Speed wobbles are scary. You’re rolling super fast down a hill and your skateboard suddenly starts careening wildly back and forth. It’s like you’re standing on a tightrope and someone is shaking violently. Fight it and you almost always lose. Staying upright is a matter of surrendering to the wild motion.
We’re in a speed wobble moment with technology. Things are moving fast and careening wildly. Fighting the moment will send you to the concrete. Find your way in the flow, and you might roll through to the other side. That’s just one thing I’ve learned about technology on a skateboard. Here are some more:
Handrails Aren’t Just for Hands
There used to be a set of green handrails where I live, in Denver, that provided years of reliable hand support for those walking down a set of long brick steps. They always gave me a rush of stoke, however, as I’d remember Jamie Thomas rolling out past the first rail for a quick backside feeble grind on the second in Toy Machine’s 1996 video Welcome to Hell.
Skaters train themselves to see the world differently. I’ll call it handrail thinking, and it readily applies to the moment we’re in with generative AI. Large language models (LLMs) like OpenAI’s GPT can do many remarkable things. Take them by the hand and they can write emails and summarize piles of unstructured data. They provide considerably more stoke as an interface. When grinded, let’s say, LLMs can become a conversational front end to a back end capable of orchestrating powerful automations.
I might pick up my phone and type this message into a rich web chat (RWC) window: “Look at all of this year’s emails and Slack messages with Elias Parker and make a list of the skateparks we said we wanted to visit. Then create an itinerary for a three-day road trip, and send him a calendar invitation that shares the itinerary. Find three-day windows that we both have free and suggest other time frames if he rejects the first invitation.”
In this scenario, an LLM helps to understand my request and orchestrate a bunch of process automations (scheduling, mapping, route planning) to facilitate a skate trip. It’s searching through unstructured data in the form of emails and Slack messages to my friend, looking for patterns, and collecting actionable information. These systems can also be made to seek information. Maybe there’s a skatepark we didn’t mention in our emails that fall along the route it’s suggesting and I get a follow-up message asking if I want to include it in the itinerary.
OpenAI has given us inklings of this behavior with their recent GPTs release, but LLMs are vastly more powerful as a skill-driven portal into a secure and reliable technology ecosystem. Keep in mind, though, that jumping on handrails often leads to falling off of them.
Get Comfortable Falling on Your Face
The first time anyone steps on a skateboard, they abruptly fall off. It can be both painful and humiliating, but there’s no other way to learn. With the surge of generative AI flooding into our work and personal lives, we’re being thrust onto a metaphorical skateboard—many of us for the first time.
Until recently, most companies were relatively safe following in the footsteps of bolder competitors, making risk-averse choices that kept stakeholders happy and outcomes relatively predictable. They could effectively watch how other people rode their skateboards and make passable attempts of their own. Businesses didn’t have to be particularly innovative to gain ground.
With the proliferation of conversational AI, organizations need to restructure their operations and technology landscape. Nimble, tech-first companies (like insurance provider Lemonade) have built their organizations around technology. They are in a position to skate the rail—providing customers and employees experiences that leverage the breadth of conversational AI. The only way to get to that place is by propping up conversational experiences, watching them fail, and then iterating on improvements. Get started by falling on your face.
In his seminal book, The Innovator’s Dilemma, Clayton M. Christensen notes that, when working with disruptive technologies, successful managers “planned to fail early and inexpensively in the search for the market for a disruptive technology.” Early attempts to automate business processes will be awkward and unsightly, but they don’t have to be expensive. They will require dedication and diligence, something that late skateboarder and streetwear titan Keith Hufnagel connected directly to skateboarding in a 2014 interview:
“The best thing about skateboarding is that it holds the keys to everything. It allows you to do anything you want to—if you want it … Because if you’re a skateboarder, you already know how to work hard: you trained yourself to be a good skateboarder. Skateboarding doesn’t come naturally. It’s not like you come out and you can do all these tricks. You work hard. And if you can translate that into a job, a real job, then you should be able to succeed.”
You don’t actually need to stand on a skateboard to adopt this mindset. There are tools available in the marketplace that allow teams and organizations to prop up conversational experiences, watch them fail, and iterate on improvement over the course of mere days or weeks. Anyone can get comfortable falling on their face if they are willing to commit.
Stay Open, Healthy, and Accessible
Skateboarding continues to draw innovative people into the fold, but it hasn’t always been so welcoming. For much of its history (roughly 50 years), skateboarding was largely represented in culture by heteronormative white dudes. Only recently, it seems, has there been a concerted effort to make sure that all outsiders are welcomed and celebrated. There was a mighty surge in 2016 when legendary pro skateboarder Brian Anderson came out in a short documentary on Vice Sports.
More recently, skateboarding’s de facto CEO, Jeff Grosso, flung the doors open wider. In one of the last episodes recorded before he passed away in 2020, Grosso spent time with LGBTQ+ skaters and invited them to share stories. In the wake of many tragic suicides within the skate community, there has also been a noticeable push for opening up dialogs around mental health and addiction. Many of the interviews with skaters in Thrasher magazine now include questions about therapy and sobriety.
This openness and accessibility shows up not just in the editorial choices made by skateboarding’s “bible.” There are also ads from both independent skate brands and global corporations like Nike featuring female, BIPOC, and non-binary skaters. In preparing this article, I’d convinced myself that skateboarding had somehow cracked the code—that a decentralized global industry had rallied around doing the right thing.
While there might be shreds of truth to that, Dave Carnie threw some fresh light on the pile. As the former editor-in-chief of Big Brother Skateboarding (the notorious and beloved magazine that provided a springboard for Johnny Knoxville and Jackass), Dave was quick to point out that skateboarding isn’t all that different from other industries in terms of being open and inclusive.
“I can see why you would think that,” he said of my assessment, “but the reality isn’t that, especially on Instagram. There’s so much hate in skateboarding. It’s not really any different than, you know, Los Angeles. [Skateboarding] didn’t put out a call for more diversity, it’s just more people are coming to skateboarding now and seeing it as a fun, athletic activity. The community is more diverse, but I don’t think it’s any more diverse than any other similar subculture. Skateboarding is evolving, but evolution doesn’t think, it doesn’t choose, it’s all by “accident.”
Skateboarding’s secret according to Dave is that it’s attractive to young people—who tend to be more diversity-minded—in an era when their interest in team sports is on the decline. It also has a fairly low barrier to entry. All you really need are streets and a skateboard, which have cost around $150 for decades. This is relevant because we’re in a moment where the barriers to technology have dropped significantly. Generative AI has made technology far easier to engage and create with. It feels like a good thing for individuals and organizations that young people can hop on generative tools as easily as they can hop on skateboards.
In a recent conversation I had with Jeff McClain, Head of AI at Morgan Stanley Wealth Management, he spoke to the changing nature of workforce composition. “Being a senior guy with 30 years experience and deep technical expertise, yeah I mean it matters, don’t get me wrong,” he said. “But being 23, being articulate and a great problem solver who can collaborate with other people? Give me a hundred of them and the impact is unbelievable.”
Conclusion
Originally, I drafted this article with business leaders in mind, but Dave reminded me that the message is perhaps even more salient for the young among us. The world is changing fast, and it’s time to adapt. All of us have an ingrained ability to use creativity to solve complex problems. Nurture this ability by applying handrail thinking to the problems you solve in your personal and professional life. Take advantage of the powerful generative tools that are now widely available. Experiment with them. Fail. Then fail again, only better.
These technologies can make us better at our jobs but they can also make life better for all of us. This only happens if they are accessible. AI should be utilized and improved upon by many people from diverse backgrounds, with their own perspectives and cultural viewpoints. Systems must be designed to benefit everyone, equally. Generative models are biased because they were trained on biased data. We need to correct these kinds of mistakes and seize the ripe opportunities for people to work collaboratively and equitably across the globe. It might be the only way to survive heavy, heavy-speed wobbles that threaten our existence.
The first step will be falling on our faces.
1. The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail, Christensen, Clayton M., 1997, Harvard Business Press, p99
