1.Personal information: once you enter it, it leaves your hands
What you type into a conversational AI is sent to the service provider's servers and processed there. Depending on the service and your settings, conversation history may be stored, reviewed by people to improve quality or used for training. How it is handled differs from service to service, and policies change. So it is safest to decide whether to enter something based on one question: "Would it be all right if other people saw this information?"
In particular, do not enter national ID numbers, passport or driver's license numbers, bank account or card numbers, passwords and verification codes, health information, or exact addresses and contact details. This applies not only to your own information but also to that of your family, customers and coworkers. Entering other people's personal information without their consent can violate their rights, and at work it can lead to legal problems.
- Don't enter: national ID numbers, bank account and card numbers, passwords, verification codes, health information, exact addresses and contact details
- Enter in altered form: names as A and B, your company as "a manufacturer," and only as many numbers as needed
- For company material: first check which services and rules your company allows
- Check your settings: look at the service's settings and policies to see whether you can turn off conversation history and use for training
- Wrong: Write a reply to the complaint email from customer John Doe (010-1234-5678, ○○ District, Seoul).Right: Customer A complained that "the delivery was a week late." Write a polite reply that apologizes and says we will send it again by next Tuesday.You don't need the name and phone number to write the reply. Keep only the information the task really needs, and delete or replace the rest.
2.Copyright: being able to make something doesn't mean you may use it
AI creates new output from the patterns of the countless texts and images it learned from. This raises two questions. One is whether AI output is too similar to someone else's work; the other is who holds what rights to AI output. On both questions, laws and rulings differ from country to country, and debates and lawsuits are still ongoing.
So it is wise to set conservative principles you can actually follow. Avoid requests to reproduce, as if copying, the sentences of a particular work or a particular character, and requests to output song lyrics or long passages of a book word for word. When you use AI output commercially or publish it, check whether the terms of the service you use allow that purpose.
You should also know that output largely made by AI may not be protected as a work created by a person. In many countries, copyright is seen as protecting human creative expression. For important creative work, keep a record of the parts you planned and revised yourself, and consult an expert if needed.
3.Bias: skewed data becomes skewed answers
As we saw in Lesson 2, learning-based AI learns from data. If the data contains society's stereotypes or skews against particular groups, the AI learns them too. For example, when asked to describe occupations, it may portray gender or age only one way, or give less accurate answers about certain regions or languages.
Bias is hard to spot, so you need to be all the more careful. If you use AI for decisions that affect people, such as hiring, lending or evaluations, you must check separately that the results are not skewed against particular groups. In everyday life, too, "the AI said so" is no proof of fairness.
- Recognize that the result contains bias that reflects stereotypes.
- Add a condition to the prompt: "Mix gender, age and job level evenly, and don't rely on stereotypes."
- Check the new result once more against the same standard.
- A person finalizes the material, reflecting the team's actual makeup and the views of the people involved.
4.Responsibility: whoever sends it out is responsible
AI is a tool, and it is a person who decides to use the result. If a report written by AI has wrong numbers, the person who submitted the report is responsible. If text produced by AI defames someone or infringes copyright, the person who posted it can be held responsible. "The AI wrote it that way" is no excuse.
So for anything that goes out under your name, check three things: Are the facts and numbers correct (Lesson 7)? Does it infringe anyone else's rights? Could it harm or mislead the people who read it? Also judge, according to the situation, whether to disclose that you used AI. If it is something readers need to know in order to make their own judgment, disclosing it is how you keep their trust.
You also need to be on guard against the misuse of AI. Fake videos and audio that imitate a real person's voice or face, and convincing scam text messages, have become easier to make thanks to AI. If someone suddenly contacts you asking for money or personal information, always verify through a different channel, even if the voice or writing style seems familiar.
5.A checklist for before and after using AI
The checklist looks long, but once it becomes a habit it takes only a few seconds. At first, apply it only to important tasks, and once you are used to it, extend it to everyday use.
| When | What to check |
|---|---|
| Before entering | Is there any personal information, password or confidential material in it? Did you keep only the information that is really needed? |
| Before entering | Does your company or school allow this service and this use? |
| After getting the result | Did you check the facts, numbers and sources against primary sources? |
| After getting the result | Are there any stereotypes or skews about particular groups? |
| Before sending it out | Does it resemble someone else's work too closely? Do the service's terms allow this use? |
| Before sending it out | Is this a situation where you should disclose your use of AI? Are you ready to take final responsibility? |
6.Applying the checklist to a real situation
A checklist only sticks once you have actually applied it. Below is an example that follows one common, everyday situation in order: before entering, after getting the result and before sending it out. The situation is made up for illustration.
- Before entering ①: Student names and scores are personal information. Change the names to Students A–E and keep only the information the messages need (change in score, strengths, areas to improve).
- Before entering ②: Check whether the workplace allows AI for this purpose, and whether there is a specific approved service.
- After getting the result: Compare it line by line with the original table to make sure scores and comments didn't get mixed up between students. Also look for wording that belittles a particular student or leans on gender or background.
- Before sending it out: Putting the real names back in place of A–E is done by a person, outside the AI. The sender is the instructor, so read it through once more before sending.
📌 Key points
- What you enter is sent to a server — enter only information that would be all right for others to see
- Delete names, contact details and the like or change them to A and B, and for company material, check the rules on what is allowed first
- Copyright judgments differ by country and are still being debated — avoid imitation and mass copying, and check the terms of service
- Skewed data becomes biased answers — the more a decision affects people, the more you need to check it separately
- Responsibility for the result lies with the person who sends it out
🤖 Try asking AI like this
Copy a prompt and replace the [ ] parts with your own situation. Don't take the answer on trust — check it against this lesson.
When you want to practice deciding what personal information to remove
Below is a practice text made with fake names and numbers. Find all the information in it that could identify a person (names, contact details, addresses, ID numbers, unusual details combined with dates, etc.) and show it as a list. Then create a version of the text with each one replaced, like [Name1] or [Contact1]. Also tell me which items are easy to miss when I remove them from real material myself. [practice text made with fake information]
When you want to check your own work for bias
Find any stereotypes or one-sided wording in the text below about gender, age, region, occupation, disability and so on. For each one, explain why it could be a problem and suggest more neutral wording. [text]
- General principles of Korea's Personal Information Protection Act (collect only what is necessary; no use beyond the stated purpose)
- General guidance on generative AI and copyright from public bodies such as the Korea Copyright Commission
Reached every goal above? Mark the lesson complete.
Storage is unavailable in this browser, so this lasts only for this page.🤖 AI Basics
- 1What Is AI? — Rules and Learning
- 2Machine Learning Basics — Data, Model, Training, Evaluation
- 3Neural Networks, Intuitively — Small Calculations Add Up to Judgment
- 4How Do Large Language Models Produce Text?
- 5Prompt Basics — Saying Exactly What You Want
- 6Advanced Prompting — Roles, Examples, Steps, Format
- 7Hallucination and Verification — How to Doubt What Sounds Plausible
- 8Privacy, Copyright and Ethics — Using AI Responsibly
- 9Working with AI — Delegate, Check, Connect
- 10Learning Strategies for the AI Era — The Basics Shape Your Questions