In looking at our current educational institutions, the majority are structured to teach to specific outcomes (i.e., teaching to the test), as this methodology was applicable to the Industrial Age. Basic literacy and numeracy were taught as essential requirements for working in factories and military service. As nations further modernized, public education systems still taught rote knowledge while emphasizing higher education institutions for those who wanted a specific skillset on which to base a career. As we further questioned our human ignorance and admitted that our prior information systems (religion, state, economy) were not sufficient to account for the wonders of modern medicine, space exploration, and computing systems, we sought to provide worldwide access to information highways via the Internet and proliferate globalization through technology and trade. Microprocessors, mobile phones, automation, and social networking condensed, connected, and concentrated our man-made systems into a technological hub that unlocked the power of the algorithm. No longer were decision-making capabilities relegated to the realm of flesh and blood, nay, we successfully offloaded this powerful mechanism to machine learning that produced incredible results built on probabilities and statistics. Why make an educated guess when mathematics can provide pattern-based predictions? Why depend on heuristics when specificity is but a computer calculation away?
As computing systems scaled up via mass amounts of data and energy, we learned that the neural nets on which our human brain operates can be applied to artificial intelligence (AI) systems that resulted in their current generative abilities. Prior to this breakthrough in deep learning, our current sense of AI capabilities was confined to narrow systems that excelled in a specific domain (ex., Deep Blue, AlexNet, AlphaGo, etc.). As witnessed by the generative pre-trained transformer (GPT) models that launched in 2022 for public use, large language models (LLM’s) versatility created renewed interest and speculation concerning AI and how to best apply it to our vast range of systems. In true “cart before the horse” fashion, this advanced technology was deployed at scale before we fully understood its potential risks or prepared world governance structures for the ethical frameworks needed to ensure Gen-AI’s creator (humans) were not displaced in a changing society. And what of the data used to train these advanced models? Or, better yet, who owns AI-generated content and who is responsible if these models produce harmful content that negatively impacts a human? We are not even certain how they work! While not a complete black box, at best it’s opaque as this is the nature of reinforcement learning techniques used to train billion-parameter datasets. It’s akin to discovering fire the second time around; life changing, yet destructive if uncontrolled and misunderstood.
If we look at our current educational landscape, as this think piece is particularly concerned, we see a patchwork of responses from various institutions as it relates to implementing Gen-AI. This result is exactly as expected when presented with a novel technology that potentially disrupts the learning process. We didn’t know how to best implement it within our established systems, so many teachers were left reacting as students were all too eager to apply their generative abilities to coursework. Currently, we see newer and more advanced AI models being developed, deployed, and open-sourced for all to use. What began as an innovative technology for those in the IT sphere has now garnered the attention of nations as evidenced by the US announcing a “private sector investment of up to $500 billion to fund infrastructure for artificial intelligence, aiming to outpace rival nations in the business-critical technology” (Reuters). This investment signaled to the rest of the world that an AI race is in progress and those who wield its true potential (Artificial General Intelligence; AGI) first, are likely to reap unprecedented benefits if aligned with our human values.
AGI, as defined by Geoffrey Hinton, uses the term to mean “AI that is at least as good as humans at nearly all of the cognitive things that humans do” (AP News). This ideal has long been the goal of computer scientists and one that seems like a potential reality soon. Leopold Aschenbrenner, a former OpenAI employee and author of Situational Awareness: The Decade Ahead, stresses the importance of aligning AI systems prior to an AGI system automating the research process, thus creating superintelligent systems that dwarf our human ingenuity. While his work is beyond the scope of this article, the process of automating research is underway as a recently produced paper by The AI Scientist-v2 on compositional generalization was submitted to the Thirteenth International Conference on Learning Representations (ICLR 2025), and became the first AI system to pass the same peer-review procedure as a human would. In short:
The AI Scientist-v2 came up with the scientific hypothesis, proposed the experiments to test the hypothesis, wrote and refined the code to conduct those experiments, ran the experiments, analyzed the data, visualized the data in figures, and wrote every word of the entire scientific manuscript, from the title to the final reference, including placing figures and all formatting (Sakana.ai).
This is an incredible feat and one that begs the following question: If AI systems can eventually learn and create at or beyond our current human understanding, then what role does formal schooling have in our society? While education is the subject matter of this thought bubble, the prior question can be framed for any institutional system if (when?) AGI is reached. Rather than “fight the machine,” let it have linear, algorithmic, and computational thinking. We can offload these tasks and peer back into history and ponder on the questions that brought us to this moment in time. Namely, what does it mean to be human when all our technical problems have been solved?
Termed by Edward de Bono (1967), lateral thinking involves approaching problems provocatively so that our creative abilities can be “unburdened by what has been” (pun intended). Realistically, de Bono’s idea harkens back to a time when western thought was being influenced by Socrates, Plato, and Aristotle. Thinkers of the truest sense, these individuals laid a foundation for our freedom of thought to flourish via probing questions into human behavior, ethics, epistemology, metaphysics, and scientific inquiry. But let’s look even further back in time and focus on what allowed these great minds to develop. What was it that allowed our species to influence one another to such an extent that we are now on the precipice of creating an artificial intelligence that has the potential to surpass our level of understanding? Put simply, our communication abilities, our cooperation agilities, and our organizational willingness to work as collective sapiens. These traits allowed us to shape our future and take control of our purpose in life.
Now, as we are primed to enter a new era of potential uncertainty, I want to remind our educators of their true mission in life, i.e., the reason you chose to enter this sacred profession. You wanted to make a difference in the lives of people by helping shape their thinking. You knew that, regardless of the agenda, curriculum, or mandate being implemented, what you were truly doing was guiding a mind. It is this principle, human thinking, that needs to be developed and curated within our educational systems. When a student asks, “Why do I have to write when AI can do it for me?”, your answer can be “Because writing involves thinking and that is what we are trying to develop.” When a student asks, “Can’t I just use AI to provide the answer?”, you can respond with “It is the questioning process that matters when searching for an answer.” When teaching history, “Why do I need to know what happened in the past”, you can answer with confidence that “Understanding how we arrived at this moment in our advanced society allows us to reflect and grow together as human beings.”
In closing, it is our thinking abilities that separate us from other animals. I would encourage my fellow lifelong learners to start constructing a future that emphasizes human creativity in meaning-making. Doing so will require us to understand the value in our emotional intelligence and learn to live with mechanistic beings that perform skills at a level unattainable by humans. If we accept these conditions then we have a chance of obtaining a level of comfort and tranquility that our forefathers would say are ripe conditions to foster human relationships. For isn’t this the key to meaning in our potential new world, i.e., learning to love one another just as we are. If so, then our level of happiness should rise and in doing so, we finally find the connection that links us all.
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