Misinformation Creates Fear and Division

As of March 2018, The Department of Homeland Security has reclassified “fake news” as Opportunistic Disinformation which they define as follows: “When predatory individuals attempt to capitalize on an event or incident for financial or political incentives.”  Disinformation of this nature does its job very efficiently as shown in a recent nationwide Stanford backed study examining the public’s ability to tell fact from fiction which produced results researchers described as “dismaying”, “bleak”, and “[a] threat to democracy.” This type of information warfare and its ability to sow dissent and division in communities are part of an erosion in the nation’s social fabric and a divisive force in communities across the country and the world with far reaching social and political ramifications. This type of disinformation can be very challenging to identify and is the focus of Blacbkird.AI’s platform.

We are a group of technology entrepreneurs and data scientists with an advisory team previously at the State Department, FBI and Homeland Security. We strongly believe that disinformation is one of the greatest threats to modern society since nuclear armaments and is a problem that needs to be taken just as seriously to regulate and mediate.

About Fake News

Types of Fake News

  • Fake Article
  • Fake Reference
  • Fake Meme
  • Fake Personality
  • Fake Representative
  • Fake Social Page
  • Fake Website
  • Fake Reviews
  • Fake Portrayal
  • Half Truth

Under The Hood

Machine Learning

We use Machine Learning to identify the style misinformation is written in and classifiers that identify "fake news" types. We've analyzed millions of fake news stories to understand and classify subtle language cues in real time.


Our Patent Pending technology extracts claims from news articles, creates non-biased consensus voting systems via smart contracts and stores results on blockchain for transparent and traceable oversight.

Credibility Score

Our Credibility Score classifies narratives into grades of reliability based on A.I. and crowd-sourced results to give users a more informed way to read news and also provides connected apps and ecosystems systems with a portable score for their content.

Gauge Credibility Using A.I. & Wisdom of Crowds

Our Credibility Engine is built using our proprietary CredStack and and ClaimChain which utilizes a combination of deep learning, neural network algorithms and the wisdom of crowdsourced human expertise to score and annotate the summation of claims stored within the ClaimChain. We analyze language across dozens of Credibility Indicators including Author Reputation, Source Trustworthiness, Ad Quality, Content Quality and much more to give readers and connected systems a deep insight into the content that they are consuming or hosting.