Psychology of Singularity – Your Source for AI News and Information

Image by Hotpot.ai

Is AI Making Students Lazy and Dumb?

By Jill Maschio, PhD

Teachers across America are concerned about their students’ lack of motivation to work hard when using AI. Students’ test scores seem to be falling, and there is more evidence that intelligence is decreasing. Is AI in the classroom making students less motivated to read, write, and learn or making them more creative and curious about learning?

As AI becomes more popular, we must realize that not all trends are equal. Some trends are helpful, while some are harmful or pretty amusing. We don’t understand the whole story about AI and how it works, according to Sam Altman (Curry, 2024), who addressed questions about AI at an A.I. conference. Whether we know the whole story about AI, education is scrambling to find practical uses in the classroom without first knowing of any real benefit for learning. If you have read my article about AI and its impact on Intelligence, you can access it here.

We need a greater understanding of the potentially harmful and beneficial effects of AI in the field of education. We would assume that there are benefits, much like society and educators thought there would be huge gains in learning when public schools first brought in computers to kindergartner rooms. Later, we learned of some harmful consequences of excessive Internet use. An example of the harm AI might have on academic performance has not been fully researched. Marcello Mariana (Dwivedi et al., 2023), writes that generative AI has not only been inaccurate at times, but using it leaves out independent thought for humans. Its use can lead to unmeaningful learning for humans and innovation. 

In a study published by the International Journal of Education Technology in Higher Education (2024), researchers studied 494 university students on the effects of ChatGPT and procrastination, memory loss, and academic performance because very few studies have examined such a relationship on academic outcomes. The participants reported on a self-reporting instrument procrastination level and memory loss, such as that they cannot retain information as much as they used to. The researchers collected their latest reported CGA to examine memory loss. They reported memory loss is associated with excessive use of ChatGPT for academic tasks. The continuous use of AI may lead students to develop a lazy attitude toward academic outcomes.

Theory of AI and Reduction in Metacognition

I hypothesize that students who lack strong metacognition may not realize what they know and what they don’t while prompting generative AI (e.g., ChatGPT). While people eagerly want information at their fingertips, they can easily ignore the thought process of reflecting on what was learned and what wasn’t to identify what the focus should be on to learn information of content. If this hypothesis is true, then overreliance on generative AI tools for learning may reduce memory formation because active cognitive engagement with information is necessary for selective priority information to be consolidated into long-term memory (Cowan et al., 2021).

The Use of AI may Limit Neurological Activity Needed for Memory Formation

Nature has predetermined that if a specific region of the brain cannot store information, then the brain cannot be modified by experience, leaving the individual unable to remember (LeDoux, 2002). Memory formation is complex. It involves neurochemicals, for instance. When first exposed to stimuli, two neurons will start to fire together, and the neurochemical glutamate helps strengthen the neural connections. If the firing neurons are activated again, the dendrites of the neurons begin to physically grow to establish a neural network.

However, factors may influence the neural network’s stability. According to Shors (2014), processing information deeply can help stabilize neural connections. The duuration of how long a neural network is active may also help stabilize the neurons. For example, the longer we spend engaging with content, the more the neural network stays active – potentially increasing its stability.

When AI Use Influence Loss of Memory Formation

Depending on how a person engages with AI, it may be comparable to using a search engine to locate information that we glance at or to scrolling on our cell phones, both of which may reduce the time spent processing information because if two neurons began firing, the connection would not become stable by moving on to other tasks or scrolling.

There is much more research to consider about this topic. All the research in the literature was not mentioned here, and I’m confident that there is great usefulness for generative AI tools for learning. I do believe that how a person uses it makes the difference, much like my example above about using search engines to locate information. We can have a search engine find information, and then we have a choice of what to do with the information. People can either simply forget it or use the information by processing it further into something meaningful.

Note: A human wrote this essay. No AI tools were used to write this article.

References

Curry, R. (2024, May 30^th). Sam Altman says OpenAI doesn’t fully understand how GPT works despite rapid progress. Observer. https://observer.com/2024/05/sam-altman-openai-gpt-ai-for-good-conference/

Dwivedi, Y. K., et al. (2023). Opinion paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642, https://doi.org/10.1016/j.ijinfomgt.2023.102642

LeDoux, J. (2002). The synaptic self: How our brains become who we are. New York: Viking Penguin.

Shors, T. (2014). The adult brain makes new neurons, and effortful learning keeps them alive. Current Directions in Psychological Science : A Journal of the American Psychological Society, 23(5), 311 –318. https://doi.org/10.1177/0963721414540167