You Cannot Say “Fire Is Dangerous, So Stay Out of the Kitchen” and Still Demand Great Cooking
Generative AI does carry real risks.
Confidential data leakage.
Personal information exposure.
False or misleading outputs.
Copying AI answers without verification.
Skill decay.
Overdependence.
These concerns are not wrong.
But jumping from those concerns to:
“Generative AI is banned.”
is a very different move.
That is not risk management.
It is a refusal to design rules.
It is like saying:
Fire is dangerous, so employees must not stand in the kitchen.
Knives are dangerous, so employees must not cook.
However, please meet customer requirements.
Please make the food delicious.
Please serve it on time.
Also, the company needs challenge and innovation.
That is incoherent.
If fire is dangerous, you teach people how to handle fire.
If knives are dangerous, you teach people how to hold and store them.
If food poisoning is a concern, you set hygiene rules, temperature controls, and procedures.
If fire accidents are a risk, you install ventilation, fire checks, and extinguishers.
You do not ban the kitchen and then demand better cooking.
Generative AI should be treated the same way.
The Risks Are Real. A Blanket Ban Is Still Too Crude.
AI risks are real.
Japan’s IPA lists AI security issues such as data theft and leakage, training data tampering, personal information and trade secret leakage, misinformation, and disinformation. It also notes that trustworthy AI use requires consideration of performance, explainability, compliance, and ethics.
Japan’s Digital Agency has also published material on identifying risks and necessary countermeasures for appropriate use of text-generative AI.
So the point is not:
“AI is safe, so use it freely.”
The point is:
“The existence of risk does not automatically justify a total ban.”
Cars can cause accidents.
We do not ban cars.
We create licenses, traffic rules, speed limits, inspections, insurance, seatbelts, and drunk-driving laws.
Cooking involves fire, knives, burns, and food poisoning.
We do not ban cooking.
We create safety procedures, hygiene rules, training, ventilation, and checklists.
Generative AI needs the same kind of risk-based design.
What Companies Need Is Classification, Not Prohibition
AI use should be divided by information sensitivity and use case risk.
For example:
| Category | Examples | Policy |
|---|---|---|
| Prohibited input | Personal data, customer data, unpublished HR data, contracts, drawings, product secrets, trade secrets | Do not input |
| High risk | External documents, legal documents, customer responses, HR or legal decisions | Approval and human review required |
| Conditional use | Draft manuals, meeting note cleanup, training material outlines, internal rewriting | Anonymize and review |
| Low risk | General proofreading, polite email rewriting, Excel function explanation, checklist generation | Generally allowed |
| Recommended environment | Enterprise AI tools, local LLMs, training-data opt-out, access control, logs | Build and maintain |
This is governance.
Japan’s Ministry of Economy, Trade and Industry publishes AI Business Guidelines with checklists and worksheets. That direction is not “ban AI because it is scary.” It is “turn AI governance into practical operations.”
The global direction is not prohibition.
It is rule design, education, checklists, and operational control.
The “Skill Decay” Argument Needs to Be Separated
The concern that AI may reduce human ability is understandable.
But we need to separate which skills are being protected and which skills are becoming more important.
Some skills may become less important:
- Writing every polite email from scratch
- Memorizing Excel functions
- Building the first draft of a manual by pure effort
- Spending 30 minutes rewording a sentence
- Producing clean business text from a blank page every time
Other skills become more important:
- Knowing what information must not be entered
- Recognizing sensitive or confidential data
- Checking whether AI output is wrong
- Adapting output to actual workplace rules
- Describing purpose, constraints, and conditions clearly
- Keeping final responsibility with humans
- Using AI to standardize, teach, and checklist work
Protecting old skills by refusing to develop new ones is backward.
It is like saying:
Calculators are banned because mental arithmetic may decline.
Cameras are banned because they may steal the soul.
Cars are banned because walking is healthier.
Cooking is banned because fire is dangerous.
Tools make some skills less central.
They also make other skills more important.
In the age of calculators, the key skill is not only mental arithmetic.
It is building the formula, checking the result, and understanding what the number means.
In the age of AI, the key skill is not writing everything manually.
It is using AI safely, questioning its output, and adapting it to real work.
If Employees Are Already Asking Basic Excel and PC Questions, Banning AI Is Especially Self-Defeating
If a workplace is full of questions like:
How do I use Excel?
What should I do on the PC?
How should I write this email?
How should I organize this manual?
How should I fix this sentence?
then generative AI is not just a toy.
It can be a training assistant.
AI should not replace final judgment.
But it is very useful for first drafts, rewording, decomposing procedures, creating checklists, explaining Excel functions, and structuring meeting notes.
For workplaces where PC skills and writing skills vary widely, AI can reduce dependence on individual teachers.
It can help:
- Rewrite manuals for beginners
- Turn procedures into checklists
- Make email drafts more polite
- Suggest Excel formulas
- Clean meeting notes into minutes
- Turn improvement activity into fill-in-the-blank worksheets
These can be done without entering confidential information.
Banning even these use cases means the same basic questions keep being thrown at human coworkers.
Teaching workload stays high.
Standardization does not improve.
Knowledge remains dependent on individuals.
Then the company says:
We need challenge.
We cannot stay as we are.
But the tools needed for challenge have been sealed away.
Blanket Bans Can Create Shadow AI
There is another problem.
A blanket ban may look safe, but it can actually increase risk.
People who know AI is useful may simply use personal AI accounts in secret.
Microsoft and LinkedIn’s 2024 Work Trend Index reported that 75% of knowledge workers were already using AI at work, and 78% of AI users were bringing their own AI tools to work. It also reported that 79% of leaders saw AI adoption as necessary to remain competitive, while 60% worried their organization lacked a vision and plan for AI adoption.
This matters.
If a company does not create rules, employees do not necessarily stop using AI.
They may use it unofficially.
The pattern becomes:
Officially banned
Employees still need help
Personal AI tools are used secretly
The company cannot see actual usage
There are no input rules, training, or logs
Real data leakage risk increases
That is not safety.
That is shadow AI.
A ban does not guarantee non-use.
It only makes usage invisible.
The World Is Moving Toward AI-Based Work Design
The outside world is already redesigning work around AI.
McKinsey’s 2025 global AI survey reported that 78% of respondents said their organizations use AI in at least one business function, and 71% said their organizations regularly use generative AI in at least one business function.
Microsoft’s 2025 Work Trend Index reported that 82% of global leaders said this is a pivotal year to rethink key aspects of strategy and operations, and 81% expected agents to be moderately or extensively integrated into their company’s AI strategy in the next 12 to 18 months.
The question has shifted from:
“Should we use AI?”
to:
“How do we use AI safely?”
“How do we redesign work around AI?”
“Which tasks should be standardized with AI?”
“Where must humans retain judgment and responsibility?”
A company that stops at “AI is banned” risks being left behind.
This is especially contradictory if the company slogan is “challenge.”
Challenge does not mean worshiping every new technology.
But it also does not mean sealing away new tools without learning how to use them.
A serious policy would say:
Do not input confidential, personal, customer, contractual, or unpublished information.
Low-risk uses such as proofreading, email rewriting, general Excel support, manual outlines, and checklist creation are allowed within approved environments and review rules.
AI output must be reviewed by a human.
External documents and judgment-heavy work require approval.
That balances safety and challenge.
Conclusion: Do Not Ban Fire. Teach Heat Control.
Generative AI risks should not be ignored.
Data leakage, misinformation, and overdependence are real risks.
That is why rules are needed.
But a blanket ban is not a rule.
It is the contradiction of saying:
Fire is dangerous, so stay out of the kitchen.
But meet customer demands.
Cook well.
Serve on time.
Be innovative.
Do not stay as you are.
If fire is dangerous, teach heat control.
Teach knife handling.
Start with simple recipes.
Separate raw meat and vegetables.
Standardize fire checks.
Install extinguishers.
Create checklists.
Generative AI should be treated the same way.
Ban dangerous uses.
Permit safe uses.
Define review responsibility.
Provide approved environments.
Start with low-risk work.
Train people.
Create checklists.
That is real risk management.
A blanket ban is not governance.
It is simply sealing away what the organization does not know how to manage.
In Mendoi-chan language, it is:
Dark magic that says “challenge,” while sealing away the tools needed to challenge.
The defense is simple:
Do not ask only whether AI should be used.
Ask what must not be entered,
what may be used,
who must review it,
and which environment is approved.
Do not ban fire.
Teach heat control.
References
- IPA, “AI Security”
https://www.ipa.go.jp/digital/ai/security/index.html - Digital Agency, “Guidebook on Risk Mitigation for Text Generative AI Use”
https://www.digital.go.jp/resources/generalitve-ai-guidebook - Ministry of Economy, Trade and Industry, “AI Guidelines for Business”
https://www.meti.go.jp/shingikai/mono_info_service/ai_shakai_jisso/20260331_report.html - Microsoft Japan / LinkedIn, “2024 Work Trend Index on the State of AI at Work”
https://news.microsoft.com/ja-jp/2024/05/09/240509-microsoft-and-linkedin-release-the-2024-work-trend-index-on-the-state-of-ai-at-work/ - McKinsey & Company, “The State of AI: Global Survey”
https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-how-organizations-are-rewiring-to-capture-value - Microsoft, “2025 Work Trend Index: The year the Frontier Firm is born”
https://www.microsoft.com/en-us/worklab/work-trend-index/2025-the-year-the-frontier-firm-is-born
