{"slug": "will-old-professors-be-forgotten-in-the-artificial-intelligence-era", "title": "Will Old Professors Be Forgotten in the Artificial Intelligence Era?", "summary": "A Psychology Today opinion piece argues that the era of AI will not make old professors obsolete but will shift the value from deep specialization to interdisciplinary breadth, citing the extended mind theory by Andy Clark and David Chalmers. The author, writing on August 17, 2026, contends that AI's ability to access and synthesize vast information across disciplines reduces the need for memorization and encourages scientists to recognize cross-disciplinary connections.", "body_md": "######\n[Artificial Intelligence](/us/basics/artificial-intelligence)\n\n# Will Old Professors Be Forgotten in the Artificial Intelligence Era?\n\n## Personal Perspective: An interdisciplinary approach will help academics in the age of AI.\n\nPosted August 17, 2026\n[\nReviewed by Kaja Perina\n](/us/docs/editorial-process)\n\n### Key points\n\n- Specialization advanced science, but also fragmented our understanding of complex scientific problems.\n- AI may become part of extended cognitive system, changing how we learn.\n- Future scientists need breadth alongside depth to recognize meaningful cross-disciplinary connections.\n\nWhen I was a student, our professors often told us that human life is not long enough to master the enormous amount of knowledge produced by science. Their advice was simple: choose one subject, go deep into it, and try to understand it as well as possible. This advice was completely reasonable. As scientific knowledge expanded, it became impossible for one person to know everything. Biology became divided into molecular biology, [genetics](https://www.psychologytoday.com/us/basics/genetics), biochemistry, physiology, [neuroscience](https://www.psychologytoday.com/us/basics/neuroscience), immunology, microbiology, and many other fields. The same happened in almost every area of science.\n\n## Specialization Both Advanced and Fragmented Science\n\nSpecialization gave us enormous scientific progress. But it also created another problem: We became very good at understanding pieces of reality while becoming less capable of seeing the whole.\n\nIt is like \"The Elephant in the Dark.\" Several people examine an elephant in darkness. Each person touches a different part of the elephant and describes it. The problem is not that any of them is wrong; rather, each person may believe that the part they have experienced represents the whole animal. Something similar may have happened to modern science.\n\nA scientist may spend twenty years studying one molecular pathway, one receptor, one microorganism, one brain region, or a particular gene. The knowledge can be deep and completely correct. However, many important problems in biology and medicine are not limited to a single pathway, organ, or discipline.\n\nAging, cancer, obesity, diabetes, consciousness, and human behavior are examples of complex systems in which multiple levels of biological processes and environmental factors interact. Perhaps the problem is not that we do not know enough. Perhaps sometimes we know too much about separate parts and too little about how the parts are connected [1].\n\n## Artificial intelligence may change the situation\n\nFor centuries, this specialization was partly forced on us because the human brain could not contain all human knowledge. But something has changed. AI can now access enormous amounts of information from different disciplines almost simultaneously. It can summarize scientific papers, explain mathematical models, write computer code, perform statistical analyses, translate technical information, and help us explore subjects far outside our original training. This changes the value of memorizing knowledge. We no longer need to keep all these details and complex calculations in our own minds.\n\n## The Extended Mind theory\n\nMore than two decades ago, Andy Clark and David Chalmers proposed the idea of the \"extended mind.\" Their famous thought experiment involved a person with Alzheimer's disease who uses a notebook to remember information needed to navigate the world. If the notebook reliably stores information and the person uses it as an integral part of their cognitive process, why should we insist that it is completely outside the cognitive system? This concept now raises a question: Can AI capacities now be considered a part of our mind?\n\nIf I can ask an AI system to retrieve a complex equation, find relevant literature, analyze my statistical data, or compare theories from different disciplines, then part of my cognitive activity no longer takes place only inside my brain. Instead of trying to store every piece of information, I can invest more of my cognitive capacity in understanding concepts, mechanisms, patterns, relationships, and questions [2].\n\n## An uncomfortable question for academia\n\nAcademic institutions have understandably been cautious about the use of AI. They are concerned about plagiarism, fabricated references, incorrect information, and the possibility that students or researchers may submit work they do not fully understand. These concerns are legitimate. However, I believe we sometimes mix two different things: There is a significant difference between asking AI to do our thinking for us and using AI to assist with tasks that free our minds to think more comprehensively.\n\nIf we use AI to find a formula that we understand, help us to write R code, translate a technical paragraph, identify relevant papers, or test whether an argument has a weakness, and then critically evaluate the results, have we really abandoned intellectual responsibility? We do not normally consider it academic misconduct when a scientist uses a calculator, statistical software, a search engine, or a reference manager. The important question should not simply be whether AI was used. The important question is: What part of the intellectual responsibility remains with the human researcher? It is plausible that academia will eventually have to confront this question more seriously.\n\n[Artificial Intelligence](https://www.psychologytoday.com/us/basics/artificial-intelligence)Essential Reads\n\n## From specialists to systemic thinkers\n\nI do not believe specialists will totally disappear. We will still need them. If AI proposes a connection between two biological phenomena, someone with deep knowledge must be able to determine whether that connection is meaningful or simply a coincidence. But perhaps the future will favor people who combine depth with breadth.\n\nImagine a scientist who understands the basic principles of several fields: metabolism, neuroscience, microbiology, immunology, evolution, and statistics. This person may not remember every formula or technical detail from each field. But when a problem appears, AI can help retrieve the necessary details. More importantly, this person may recognize something that a highly specialized scientist does not immediately see because each discipline has developed its own language and literature. Perhaps these apparently different phenomena are parts of the same system.\n\nIt is not merely about knowing many things; it is about recognizing relationships between concepts that are typically studied separately. This does not mean that AI cannot make such connections. In fact, AI can generate numerous connections, likely more than any individual human can.\n\nHowever, generating a connection is not the same as understanding its meaning. AI can indicate that two phenomena are correlated, identify similarities between theories, and suggest unexpected hypotheses. The human role may increasingly become deciding which of these connections are meaningful, which are coincidental, and which warrant further scientific investigation. Perhaps the challenge will move from finding connections to understanding which connections matter.\n\nNow, the question is: what will we do with this new freedom? Will we use AI to produce answers faster? Or will we use it to see connections that specialization prevented us from seeing?\n\nPerhaps the next scientific revolution will be a return to the discipline that originally gave rise to all sciences: [philosophy](https://www.psychologytoday.com/us/basics/philosophy). Philosophy addresses holistic questions about the world and fundamental human concerns. Most PhD students, and even professors, have forgotten that \"PhD\" stands for Doctor of Philosophy. Being grounded in this discipline may help academicians to see connections between phenomena and answer the unresolved questions within their fields. A philosophical perspective encourages scientists to seek meaningful connections, evaluate their significance, and explore what constitutes a meaningful relationship between ideas.\n\nReferences\n\n1. Casadevall A, Fang FC. Specialized science. Infect Immun. 2014 Apr;82(4):1355-60.\n\n2. Clark, A., & Chalmers, D. (1998). The Extended Mind. Analysis, 58(1), 7-19.", "url": "https://wpnews.pro/news/will-old-professors-be-forgotten-in-the-artificial-intelligence-era", "canonical_source": "https://www.psychologytoday.com/us/blog/the-behavioral-microbiome/202608/will-old-professors-be-forgotten-in-the-artificial", "published_at": "2026-08-17 20:20:56+00:00", "updated_at": "2026-08-17 20:44:24.358223+00:00", "lang": "en", "topics": ["artificial-intelligence"], "entities": ["Psychology Today", "Andy Clark", "David Chalmers"], "alternates": {"html": "https://wpnews.pro/news/will-old-professors-be-forgotten-in-the-artificial-intelligence-era", "markdown": "https://wpnews.pro/news/will-old-professors-be-forgotten-in-the-artificial-intelligence-era.md", "text": "https://wpnews.pro/news/will-old-professors-be-forgotten-in-the-artificial-intelligence-era.txt", "jsonld": "https://wpnews.pro/news/will-old-professors-be-forgotten-in-the-artificial-intelligence-era.jsonld"}}