[태그:] AI Education

  • Parenting in the AI Era: Five Abilities Children Need Before a Good University

    Parenting in the AI Era: Five Abilities Children Need Before a Good University

    When an era arrives in which AI can study on a child’s behalf, what should parents leave their children with? In an interview with Jisik Inside, Professor Jo Byeok raises this question quite directly. If parents hold only to good universities, high scores, and more private education, they may fall one step behind the changes of the AI era.

    The point is not “let’s stop studying.” Basic knowledge is still necessary. But using all of a child’s time to chase correct answers is becoming increasingly risky. In an age when AI can find correct answers quickly, the ability to ask questions, build relationships, and interpret one’s own experiences becomes more important.

    Scene from an interview with Professor Jo Byeok
    Source: Screenshot from the Jisik Inside YouTube video

    Why a good-university strategy is no longer enough

    For Korean parents, the strategy for a child’s success has long been simple: get good grades, enter a good university, and secure a stable job. Professor Jo Byeok says this strategy was quite powerful in the past, but it may not work the same way in the AI era.

    The video includes a striking analogy. In a family photograph taken about 100 years ago, three brothers are in the same place at the same time, yet they look as if they are living in completely different eras. One is holding on to old symbols of success, while another has moved toward the education of a new age. The scene asks today’s parents the same question: Is the “good path” we are holding on to really the path our children will live on?

    Scene explaining changing times and educational choices
    Source: Screenshot from the Jisik Inside YouTube video

    1. Character is not etiquette; it is a capability in the AI era

    The first message in the video is that “character is also a capability.” Here, character does not simply mean being kind and polite. Professor Jo describes character as a uniquely human quality: communication, empathy, collaboration, and resilience, all human strengths that AI has difficulty replacing.

    In the past, when knowledge and skills came first, character was sometimes treated as an extra. But as AI increasingly handles knowledge processing and the search for correct answers, the situation changes. People still have to work with people and solve ambiguous problems together. That is why character is no longer merely “nice to have,” but a core competency that helps a child endure over the long term.

    2. The ability to ask questions is deeper than prompt technique

    As the AI era begins, many people say that we need to “ask good questions.” The ability to write good prompts is certainly necessary. But the questioning ability discussed in the video is broader than that. It is closer to a child taking ownership of their own learning.

    Children naturally ask many questions. But as they grow older, the number of questions decreases. That ability is suppressed by phrases such as “Don’t think about useless things; just study,” “Hurry up and do your homework,” and “Solve this problem first.” What parents need to do is not give children more answers, but restore an atmosphere in which it is safe to ask questions.

    Scene explaining questions and uniquely human abilities
    Source: Screenshot from the Jisik Inside YouTube video

    3. Future literacy is not the ability to predict the future

    Professor Jo does not describe “future literacy” as the ability to forecast the future. Instead, he describes it as the ability to create the future one wants to live in. This distinction is important.

    AI may be better at prediction. Reading data and patterns and calculating possible scenarios are AI strengths. But deciding what future we want, what life we will choose, and what relationships we will protect is the human role. That is why parents should help children become not “children who guess the right answer,” but “children who design their own future.”

    4. Unique matters more than best

    Admissions competition keeps children comparing themselves with others. The standards become who scored higher, who entered a better school, and who got ahead faster. But in the AI era, competitiveness does not have to come only from beating others.

    Professor Jo emphasizes “unique” over “best.” When a child has their own experiences, interests, questions, failures, and stories of recovery, they can become competitive without constantly competing. A person who quickly gives the same correct answer as everyone else will be compared with AI. But a person who sees problems from their own perspective and contributes through collaboration with others is not easily replaced.

    Scene explaining future literacy and questions
    Source: Screenshot from the Jisik Inside YouTube video

    5. A parent’s first question should be about feelings, not scores

    The final advice in the video is the most practical. When a child comes home from school, parents who ask “What did you learn today?” or “What score did you get?” may be moving against the AI era. A parent who instead asks “Did you have fun at school today?” connects with the child’s emotions.

    This does not mean giving up on study. It means restoring the child’s vitality and relationships first. The parent-child relationship is not a project that disappears once college admissions are over. It is a lifelong relationship. When that relationship feels safe, children ask more questions, explore farther, and stand up again even after failure.

    Interview scene explaining empathetic questions from parents
    Source: Screenshot from the Jisik Inside YouTube video

    Five questions parents can change today

    Parenting in the AI era is not something that has to wait for sweeping institutional reform. Parents can begin by changing the questions they use at home.

    1. Instead of “What score did you get today?” ask “What was the most interesting moment today?”
    2. Instead of “Why don’t you even know that?” ask “Where did it start to feel confusing?”
    3. Instead of “That dream is unrealistic,” ask “What experience would help you get closer to that dream?”
    4. Instead of “Everyone else is doing it, so why aren’t you?” ask “What would you like to try in your own way?”
    5. Instead of “Hurry up and say the correct answer,” ask “What would happen if we changed it into a different question?”

    When the question changes, the way a child brings out their own thoughts also begins to change little by little. It may feel awkward at first. As the video says, it is not so much difficult as unfamiliar.

    Recommended reading

    FAQ

    Will school study become less important in the AI era?

    Basic knowledge is still important. However, spending all available time only on score competition is risky. On top of basic learning, children also need to develop questioning ability, AI literacy, empathy, collaboration, and resilience.

    Does the character Professor Jo talks about mean only being nice?

    No. In the video, character is closer to a uniquely human quality. It includes abilities that AI has difficulty replacing, such as communication, empathy, collaboration, and resilience.

    How can parents support a child’s questions?

    Rather than giving the correct answer immediately, first listen to what kind of thinking led to the child’s question. If you create an atmosphere that welcomes questions without judging them, children can gradually regain ownership of their own learning.

    Is it wrong to aim for a good university?

    The goal itself is not wrong. The problem is treating a good university as the only strategy for success. In the AI era, what matters more than the name of the university is what questions a child can create, how they interpret their experiences, and what contribution they can make.

    References

    Original Korean article: Parenting and education in the AI era with Jo Byeok

    Image source: Captured images used in this article are stills from the original YouTube video. They are used for review, commentary, and educational explanation, and copyright remains with the original rights holders and the channel.

  • Seoul Learn Generative AI Service Support: Free Access for 1,000 High School and Older Students

    Seoul Learn Generative AI Service Support: Free Access for 1,000 High School and Older Students

    The Seoul Metropolitan Government is launching **generative AI service support** for Seoul Learn members. The core is simple: among Seoul Learn students in high school or older, the first 1,000 selected participants can use paid generative AI services without separate subscription costs.

    Official promotional image for Seoul Learn generative AI service support
    Official promotional image for Seoul Learn generative AI service support. Source: Seoul City and Seoul Learn guide materials, as shown in The Fact article image.

    AI in learning has moved beyond simple search. It can summarize writing, guide problem solving, refine English sentences, and help with career-exploration questions. Paid AI services, however, can be a cost burden for students. This Seoul Learn program focuses on lowering that barrier.

    ## What is Seoul Learn generative AI service support?

    **Seoul Learn generative AI service support** helps students participating in Seoul Learn use the latest AI services for study. According to the promotional image, selected participants can use a total of nine paid generative AI services, including ChatGPT, Claude, Gemini, and Perplexity, for free.

    Rather than simply handing out AI accounts, it is closer to an education-support program that reduces learning gaps and broadens AI-use experience. High-school-and-older students can use AI for assignments, admissions preparation, personal-statement drafts, career exploration, and foreign-language learning.

    ## Recruitment and support period

    | Category | Details |
    |—|—|
    | Recruitment period | June 9 to June 26 |
    | Support period | June 2026 to February 2027 |
    | Number recruited | First 1,000 participants |
    | Target | Seoul Learn participating students in high school or older |
    | Application method | Online application on the Seoul Learn website or participation through the pre-diagnosis QR code |

    Because the support period runs until February 2027, selected students can use AI services for a relatively long period, not just a short-term semester trial.

    ## Who can apply?

    The target is 1,000 Seoul Learn participating students in high school or older. The important condition is Seoul Learn membership. This should be understood as an education-support program for Seoul Learn participants rather than a public event open to everyone.

    The image also says, “Check eligibility requirements and application on the Seoul Learn website.” Before applying, confirm participation eligibility, grade criteria, selection method, and pre-diagnosis conditions on the Seoul Learn site.

    ## Which AI services can be used for free?

    The guide mentions nine paid generative AI services, including ChatGPT, Claude, Gemini, and Perplexity. Each has different strengths.

    – ChatGPT: useful for writing, summarizing, organizing problem-solving approaches, and expanding ideas.
    – Claude: strong for reading long text, summarizing materials, and refining sentences.
    – Gemini: useful for information exploration and document support connected with the Google ecosystem.
    – Perplexity: a search-style AI useful for research and checking sources.

    For students, the important question is not “Which AI is best?” but “Which AI should I use for this assignment or learning situation?” For example, use explanatory AI for first understanding a concept and search-style AI for source research.

    ## How to apply

    The image describes two routes.

    – **Online application on the Seoul Learn website.** The image shows the address http://slearn.seoul.go.kr.
    – **Participation through the pre-diagnosis QR code.** The guide says final selection follows review of the AI Ollie guide and participation in a pre-competency diagnosis.

    This means the process may not be just pressing an application button. AI-use guide review and pre-diagnosis may be part of selection, so read the application page through the end.

    ## How should students use it?

    If selected, use AI as a learning coach rather than an answer generator.

    For a math problem, instead of immediately asking for the answer, ask, “What concept should I check first in this problem?” For English writing, ask, “Please make this sentence more natural and explain why you revised it that way.” That creates more learning value.

    Recommended uses include:

    – Have an unfamiliar concept explained at a level a middle-school student can understand.
    – Summarize long passages or textbook content into key sentences.
    – Receive English-sentence corrections and check the reasons.
    – Create lists of questions about careers or majors.
    – Structure presentation materials for performance assessments.
    – Check sources and evidence during research.

    Submitting AI-generated answers as-is is risky. The answer may contain errors or may not match school assignment rules. Use AI responses as drafts and references; final judgment and expression should be the student’s own.

    ## Checklist before applying

    – Am I a Seoul Learn participating student?
    – Am I included in the high-school-or-older criterion?
    – Am I applying during June 9–June 26?
    – Is a pre-diagnosis QR or AI-use guide procedure required?
    – Which AI services can I use after selection, and until when?
    – Do I know the rules for using AI in school assignments or test preparation?

    Because recruitment is described as first-come for 1,000 students, interested students should check quickly within the application period.

    ## Conclusion

    Seoul Learn generative AI service support is an opportunity for students to experience the latest AI tools without cost burden. The important point is not only free access, but the experience of properly connecting AI to learning.

    AI is not a tool that studies instead of you. But if you ask good questions, it can be a strong assistant for concept understanding, writing, research, and career exploration. Seoul Learn students in high school or older should check the recruitment period and conditions.

    ## FAQ

    ### Who is the Seoul Learn generative AI service support for?

    According to the image, it targets Seoul Learn participating students in high school or older, with 1,000 participants recruited.

    ### When is the recruitment period?

    The recruitment period is shown as June 9 to June 26.

    ### Which AI services can be used for free?

    The guide says participants can use a total of nine paid generative AI services, including ChatGPT, Claude, Gemini, and Perplexity.

    ### Where do students apply?

    The guide indicates online application on the Seoul Learn website or the pre-diagnosis QR code included in the image.

    ### Are students selected immediately after applying?

    The image says final selection follows review of the AI Ollie guide and participation in a pre-competency diagnosis. Final conditions must be checked on the Seoul Learn website.

    ## References

    Image source confirmation: [The Fact, Seoul Learn provides free ChatGPT and Claude access to 1,000 members](https://news.tf.co.kr/read/life/2330694.htm)

    – [Seoul Learn website](https://slearn.seoul.go.kr)
    – Seoul Learn generative AI service support guide image

    ## Further reading

    – [In the AI Era, What You Need to Learn Before Prompts Is Your Own Language](https://www.thinknote.co.kr/ai-korean-prompt-literacy/)
    – [Metacognition in the AI Era: How to Check Your Thinking](https://www.thinknote.co.kr/metacognition-ai-thinking-checklist/)
    – [In the AI Agent Era, How Knowledge Workers Must Change](https://www.thinknote.co.kr/ai-agent-valuable-education/)

    [Original Korean article](https://www.thinknote.co.kr/seoul-learn-generative-ai-service-2026/)

  • Knowledge Workers in the AI Agent Era: From Content Producers to Judgment Designers

    Knowledge Workers in the AI Agent Era: From Content Producers to Judgment Designers

    This English version is a fuller translation and adaptation of the original Korean article, “AI Agent 시대, 지식근로자는 어떻게 달라져야 할까,” for global readers. The article explores the changing role of knowledge workers in the AI agent era and how education should adapt to these changes. As AI becomes an integral part of our daily work, the question is no longer about how to use AI, but about how to connect AI to the work context and create valuable results.

    knowledge workers in the AI agent era
    Knowledge workers need new skills when AI agents become part of everyday work.

    Original Korean article: AI Agent 시대, 지식근로자는 어떻게 달라져야 할까

    The Competition Between AI Users and Non-Users is Already Over

    When generative AI first emerged, there was a significant difference between those who used AI and those who did not. However, the situation has changed. AI utilization has become a natural choice in many tasks, such as search, summarization, translation, report drafting, meeting minutes, and image generation. Therefore, the criteria for competition have also changed. It is no longer about whether one uses AI or not, but about how well one uses AI, what tools one uses, how well one formulates questions, how accurately one provides work context, how well one reviews and judges results, and how well one connects with the organization’s work style.

    Context is More Important than Prompts

    When discussing AI utilization, prompts often come to mind first. A good question is indeed crucial, and the more clearly one defines the desired output, role, format, and conditions, the better the result will be. However, prompts alone are not enough. For AI to produce a good answer, it needs to know the purpose of the task, the current situation of the organization, the reference materials, the applicable standards, the intended user of the output, the constraints to be considered, and the final form of the output. The same question can have different answers depending on the context. In tasks where context is crucial, such as curriculum design, policy document review, report writing, and performance management, this is especially true. Prompt engineering is the art of crafting good questions, while context engineering is the process of constructing the necessary context and materials for AI to work. In the AI agent era, an additional step is required: designing the work flow itself so that AI can understand the goal, perform the necessary procedures, and produce the output.

    AI education for knowledge workers
    AI education should connect tools with real work context and judgment.

    The Role of Knowledge Workers Shifts from Content Producers to Judgment Designers

    Knowledge workers are responsible for creating documents, finding and analyzing data, reporting, and supporting decision-making. AI can quickly process a significant part of this work. It can draft reports, summarize long documents, compare data, summarize meeting minutes, and structure ideas. However, this does not mean that the value of knowledge workers disappears. Instead, their role changes. The more important roles that knowledge workers will play in the future include defining problems, providing context, reviewing results, making judgments and choices, and improving work flows. As AI takes over routine tasks, humans must focus on higher-level problem-solving and deeper understanding.

    From Knowledge-Consuming to Knowledge-Creating Organizations

    In the AI era, organizations should not stop at simply acquiring external knowledge. They must accumulate internal experiences, standards, cases, and judgment processes. Educational organizations are no exception. Operating educational programs is not just about managing schedules or recruiting instructors. For education to be connected to actual work performance, knowledge must remain within the organization. This includes materials such as educational program design criteria, course-specific learning objectives, frequently encountered problems in the field, questions and difficulties faced by learners, post-lecture application cases, performance indicators, and areas for improvement in the next education session. AI is strong in organizing and connecting such materials, but it is up to humans to decide what materials are important, how to interpret them, and in which direction to improve.

    human judgment supervising AI agents
    Human judgment becomes more important as AI agents produce drafts and decisions.

    Education Becomes a Process of Developing Problem-Solving Capabilities

    If AI education focuses only on tool usage, it will soon reach its limits. The buttons and functions of tools are constantly changing, and models, pricing plans, and platform strengths also change. Therefore, the center of AI education should shift from explaining functions to problem-solving. Questions that should be addressed in education include what tasks AI can take over, what tasks require human judgment, what materials should be provided to AI for better results, what standards should be used to verify AI results, how to automate repetitive tasks, and what kind of knowledge database should be created at the organizational level. By dealing with these questions, education can go beyond simple “AI utilization” and help learners re-examine their work. Organizations can begin to change their way of working through education.

    Distinguishing Between Tasks that AI Can Replace and Human Value

    AI is fast and strong in reading and creating drafts, comparing and summarizing data, and generating images. However, the results produced by AI are not always valuable. Value comes from human problem awareness, purpose, interpretation, and choice. Tasks that AI can do well can be entrusted to AI, such as drafting, data summarization, table organization, repetitive investigation, sentence refinement, idea expansion, and format conversion. However, tasks that humans should focus on are different, including determining why a task is being done, judging who needs the results, reflecting field context, reviewing risks and responsibilities, selecting the final direction, and converting the results into meaningful experiences for humans.

    organization learning with AI agents
    Organizations need learning systems that turn AI use into shared capability.

    Without Organizational Change, AI Education Alone Has Limited Effect

    Even if AI education is increased, if the organization’s work style remains the same, the effect will be small. This is because individuals will find it difficult to apply what they have learned in actual work. AI utilization is not completed by individual skills alone; work, members, culture, structure, and strategy must move together. Organizations should check the following questions together: what tasks to redesign with AI, what materials to manage as common knowledge, what authority and security standards are needed for AI use, who will take responsibility for reviewing results, how to connect educational outcomes with field application, and how to expand individual experiments into organizational processes. In an era where AI becomes a team member, the organization must also move like a team. The structure of organizational learning and work must change together, beyond individual productivity improvement.

    Efficient Education and Valuable Education Must Go Together

    AI can increase the efficiency of education. Investigation time can be reduced, educational program drafts can be created quickly, and learning materials can be diversified. However, efficiency alone is not enough. The purpose of education is not just to save time but to enable better judgment, deeper understanding, and more practical problem-solving. Efficient education is about operating education quickly, while valuable education is about helping learners behave differently in their actual work. In the AI agent era, these two must be designed together: reducing repetitive tasks with AI, systematically collecting materials, reflecting the learner’s work context, designing problem-solving tasks, connecting results with field application, and accumulating knowledge that remains after education as an organizational asset.

    AI agent era education roadmap
    Education for the AI agent era should redesign work, not only teach prompts.

    Conclusion: The Role of Educators in the AI Era

    In the AI agent era, the role of educators also expands. They move from being operators of education to designers of the organization’s work style. Future education must ask new questions, not stopping at “what AI tools to teach” but going further to “how this organization can create better results with AI.” AI processes tasks quickly, but humans create meaning and judge. Education connects these two. Efficient and valuable education in the AI agent era starts with designing this connection.

    Related Reading

    Continue with these related Thinknote English articles in the Digital Transformation cluster.

    FAQ

    What is this article about?

    This article explains a digital transformation, platform, market-structure, or technology-adoption topic with Korea-specific context and global implications.

    How should I use this guide?

    Use it to understand market signals and strategic patterns. Combine it with current market data before making business or investment decisions.

    Where can I read the original Korean article?

    The original Korean article is available here: Knowledge Workers in the AI Agent Era: From Content Producers to Judgment Designers.