In the rapidly evolving technological landscape, the relationship between human cognition and artificial intelligence (AI) has become a topic of critical importance and intense debate. What is at stake if we allow AI to overshadow human wisdom? Imagine a professional setting where an individual relies heavily on AI-generated summaries for decision-making rather than engaging directly with full reports, research papers, peer-reviewed studies, and related materials. This reliance creates a false sense of efficiency, as decisions are made faster but lack depth and informed understanding. As we increasingly depend on machines to think for us, we face a paradox: while efficiency soars, the essence of human wisdom may be fading. This shift echoes historical technological revolutions, such as the Gutenberg press, which, while revolutionizing information dissemination, also displaced traditional crafts and altered the fabric of human knowledge production. The question we now face is whether our embrace of AI represents genuine progress or a subtle form of abdication of our uniquely human capacities.
The core of this dilemma lies in clearly distinguishing between using AI as an assistive tool and fully delegating our cognitive processes to it. For instance, calculators enhance our mathematical skills without supplanting our understanding, serving as tools that support, not replace, our mindset. In contrast, AI ‘agents’ that plan, write, and make decisions for us may substitute essential human capacities. Spell checkers and grammar tools extend our language abilities by catching errors we might overlook, but they do not remove our need to understand grammar rules or originate ideas. However, when AI generates entire documents, it moves from assisting our creative input to potentially replacing it. Similarly, navigation systems suggest optimal routes but do not account for the nuanced decision-making only a driver can make based on preferences and situational judgments. For example, as a child, I watched for the multicoloured entrance to the Lawrence subway station from the car—it was my personal landmark, not chosen by any algorithm. This surrender of thought processes risks eroding our agency and critical thinking. Our grade school math teachers often stressed that understanding the steps behind a solution is more valuable than arriving at the answer itself—a distinction that becomes vital in the age of AI.
Heidegger’s idea of the “forgetfulness of Being” captures the threat of losing touch with our essential human qualities as we fixate on technology’s outputs. Focusing only on AI’s abilities risks sidelining the deeper cognitive and ethical purposes behind our engagement with technology. Our relationship with AI raises profound questions not only about what it does for us, but about what we risk losing as human thinkers and agents.
The comparison between the Gutenberg press and generative AI further illuminates the stakes. While the printing press scaled the distribution of human-created content, it did not generate new content on its own. Human intention and authorship remained the bottleneck, while the creative input remained the backbone and intent of the writings, though the scale and distribution changed exponentially. In contrast, generative AI can produce content itself, mimicking human expression and decision-making. For example, leading AI models can generate millions of words and thousands of images daily, fundamentally altering content production. This shift from scaling distribution to scaling production poses new challenges, including the proliferation of misinformation and the blurring of lines between reality and AI-generated fantasy.
The negative impacts of the Gutenberg press offer a cautionary tale. While it revolutionized information dissemination, it also facilitated the faster spread of misinformation and propaganda. Printed texts made it easier to mass-produce false, inflammatory, or manipulative material. Similarly, in our current era, we see the proliferation of deepfakes and AI-generated content that further blur the lines between truth and fiction. As of 2026, with high finance moving investments into the entire AI value chain, the metaphorical horses have left the barn, and we face an unprecedented challenge in distinguishing reality from AI-generated fantasy.
As AI technology scales rapidly, it outpaces our ability to govern and regulate it effectively. The rush to capitalize on AI’s potential often prioritizes profit and control over ethical considerations and societal benefit. In early 2026, the Mag 7 are not off to a blazing start; however, valuations are bloated, and P/E ratios are also severely inflated (Greenberg, 2026). But this imbalance risks amplifying existing problematic incentives without fostering moral or political growth. When we expand into new technological frontiers like AI, the acceleration often surpasses the gates of good governance and regulation. Investors and founders, blinded by the promise of limitless monetary outcomes, may move away from creating real value for humanity, such as improving the quality of life, health, and alleviating poverty. Early adoption of AI has spread into manufacturing and finance. This is a noticeable shift toward more lucrative areas that cater to the power-hungry first-world nations (McKinsey & Company, 2025). Examples include significant investments in sectors like autonomous weapons systems, which enhance defence capabilities but pose ethical dilemmas, and in the control of fossil fuels, where energy companies leverage AI to maximize extraction and profits. Additionally, social media platforms have become prime targets for AI-driven strategies designed to manipulate and control public narratives, ultimately serving the interests of those in power.
Perhaps most concerningly, the routine use of AI for decision-making and information processing may lead to the atrophy of our cognitive and ethical faculties. Like any skill, these capacities diminish without regular practice. The danger lies not in AI surpassing human intelligence but in humans voluntarily relinquishing their cognitive capabilities. If we routinely use AI agents to decide what to read, how to interpret information, what to believe, and what to say, we train ourselves out of certain capacities: critical thinking, synthesis, imagination, and discernment. This point of mental atrophy cannot be emphasized enough, as our brains are forced to become conduits for information transfer rather than processors and interpreters, and to rely on our own insights.
The loss goes beyond practical skills and affects the habits that shape our character and judgment. Calligraphy, for example, was not just about making beautiful letters. It also helped people develop patience, attention to detail, and artistic expression. In the same way, if we rely only on AI for decision-making, we risk missing out on personal growth. Learning calligraphy in the past meant gaining a deep appreciation for the written word. Today, even with AI everywhere, we should still aim to build critical thinking and creativity. Apple is a leading technology company, and its founder, Steve Jobs, attended Reed College in Portland from 1972 to 1974. Although he dropped out, he continued to sit in on classes he found interesting, including a calligraphy course taught by Robert Palladino. That class taught him about serif and sans-serif fonts, letter spacing, and the art and technique of type. This experience influenced the Macintosh’s typography and design, demonstrating how studying the humanities can inspire technological innovation and a design focus (Jobs, 2005). This example highlights why it is important to keep developing our thinking skills and ethical judgment, so they do not fade as we use more automation.
In the end, it is the Techno Oligarchs whose relationship with money and the wealth illusion drives them to chase an infinite number by whatever means necessary. As John Maynard Keynes wrote, “Capitalism is the extraordinary belief that the nastiest of men, for the nastiest of motives, will somehow work for the benefit of us all” (Keynes,1931). Coupled with our own obsession with AI and the outsourcing of thinking to machines, efficiency wins—but wisdom fades, and the mind begins to automate itself out of relevance. Like most things in life, they are not always as great as we think they are, and in the end, things are never as bad, or so one would hope. It is important to be cautiously optimistic with AI in a world where hope springs eternal.
Resources:
Greenberg, K. (2026, January 26). The ‘Magnificent 7’ are off to a mixed start in 2026: Here’s what to watch as their earnings start. Investopedia. https://www.investopedia.com/the-magnificent-7-are-off-to-a-mixed-start-in-2026-here-is-what-to-watch-as-their-earnings-start-11891595.
Heidegger, M. (1927/1962). Sein und Zeit [Being and Time] (J. Macquarrie & E. Robinson, Trans.). New York: Harper & Row. (Original work published 1927).
Jobs, S. (2005, June 12). Commencement address at Stanford University. Stanford University. https://news.stanford.edu/2005/06/14/jobs-061505/
Keynes, J. M. (1931). The end of laissez‑faire. In Essays in Persuasion (pp. 272–287). Harcourt, Brace and Co.
McKinsey & Company. (March 12, 2025). The state of AI: How organizations are rewiring to capture value. McKinsey & Company (QuantumBlack Insights).