Background: In the digital age, political misinformation and fake news have become rampant, influencing public opinion and potentially swaying election outcomes. The challenge is to develop an AI-powered solution to detect and mitigate the spread of fake news related to politics.

Goal: Create an innovative AI model that identifies, analyzes, and classifies political news content as legitimate or fake with high accuracy. The solution should incorporate real-time detection capabilities and be scalable across various digital platforms.

Challenge Statement: Participants are tasked with developing an AI system capable of discerning the veracity of political news stories, tweets, and other forms of digital content. The system should help social media platforms, news agencies, and end-users proactively combat the dissemination of false information.

Data Set: Participants will be provided with a dataset that includes a range of political news articles, social media posts, and fact-check verifications from reliable sources to train their models.

Expected Deliverables:

• An AI algorithm/model for detecting fake political news.

• A proof-of-concept application demonstrating the model's capabilities.

• Documentation outlining the approach, methodologies, and technologies used.

• An analysis of the model's accuracy, including testing results with precision, recall, and confusion matrix metrics.

• A presentation or pitch explaining the solution's functionality and potential impact.

Criteria for Evaluation:

• Accuracy and reliability of the fake news detection model.

• Innovation in approach and use of AI techniques (e.g., NLP, machine learning, deep learning).

• Quality of the user interface and experience for the proof-of-concept application (if applicable).

• Scalability and integration potential with existing digital platforms.

• Depth of analysis and insights gathered from the model’s performance.

• Quality and clarity of documentation and presentation.

Resources: Participants will have access to:

• A curated dataset with labeled examples of political fake and real news.

• A set of APIs for integration with social media platforms for real-time data fetching (where applicable).

• Computing resources such as cloud credits for training complex models.