生成AIパスポート · LESSON 4
Chapter 4: Generative AI Risk Prevention, AI Ethics and Governance29%(当サイト設定) · 9 topics
Learn the mindset for generative AI users, typical risks, shadow AI, verifying output, protecting personal information and secrets, copyright, AI ethics, governance, and laws and international rules.
4.1Basic mindset for generative AI users
Concept
Generative AI is a useful tool, but final responsibility for output lies with the person who used it. The basic stance is: don't trust output blindly—check it; consider whether information may be entered; follow company rules; and indicate AI use when needed.
How it works / steps
- Before using, check company guidelines and which tools may be used
- Check that the information you enter is not confidential or personal
- Check facts, figures and sources in output before using it
Workplace example
Draft a customer proposal with generative AI, and the person in charge checks figures and product specs against materials before submitting.
Common confusions and exam tips
- “The AI said so” is no excuse for responsibility
- Don't bypass company rules for convenience
- Design work allowing for the effort of checking
Mini quiz
Q1. Which is the most appropriate basic stance when using generative AI at work?
- When AI is wrong, the service provider bears all responsibility
- AI is an assistant; people bear final responsibility for whether to adopt output and for the results
- Make AI-assisted work efficient by skipping human checks
- AI output is based on vast data, so it always takes priority over human judgment
Show answer and explanation
Answer: B AI is an assistant; people bear final responsibility for whether to adopt output and for the results
Generative AI can produce plausible errors. People verify output and make decisions responsibly.
Q2. Which best describes the difference between search engines and generative AI?
- Both work the same way and differ only in display format
- Generative AI always searches the internet, so its evidence is more reliable
- Search engines point to existing sources while generative AI writes new text, so checking evidence matters more
- Search results are accurate, so only generative AI output needs checking
Show answer and explanation
Answer: C Search engines point to existing sources while generative AI writes new text, so checking evidence matters more
Generative AI answers often show no sources. Check important information against primary sources. [Other options] Generative AI does not always search. Search sources can be wrong too. The mechanisms differ.
Reference links
4.2Typical risks of generative AI
Concept
Typical risks include hallucination (misinformation), information leaks (outflow of entered secrets), infringement of rights such as copyright, biased or discriminatory output, misuse (fraud, deepfakes, cyberattacks), prompt injection and over-reliance.
How it works / steps
- Identify which risks are largest for each task
- Decide countermeasures according to risk (checks, input limits, tool choice)
- Set reporting procedures for when problems occur
Workplace example
When using generative AI to evaluate application documents, the bias risk is high, so AI only summarizes and people evaluate.
Common confusions and exam tips
- Hallucinations are “plausible,” so they are hard to notice
- Risk cannot be reduced to zero, so manage it by impact
- Watch for new kinds of risk too (agent misoperation, etc.)
Mini quiz
Q1. Fearing leaks, a company banned generative AI company-wide. Which best describes the "risk of not using AI"?
- Internal data becomes more likely to leak
- Missing chances for efficiency and competitiveness, while shadow AI may grow
- Security updates for existing systems stop
- Not using AI is itself a legal violation
Show answer and explanation
Answer: B Missing chances for efficiency and competitiveness, while shadow AI may grow
Banning AI uniformly out of fear can lead to shadow AI or lost competitiveness. Managing risk while using it matters. [Other options] Not using AI does not raise leak risk. It is not illegal. It is unrelated to system updates.
Q2. Which is the most appropriate countermeasure against hallucination?
- Have it answer with Temperature at maximum
- Ask the same question many times and decide the right answer by majority vote
- Check the facts, figures and sources in the output against primary sources
- Have it answer at length, since longer output is more accurate
Show answer and explanation
Answer: C Check the facts, figures and sources in the output against primary sources
Majority votes and length do not guarantee accuracy. Checking against primary sources and prompting it to show its basis are the basics.
Reference links
4.3Shadow AI and corporate compliance
Concept
Shadow AI is employees using generative AI services at work that the company doesn't know about or allow. It risks information leaks from entering secrets and violations of contracts and rules. The countermeasure is not just banning but providing approved tools that can be used safely, and spreading correct use through rules and training.
How it works / steps
- Understand actual usage
- Provide safe approved tools and usage rules
- Through training, publicize what may be entered and what is prohibited
Workplace example
It turns out employees were summarizing customer information with personal free accounts, so the company introduces an approved business tool and bans business use of personal accounts.
Common confusions and exam tips
- A total ban can actually increase hidden use (shadow AI)
- Free and business versions often handle input data differently
- Compliance includes following internal rules and contracts, not just laws
Mini quiz
Q1. Which best describes shadow AI?
- AI running automatically at night, out of people's sight
- Embedding invisible watermarks in AI output
- Employees using AI tools the company has not approved for work
- A way of hiding model weights from outsiders to prevent leaks
Show answer and explanation
Answer: C Employees using AI tools the company has not approved for work
Shadow AI creates risks such as information leaks and no usage records (lack of traceability).
Q2. Which best describes why shadow AI arises?
- Because once AI tools are approved, usage is recorded and they automatically become unusable
- Because approved tools disable all generative AI functions for security reasons
- Because the law requires using AI at work and employees must provide their own tools
- Because with no approved tool, a hard-to-use one, or a heavy request process, employees use tools close at hand
Show answer and explanation
Answer: D Because with no approved tool, a hard-to-use one, or a heavy request process, employees use tools close at hand
Bans alone hardly prevent it. Countermeasures are providing approved tools, clear rules and simpler requests.
Reference links
4.4Evaluating and verifying AI output
Concept
Verify AI output for factual accuracy (check against primary sources), presence of basis and sources, calculations, bias or inappropriate wording, and rights issues. The more important the document, the stricter the check; back it up with multiple sources (fact-checking).
How it works / steps
- Check facts, figures and proper nouns in the output
- When sources are shown, actually open them and check
- When used for important decisions, back them up with experts or multiple sources
Workplace example
Checking a law article number shown by generative AI in Japan's e-Gov legal search reveals it was wrong, so it is corrected.
Common confusions and exam tips
- Sources or URLs shown by AI may not exist at all
- Confident-sounding wording isn't necessarily correct
- Just asking the same AI again is not verification
Mini quiz
Q1. Which is the most appropriate concrete example of shadow AI?
- Summarizing internal emails with an AI summary browser extension the company has not allowed
- Summarizing an already-published press release with a company-approved generative AI tool
- Using an approved translation tool in line with internal guidelines
- Trying a tool IT is evaluating in a test environment, following procedures
Show answer and explanation
Answer: A Summarizing internal emails with an AI summary browser extension the company has not allowed
With browser extensions or personal-account tools, the company cannot know how entered information is handled.
Q2. If false content made by generative AI that lowers a specific person's social standing is published, what is most likely to be the issue?
- Unauthorized access
- Defamation
- Design right infringement
- Patent infringement
Show answer and explanation
Answer: B Defamation
Even with generative AI output, the person who published it can be held responsible. Check facts in statements about people.
Reference links
4.5Personal information, privacy and confidentiality
Concept
Entering personal information into generative AI involves the purpose-of-use scope and the handling of third-party provision and outsourcing under Japan's Act on the Protection of Personal Information. Company trade secrets and information under NDAs with partners can also leak through input. Choose services whose settings or contracts keep input out of training, and enter only needed information, anonymized or masked.
How it works / steps
- Judge whether the information you plan to enter is personal or confidential
- Use services whose settings or contracts keep data out of training
- Replace names and the like with pseudonyms or symbols before entering
Workplace example
Before summarizing customer complaint emails, replace names, phone numbers and addresses with placeholders like [Customer A].
Common confusions and exam tips
- Even with “not used for training” settings, the service may store data for some period
- Check NDA terms for partner information
- Handle sensitive personal information (medical history, etc.) with special care
Mini quiz
Q1. Which of the following is "personal information" under Japan's Act on the Protection of Personal Information?
- A record with only an employee number that identifies the person when matched with the staff list
- Visitor counts processed into statistics that cannot identify anyone
- A corporate client's name, address and main phone number
- A deceased customer's name and purchase history
Show answer and explanation
Answer: A A record with only an employee number that identifies the person when matched with the staff list
Even published information counts as personal information, as does anything containing individual identification codes. [Other options] Personal information concerns living individuals and includes data identifiable by easy matching with other data. Data on the deceased, corporations or statistics does not qualify.
Q2. Which is the most appropriate principle regarding the purpose of use of personal information?
- Specify the purpose of use as far as possible and handle it within that scope
- Only the internal staff in charge need to know the purpose of use
- Acquired personal information can be used freely for any purpose
- The purpose limitation no longer applies when entering it into generative AI
Show answer and explanation
Answer: A Specify the purpose of use as far as possible and handle it within that scope
When entering personal information into generative AI, also check that it is within the purpose of use.
Reference links
4.6Copyright, intellectual property and rights in generated content
Concept
Article 30-4 of Japan's Copyright Act allows using works for information analysis such as AI training under certain conditions, but not when it unreasonably harms the copyright holder's interests. At the generation and use stage, similarity to and reliance on an existing work can be infringement. Content AI generates autonomously is unlikely to be recognized as a work, while human creative contribution can make it one. Watch also for trademarks, designs, portrait rights and the right of publicity.
How it works / steps
- Check that output doesn't resemble existing works, logos or characters
- Avoid prompts that imitate a specific artist's style or name works
- Check the service's terms for rights in output and commercial use conditions
Workplace example
An ad illustration came out resembling a famous character, so it is dropped in favor of a version reworked by a designer.
Common confusions and exam tips
- Article 30-4 covers the “training” stage; it doesn't make using output free
- Both similarity and reliance are factors in judging infringement
- Prompts alone are unlikely to count as creative contribution
Mini quiz
Q1. Which combination of factors is most important in judging whether copyright infringement occurred?
- Publicity and registrability
- Novelty and inventive step
- Similarity and reliance
- Usefulness and non-public status
Show answer and explanation
Answer: C Similarity and reliance
It can be infringement when it resembles the creative expression of an existing work (similarity) and is based on it (reliance). The same applies to AI output.
Q2. Which is the most appropriate precaution when entering someone else's work into generative AI?
- A work entered into generative AI becomes free for the user to use, even if the output resembles it
- A work entered into generative AI is treated as a published work under the service's terms
- A work entered into generative AI is considered out of copyright once used for training
- Even if the input itself is no problem, if the output resembles that work and you use it, it can be infringement
Show answer and explanation
Answer: D Even if the input itself is no problem, if the output resembles that work and you use it, it can be infringement
Entering an existing work to generate something similar and then publishing or selling it makes similarity and reliance easier to establish.
Reference links
4.7AI ethics and the AI Guidelines for Business
Concept
AI ethics is the thinking that AI should be human-centric and used fairly, safely and transparently. Japan's AI Guidelines for Business (Ministry of Internal Affairs and Communications and Ministry of Economy, Trade and Industry) give AI developers, providers and users common principles such as human-centricity, safety, fairness, privacy protection, ensuring security, transparency and accountability. They are non-binding soft law.
How it works / steps
- Confirm your role (developer, provider or user)
- Review how you use AI at work against the common principles
- Bring the guidelines' thinking into internal rules
Workplace example
As a “user” of AI at work, the company refers to the guidelines to set rules for checking output and explaining AI use to customers.
Common confusions and exam tips
- The AI Guidelines for Business are soft law, not a law
- Users are also expected to use AI responsibly
- The guidelines are revised, so check the latest version
Mini quiz
Q1. Which is the most appropriate item included in the common guiding principles of the AI Guidelines for Business?
- Human-centricity, safety, fairness, privacy protection, ensuring security, transparency, accountability
- Total ban on use, domestic storage of training data, public release of models, caps on usage fees
- Development speed, high performance, low cost, market share growth, promoting overseas expansion
- Licensing of development, notification of use, fines for violations, business registration, regular state audits
Show answer and explanation
Answer: A Human-centricity, safety, fairness, privacy protection, ensuring security, transparency, accountability
The AI Guidelines for Business set common principles that also include education and literacy, ensuring fair competition, and innovation.
Q2. Which best describes ELSI?
- An indicator for estimating the economic effects of new technology before introduction (Economic Impact Index)
- A scheme for certifying AI training data quality from a legal perspective (Legal Data Certification)
- The ethical, legal and social issues raised by new technology (Ethical, Legal and Social Issues)
- A test procedure set by international bodies to evaluate AI safety (Evaluation and Safety Index)
Show answer and explanation
Answer: C The ethical, legal and social issues raised by new technology (Ethical, Legal and Social Issues)
In developing and using AI, considering impact from the ELSI perspective, not just the technical side, is required.
Reference links
4.8AI governance and internal guidelines
Concept
AI governance is the set of mechanisms for an organization to use AI while managing its risks. Internal guidelines set the tools that may be used, what may be entered and what is prohibited, responsibility for checking output, conditions for using output, and a contact for reporting problems. Assign responsible departments and owners, and carry out training and regular reviews.
How it works / steps
- Decide who is responsible for AI use and a help desk
- Create internal guidelines and publicize and train everyone on them
- Track usage and incidents and review regularly
Workplace example
IT and Legal jointly create internal generative AI guidelines and revise them every quarter in light of new tools and risks.
Common confusions and exam tips
- Guidelines must be embedded through training and operation, not just written
- Technology changes fast, so fixed rules quickly become outdated
- Showing recommended uses, not just prohibitions, helps adoption
Mini quiz
Q1. Which best describes AI governance?
- Banning AI use in the organization uniformly with no exceptions to avoid risk
- Government directly running AI service companies and centrally controlling AI use
- Rules only developers must follow on how to write programs and evaluate models
- An organization setting up and operating policies, structures and rules to manage risks of AI use and gain its benefits
Show answer and explanation
Answer: D An organization setting up and operating policies, structures and rules to manage risks of AI use and gain its benefits
AI governance emphasizes agile governance, which revises rules as circumstances change.
Q2. A company that made internal generative AI rules wants to adopt agile governance. Which approach fits best?
- Leave rule details to teams and set no company-wide policy
- Write very detailed rules and handle change through exception procedures
- Repeat design, operation, evaluation and review of the rules as conditions change
- Have legal revise all rules together once a year
Show answer and explanation
Answer: C Repeat design, operation, evaluation and review of the rules as conditions change
Generative AI changes quickly, so rules should not be fixed but revised continuously. [Other options] Yearly revision cannot keep pace. Without company policy there is no control. Detailed rules plus exceptions do not form an evaluate-and-review cycle.
Reference links
4.9AI laws, international rules and AI security
Concept
In Japan, the Act on Promotion of Research, Development and Utilization of AI-Related Technologies (AI Promotion Act) was enacted in 2025, setting a basic framework that balances promoting innovation with addressing risks. The EU AI Act takes a risk-based approach regulating according to risk: it bans AI with unacceptable risk and imposes strict obligations on high-risk AI. Internationally there are frameworks such as the G7 Hiroshima AI Process, and security issues such as military use of AI and misinformation are also discussed.
How it works / steps
- Check regulations in countries and regions relevant to your business
- If providing AI in the EU, check the AI Act's risk categories
- Regularly check trends in domestic and international rules
Workplace example
A company providing AI that supports hiring decisions to EU customers checks whether it falls into the AI Act's high-risk category and plans the needed steps.
Common confusions and exam tips
- Japan's AI Promotion Act differs in nature from comprehensive regulation with penalties like the EU AI Act
- The EU AI Act can apply to businesses outside the EU
- A risk-based approach does not “regulate all AI the same way”
Mini quiz
Q1. Which is the most appropriate statement about Japan's AI Promotion Act?
- A law banning business use of generative AI except uses the state permits
- A law giving AI legal personhood, liable with its developers for damage
- A law promoting AI R&D and use, setting roles of the state, businesses and citizens, an AI Basic Plan and an AI Strategy HQ
- A law licensing AI development, with heavy fines for unlicensed work
Show answer and explanation
Answer: C A law promoting AI R&D and use, setting roles of the state, businesses and citizens, an AI Basic Plan and an AI Strategy HQ
The AI Promotion Act is a promotion law aiming to balance innovation with risk response, operated together with existing laws and guidelines.
Q2. Which is the most appropriate description of the EU AI Act's approach?
- A risk-based approach that classifies AI systems by level of risk and imposes obligations according to risk
- Regulation favoring the region, allowing only companies based in the EU to develop and provide AI
- Regulation imposing identical obligations uniformly on all AI systems regardless of risk
- A policy of no legal regulation, leaving things to voluntary efforts so as not to hinder AI progress
Show answer and explanation
Answer: A A risk-based approach that classifies AI systems by level of risk and imposes obligations according to risk
AI with unacceptable risk is banned, and high-risk AI faces strict obligations.
Reference links
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