Our Duty as Era-Spanners
Understanding the world before and after a major technological change creates an opportunity and obligation to guide how moral questions are answered.
Those of us that are mid-range millennials span eras. And that is important.
We have one foot in the era that pre-dates the internet. We remember personal computers that weren’t networked – whether it was Windows 3.1, DOS prompts, or Reader Rabbit software we had to install via a floppy disk.
We have another foot in the internet era. We remember that sound of telephone modems and “you’ve got mail” which ushered us into the networked age.
This is the same with mobile phones and social media. Just as we witnessed the transformation from landlines to smartphones, our generation experienced a dramatic shift in how we communicate and consume information. Those of us born within +/- 5 years of 1987 didn't just observe these changes; we lived them. We navigated from the simplicity of phone calls and printed newspapers to the complexities of instant messaging and social media feeds. This journey from dial-up connections to Wi-Fi, from bulky desktops to sleek smartphones, gives us a profound understanding of how these advancements have reshaped society.
Consider the children who are about 10 years old today. They are poised to become the next generation of era spanners, mirroring our experiences but with a different technological frontier: generative AI. This shift is akin to our transition from analog to digital, but for them, it's from digital to AI-driven. As with the journey we mid-range millennials undertook, these mid-range alphas will face even higher stakes. They will navigate a world where AI is not just a tool, but a fundamental part of daily life – shaping how they learn, interact, and understand the world. Our experiences can serve as a guiding light for them, showing the importance of adaptability and ethical considerations in a rapidly changing tech landscape.
The escalating power of technology underscores the critical need for strong moral character. It's not just about the tools we use; it's about who we are as we use them. As technology's reach extends, touching every aspect of our lives, it becomes imperative that those who wield these powerful tools – that's us – do so with a keen sense of ethics and responsibility. Our character shapes how we employ these technologies, whether to create and innovate for the betterment of society or, conversely, to cause harm. Hence, nurturing a well-rounded character is more than personal growth; it's a societal necessity.
Our place between the pre- and post-internet worlds is more than just a quirky fact. It places us in a unique position to understand both worlds. This insight is vital, not just for nostalgia, but for making sense of how we got here and where we're heading. We’re not just observers; we're interpreters, capable of seeing the implications of technological shifts from both sides. This perspective isn't just valuable – it’s essential for guiding the responsible use of technology. It’s about using our understanding to help steer things in a positive direction.
In essence, our role as mid-rangers is much like that of a bridge, connecting two different landscapes. This isn’t just about standing between two eras; it's about actively facilitating the journey from what was to what will be. It requires resilience, a firm understanding of both sides, and the foresight to navigate potential challenges. We’re not just passively spanning a gap – we’re actively ensuring a safe passage into the future. It’s a significant responsibility, one that calls for thoughtfulness and a commitment to guiding progress in the right direction.
Beyond Efficiency: Strategically Deploying Gen AI in Enterprises
Speed is different than velocity. This concept has helped me think about deploying Gen AI to an enterprise.
The concept that velocity is different from speed is one of the core ideas I draw upon when thinking about strategy, leadership, and organizational management. Lately, I've been using this concept to think about how to deploy emerging tech, like Generative AI, within enterprises.
The difference between speed and velocity is crucial. Speed is about how fast we're moving, for example, 55 miles per hour. Velocity, however, describes moving at 55 mph towards a specific direction, like heading East. This distinction has helped me see some nuance when discussing generative AI with colleagues and peers. For example, a computer software engineer can debug code faster using a large language model as a coding partner. While generative AI certainly helps with speed, merely focusing on productivity through speed probably misses the larger opportunity generative AI provides to managers of teams and enterprises.
In this example, improving speed might actually reduce overall productivity and impact, if the software being improved isn't solving a valuable problem in the first place. Here, generative AI would be more useful in helping the software engineer determine which feature would be most relevant and impact for the user. Going faster is only helpful if you're going in the right direction, the most valuable direction, to begin with. Using generative AI to increase speed in the wrong direction would be a missed opportunity.
It might be tempting to think of generative AI as a tool to "make our employees more efficient." However, it would probably be more transformative to use generative AI as a tool to "help our colleagues spend their time on the most valuable problems." This logic doesn't just apply to IT departments. For example, generative AI can help marketing teams draft copy faster, but it's probably more valuable to ensure they're targeting the best possible consumer segment. For operations teams, Gen AI might help to spot and improve manufacturing inefficiencies, but it might be more useful to help spot which product lines aren’t worth producing in the first place.
As an enterprise leader scrambling to deploy Gen AI, it’s easy to assume that the job to be done is to make everyone else more efficient. While this is partly true, business and technology leaders, especially those deploying powerful, emerging, tech like AI, should also contemplate use cases that improve the quality of leadership and strategy in enterprises - even though doing so might indicate that those leaders had it wrong in the first place.
Employing generative AI in a self-aware manner will require a significant degree of humility. But I believe it's worth it. After all, what's the point of heading east faster if we should be going northwest to begin with?
Consider the lesson learned from my own experience at work, which vividly underscores the crucial difference between speed and velocity in the application of generative AI. As a product owner for data, I've seen my engineering colleagues leverage tools like ChatGPT to streamline coding SQL queries, boosting our operational speed. However, a pivotal moment came when I discovered that a dataset we had meticulously prepared and delivered was left untouched by our business customer for months. Which, by the way, indicated that I had made a poor decision on what was worth spending time on.
Despite our efficiency in producing the dataset, it lacked the essential element of value to the customer. This incident revealed a stark truth: our focus on making engineering tasks faster, though beneficial, paled in comparison to the importance of selecting the right targets from the outset. There have been instances where the right datasets, aligned with clear and compelling use cases, saved our customers millions of dollars. The real win, therefore, isn't just in enhancing our engineers' efficiency but in ensuring that our efforts are directed towards creating datasets so valuable and relevant that our customers are eager to utilize them for significant impact from the moment of delivery.
To truly leverage the potential of generative AI within our enterprises, we must go beyond the pursuit of efficiency. The most obvious path is often the least disruptive—enhancing what already exists. However, the opportunity to create significant, long-lasting value lies in our willingness to question the fundamentals of our strategies and leadership approaches. It's about asking ourselves:
Where are we merely maintaining the status quo when we could be exceeding it?
In what areas are we failing as leaders and strategists to anticipate and shape the future?
How can we redefine our objectives to not just improve but transform our enterprise?
This journey requires a substantial dose of humility and a willingness to embrace change, characteristics not often associated with leadership but absolutely critical in this context. Challenging our 'sacred cows' and reevaluating our core assumptions about what our enterprises do can reveal the most impactful opportunities for applying emerging technologies. Let's commit to this introspective and transformative approach, aiming not just to enhance but to innovate and redefine our enterprises for the better.