Challenges/Provn/General/AI Driven Review of Hobby Showcases

AI Driven Review of Hobby Showcases

Design and prototype a hobby showcase screening system

Algorithm

Prompt Engineering

Estimated Time:

1 hour

Difficulty:Intermediate

Status:Not started

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Create a free account to upload your work. Your progress saves as a draft until you submit.

What You'll Be Doing

A growing online hobby community wants to use AI tools to help volunteer moderators highlight the most inspiring and educational hobby project showcases for their weekly featured collection. As someone interested in AI/ML, you'll learn to work alongside AI tools to build simple but effective systems that assist (not replace) human curation, ensuring diverse voices and projects get recognized fairly.

Challenge #1: AI-Powered Curation System (20 minutes)

Deliverable:

AI Collaboration Documentation - Your conversation with AI about building fair showcase selection
Curation Framework - Simple system developed with AI assistance for identifying valuable community content
Video (<10min) - Demonstration of your solution and thought process

Challenge #2: AI-Powered Fairness Problem Solving (10 minutes)

Fairness Challenge: A hobby showcase features excellent technique and creativity, but the creator is soft-spoken in their explanation video and doesn't use technical terminology. Meanwhile, another showcase has flashy presentation but less educational value. Community moderators are unsure how to fairly evaluate these different presentation styles without bias.

Work with AI to develop a fair evaluation approach that considers:

Different communication styles and comfort levels
Educational value vs. presentation polish
Accessibility for learners with different backgrounds
Cultural and linguistic diversity in the community

Show Your Work: Document your conversation with AI and explain:

Which AI suggestions were most helpful for addressing bias and why
What you learned about fairness in AI-assisted curation systems
How you would explain your approach to community volunteers without technical backgrounds
What questions you still have about AI-assisted content curation

Deliverables

AI Collaboration Log - Your conversation with AI and key learnings about fair showcase selection
Fair Evaluation Framework - Bias-aware approach developed with AI assistance
Community Guidelines - Simple explanation for volunteer moderators on implementing fair curation
Video (< 10min) - Explain your approach to non-technical community members, what you learned about AI fairness, and remaining questions about AI-assisted community curation

Bonus Points:

Creative use of AI to identify overlooked forms of bias in content curation
Thoughtful consideration of diverse community member needs and communication styles
Evidence of understanding how AI tools can both help and harm community inclusivity
Innovative approaches to balancing different types of valuable contributions

Challenge Guidelines

Document your complete AI conversation process, including prompts and responses
Include your final framework with clear explanations for community volunteers
Record your walkthrough video explaining technical concepts in accessible language
Show specific examples of how AI helped you understand fairness and bias issues
Reflect on remaining questions and areas for further learning about responsible AI use

What You'll Accomplish

• AI Prompt Engineering: How to ask AI effective questions about fairness and bias

• Algorithmic Fairness: Understanding how AI systems can inadvertently discriminate

• Community Values: Balancing different types of valuable contributions (technical skill vs. teaching ability vs. creativity)

• Inclusive Design: Creating systems that work for diverse communication styles and backgrounds

• Human-AI Collaboration: Using AI as a tool while maintaining human judgment and values

How Your Work Will Be Scored

1. AI Learning Effectiveness (40%) - How well you used AI to learn about fairness, bias, and inclusive system design2. Problem-Solving Curiosity (25%) - Quality of questions asked about community needs and fairness challenges3. Bias Awareness (20%) - Understanding of fairness issues in AI curation systems, developed through AI guidance4. Communication of Learning (15%) - Clear explanation of your AI-assisted learning process to non-technical community members

What to Submit

AI Collaboration Log - Your conversation with AI and key learnings about fair showcase selection
Fair Evaluation Framework - Bias-aware approach developed with AI assistance
Community Guidelines - Simple explanation for volunteer moderators on implementing fair curation

• Video (<10min) - Explain your approach to non-technical community members, what you learned about AI fairness, and remaining questions about AI-assisted community curation

AI Collaboration Log

Document · 2 pages maxRequired

Format: .pdf, .doc, .docx, .rtf, .txt, .md

PDF or Document. Your conversation with AI and key learnings about fair showcase selection.

Fair Evaluation Framework

Document · 1 page maxRequired

Format: .pdf, .doc, .docx, .rtf, .txt, .md

PDF or Document. Bias-aware approach developed with AI assistance for fair showcase evaluation.

Community Guidelines

Document · 1 page maxRequired

Format: .pdf, .doc, .docx, .rtf, .txt, .md

PDF or Document. Simple explanation for volunteer moderators on implementing fair curation.

Video Recording

Video · 10 min maxRequired

Format: .mp4, .mov, .webm

MP4 format. Explain your approach to non-technical community members, what you learned about AI fairness, and remaining questions about AI-assisted community curation.

Start this challenge

Create a free account to upload your work. Your progress saves as a draft until you submit.

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