We’ve covered education enhanced by Artificial Intelligence for our children in Part One and Part Two. Now I want to turn my lens to the learning ecology of AI inside of companies. Our emergent transformation into a “superorganism” is easing and accelerating the ever-important ramp-up of both new and existing employees who will master the facts that they need to effectively do their jobs – and to effectively help our customers do theirs.
So just what are we up to?
Essentially, we are doing this with two broad clusters of initiatives. One is “Interactions with Archie”, which seeks to better connect data.world and our team with our prospective customers. The second cluster is our “AI Hacks Library”, where we are using AI tools for the team itself to accelerate and bolster coherence and communication.
The idea behind both sets of initiatives harkens back to that great adage about teams, one at the core of my leadership philosophy: “All of us are smarter than any of us.” And now, we’re slapping on the thrusters and “all of us” are getting an assist from AI. Let me explain.
The new table stakes for every company – generative AI
Our initial foray is “Interactions with Archie”, effectively our own version of ChatGPT. We have trained it on all of our whitepapers, marketing collateral, case studies, webinars, competitive intel, and more. It was conceived by my co-founder and our CTO at data.world, Bryon Jacob, and our VP of Strategic Initiatives, Brandon Gadoci, during our AI Hackathon in August.
More on that later and how it evolved from our suite of Bots, but the broad point of it all is that these are empowerment tools — a form of what I call “enabling innovation”.
With that innovation, we seek to fill a gap in our collective perception of this emerging kaleidoscope of AI technologies that is transforming our planet. This gap we seek to fill is the limited way that we tend to conceptualize AI. Unfortunately, we usually think about AI’s power with comparisons to human capacity.
Can generative AIs pass the bar exam? Can they outperform a radiologist? Will an AI tool write this article more elegantly than me? Fair enough, great questions. But these questions miss a key point: Progress and innovation are seldom, if ever, the work of individuals – a great case in point being this week’s winners of the Nobel Prize in Medicine.
Those scientists, Katalin Kariko and Drew Weissman, are part of a long story of collaboration. That story dates at least to the time of ancient humans corralling game with sophisticated coordination two million years ago, then on to the labors of their global group of science-in-the-fast-lane researchers who delivered us an mRNA pandemic vaccine in nine months. Teams are where the cognitive action is, as I argued in a data.world blog post last year. In that post, I cited Kariko and Weissman as enablers of innovation whom we should emulate. In the phrase of my friend and author Byron Reese, our teams are becoming at one with a planetary “superorganism.” Let’s unpack that.
From the proverbial ‘six degrees’ to no separation at all
Human progress has steadily been propelling us toward what Byron calls the “Agora”, a planetary public square, in which the “superorganism” is now emerging. In his fourth book published last summer, Stories, Dice, and Rocks That Think – How Humans Learned to See the Future - and Shape It, Byron summed up the new cognitive choreography this way: “If knowledge is power, such a system is by definition the ultimate in empowerment.”
In his new and fifth book, We Are Agora – How Humanity Functions as a Single Superorganism That Shapes Our World and Future, Byron takes it further: “Agora includes all the world’s people who are connected to one another, which today is virtually everyone.” In that book, which will publish in December, he puts the AI-driven Agora in context: “The entire world now functions as a single metroplex, and so Agora has grown to be a planet-scale superorganism. Not only is it all humans, it is only humans.” Take a moment to ponder and savor that sentence.
Last year, I explored that fourth book of Byron’s in a six-part series leading up to his keynoting of our data.world summit last year: “We will become a single vast intellect, and will gain mastery over the future,” Byron told our summit attendees.
Another great perspective on this “vast intellect” – the collective thinking of teams – comes from Inflection AI co-founder and CEO Mustafa Suleyman in his brilliant new book on AI, The Coming Wave – Technology, Power and the 21st Century’s Greatest Dilemma.
“Organizations too are a kind of intelligence,” writes Suleyman. “Companies, militaries, bureaucracies, even markets – these are artificial intelligences, aggregating and processing huge amounts of data, organizing themselves around specific goals, building mechanisms to get better and better at achieving those goals.”
That catalyst of all human progress – ‘Great Groups’
Byron threw this pitch and Suleyman is knocking it out of the park. Yes, we need to master AI to extend the reach of the human mind. We need to empower students with AI tutors, and teachers with AI assistants. But the heavy lifting in the coming transformation will not be carried by the swashbuckling “heroes” the media so like to venerate. No, it will be carried out by what Warren Bennis and Patricia Ward Biederman dubbed “Great Groups” in their also-brilliant book a quarter century ago, Organizing Genius: The Secrets of Creative Collaboration. The much larger challenge than the one we’re debating is this question: How can we use AI to extend the reach and grasp of our collective team intelligence?
One Great Group seeking to answer that question is the one better known as data.world. We are marching forward at a very brisk pace. Or, really sprinting, as a matter of fact.
As I mentioned above, this sprint is now framed by two interlocking initiatives. Internally, we're harnessing AI to elevate our teams and foster critical thinking, introspection, and empathetic collaboration. Externally, we’re using AI to reshape how we engage with customers and prospects, liberating them from the virtual arms race of sales tactics to provide an efficient and informative platform to explore how our services align with their own unique needs. So far, I believe we are the only company in the data space with a tool like “Interactions with Archie”. In exploring this as we’ve refined our AI strategy in recent months, I should add that I’ve drawn heavily from lessons on which I elaborated in my book, The Entrepreneurs Essentials, in the fourth chapter on the always be learning life. That’s another core idea here: always be learning, and do so with these new tools.
It always starts with the kids and then it affects us all; AI will become our new norm and expectation for skill mastery. You won’t be replaced by AI but you may very well be replaced by someone more skilled at your job because they have already mastered AI while you have chosen to lag behind (and it really is a learning choice that only you can make).
Toward that goal, back in May we integrated generative AI into our data catalog platform to make it easier for everyone – even non-data experts – to use data in a meaningful way. As I wrote at the launch of those capabilities, called Archie Bots, generative AI is helping us extend our mission as an organization. Our company’s mission has always been to build the most meaningful, abundant, and collaborative data resource in the world – to make data accessible to everyone who wants or needs to use it.
There are prohibitive barriers to entry, however. On a fundamental level, many people simply aren’t yet comfortable working with data, and query languages SQL or SPARQL particularly. They don’t know where to start, what questions to ask, how to answer those questions, or how to determine if they are using the right data in the first place. Ultimately, this discomfort with data leads to low adoption and data abandonment. Workers then resort to standing in a “data breadline” waiting for the more data-skilled workers to serve them, as described so clearly in the great book Winning with Data: Transform Your Culture, Empower Your People, and Shape the Future by Frank Bien and Tomasz Tunguz. This is frustrating and slows everything down, including the collective intelligence of the entire company, really challenging the “superorganism” concept in practice.
By integrating generative AI into data discovery via our Archie Bots, we are changing the way people interact with data.world. Archie Bots make it far more efficient to get to the data, or facts of the business, that you need to do your job and then query it, document it, and ultimately learn from it.
In fact, the name “Archie” was inspired by Archimedes, the noted mathematician and engineer, and Merlin’s clever pet owl in the animated Disney film The Sword in the Stone. With Archie Bots, users have a data expert at their disposal, one that knows the ins and outs or their organization. By simply using natural language, Archie Bots can trace complex relationships between data, people, tools, and decisions to find answers and return relevant data. Archie Bots can suggest definitions or concepts where they don’t yet exist. These friendly bots guide the user through the means to work with data by suggesting use cases and bridging the SQL gap by automatically translating natural language questions into complex SQL queries (or interpreting those queries into natural language, so the user can understand what’s going on behind the scenes).
A foundation of diverse, AI-connected data halts the marketing ‘arms race’
WPP, the largest advertising agency in the world with over 100,000 employees, is leveraging these capabilities to provide users with the relevant datasets required for projects – to help spur and suggest potential creative campaigns. By incorporating data-driven insights into its pitch preparation, WPP not only showcases its creative solutions but also demonstrates its ability to effectively address clients' challenges.
As Vip Parmar, WPP’s global head of data, puts it: “AI is changing the way we work, but its outcomes are only as good as the data that’s put into it. That’s why it’s key to have a foundation of diverse, connected data that’s contextual and relevant and works in conjunction with AI.”
Like any good company, we are applying the innovations we are providing to our customers to our own organization, helping to improve how we as employees find and use data.
data.world’s Brandon and Bryon, who as I mentioned have led on this idea, liken our evolution to Byron’s metaphor of the Agora. When one ancient salesman found a successful formula to market his bronze axes and nails, others quickly adopted the same techniques. This adoption curve has been happening in the marketplace ever since and now happens at digital speed. Fast forward to our day. We’ve seen this pattern time and again: flyers, direct mail, catalogs, door-to-door sales, cold calling, personalized offers, inbound marketing, sales email automation, third-party intent data, social signal aggregation, etc. It’s a kind of “arms race” in Brandon’s phrase.
And we’re calling a halt to the escalation.
Now, instead of navigating through drop-down menus, CTAs, gated assets, and complicated forms, the buyer (or merely curious prospect) is interacting with Archie and can get the information they need for evaluation in a fraction of the time. And they can do so using a user interface with which they are familiar because it is so like ChatGPT. Type. Chat. Learn. The customer is now in control as never before. Check it out.
Meanwhile, internally, our "AI Hacks" library is more than just a resource; it's a living ecosystem currently built on Google Sites. Initially, the library started as a crowd-sourced collection of videos from our own employees, sharing their AI "hacks" and innovative ways to leverage generative AI tools like ChatGPT. These videos serve as a catalyst, encouraging even the AI novices among us at data.world to integrate these tools into their daily workflows. We've also provided comprehensive guidelines on the secure, ethical, and effective use of AI, ensuring everyone is informed and responsible.
In data.world's hybrid-forward work environment and the broader work-from-home landscape, our library has been a game-changer for standardizing the onboarding experience, ensuring every new hire starts off on the right foot. Additionally, we use AI to summarize transcripts from Zoom meetings and Loom video recordings, quickly distilling key takeaways. To assess our employees' grasp of training content, we can swiftly launch AI-created quizzes—a process that used to take hours is now reduced to mere minutes.
But we're not stopping there. Our AI Hackathon has enriched the library with presentations showcasing new, innovative ways to utilize AI tools within our organization. We're in the process of adding role-specific Prompt Libraries that will offer tailored AI prompts based on specific job roles and use cases, making the library even more relevant and actionable. As we continue to evolve away from traditional training methods, our focus remains on empowering our employees to excel in their roles, armed with the best AI tools and knowledge at their fingertips. The lift in productivity has been incredible – one of our best engineers produced 15,000 lines of code in the past two months. He’s one of those fabled 10x engineers and used to produce around 10,000 lines of code in a year.
So in conclusion, a few words of thanks to the community of readers, my circle of friends and colleagues. I appreciate you joining me on this writing and reading journey on topics so near to my heart as a father, and central to my mission and work as a long-time technologist – education, learning, and the future. We’ve explored the global polycrisis of education, better termed as the crisis of learning. And how AI can fix much of that. We’ve worked through the Strangers in a Strange Land (apologies to Robert A. Heinlein) of schooling almost everywhere. You have indulged me in my invention of a new word, “linearalism”. Our 19th century schooling model just doesn’t fit well in the 21st, does it?
I was filled with a father’s pride sharing with you the mastery over AI that my son Levi has acquired in just a few months, while making leaps of years in learning as a result. And I’m sure you agree that the students at Austin’s Huston-Tillotson University are creating and shaping this new learning ecology in inspiring ways. It’s amazing that they literally developed, installed, and trained all the professors in “remoteware” so they could teach online in the pandemic. Indeed, AI eats generational assumptions for breakfast.
On the last leg of this tripod on AI in learning and education, I’ve strung these thoughts together and tied them to my own company where we are riding on our boards at the crest of the wave. I’ve searched and searched for the analogy, and the best I can come up with is that we’re kind of like a crack basketball league, suddenly in outer space. Reinventing basketball, its rules, strategies, and metrics of winning and losing in zero-gravity would be challenging for sure. That’s kind of how it feels. Empowered, liberated, and challenged. Exciting, fascinating, intimidating, but all with a sense of true awe and intense inventiveness at this unfolding transformation in which we have so much to learn.
As AI-in-education pioneer and Wharton Professor Ethan Mollick frames it with his usual elegance, the future of AI in our institutions, businesses, and ultimately our lives is unknowable – not even by the developers of ChatGPT, Bard, Pi, Claude, Llama, or the many others in this growing family of technologies. So it’s up to us. While Mollick was writing on visual AI technology specifically, his latest prose has broader and general resonance — on vision. It is up to all of us to give AI vision! This is precisely our endeavor at data.world.
“Once you give AIs vision,” Mollick wrote, “they gain a new method of interacting with the world, one that expands their capabilities into industries and uses that most of us had never considered.” Onward!
