Staying Curious and Being Human in the AI Age
Today I learned about a military term that has come into the culture: VUCA, which stands for volatility, uncertainty, complexity, and ambiguity. That certainly describes our current times.
All of this VUCA makes me concentrate on what is stable and slow to change. Its easy to get distracted by that which changes quickly and shines in the light. Its harder to be grateful for what changes slowly. Its harder to see what those things might even be.
In the face of AI and the way it will transform all industries (if not now, very soon), its important to remember what AI can not yet do well. Maybe it will learn how to create a facsimile of these traits in the future as it becomes more “human” (trained on human data with all its flaws might mean it has embedded within it those traits we find undeniably human). However, these skills seem like the ones that can help us navigate the VUCA that is life today.
Be Curious
AI can ask follow-up questions for clarification, but it does not (yet) ask questions for its own curiosity. It asks when it has been directed to do something. It does not sit idle and wonder what the world is like beyond the walls of the chat window.
Humans and high-order animals have curiosity. We seek information and naturally have questions about our world — why is the sky blue? why does the wind blow? why do waves crash onto the shore?
In our operations, Oomph prides itself on Discovery. This is our chance to ask the big questions — why does your business work the way it does? why are those your goals? who is your audience you have vs. the audience you want?
In life and work, curiosity is one of our best traits. This means trying new tools, changing our processes and habits for improved outcomes, and exploring something new just to see what it can do. Even with all the VUCA in the world, approaching uncertainty with curiosity keeps us open and engaged with what we can learn next.
Use Judgement
Another important human trait is judgement, and this continues to be invaluable as humans are needed to evaluate AI outputs.
AI is very good at creating dozens, if not hundreds of outputs. In fact, probabilistic (not deterministic) output is the strength and sometimes weakness of AI — you almost never get the same answer twice.
Our human expertise is needed to curate these outputs. We need to discard what is average and unremarkable to find the outputs that are surprising and valuable. We need to use our judgement and experience to find the ideas that are applicable to the client, the project, and the moment. Given the same 100 outputs, the right ones might be a different selection depending on the problem we want to solve and the industry in which it will be applied.
Exude Empathy
In the world of design and creating software for humans, empathy is what drives the decisions we need to make. In the flow of vibe coding, our judgments will drive technical and architectural decisions while empathy drives interface design and product feature decisions. Humans are still the ones who need to find the problems that are worth solving.
The language on the page, the helpfulness of the tooltip, and the order in which the form elements appear are some examples of how empathy drives interactions. Empathy helps team members identify confusion and redundancy.
Further, until we are designing for AI Agents and robots as our product’s primary users, we are designing for humans. This means we need to continue to ask humans for feedback, monitor human behavior on our sites and in our apps, and understand why they make the decisions they make. All of this continues to make empathy an important human trait to cultivate.
Make Connections
Mike Bechtel, Chief Futurist at Deloitte Consulting, gave a talk at SXSW this year about how the future favors polymaths instead of specialists. His argument boils down to this: AI is a specialist at almost anything but what humans have shown over time is that the greatest inventions and insights come from disparate teams putting their expertise together or individuals making new connections between disciplines.
Novel ideas are mash-ups of existing ideas more than brand-new ideas that have never been thought of. And these mash-ups come from curious humans who have broad experience, not deep specialization. They are the ones who can identify and bring the specialists together if need be, but most of all, they can make the connections and see the bigger picture to create new approaches.
Support Culture
No matter how smart AI gets, it doesn’t “read the room.” It doesn’t build relationships between others, react to group dynamics, or pick up on body language. In an ambiguous human way, it does not sense when something “feels off.”
In group settings, humans command culture. AI won’t directly help you build trust with a client. It won’t read the faces in the room or over Zoom and pause for questions. It won’t sense that people are not engaging and reacting, and therefore you need to change a tactic while speaking. AI is interested in the facts and not the feelings.
Broad team culture and the culture that exists between individuals is built and nurtured by the humans within them. AI might help you craft a good sales pitch, internal memo, or provide ice breaker ideas, but in the end, humans deliver it. Mentoring, supporting culture, collaborating, and building trust continue to be human endeavors.
Break Patterns
AI is very good at replicating patterns and what has already been created. AI is very good at using its vast amount of data to emphasize best practices with patterns that are the most prevalent and potentially the most successful. But it won’t necessarily find ways to break existing patterns to create new and disruptive ones.
Asking great questions (being curious), applying our experience and judgement, and doing it all with empathy for the humans we support leads to creative, pattern-breaking solutions that AI has not seen before. Best practices don’t stay the best forever. Changes in technology and our interface with it create new best practices.
The easiest answer (the common denominator that AI may reach for) is not always the best solution. There is a time and a place to repeat common patterns for efficiency, but then there are times when we need to create new patterns. Humans will continue to be the ones who can make that judgement.
Be Human
AI will continue to evolve. It may get better at some of the attributes I mention — or at best, it may get better at looking like it has empathy, supports culture, and mashes existing patterns together to create new ones. But for humans, these traits come more naturally. They don’t have to be trained or prompted to use these traits.
Of all these traits, curiosity may be the most important and impactful one. AI has become our answer-engine, making it less necessary to know it all. But we need to continue to be curious, to wonder about “what if?” AI shouldn’t tell us what to ask, but it should support us in asking deeper questions and finding disparate ideas that could create a new approach.
We no longer need to learn everything. All the answers to what is already known can be provided. It is up to humans to continue with curiosity into what we do not yet know.
