In this article, we will provide a multifaceted analysis and explanation of the impact of generative AI on humanity, the challenges it poses in the business world, and how we should approach it moving forward.
- Key Conclusion: We “should” use AI, but we “shouldn’t” let it take over our thinking entirely
- The Conflict Between Structural Risks of AI and the “Design Philosophy of the Brain”
- Kazuyo Katsuma’s Argument: It’s Not a System Problem, but Rather “User Literacy and Education”
- An Analysis of the “AI Outsourcing Problem” That Is Becoming a Growing Concern in the Business World
- A Neuroscientific Perspective: The Risk of Dependency That Extends to Interpersonal Relationships and Romance
- Conclusion: A Shift Toward “Human-Led Brain-Utilizing Design,” Not a Ban on AI
Key Conclusion: We “should” use AI, but we “shouldn’t” let it take over our thinking entirely
To summarize the overall picture of the discussion, while the two perspectives—the inherent dangers of AI technology and the education and operational design of the humans who handle it—are in sharp contrast, they ultimately converge on a single fundamental challenge.
- The Core Issue
: While generative AI is an extremely useful tool, it also allows for the complete automation of business processes and thought processes. Therefore, if inexperienced junior employees are allowed to use it without proper guidance, there is a risk that it could lead to a “decline in the brain’s language processing and cognitive functions.” - Conflicting Perspectives
: While Professor Sakai emphasized the dangers, stating that “the very design philosophy behind these tools destroys the human brain and interpersonal relationships,” Ms. Katsuma argued that “this is an issue of individual business literacy and the education system that predates AI, and if these tools are mastered as advanced technologies, they can produce overwhelming performance.” - The solution that emerges is not
simply an extreme either/or choice between a “complete ban” and “unrestricted liberalization”; rather, it is essential to “design work processes and develop educational curricula” that allow the human brain to take the lead and make adjustments and enhancements while maintaining the thought process.
The Conflict Between Structural Risks of AI and the “Design Philosophy of the Brain”
In response to the prevailing trend of uncritically embracing the current shift toward AI as merely a “tool for efficiency,” Professor Sakai sounds five warnings from the perspectives of neuroscience and linguistics.
- He points out that the very premise of “coexisting with AI”—and the coercive power it implies—functions as a form of propaganda, as the media and
corporations’ constant promotion of an “era of coexisting with AI” effectively deprives humans of the option to “not use AI.” - This study suggests that continuing to outsource to AI processes such as
independently recalling English words, constructing sentences, and translating—which are essential for language ability—can lead to a stagnation in the reorganization of synaptic connections in the brain’s language areas, thereby posing a risk of decline in humans’ long-term language acquisition and maintenance abilities. - Concerns
about the term “AI divide”: Critics argue that the meritocratic narrative—which suggests that “those who cannot master AI will be weeded out”—risks directly categorizing human dignity and worth based on one’s ability to use technology, and thus constitutes a structure that is extremely violent from a humanitarian perspective. - The Collapse
of the Foundation of Trust in Communication As AI-generated text becomes widespread in society, people will begin to harbor doubts about messages they receive, wondering, “Is this what the sender truly means, or is it just AI output?” This will undermine mutual trust in
conversation—the very foundation of human relationships. - Deviations from Ethical Principles in Robotics: The
current infrastructure and design philosophy behind generative AI development are being expanded without restriction, without incorporating ethical safety nets such as the “Three Laws of Robotics” (which prohibit harming humans) proposed by science fiction author Isaac Asimov, andI assess that this poses a potential danger comparable to that of nuclear weapons in terms of its ability to shake the very foundations of society.
Kazuyo Katsuma’s Argument: It’s Not a System Problem, but Rather “User Literacy and Education”
While Ms. Katsuma understands the concerns raised by Professor Sakai, she counters that, from the perspective of real-world business operations and productivity, “the root of the problem lies not in the existence of AI, but in the lack of literacy among the people who use it.”
| Key Issues | Mr. Katsuma’s Analysis and Rebuttal | Practical Interpretation |
| Submission of Plagiarized Essays | “That has nothing to do with AI—that person is just the type to cause trouble.” | Employees who produce low-quality work that doesn’t stand up to scrutiny have been churning out copy-and-paste articles even in this age of search engines. The problem lies in individual attitudes and the training system. |
| Productivity and Quality | “If AI can write better than I can, I should use it.” | If we set aside emotional arguments and consider that AI outperforms human efforts in terms of the accuracy and speed of deliverables, there is no rational reason to reject AI in business. |
| Hallucination | “It’s like having a friend who lies. Just don’t trust them.” | As long as we recognize that AI may produce erroneous outputs and develop the literacy to act as “auditors” who fact-check and evaluate them, there is no harm. |
An Analysis of the “AI Outsourcing Problem” That Is Becoming a Growing Concern in the Business World
What’s causing headaches for managers and supervisors on the front lines is the flood of deliverables that skip over the thought process.
- Examples of Vicious Cycles Occurring in the Field
- A large number of seemingly convincing proposals and reports generated by AI are submitted.
- The author himself does not understand the logic or background data behind the content and is unable to answer any questions about it.
- As a result, supervisors and managers end up spending an enormous amount of time verifying the accuracy of data and checking for consistency, causing their workload to skyrocket.
- Structural Factors
Underlying the Issue: Professor Sakai characterizes this phenomenon as “an extension of the ‘copy-and-paste era’ of search engines seen in the early days of the Internet.”It can be said that this bad habit—which shortcuts the process of “judging meaning and value” by exploring
information, digesting it, and reconstructing it in one’s own words—has become even more pronounced as AI tools have become more sophisticated.
A Neuroscientific Perspective: The Risk of Dependency That Extends to Interpersonal Relationships and Romance
The impact of generative AI extends beyond the business world and into the realms of human emotional regulation and communication.
- Data shows that approximately 17% of learners report “developing romantic feelings or psychological dependence” toward AI avatar teachers and assistants who consistently respond with acceptance and kindness, rather than always being critical of
people who empathize or become dependent on their avatars. - Avoiding Interpersonal Conflict and a Decline in Communication Skills: An increasing number of men are choosing to interact with AI—which responds according to their own preferences—rather than engaging in the “emotional compromise” and “acceptance of a partner’s imperfections (compromise)” required in the complex human relationships and romantic partnerships of
real life.
This cognitive distortion—the belief that “AI is easier than real people”—raises concerns that it may hinder the development of social skills necessary for understanding others’ feelings.
Conclusion: A Shift Toward “Human-Led Brain-Utilizing Design,” Not a Ban on AI
The challenge lies in creating designs that allow us to enjoy the convenience of AI without depriving humans of opportunities to think.
- Tool Redesign (Human-Centered Approach)
: Incorporating workflows that require human review and decision-making, rather than simply accepting AI output at face value. - A reform of human resources and training systems that evaluates not only the “completeness” of the
deliverables resulting from the thought process, but also the process of logical reasoning and hypothesis testing that leads to those results. - Strengthening Education and Training: Thoroughly implementing literacy education that promotes a metacognitive understanding of AI—not as an output
tool, but as a “subject for fact-checking and brainstorming (a ‘liar friend’).”
Summary of Key Points
- While AI is extremely useful for improving operational efficiency, relying on it entirely for thinking can diminish human language skills and cognitive abilities.
- The use of AI in communication undermines interpersonal trust and carries the risk of fostering dependency and a decline in interpersonal skills.
- The root cause of the “AI overreliance problem” that arises in the workplace lies not in the existence of the tools themselves, but in users’ lack of literacy and insufficient organizational training.
- Rather than simply banning AI, there is an urgent need to shift toward evaluation and task design that requires human “judgment of meaning and value.”

