AI သည် ပညာရေးကို အကောင်းဘက်ရော၊ အဆိုးဘက်ပါ နည်းလမ်းများဖြင့် ပြောင်းလဲနေပြီဖြစ်ပြီး၊ ဤအရှိန်အဟုန်မှာ ပိုမိုမြန်ဆန်လာနေပါသည်။ ဤပြိုင်ပွဲမှာ ပညာရှင်များ၊ သုတေသီများ၊ နည်းပညာရှင်များ၊ ကျောင်းသားများ နှင့် အခြားသူများအားလုံးကို ၂၀၂၈ ခုနှစ်အကုန် တွင် ပညာရေးအပေါ် AI ၏ သက်ရောက်မှုနှင့်ပတ်သက်၍ တိကျခိုင်မာပြီး ခုခံချေပနိုင်သည့် ခန့်မှန်းခြင်းဖြင့် ပါဝင်နိုင်သော အခွင့်အလမ်းတစ်ခုဖြစ်ပါသည်။
ကျောင်းများ၊ တက္ကသိုလ်များ၊ ဆရာ/ဆရာမများ နှင့် ကျောင်းသားများသည် ဤပြောင်းလဲနေသော အခြေအနေကို ကိုင်တွယ်ဖြေရှင်းရန် အကောင်းဆုံး ကြိုးစားနေကြသော်လည်း၊ အမှန်တကယ် မည်သည့်အရာများ ဖြစ်လာမည်ကို သိရှိရန်အတွက် ပိုမိုကောင်းမွန်သော စုပေါင်းဉာဏ်ရည် (collective intelligence) လိုအပ်နေပါသည်။ သတင်းအချက်အလက် ပြည့်စုံသူ ရာပေါင်းများစွာထံမှ ခန့်မှန်းချက်များကို စုစည်းခြင်းဖြင့်၊ ဖြစ်နိုင်ခြေရှိသော အနာဂတ်ပုံရိပ်ကို ပိုမိုပြည့်စုံစွာ ဖန်တီးနိုင်မည်ဖြစ်သည်။
ခန့်မှန်းချက်များကို ကျွမ်းကျင်သော ဒိုင်အဖွဲ့မှ ပြန်လည်သုံးသပ်မည်ဖြစ်ပြီး၊ အကောင်းဆုံး ခန့်မှန်းချက်များကို လူသိရှင်ကြားမျှဝေကာ ဆုကြေးငွေများ ရရှိမည်ဖြစ်သည်။
လျှောက်ထားရန် နောက်ဆုံးရက်: အင်္ဂါနေ့၊ ဒီဇင်ဘာလ ၁၆ ရက်၊ ၂၃:၅၉ GMT (ဂရင်းနစ်စံတော်ချိန်)
လျှောက်ထားသင့်သူများ
ပညာရေး၏ အနာဂတ်အပေါ် စဉ်းစားတွေးခေါ်သော ရှုထောင့်မှ ကြည့်မြင်တတ်သူတိုင်း လျှောက်ထားနိုင်ပါတယ်။ AI ကျွမ်းကျင်သူဖြစ်ရန် မလိုအပ်ပါ၊ ပညာရေးလော,က၏ အနာဂတ်ကို ဂရုတစိုက် တွေးခေါ်သူဖြစ်ဖို့သာ လိုပါသည်။
အထူးအားဖြင့် အောက်ပါပုဂ္ဂိုလ်များကို ပါဝင်လျှောက်ထားရန် တိုက်တွန်းပါသည်။
- နည်းပညာရှင်များ၊ ပညာရေးနည်းပညာ (edtech) လုပ်ငန်းရှင်များ နှင့် ဆော့ဖ်ဝဲလ်ရေးဆွဲသူများ
- အတန်းပိုင်ဆရာ/ဆရာမများ နှင့် ကျောင်းအုပ်များ/ကျောင်းခေါင်းဆောင်များ
- တက္ကသိုလ်ကထိကများ နှင့် ပညာရှင်များ (academics)
- ကျောင်းသားများ နှင့် မကြာသေးမီက ဘွဲ့ရရှိသူများ
- ဘာသာရပ်ပေါင်းစုံမှ သုတေသီများ
- မူဝါဒချမှတ်သူများ နှင့် အုပ်ချုပ်ရေးမှူးများ
- လုပ်ငန်းခွင် လိုအပ်ချက်များကို စဉ်းစားနေသော စက်မှုလုပ်ငန်းပညာရှင်များ
Forecasting Tracks
1. Teaching Profession
Scenario: By the end of 2028, what percentage of non-interpersonal teacher activities (lesson planning, grading, and parent communication) will teachers routinely delegate to AI systems?
Note: We are excluding activities that require social, emotional, or live human-to-human interaction support—such as classroom management, building relationships, or providing pastoral care.
Your prediction: Please start with a quantitative answer to the above question.
Rationale: What would have to be true technologically, institutionally, and politically for your prediction to be correct?
Implications: What are some of the follow-on consequences of your prediction? For instance:
- Would this lead to teacher substitution (job losses) or augmentation (more time for relational aspects of teaching, improved efficacy across the teacher workforce)?
- Would teacher prestige and compensation increase or decrease?
- How would the parent and student agency, relative to school authority, change?
2. Cognitive Development & Mathematics Education
Scenario: AI systems can already solve mathematics problems at expert human levels. By the end of 2028, will this capability contribute towards an increase or decrease in enrolment in advanced mathematics courses in high school / secondary school & sixth form, and by how much? (Current baseline: approximately 15-20% of students take calculus in the US).
Your prediction: Predict whether enrollment will increase, decrease, or stay roughly the same by the end of 2028, and by approximately what percentage. Explain your reasoning.
Rationale: What would have to be true technologically, institutionally, and politically for your prediction to be correct?
Implications: What are some of the follow-on consequences of your prediction? For instance:
- Would widespread AI assistance in mathematics improve mathematical literacy by making it more accessible or create cognitive dependencies?
- What happens to students’ problem-solving abilities and tolerance for intellectual challenge when AI can instantly solve problems many find difficult?
- What would be the implications for STEM career preparation and the development of quantitative reasoning skills?
3. Student Motivation, Personalization & Socialization
Scenario: By the end of 2028, what percentage of high school students will spend more than 2 hours per day in school learning through AI-powered, personalized and/ or gamified educational content that adapts to their individual interests and learning pace?
Your prediction: Please start with a quantitative answer to the above question.
Rationale: What would have to be true technologically, institutionally, and politically for your prediction to be correct?
Implications: What are some of the follow-on implications of your prediction? For instance:
- Is sustained engagement with highly personalized learning inherently beneficial, or does education require developing tolerance for boredom, difficulty, and learning things that don’t immediately interest you?
- How would this affect students’ capacity for self-directed learning, intrinsic motivation, and ability to collaborate with peers who have learned different things?
- What would be the implications for cognitive diversity, shared cultural knowledge, and democratic participation when students increasingly follow individualized learning paths?
4. Higher Education Assessment & Academic Integrity
Scenario: By the end of 2028, what is the likelihood (expressed as a percentage) that AI systems’ ability to complete written assessments will force a significant shift back to in-person, proctored assessment methods (such as handwritten exams, oral presentations, or live demonstrations) in higher education?
Your prediction: Please start with a quantitative answer to the above question.
Rationale: What would have to be true technologically, institutionally, and politically for your prediction to be correct?
Implications: What are some of the follow-on implications of your prediction? For instance:
- If universities DO shift to in-person assessments:
- Would this increase or decrease the quality and validity of what we’re measuring?
- How would this affect the types of skills prioritized when complex written work becomes impossible to assess authentically?
- If universities DO NOT shift to in-person assessments:
- What are the implications for the value and credibility of college degrees when AI can complete most coursework?
- What unique value would universities provide beyond social networking and credentialing functions?
5. AI Tutoring
Scenario: By the end of 2028, what is the percentage likelihood that AI tutoring platforms will be able to provide learning growth equivalent to today’s high-quality professional human tutors?
Note: We are intentionally excluding other valuable aspects of human tutoring such as college counselling, mentorship, emotional support, or social connection.
Your prediction: Please start with a quantitative answer to the above question.
Rationale: What would have to be true technologically, institutionally, and politically for your prediction to be correct?
Implications: What are some of the follow-on implications of your prediction? For instance:
- Would this democratize access to high-quality instruction, or would wealthy families find new ways to maintain educational advantages?
- What would be the implications for educational equity and social mobility?
- How would this affect the professional tutoring industry and education labour markets?
Guidance For Applicants
Making Strong Predictions: Avoid extreme predictions (0%, 100%) unless you have compelling structural arguments, and avoid hedging around 50%. Make clear, reasoned predictions that reflect your genuine assessment of likelihood.
All Perspectives Welcome: We have no preference for optimistic versus pessimistic forecasts. We also ask you to separate probability from desirability, so you can argue that a scenario can be likely yet harmful, or beneficial yet unlikely. Submissions are evaluated on clarity of reasoning and quality of argumentation.
Geographic Focus: Unless a question specifies otherwise, make predictions at the national level. You can choose any country—just declare it clearly. National-level predictions make it easier to compare submissions and ground forecasts in available data.
Each Submission Must Include:
An analytical essay
- Must be 500 to 1,000 words.
- Figures and data are not required, but may be included and do not count against the word limit.
A short audio note or video summarizing your core argument
- Must be 2 to 5 minutes in length.
- This recording will be reviewed only by the program team for quality assurance—not by judges. It will not be shared publicly without your express written consent.
