AI's Cognitive Cost: How Over-Reliance on AI Tools Impacts Critical Thinking

Tools driven by artificial intelligence (AI) are improving our learning, working, and decision-making processes. There is a cost involved in this change, though. With an eye toward cognitive offloading—the process by which we assign mental tasks to outside aids like digital assistants, search engines, or recommendation systems. 

In this article, I examine a 2025 study by Michael Gerlich. It provides a thorough and sophisticated investigation into how artificial intelligence tools influence critical thinking. The study offers a data-rich perspective on a rising issue: depending more on AI to think for us reduces our own cognitive capacity.

Gerlich's study combined 50 qualitative interviews with a systematic survey of 666 UK-based participants. The study used validated instruments, including Terenzini's self-reported cognitive development measures and the Halpern Critical Thinking Assessment (HCTA), to choose participants to reflect different age groups and educational backgrounds.

Two main questions directed the research:  

RQ1: In what ways might using AI tools affect critical thinking abilities?  

RQ2: In the link between artificial intelligence tool usage and critical thinking, what mediator role does cognitive offloading serve?

Two hypotheses sprang from these questions:    

H1: Reduced critical thinking ability is linked to more artificial intelligence tools used.  

H2: Cognitive offloading moderates the link between critical thinking ability and AI tool usage.

Combining descriptive statistics, ANOVA, correlation analysis, multiple regression, and random forest regression, the study tested these hypotheses. Semi-structured interviews yielded qualitative insights, which were examined using Braun and Clarke's six-phase thematic framework. Some important conclusions were later drawn.  

AI Use Negatively Correlates With Critical Thinking  

Support for the first hypothesis was found by analysis showing a strong negative correlation between frequent use of AI tools and critical thinking abilities. Participants who regularly turned to AI tools for information retrieval and decision-making scored lower on measures of critical thinking.  

• AI tool use and critical thinking: r = -0.68 Pearson correlation  
• ANOVA findings: p = 0.001  
• Multiple regression coefficient for artificial intelligence tool use:  -1.76 (p < 0.001)  

Frequent users of AI tools also showed less involvement with deep-thinking activities and reported more dependence on AI for decisions. This corresponds with worries that convenience might compromise free will to reason.

Cognitive Offload as a Mediating Variable  

Furthermore supported was the second hypothesis. One important mediator in the link between artificial intelligence use and reduced critical thinking turned out to be cognitive offloading.  

• Cognitive offloading and critical thinking: r = -0.75
• Mediating indirect effect: b = -0.25, SE = 0.06, p = 0.001 
• Total effect of artificial intelligence on critical thinking: b = -0.42, SE = 0.08, p = 0.001

The results highlight that cognitive offloading is not only a side effect but also a major clarifying factor for why critical thinking might drop in environments high in artificial intelligence. Those who rely on artificial intelligence tools to finish mental tasks are less likely to do reflective analysis, hypothesis testing, and decision-making.  

Variations in Demographic AI Usage and Critical Thinking  

The study also looked at how age and education level affected critical thinking performance, cognitive offloading, and usage of AI tools.  Along with the lowest critical thinking scores, younger participants (17–25 years) used artificial intelligence tools and cognitive offloaded most. Older participants (46 years of age and above) reported much reduced use of artificial intelligence tools and improved critical thinking capacity. Deep thought activities and critical thinking scores were favorably correlated with increasing degrees of higher education.  

Using Kruskal-Wallis and Dunn's tests, post hoc analysis revealed that those with a bachelor's degree or above participated more often in deep thinking activities than those with only secondary education. This suggests that reducing the possible cognitive costs of artificial intelligence use depends much on educational exposure.  

Random Forest Regression Outcomes  

Using a random forest regression to find the most significant predictors of critical thinking complemented conventional regression. With R² = 0.370, the model accounted for 37% of the variance in critical thinking scores. The most important traits were:  

• Cognitive outloading  
• Degree of education  
• Activities using deep thought  
• Reliance on AI decisions  

Usually distributed were residuals; cross-validation verified the model's robustness. Furthermore, important was the interaction term between AI tool use and education level, which implies that more education could help to offset the negative consequences of artificial intelligence dependence.  

Thematic Understanding Gleaned from Interviews  

Important background for the statistical findings came from the qualitative data from fifty semi-structured interviews. The interviews turned out to have three main themes:  

1. One's Reliance on Artificial Intelligence  

Participants regularly claimed to use AI tools for a variety of tasks, including decision-making, information retrieval, and scheduling. Many said they couldn't live without artificial intelligence in their daily lives. "I find information using AI and schedule everything using it as well. It's evolved into something I consider to be natural.  This reliance on artificial intelligence tools reveals a cognitive change whereby outside systems progressively replace internal mental effort.  

2. Lower Cognitive Involvement  

Participants voiced worries about how artificial intelligence tools were limiting their chances to practice deep introspection. "I feel less need to personally solve problems the more artificial intelligence I use. Like I'm losing my capacity for critical thinking.". Particularly among younger participants and those who regularly applied artificial intelligence in both personal and professional spheres, this attitude was rather common.  

3. Ethical and Trust Issues  

Interviewees also expressed concerns about the dependability and openness of artificial intelligence technologies. "I sometimes wonder if artificial intelligence is gently guiding me towards decisions I wouldn't usually make". While some participants admitted to using AI-generated recommendations without checking, others were dubious of them. This emphasizes how dangerous naive faith in artificial intelligence systems can be.

Chris Westfall explores in a Forbes piece how artificial intelligence is changing our decision-making and information processing, so often reducing our dependence on our own cognitive capacity. Although artificial intelligence tools provide ease, he points out that as people rely more on automated systems, they might also cause a drop in critical thinking and problem-solving ability.  

How Artificial Intelligence Affects Cognitive Function: Are Our Brains Under Attack?  

SFI Health expresses worries on the overuse of artificial intelligence and its possible capacity to limit our capacity for critical thinking and autonomous development. To maintain brain health, the paper stresses the need to match AI use with activities that boost cognitive ability, such as digital detoxing and screen time monitoring.  

Artificial Intelligence and the Erasure of Human Cognition  

Psychology Today looks at how the entry of artificial intelligence into spheres of human cognition marks a basic change. The paper challenges the uniqueness of human cognition in an AI-augmented environment and addresses how depending too much on AI could cause a drop in our cognitive capacity, including critical thinking and creativity.  

AI Systems Replacing Cognitive Activities  

Research reported on the National Center for Biotechnology Information (NCBI) website shows that people may lose mental engagement and stimulation when artificial intelligence systems replace cognitive tasks. Lack of active cognitive participation might cause critical thinking to drop, problem-solving ability to fade, and creativity to suffer.  

Concerning Society and Education  

Gerlich's results imply that user involvement and openness should come first in the design of artificial intelligence tools. AI systems should inspire consumers to consider, check, and critically assess material rather than providing ready-made responses, which can create an environment for cognitive invasions.

Interventions in Education  

Schools must include critical thinking instruction in courses utilizing artificial intelligence-enhanced learning environments. Although AI-based grading systems and tutoring tools might increase efficiency, they should not replace the need for students to think creatively and independently.  Using adaptive learning systems has to be counterbalanced with activities promoting alternative thinking, evidence evaluation, and hypothesis generation.  

Higher critical thinking development is correlated with instructional strategies encouraging active learning, including group discussions and problem-based learning.

Correcting the Digital Divide  

According to the study, people with a lesser educational background could be more vulnerable to the negative cognitive effects of artificial intelligence use. This begs questions regarding a digital cognition divide: those without the knowledge to use artificial intelligence critically could lag behind as it spreads more and more.    

Policies and Workplace Issues  

Particularly in sectors like healthcare and finance, organizations should exercise great caution when implementing AI-driven decision-support systems. Although these systems can simplify processes, they might also discourage professionals from participating in autonomous critical analysis, so causing over-dependence and less responsibility.  

Methodological Accuracy  

The method of the study is strong. To improve validity, it used both quantitative and qualitative data triangulation in addition to a statistically relevant sample size—666 participants against a needed 384. The survey was first tested; member-checked interview transcripts were used in thematic analysis using accepted frameworks.

Gerlich was able to verify that the cognitive effects of artificial intelligence tool use are both statistically significant and experientially validated by combining several data sources and analytical approaches.

Conclusion

Michael Gerlich's 2025 research offers convincing proof, especially via the mechanism of cognitive offloading, that over-reliance on artificial intelligence technologies is linked to diminished critical thinking. While higher education and participation in deep thinking events act as protective elements, younger people and those with reduced educational attainment seem most vulnerable.  

It is impossible to overlook the impact of artificial intelligence tools on our cognitive processes as they continue to develop and integrate into daily life. The difficulty is striking a balance — design and application of artificial intelligence should improve rather than replace human cognition.  

Gerlich's studies, together with ideas from current literature, remind us of the ongoing value of deep thinking, reflective judgment, and intellectual autonomy in a digital age that honors speed and convenience. AI can help us, but it should never be let to think for us instead.