Fake News Detection Using A.I. & Crowdsourcing

Using AI, Crowdsourcing and Blockchain to Classify Fake News and Temporal Evolution of Disinformation

Real Time News

We analyze real time data from over 35,000 news organization in 65 languages as well as social media outlets and other open source information types which are tagged by A.I. into entities such as people places and concepts for visualization and relational mapping.

A.I. Classification

Proprietary A.I. using Deep Learning and NLP helps to classify the claims that make up a piece of content and completes a tier check on the stylistic nature of different types of misinformation, satire, hate speech and more in preparation for crowd verification.

Claim Concensus

Our decentralized application sends claims (a component of an entire piece of content) to users across the world based on topical expertise match and adds up user verified claims into a consensus score for a an entire piece of content using proof of stake token incentivization methods to increase quality work and decrease impact of malicious intent.

Blockchain Verification

Our blockchain verification method is a transparent and traceable system that irrefutably stores verified claims and content created by A.I. and crowd sourced systems. Blockhain is used to help reduce bias perceptions by Blackbird.AI allowing all Claims and results to remain transparent.

Options Built With Analysts in Mind

While Blackbird.AI offer’s bleeding edge Machine Learning and options under the hood, all of them are practical and user friendly. Because Blackbird.AI was built with the the customer in mind, working with it will provide a streamlined experience and make you feel in control.

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Captivating User Experience

Award Winning Technology

Our team took first place at IBM Watson’s Hackathon in NYC. We were honored to have achieved this with so many teams competing.

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