# Beijing – 2025‑11‑02
## What Can Seniors Offer AI?
### **Their Unique Value in the Age of Artificial Intelligence**
We often assume seniors are *passive recipients* of new technology. In fact, over a lifetime they have cultivated **emotional intelligence**, **life experience**, and **interpersonal wisdom** — precisely the areas where AI remains limited.
This raises two key questions:
- What can seniors truly contribute to AI?
- What is their **unique value** in the AI era?
Tencent Research Institute, together with Professor Zhang Weiwei’s team at Beijing University of Posts and Telecommunications, has released the annual **AI × Aging** report: *“Artificial Intelligence Standing on the Shoulders of Elders.”*
Building upon the Tencent **AI for Good Elderly Corpus**, the study gathered an additional **1,408** high‑quality texts authored by older adults, expanding to a total of **9,455 authentic, richly contextual entries** (including the original 8,047). This forms a systematic **“Wisdom of the Elders”** dataset.
The team invited **44 seniors** to serve as “emotional experts,” helping AI interpret underlying feelings, identify collective challenges, and co‑create emotional insight. This transforms seniors from passive questioners into **active collaborators** in AI development — infusing technology with warmth and depth.
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## 01. Seniors’ Unique Value
### **1.1 Emotional Knowledge**
- Elders possess **decades of refined emotional literacy** through family ties, social roles, and historical depth.
- They can **detect unspoken feelings** and respond with subtle care, cultivating trust over time.
- AI may excel at data patterns, but struggles to mimic nuanced human empathy; seniors’ experience offers a “textbook” for AI to learn the **human context**.
### **1.2 Longitudinal Life Wisdom**
- Elders’ wisdom reflects both **historical perspective** and everyday adaptability.
- They understand **elastic logic** — the balance between rational reason and lived reality.
- Their value judgments emphasize **stability, responsibility, and long‑term thinking**, supporting **sustainable AI reasoning**.
### **1.3 Unique Response Styles**
- Seniors often communicate indirectly, using hints and experience‑laden remarks.
- This preserves harmony, self‑respect, and embeds rich **contextual subtext**.
> **Key Insight:** AI responses that embody senior language patterns — respecting pace, “leaving room,” and navigating indirectly — resonate more with older users, fostering trust and engagement.
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## 02. Pathways for Seniors to Participate in AI Training
### **2.1 Data Co‑Creation**
- Tencent’s **AI for Good Elderly Text Corpus**:
- **8,047** real Q&A pairs between seniors and social workers.
- Covers health, psychology, family, and social participation.
- Additional **1,408 peer‑to‑peer answers** by seniors — rich in life wisdom and emotional warmth.
- Combined dataset: **9,455** authentic samples, forming the *Elder Wisdom Language* dataset.
---
### **2.2 Emotional Knowledge Mining**
- Semi‑structured interviews yield **three‑stage framework**:
1. **Initial Answer**
2. **Deep Probing** (“Why did you say that?”)
3. **Logical Deconstruction**
- Example:
- Surface request: Solutions for living alone.
- Hidden need: Recognition of successful child‑raising before problem‑solving.
- Researchers extract **unstated emotional drivers** and turn them into AI‑learnable structures.
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### **2.3 Co‑Creation & Feedback**
- Seniors act as **AI trainers**:
- Participate in scenario testing (e.g., medical consultations, smart device use).
- Evaluate AI tone, emotional resonance, and practicality.
- Suggestions address issues like “overly mechanical” responses or insufficient warmth.
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## 03. Analysis & Expansion of Aging‑Friendly Datasets
### **3.1 Analysis of 8,047 Q&A Pairs**
- Multi‑level scenario classification:
- 6 main categories → 16 subcategories → 37 specific items.
- Dual **Scenario + Emotion** framework to capture **blended emotions**.
- Example: Joy of video calls balanced with fear of burdening family.
- Findings:
1. Needs intertwine surface scenario with deeper emotional demands.
2. Strong correlations between tech adaptation and end‑of‑life care topics.
---
**Implications for Silver Economy:**
- Shift product design from **function-driven** to **dignity & emotion-driven**.
- Preserve autonomy and social value recognition in solutions.
---
### **3.2 Expanding & Analyzing Elders’ Responses**
- 44 seniors act as “emotion experts” reviewing 32 typical questions.
- Seniors identify hidden dilemmas, e.g.:
- Loneliness reframed as need for recognition and accompaniment.
- **Four key response styles** observed:
- Empathic Support
- Rational Guidance
- Experience Sharing
- Practical Instructions
---
**Style Evaluation Criteria:**
1. Understanding of question
2. Empathy
3. Actionable help
Findings:
- Empathic Support generally ranked highest.
- Rational Guidance preferred for highly emotional topics (e.g., end‑of‑life care).
- Seniors value **gentleness, understanding, and professionalism** across scenarios.
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## 04. Significance & Future Directions
### **4.1 Emotional Knowledge in AI Models**
- Elders’ mediation strategies and empathy enable AI to evolve **from tool to companion**.
- Enhances AI’s **emotional resonance** beyond functional competence.
### **4.2 Reshaping Senior Roles**
- Seniors shift from **service recipients** to **knowledge contributors**.
- Participation bridges the digital divide and validates self‑worth.
### **4.3 Intergenerational Co‑Creation**
- Preserves and transmits elder wisdom via AI.
- Ensures silver‑age needs are met inclusively.
- Promotes **human‑centered intelligent society**.
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## Conclusion
Older adults’ wisdom represents **emotional knowledge** highly valuable for AI. Integrating their perspectives ensures technology evolves toward **dignity‑oriented elder‑friendliness**. Being **seen, heard, and included** must become foundational to AI’s development logic.
---
## Recommended Reading
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