that bring it all together. We could not do this without you. Thanks.
Peter, Good stuff! In my space of direct response marketing I have seen some pushback regarding AI. It's funny how people lament about both the amount and relevance of ads they receive. Data Scientists are now leveraging AI to find "in-market" prospects. They do this thru both online and offline data. They are looking for patterns of activity and purchases preceding an ultimate purchase across as wide a swath of past customers as possible. The end goal is to make ads relevant as these prospects have literally raised their hands with interest in a given product or service. While the amount of ads might not go down their relevance increases. Which I would argue is a win for the consumer.
The list goes on. One I would like to build on - education. Inclination by schools - shut it down. Fear. What will we do. Students at all levels will cheat. What I’ve found, albeit w master and doctoral students, is use that flexes a different and perhaps more important muscle. Critical thinking. Read the output. Is it correct? What is wrong, what needs to be added, what is right, “oh I never thought of that” are all a part of utilizing the output. Maybe a little extra effort if fearful (teachers or Professors) do not ask for papers. Other ways to demonstrate cognition. Much more to say about the other categories but since I teach this in Adult Ed, this is my approach. Encourage its use. Use it well. And, for now, ICs and managers have the advantage while the big corporate machines figure out new “strategies” which may (will) be obsolete by the time there is ideation, agreement, and consensus. Thanks!