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A sneak peak of our app:
Future directions:
With more time and funding, we can expand TIMIO even further
Fact-Checking Integration
Organizations like Snopes and Fact Check Insights keep databases of fact checking work. This data can be added to Torch’s knowledgebase, allowing it to identify and verify common fact-checked statements and figures.
Statistical Analysis
“There are three kinds of lies: Lies, Damned Lies, and Statistics” – Mark Twain
Torch can be trained on statistical analysis and visual representations of data to point out confounds and misleading charts. This technology can further be expanded to help analyze research papers.
Common Misconceptions
Data from Torch’s analysis and search engine trends can be combined to identify common misconceptions. TIMIO can use these to show users a list of the most popular articles with low levels of factuality.
Dynamic Icons
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Machine-Learning algorithms and LLMs can be trained to identify articles with click-bait, missing sources, primary sources, conflicts of interest and more.
Our app can then label articles in our feed with icons, so users know what they’re getting into when they tap on an extravagant headliner. Each icon would be assigned a standardized meaning on TIMIO, provided in a description users see when they tap on it.
Interested in collaborating?
This page contains early concepts, placeholders and features of the TIMIO app and its AI; they do not represent final products and may be changed before public release. By using this page, you agree not to share, save, replicate, reverse-engineer, or distribute any content on this page without permission from Timio News LLC
