Jessica Cole

Category: Artificial Intelligence (AI)

  • Stop Asking AI Stupid Questions.  

    Stop Asking AI Stupid Questions.  

    Let’s be brutally honest. Most companies are getting AI wrong.

    We are seeing the friction of trying to fit a 21st-century sense into a 20th-century business model.

    They’re spending millions on a new technology and getting… faster spreadsheets? More polite chatbots? Marginally better marketing plans?

    The initial hype is clearly dead, and for many leaders, the ROI is looking dangerously thin.

    Why?

    Because we’re asking it stupid questions.

    We are treating the most powerful perceptual tool ever invented like a slightly-smarter, cheaper intern. We ask it to summarize reports, fetch data, and write boilerplate emails. We are focused on optimization.

    Not only is this incredibly inefficient, but it is a (borderline embarrassing) failure of imagination.

    Granted, this isn’t really our fault. Our entire mental model for business was forged in the Industrial Revolution. We think in terms of efficiency and inputs/outputs. We hire “hands” to do work, and we look for tools to make that work faster.

    So when AI showed up, we put it in the only box we had: the faster intern box.

    We ask it Industrial-Age questions: “How can you write my emails faster?” “How can you summarize this 50-page report?” “How can you optimize my marketing budget?“

    These aren’t necessarily bad questions. They’re just lazy. They are requests for efficiency.

    They are limited, and they are all, at their core, asking how to do the same things, just faster. As long as we are only optimizing, we are missing the potential revolution entirely.

    The real breakthrough, I believe, will come when we stop seeing AI as an extension of our hands and start seeing it as an extension of our perception.

    Your intern is an extension of your existing ability. They do the tasks you assign, just saving you time. A new sense, like infrared vision, grants you an entirely new ability (thinking X-Men). It lets you see heat, a layer of reality that was completely invisible to you before.

    This is the shift we’re missing.

    Its true power isn’t in doing tasks we already understand, but in perceiving the patterns, connections, and signals we are biologically incapable of seeing. Humans are brilliant, but we are also finite. We can’t track the interplay of a thousand variables in real-time. We can’t read the unspoken sentiment in ten million data points.

    AI can.

    When you reframe AI as a sense, the questions you ask of it change completely. You stop asking about efficiency and you start asking about insight. You stop asking, “How can I do this faster?” and you start asking, “What can I now see that I couldn’t see yesterday?” For example, perceiving a hidden market anxiety.

    So what does this shift from intern to “sense” actually look like?

    It comes down to the questions we are asking. The quality of our questions is the limiting factor, not the technology (for the most part).

    Look at marketing. The old paradigm, the “intern question,” is focused on automating grunt work:

    The Intern Question: “AI, write 10 social media posts and five blog titles for our new product launch.”

    This is a request for efficiency. It gets you to the same destination a little faster.

    But the organ question is a request for perception:

    The Organ Question: “AI, analyze the 5,000 most recent customer support tickets, forum posts, and negative reviews for our competitor. What is the single unspoken anxiety or unmet need that connects them?”

    The first answer gives you content. The second answer gives you your next million-dollar product.

    Let’s look at strategy. The intern question is about summarization:

    The Intern Question: “AI, summarize the top five industry trend reports for the next quarter and give me the bullet points.”

    This is a request for compression. You’re asking AI to act as an assistant, saving you a few hours of reading.

    But the “Organ Question” is about synthesis and signal detection:

    The Organ Question: “AI, find the hidden correlations between global shipping logistics, regional political sentiment, and our own internal production data. What is the emergent, second-order risk to our supply chain in six months that no human analyst has spotted?”

    The first question helps you prepare for the meeting. The second question helps you prepare for the future.

    To summarize all of this word vomit, I believe that the AI revolution isn’t stalling; more so waiting. It’s waiting for us to catch up.

    What we are seeing is the friction of trying to fit a 21st-century sense into a 20th-century business model.

    We are all still pointing this new tech at our old problems; our inboxes, our reports, our slide decks. We are asking it to help us optimize the past, when its real ability is to help us perceive the future.

    The most critical skill for leadership in this new era will not be prompt engineering. It will be question design. Stop asking “How can AI do this job faster?” and start asking, “What new work becomes possible because we can now see in this new way?”

    So, ask yourself and your team: Are you using AI to get better answers to your old questions? Or are you using it to find entirely new questions?

  • Navigating Value and Purpose as AI Advances

    Navigating Value and Purpose as AI Advances

    Across continents and cultures, we observe a phenomenon of accelerating consequence: the infusion of machine intelligence into the core processes of our economies and societies. This technological trajectory, marked by advancements in artificial intelligence and automation, transcends mere industrial optimization. It prompts a fundamental inquiry into the evolving nature of human contribution and the very definition of value. We are entering what might be termed the nascent Cognitive Age.

    As cognitive labor itself becomes increasingly automatable, we are compelled to move beyond reactive adaptation. We must engage in a deeper, more strategic consideration of humanity’s role and purpose. The discourse is often dominated by anxieties surrounding labor displacement; a valid concern, yet one that potentially obscures a more profound transformation. The critical questions extend further. When machines can execute complex analytical and even creative tasks with remarkable speed and scale, what becomes the distinct value proposition of human cognition? How must our organizations, educational systems, and socio-economic frameworks evolve? These questions demand our focus. Ignoring them risks navigating this pivotal time without a compass.

    A necessary first step involves shifting the frame. We must move from a simple human-versus-machine contest to an exploration of comparative advantages. While AI excels at pattern recognition, prediction within defined parameters, and high-volume data processing, certain domains remain, for now, distinctly human precincts. These are not “soft skills.” They are higher-order cognitive functions, crucial for navigating complexity and ambiguity.

    Consider the capacity for true origination. Not only iterating on the known, but also generating genuinely novel concepts, perhaps sparking a new artistic paradigm or forming a scientific hypothesis that redraws the boundaries of our understanding, drawn from a deep well of lived experience and intuition. Equally vital is the facility for nuanced ethical reasoning. This involves making judgments in situations fraught with ambiguity, conflicting values, and human consequences – deciding not merely if a technology can be deployed, but if and how it should be, a process demanding wisdom beyond algorithms.

    Furthermore, the realm of interpersonal connection and empathy remains intrinsic to effective leadership, collaboration, and care. Building trust across diverse global teams, mentoring talent through challenges, and navigating intricate social dynamics rely on an emotional intelligence that machines currently simulate but do not genuinely possess. Complementing this is the capacity for integrative systems thinking. This means perceiving the intricate, fluctuating web of interactions within our world; seeing the potential ripple effects of a policy decision across an entire ecosystem. For instance, demanding a holistic understanding that defies linear processing.

    And perhaps most fundamentally, there is the uniquely human drive for purpose and meaning-making. This ability to define why an endeavor matters beyond its immediate utility remains central to setting direction and inspiring collective action towards aspirational, value-driven goals.

    Recognizing these enduring human strengths presents a strategic imperative for organizations worldwide. The challenge extends beyond simply implementing AI tools. It requires redesigning organizational structures and cultures from their core to amplify human potential in collaboration with intelligent technologies. This is essential work.

    This necessitates a move beyond efficiency as the primary metric. It means fostering learning ecosystems where continuous adaptation, critical inquiry, and cross-disciplinary problem-solving are inherent – supported by psychological safety. It requires cultivating new benchmarks for value creation.

    Imagine actively measuring success not only through financial returns but also through demonstrable gains in innovation capacity, workforce adaptability, ethical conduct, or positive community impact. Embracing greater flexibility and distributed models of work becomes essential, focusing on outcomes and empowering talent irrespective of geographical constraints. Crucially, it demands principled leadership committed to the ethical governance of technology, ensuring fairness, transparency, and accountability in human-AI systems. This is a consideration with varying nuances across different cultural contexts but universal importance.

    The implications, however, extend far beyond the boundaries of individual firms or institutions. We face a period demanding the co-evolution of our broader societal structures. Foundational assumptions underpinning education, social welfare, and economic participation warrant re-examination. How must educational philosophies adapt globally to cultivate the creativity, critical thinking, and socio-emotional intelligence essential for this future? What revisions to social contracts and economic frameworks might be necessary to ensure equitable participation and security in a world where the traditional link between labor and income may be less universal for many? Addressing these systemic questions requires open, globally-informed dialogue and a willingness to experiment with new models for societal well-being.

    The journey into the future is not predetermined. Technology provides powerful new capabilities; its ultimate impact hinges on human choices and values. Navigating this era successfully requires more than technological prowess alone. It demands wisdom, foresight, and a conscious commitment to placing human flourishing at the center of progress. It calls for thoughtful stewardship from leaders across all sectors and societies, fostering the collaboration needed to shape this future with intention. The helm is ours to grasp.

    Jessica Cole