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Challenge

AI-Powered Content Moderation System

Develop an AI system to moderate user-generated content on a platform similar to Medium, focusing on identifying AI-generated content and ensuring human curation guidelines are met. The system should analyze text for originality, factual accuracy, and adherence to community standards. It needs to balance automated flagging with the ability for human moderators to review and make final decisions, incorporating user feedback. The goal is to create a robust and scalable system that maintains a high-quality user experience while protecting against harmful or misleading content.

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Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Build an AI system for content moderation that balances automated flagging with human review and user feedback.

Delivery guide

How work is evaluated

Evaluation

The system will be evaluated based on its accuracy in detecting AI-generated content, its efficiency in processing large volumes of data, and its ability to incorporate user feedback.

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

Learning goals

What you should walk away with

  • Create a user feedback mechanism to improve model accuracy.

  • Build a scalable and efficient system for large volumes of data.

  • Develop a system for flagging potentially problematic content.

  • Design a human-in-the-loop system for review and final decisions.

  • Implement a model to detect AI-generated text.

Resources and assets

Reference links and supporting material

Dataset notes

Sample data for 1 tasks

Challenge setup

The system will be evaluated based on its accuracy in detecting AI-generated content, its efficiency in processing large volumes of data, and its ability to incorporate user feedback.

Challenge input

A list of text samples (human-written and AI-generated).

Agent execution

No agent tool is listed for this challenge.

Evaluated output

A list of predictions (human-written or AI-generated) with confidence scores.

Evaluation checks
  • No evaluation checks are configured.
Configured evaluation evidence
  • Accuracy target: 0.85
Configured runtime
  • Python execution harness

Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.

View technical recipe

Configured tools

No tool records are attached.

Evaluation contract

  • No evaluation checks are configured.

Metrics

  • Accuracy ยท Target 0.85

Workflow tasks

  1. Task 1

    Input: A list of text samples (human-written and AI-generated).

    Output: A list of predictions (human-written or AI-generated) with confidence scores.

    Execution harness: Python

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about AI-Powered Content Moderation System