Manual Standardization AI Development Supporting AI Utilization, RAG Implementation, and AI Proofreading Support

AI proofreading is a method that utilizes generative AI, including ChatGPT, to automatically check and correct typographical errors, inconsistencies in notation, and unify writing styles. Since proofreading tasks that were traditionally done manually can be made more efficient by leveraging AI's language processing capabilities, many companies are adopting or considering adopting this technology.

Why AI-Based Text Proofreading Is Gaining Attention Now

The number of documents created by companies is increasing year by year, and quality management is required for a wide variety of documents such as manuals, technical documents, proposals, and internal reports. However, proofreading work is time-consuming and requires specialized skills. This is why the automation of proofreading using AI is attracting attention. Large language models like ChatGPT can understand context and suggest natural text corrections, enabling not only simple typo and error checks but also overall text improvement proposals. In particular, ChatGPT’s easy-to-use interface and the ability to perform advanced proofreading tasks depending on the prompts have contributed to its rapid adoption.

Challenges Faced by Traditional Proofreading Work

Traditional proofreading work that relies on manual effort faces the following challenges.
・Personalization and Inconsistent Quality: The sharpness of corrections and the expressions adopted vary depending on the proofreader’s experience, knowledge, or even their condition on the day. For example, one person may prioritize technical accuracy while another focuses on readability, causing “perspective fluctuations” that make it difficult for the organization to maintain uniform quality in the final output.
・Increased Costs and Time: Outsourcing to external specialists can ensure high quality but requires corresponding cost increases and lead times of several days. Additionally, when internal staff handle proofreading alongside other duties, there is an “invisible opportunity loss” as creative work and strategic tasks that should be the focus get squeezed. In today’s business environment with shorter deadlines, this time lag becomes a significant bottleneck.
・Psychological and Cognitive Load and Risk of Oversights: The task of continuously searching for subtle inconsistencies in hundreds of pages of manuals or typos that are not easily noticeable requires maintaining extremely high concentration for long periods. For the human brain, this repetitive and nerve-wracking work inevitably causes “attention decline” due to fatigue. As a result, oversights occur in critical areas, always carrying the risk of missing serious errors that affect product reliability.

Reasons Why ChatGPT Has Started to Be Used for Proofreading

The reason ChatGPT has begun to be used for proofreading lies in its high language comprehension ability and flexibility. Traditional proofreading tools operate based on dictionaries or rule-based systems, making it difficult to propose corrections that understand context. On the other hand, ChatGPT can grasp the overall meaning and context of a text and suggest natural corrections. Furthermore, ChatGPT’s behavior can be customized through prompts, allowing flexible responses by providing instructions tailored to a company’s unique proofreading rules and document types.

Proofreading using ChatGPT can handle advanced text improvements that were difficult with conventional proofreading tools. Here, let's take a look at the specific types of proofreading tasks that are possible.

Checking for Typographical Errors and Inconsistencies in Notation

ChatGPT can detect obvious input errors and conversion mistakes while understanding the context. For example, if "以上の通りです" (as stated above) is mistakenly entered as "異常の通りです" (as abnormal), it will suggest an appropriate correction based on the context.
It is also proficient at checking inconsistencies in notation. It can unify long vowel notations such as "サーバー" and "サーバ", or "ユーザー" and "ユーザ", unify okurigana variations like "行う" and "行なう", and standardize numbers between half-width and full-width characters, all according to consistent criteria specified in the prompt. Especially in technical documents and manuals, unifying terminology is important. By instructing ChatGPT with commands like "Unify to ‘install’ in this document," it can standardize variations such as "install", "instool", and "setup."

Unifying Style and Tone

Unifying the overall style of a document is also a task that ChatGPT excels at. For example, you can instruct it to unify a text that mixes "desu/masu" and "da/dearu" styles into one or the other. It can also adjust the tone appropriately for business documents. You can change overly colloquial expressions to formal ones, or conversely, make overly stiff expressions easier to read. By giving instructions such as "Make the tone polite and friendly since this is a manual for customers," you can adjust the tone to suit the purpose of the document.
Balancing passive and active voice and simplifying redundant expressions can also be done as part of style unification. This helps to unify the overall impression of the document and produce a text that is stress-free for the reader.

Improvement of Readability and Comprehensibility

If a sentence is too long and difficult to understand, ChatGPT can split the sentence at appropriate points. It can also rewrite sentences where the subject and predicate are too far apart or where the modification relationships are ambiguous into clearer structures. In documents that heavily use technical terms, it is also possible to add supplementary explanations as needed. By giving instructions such as "Add a simple explanation since this term appears for the first time," you can obtain revision suggestions that help readers' understanding. Suggestions for improving visual readability, such as using bullet points and optimizing paragraph breaks, can also be made. Instructions like "Use bullet points for procedural explanations" or "Separate and organize conceptual explanations into paragraphs" support the structuring of information.

This explains the basic steps for actually performing proofreading with ChatGPT. Proper preparation and prompt design are important for effective use.

Prepare the Text for Proofreading

First, prepare the text to be proofread. Since ChatGPT has a character limit, it is more effective to split long texts by chapters or sections when inputting. A suitable amount of text to process at one time is about 2000 to 3000 characters. When preparing the text, decide whether to preserve the original document’s formatting information (such as heading levels, bullet points, tables) as much as possible or to extract only the text. If you want to maintain the structure, inputting in Markdown format makes it easier for ChatGPT to recognize headings and bullet points.
Also, organizing information such as the document’s purpose, intended audience, and usage context before proofreading allows you to give more appropriate instructions. Including this information in the prompts described later improves the accuracy of proofreading.

Basic Prompt Example for Requests to ChatGPT

To perform effective proofreading, a prompt containing clear instructions is necessary. Below is an example of a basic prompt.

Please proofread the following text.

[Proofreading Conditions]

• Correct typographical errors and omissions
• Unify notation variations (use the long vowel mark “ー”, and half-width digits)
• Unify the writing style to the polite form (“desu/masu” style)
• If a sentence is long, split it appropriately
• Add reasons for corrections

[Document Type]
Customer-oriented product manual

[Intended Audience]
Corporate personnel with intermediate-level IT knowledge

[Text to be Proofread]
(Paste the text here)

By clearly specifying the concrete criteria for proofreading, the nature of the document, and the intended audience, ChatGPT can provide more appropriate correction suggestions. If you require more detailed proofreading, the following additional instructions are also effective.

Please proofread the following text.

[Proofreading Conditions]

• Correct typographical errors and omissions
• Unify notation variations (use the long vowel mark “ー”, and half-width digits)
• Unify the writing style to the polite form (“desu/masu” style)
• If a sentence is long, split it appropriately
• Add reasons for corrections

[Additional Proofreading Items]

• Consider changing passive voice to active voice if passive constructions are used excessively
• Add a brief explanation when technical terms appear for the first time
• Use bulleted or numbered lists for procedure explanations
• Rewrite vague expressions (such as "etc." or "as appropriate") with specific terms

[Document Type]
Customer-oriented product manual

[Intended Audience]
Corporate personnel with intermediate-level IT knowledge

[Text to be Proofread]
(Paste the text here)

How to Review and Revise Output Results

Since AI suggestions are not always correct, any correction proposals presented by ChatGPT must be reviewed by a human. Especially for technical terms, proper nouns, and industry-specific expressions, ChatGPT may suggest incorrect corrections. It is important to verify that the original meaning is accurately preserved and that technical accuracy is not compromised. Rather than adopting ChatGPT's correction proposals as-is, understanding "why this correction was suggested" is also crucial. Confirming the reasons for corrections contributes to improving the quality of future document creation and proofreading. When necessary, it is also effective to ask additional questions such as "Please explain why this correction was proposed."

To achieve effective AI proofreading, prompt design is crucial. Here, we explain practical points for creating prompts that can be used in real work situations.

Clarify the Purpose of Proofreading

Clearly state the purpose of proofreading in the prompt. Whether it is "checking only for typographical errors" or "aiming to improve the overall quality of the text" will greatly affect ChatGPT's output. If the purpose is unclear, unnecessary correction suggestions may increase, or necessary points may be overlooked. For example, the desired proofreading level differs depending on whether it is a detailed check before final review or a rough improvement at the draft stage. By specifying concrete purposes and priorities, such as "This document is a formal proposal to be submitted to the client, so checking for typos and the business document format is the top priority," more appropriate proofreading can be achieved.

Specify the type of document (manual, technical document, etc.)

The appropriate proofreading standards vary depending on the type of document. The required tone and level of politeness differ for technical manuals, sales materials, internal reports, and customer proposals. For example, in technical manuals, clarity and accuracy of procedures are the highest priority. Specific instructions such as "List procedures in numbered lists, and start each step with a verb" are effective. On the other hand, sales materials require expressions that emphasize persuasiveness and readability. By specifying the document type, ChatGPT applies correction standards suitable for that category. Instructions like "Since this is an operation manual, unify the commands in the form of 'please do ~'" or "Since this is a technical specification, avoid ambiguous expressions and prioritize quantitative descriptions" enable proofreading that aligns with the document’s purpose.

The Importance of Providing Proofreading Rules and Preconditions

Many companies and organizations have their own unique notation rules and style guides. By including this information in the prompt, proofreading that complies with internal standards can be achieved. Specifically, the following types of information are clarified.

・Unified notation rules: whether to use "server" or "serva", and whether numbers are full-width or half-width
・Definition of terms: official notation of specific product names and technical terms
・Prohibited expressions: expressions and phrases to avoid using
・Style standards: polite form (desu/masu style) or plain form (da/dearu style)

If including these rules in the prompt every time is cumbersome, it is also effective to compile them into a single document as "proofreading rules" and have ChatGPT read it first. By utilizing ChatGPT's "Custom Instructions" feature or project functions, you can save the effort of entering the same rules each time.

ChatGPT is a powerful tool, but if not used properly, it will not deliver the expected results. Here, we explain the main points to keep in mind when using it in practical work.

Quality Is Unstable Without Proofreading Standards

 
ChatGPT performs proofreading based on instructions, but without clear standards, its judgments may lack consistency. When proofreading the same document at different times, it may present different correction suggestions. Unless clear proofreading rules and judgment criteria are provided, the AI will base its decisions on "common expressions" and "general writing conventions," and cannot accommodate company-specific requirements. To ensure stable quality, it is essential to document the proofreading criteria and include them in the prompt. If there are specific rules such as "correct like this in this case," ChatGPT’s output will also become consistent.

Risk of Incorrect Corrections for Technical and Industry-Specific Terms

ChatGPT operates based on general language knowledge, so there is a risk that it may incorrectly correct highly specialized terms or industry-specific expressions. For example, it might replace technical terms correctly used in technical documents with more general words. Additionally, proper nouns for companies or products, as well as abbreviations used only within certain industries, may not be recognized by ChatGPT. As a countermeasure, it is effective to include a list of terms that must not be corrected in the prompt. Clearly stating "The following terms are technical terms and should not be corrected" can prevent incorrect corrections. Furthermore, the proofreading results must always be finally reviewed by a person with specialized knowledge to verify technical accuracy.

Handling of Confidential and Proprietary Information

Information entered into ChatGPT may be used as training data for the service (depending on settings). Therefore, inputting documents containing confidential or proprietary information as-is carries a risk of information leakage. When using it for business purposes within a company, the following measures should be considered.
・Use ChatGPT Enterprise or API plans that do not use data for training
・Mask confidential information before inputting (e.g., replace product names with "Product A" and customer names with "Company X")
・Limit AI proofreading to documents that can be publicly disclosed

Documents containing especially customer information, financial data, or unpublished product information require careful judgment. It is important to establish appropriate operational rules in accordance with the information security policy.

There are cases where implementing ChatGPT does not yield the expected results. Let’s look at the main causes and countermeasures.

The quality of the documents themselves is inconsistent

As a prerequisite for AI proofreading, the original documents need to have a certain level of quality. If there are fundamental issues such as broken sentence structure, unclear relationships between subjects and predicates, or unnatural logical flow, even ChatGPT will find it difficult to make appropriate corrections. Additionally, if the quality of documents varies depending on the author, the proofreading results will also be unstable. For some documents, minor corrections may suffice, while others may require extensive rewriting, making the proofreading workload unpredictable.
As a countermeasure, it is important to establish minimum quality standards at the document creation stage. For example, develop writing guidelines such as “Keep sentences within 60 characters,” “Each paragraph should have about 3 to 5 sentences,” and “Explain technical terms at their first appearance,” and inform the authors accordingly. Also, by using ChatGPT not only for proofreading but also for writing assistance, you can create documents with a consistent quality from the start. Requesting “Please write this content in the format of a customer manual” will provide a draft that follows the guidelines.

Unestablished Notation Rules and Guidelines

In many companies, notation rules are either not documented or have become obsolete. Introducing AI proofreading without established rules results in unclear criteria for corrections, making effective proofreading unattainable. The absence of notation rules not only undermines consistency in proofreading but also causes correction decisions to rely on individuals. Consequently, even the same document may receive different corrections depending on the person in charge, leading to unstable quality.

When establishing notation rules and guidelines, it is recommended to include the following items.

・Unification of writing style (distinguishing between polite and plain forms)
・Unification of orthography and terminology (okurigana usage, notation of loanwords, half-width/full-width numbers)
・Definition and notation of technical terms
・List of prohibited and recommended expressions
・Special rules for each document type

These rules can be automatically applied by incorporating them into ChatGPT prompts. By advancing rule development and AI utilization in parallel, synergistic effects can be achieved.

Applying it to business use as an extension of personal use

Since ChatGPT is easy to use even for individuals, there are cases where it is introduced into business with the mindset of personal use. However, using it in business requires a different perspective than personal use. In personal use, it may be sufficient if only oneself understands, but business documents involve multiple stakeholders and are used over the long term. Therefore, standards for proofreading, records of corrections, and quality management processes become important. Also, while personal use allows trial and error to achieve optimal results, business use demands reproducibility and efficiency. Using different prompts each time leads to unstable quality and unpredictable work time.

The following organizational arrangements are necessary for business use.

・Creation of standardized prompt templates
・Establishment of proofreading processes and quality check systems
・Mechanisms for recording and analyzing revision histories
・Education and training for personnel in charge
・Implementation of information security measures

To elevate individual ingenuity into business processes, it is essential to establish organizational systems.

To continuously leverage AI proofreading using ChatGPT in business, it is important not only to introduce the tool but also to design the overall operation.

The Importance of Final Human Review

AI proofreading is efficient, but it cannot completely replace human proofreaders. Since ChatGPT's suggestions are based on probabilistic reasoning, they may include errors due to misunderstandings of context or lack of specialized knowledge.

The following perspectives, in particular, require human judgment.

・Verification of specialized accuracy
・Validity of the overall logical structure of the document
・Appropriateness considering the reader's level of understanding and usage context
・Consistency with brand image and corporate policies

AI proofreading should be positioned as a "first check," with the final quality assurance carried out by humans. AI handles routine checks and the extraction of a large number of candidates, allowing humans to focus on parts that require human judgment, thereby balancing overall efficiency and quality. Additionally, the process of reviewing AI's correction suggestions itself contributes to improving the skills of writers and proofreaders. Understanding "why this correction was proposed" leads to enhanced quality in future document creation.

Designing Proofreading Rules and Quality Standards

The foundation of effective AI proofreading is clear proofreading rules and quality standards. Without these, ChatGPT must rely on general writing conventions and cannot meet company-specific requirements. A step-by-step approach is effective when designing proofreading rules. First, analyze the current documents to identify common issues and correction patterns. If past proofreading records are available, use them as a reference. Next, gradually establish rules starting with the highest priority ones. Rather than trying to perfect everything at once, begin with the items that have the greatest impact. Rules should be written in a concrete and assessable manner. Instead of vague instructions like "write clearly," provide clear criteria such as "limit each sentence to 60 characters or fewer" and "add explanations in parentheses when technical terms appear for the first time." Additionally, rules should be reviewed regularly and updated to reflect issues discovered during actual use. Analyzing ChatGPT’s proofreading results can also reveal gaps or ambiguities in the rules.

Building an Operational Flow for Continuous Use

To utilize AI proofreading continuously rather than as a temporary measure, it is necessary to establish an operational flow integrated into the practical workflow. An effective operational flow includes the following elements. First, clarify the process from document creation to proofreading and approval. Define at which stage AI proofreading is performed and who is responsible for the final check. For example, a flow such as "conduct AI proofreading after the first draft is completed, have the person in charge review the corrections, and then have the supervisor give the final approval." Next, prepare standardized prompt templates. Create templates of frequently used prompts for each document type so that anyone can perform proofreading with consistent quality. This prevents reliance on individual skills and improves work efficiency. Recording and analyzing correction results is also important. By analyzing what kinds of corrections frequently occur and which rules are not being followed, improvements can be made during the writing stage and rules can be revised accordingly. Additionally, develop guidelines and manuals for those responsible to create a system where new members can smoothly participate in the operation. Sharing best practices and establishing a consultation desk for issues also stabilizes the quality of operations.

When deploying AI proofreading using ChatGPT on a full scale in business operations, it can sometimes be difficult to complete everything in-house. This explains key points to consider when exploring the use of external services.

Limitations of Introducing Tools Alone

Many companies first consider introducing proofreading tools. However, there are many cases where simply introducing a tool does not yield the expected results. This is because the quality of proofreading depends not only on the tool's performance but also heavily on how it is used and the underlying conditions. No matter how advanced the AI tool is, without appropriate prompts and proofreading rules, it cannot fully demonstrate its capabilities. Furthermore, even if a tool is introduced, without the know-how to use it effectively and a system to maintain document quality, the outcome ultimately depends on the individual skills of the person in charge. This is especially true when multiple departments use the tool or when handling a large volume of documents, making an organizational operational framework indispensable. Additionally, for specialized documents such as technical documents and manuals, general proofreading tools may not be sufficient. Because industry-specific terminology, notation rules, and document structures need to be addressed, customization and specialized knowledge are required.

The Importance of Support Including Document Quality Design

To achieve effective AI proofreading, it is important to provide comprehensive support not only in supplying tools but also in designing document quality and establishing operational frameworks. Document quality design refers to defining "what kinds of documents are created and managed according to what standards." This includes establishing notation rules, creating templates, and setting quality check items. Without these in place, AI proofreading cannot demonstrate its effectiveness. Additionally, in building the operational framework, processes such as who is responsible for what, when proofreading is conducted, and how to handle issues when they arise are designed. Especially during initial implementation, trials using actual documents and training for personnel are necessary. Furthermore, a mechanism for continuous improvement is also important. Even after starting operations, analyzing proofreading results, reviewing rules, and addressing new challenges are required. Since handling all these internally can be burdensome, support from partners with specialized expertise is effective.

Perspectives for Choosing a Service Strong in Technical Documents and Manuals

Especially in the proofreading of technical documents and manuals, expertise different from general document proofreading is required. When selecting a service, the following perspectives are important. First, whether the service understands the unique requirements of technical documents. Technical documents have specific quality demands such as how to write procedural explanations, consistency with diagrams and tables, terminology consistency, and internationalization support. Choosing a service well-versed in these areas ensures accurate support. Next is understanding the industry and product domain. Terminology and document structure vary greatly depending on the industry, such as IT, manufacturing, or healthcare. A service with knowledge of your industry can provide more appropriate rule design and proofreading. Additionally, a track record and know-how in AI utilization are important selection criteria. You should choose a service that not only provides tools but also possesses practical knowledge in prompt design, operational know-how, and methods for measuring effectiveness in AI utilization.

Human Science has over 40 years of experience in the production and translation of technical documents and manuals. In recent years, leveraging this extensive expertise, we have been offering services that support document quality management in the AI era. Specifically, we provide comprehensive support ranging from analyzing the current state of documents, formulating proofreading rules, designing proofreading processes utilizing AI tools such as ChatGPT, to assisting with actual operations. We have a wealth of experience particularly with highly specialized documents such as technical manuals and software documentation. Furthermore, our support goes beyond mere proofreading assistance to include overall document quality improvement, multilingual support with a view to global deployment, and optimization of information design, all from a comprehensive document quality management perspective.

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AI proofreading using ChatGPT is a powerful method that, when properly managed, can simultaneously improve document quality and streamline operations. However, its effectiveness is greatly influenced by the "usage" and "underlying design."

ChatGPT is convenient but not万能.

ChatGPT possesses advanced language processing capabilities and can support a wide range of proofreading tasks. It has the potential to streamline tasks that traditionally relied on manual effort, from checking typos and spelling errors to unifying writing style and improving readability. However, ChatGPT is not omnipotent. There remain areas that require human involvement, such as ensuring the accuracy of specialized knowledge, making sophisticated judgments based on context, and addressing company-specific requirements. Furthermore, even when using the same tool, the results can vary significantly depending on the quality of the prompts and the presence or absence of proofreading rules. Simply instructing ChatGPT to "proofread" will not achieve consistent, high-quality proofreading. What is important is to understand ChatGPT’s strengths and weaknesses and to use it appropriately where it fits best. The most effective approach is to delegate routine checks and large-volume processing to AI, while humans handle parts that require judgment and the final quality assurance.

Document Quality and Operational Design Determine the Success or Failure of AI Utilization

To achieve results with AI proofreading, the foundation of document quality and operational design are more important than the tool's performance.
First, without clear proofreading rules and quality standards, AI cannot make appropriate judgments. Defining "what kind of documents are created and by what standards" is a prerequisite for effective AI utilization. Next, it is necessary to design an operational workflow that incorporates AI proofreading. If the process of when, who, and how AI proofreading is conducted and how quality is verified is not clear, continuous use will be difficult. Additionally, the quality of the original document is also important. Documents with broken sentence structures or unclear logical development cannot be improved by AI proofreading alone. By combining quality control from the writing stage with AI proofreading, the overall document quality can be elevated.

Only after these foundations are established can AI tools, including ChatGPT, fully demonstrate their capabilities. When considering the introduction of AI proofreading, a comprehensive approach is necessary—not only selecting the tool but also analyzing the current state of document quality, establishing rules, and building an operational framework. Especially for highly specialized documents such as technical documents and manuals, support from partners well-versed in both industry knowledge and AI utilization will be the shortcut to success.

AI proofreading using ChatGPT is a powerful method that, when properly managed, can simultaneously improve document quality and streamline operations. However, its effectiveness is greatly influenced by the "usage" and "underlying design."