Generative AI has rapidly transformed into a comprehensive toolset since its maturation in 2023 and 2024. These tools offer remarkable capabilities, enabling users to research topics in record time and develop work products tailored to specific writing styles. By accelerating workflows and enhancing accuracy, AI presents undeniable advantages. Yet, it raises a critical question: does the ease of completing tasks with AI risk creating “lazy brains”?
As Inzlicht, Shenhav, and Olivola (2018) observed, human effort is paradoxical. While effort is often seen as burdensome and something to avoid, it is also linked to the satisfaction derived from achieving rewards. Interestingly, the actual value of a work product does not necessarily increase with the effort expended. This paradox fuels the argument for AI as a time-saving tool that allows individuals to reap rewards with minimal effort. However, this logic has blind spots: (1) the emotional satisfaction tied to achieving goals may diminish when tasks are too easily completed, and (2) the brain’s capacity to engage in sustained effort declines without continuous mental stimulation.
Yale anthropologist Lisa Messeri highlights a deeper concern about AI’s impact on learning. Messeri (as cited in Cummings, 2024) suggests that while AI might boost the volume of work produced, it could simultaneously reduce meaningful learning. The danger lies in fostering a false sense of understanding among users, leading them to believe they grasp the world more comprehensively than they truly do. History offers ample evidence of plans executed based on erroneous assumptions, often with dire societal consequences.
This is not to say that AI cannot be a powerful ally in human learning. In fact, several educational platforms are harnessing generative AI to enhance student engagement and comprehension. Similarly, businesses employing AI can accelerate knowledge-sharing, benefiting employees, organizations, and stakeholders. Like any other tool humanity has developed, AI holds great potential for good when used ethically and responsibly. As Adelakun (2024) emphasizes, ethical standards must govern the development and deployment of AI tools.
The architects of AI platforms carry significant responsibility for ensuring these technologies serve positive ends. With well-defined guardrails and proper adherence to ethical principles, AI can support human learning and understanding on an unprecedented scale. Yet, society must address the challenge of maintaining critical thinking skills amid increasing reliance on AI. Without these skills, individuals risk becoming overly dependent on technology, potentially eroding their capacity for independent analysis and decision-making.
Of course, the misuse of AI remains a legitimate concern. My grandfather’s saying comes to mind: “Figures don’t lie, but liars can figure.” The temptation to exploit AI for dishonest purposes will always exist. Thus, cultivating a society with robust critical thinking skills becomes more urgent than ever. Educating people on ethical AI use and teaching them to harness its capabilities responsibly is essential. Only by striking this balance can humanity ensure AI serves as a catalyst for progress rather than a crutch that weakens intellectual growth.
In conclusion, AI’s role in human learning is a double-edged sword. It offers transformative opportunities but demands vigilant oversight to maximize benefits while safeguarding against potential pitfalls. The future of AI in education and work will depend on how effectively we address these challenges.
References
Adelakun, N. O. (2024, May 14). Exploring the Impact of Artificial Intelligence on Information Retrieval Systems. Https://Informationmatters.org. Retrieved January 9, 2025, from https://informationmatters.org/2024/05/exploring-the-impact-of-artificial-intelligence-on-information-retrieval-systems/
Cummings, M. (2024, March 7). Doing more, but learning less: The risks of AI in research. Https://News.Yale.edu. Retrieved January 9, 2025, from https://news.yale.edu/2024/03/07/doing-more-learning-less-risks-ai-research
Inzlicht M, Shenhav A, Olivola CY. The Effort Paradox: Effort Is Both Costly and Valued. Trends Cogn Sci. 2018 Apr;22(4):337-349. doi: 10.1016/j.tics.2018.01.007. Epub 2018 Feb 21. PMID: 29477776; PMCID: PMC6172040.
Comments
5 responses to “AI: A Benefit or Detriment to Human Learning”
Your concern about AI fostering “lazy brains” overlooks how AI complements, rather than replaces, human effort. By automating repetitive tasks, AI frees individuals to focus on higher-order cognitive skills like analysis and creativity. Emotional satisfaction from learning doesn’t diminish with ease; instead, mastery of complex tasks remains rewarding. While Messeri’s critique about false mastery has merit, this is not unique to AI but reflects the need for critical engagement. Ethical AI use and literacy are essential, but AI’s integration into education offers transformative potential, shifting focus from rote effort to meaningful intellectual growth when embraced responsibly.
Thanks for your feedback Dale. I agree with you that AI can complement human effort, and I am hopeful that many students will take advantage of the multiplier effect of AI in learning. Were my opinion diverges from yours is in the “will they” use it to their advantage. As Inzlicht, Shenhav, and Olivola (2018) demonstrated, the level of emotional satisfaction of learning is diminished when the learning becomes easy. For the human to continue to want to experience the higher level of satisfaction, the learning must remain challenging over the longer team. Can you provide a reference that counters Inzlicht, Shenhav, and Olivola (2018) theory?
Thanks for your feedback Dale. I agree with you that AI can complement human effort, and I am hopeful that many students will take advantage of the multiplier effect of AI in learning. Were my opinion diverges from yours is in the “will they” use it to their advantage. As Inzlicht, Shenhav, and Olivola (2018) demonstrated, the level of emotional satisfaction of learning is diminished when the learning becomes easy. For the human to continue to want to experience the higher level of satisfaction, the learning must remain challenging over the longer team. Can you provide a reference that counters Inzlicht, Shenhav, and Olivola (2018) theory?
I think this idea is what the best hope was for A.I., however it is now starting to replace things like creativity. There was recently controversy when Adobe changed its terms to allow them to train their Ai models on artists’ work. Effectively stealing their work. Artists have spoken out about how they were able to find generative images under their names on their site. I think A.I. should help us with the mundane tasks; not the creative endeavours.
A big worry I have when it comes to the concern of false understanding is also the spread of false information itself. This study found that new A.I. models are actually more likely to give incorrect answers than admit that they are wrong: https://www.nature.com/articles/s41586-024-07930-y#citeas
Even people using ai can cause issues spreading false, and dangerous information. When you blindly trust the Ai and don’t do any of your own learning you can end up producing a deadly cookbook. Like this professor in Manitoba discovered: https://winnipeg.ctvnews.ca/the-risk-is-real-book-on-manitoba-mushrooms-suspected-to-be-written-by-ai-1.7076001
What will we do when the BOOKS aren’t being peer-reviewed?!