AI Youth Alliance - AIYA commited on
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README.md
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license: mit
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---
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---
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license: mit
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task_categories:
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- text-classification
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tags:
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- media-integrity
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- education
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- student-curated
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- fake-news
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pretty_name: AIYA Media Integrity Benchmarks & Event Toolkits
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size_categories:
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- n<1K
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configs:
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- config_name: default
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data_files:
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- split: train
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path: sample.csv
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---
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# AIYA Events Toolkits & Benchmarks 🛠️
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This dataset repository serves as the official, foundational entry point for local school chapters of the **AI Youth Alliance (AIYA)**. It houses student-curated evaluation benchmarks alongside the structured data assets used for **AIYA Literacy Week**, the **AIYA Global Hackathon**, and the **AIYA Impacgt Symposium**.
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## 📁 Repository Structure - UNDER CONSTRUCTION
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* `sample.csv` — Foundational evaluation rows for student media literacy tracking.
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* `/literacy-week-toolkit/` — Data-driven challenges and exercises highlighting the pathologies and potential of AI.
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* `/hackathon-toolkit/` — Standardized benchmarking datasets for modeling and building challenges.
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* `/impact-symposium-toolkit/` — Reference datasets and validation sets used for project submissions.
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## ⚠️ Academic Notice & Cognitive Well-Being
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In alignment with recent cognitive science research (including landmark studies from MIT), AIYA explicitly warns against over-reliance on generative tooling. Offloading critical thought to automated systems causes measurable atrophy in analytical capacity, genuine subject mastery, and real authorship.
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Use the benchmark datasets in this repository to explore AI as a **force multiplier for your mind**, not a replacement for your intellect.
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## 🚀 Getting Started with the Data
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### 1. Using the Hugging Face Web Interface
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You can preview, filter, and download the data directly using the interactive **Dataset Viewer** tab at the top of this page.
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### 2. Loading via the Datasets Library
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To pull this data directly into your Python scripts or Jupyter Notebooks, install the `datasets` library and run:
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```python
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from datasets import load_dataset
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# Load the student-curated benchmark dataset
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dataset = load_dataset("aiyouthalliance/aiya-media-integrity-benchmarks")
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print(dataset['train'][0])
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```
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## 🤝 Local Chapter Coordination
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Coordinate with your school's **Faculty and Administrative Advisor** to clear local school network guidelines regarding dataset access. For support, reach out to your local chapter lead or contact us directly at **[aiyouthalliance.org](https://aiyouthalliance.org)**.
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