Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Kamala Harris
Caution! Due to inherent human biases, it may seem that reports on articles aligning with our views are crafted by opponents. Conversely, reports about articles that contradict our beliefs might seem to be authored by allies. However, such perceptions are likely to be incorrect. These impressions can be caused by the fact that in both scenarios, articles are subjected to critical evaluation. This report is the product of an AI model that is significantly less biased than human analyses and has been explicitly instructed to strictly maintain 100% neutrality.
Nevertheless, HonestyMeter is in the experimental stage and is continuously improving through user feedback. If the report seems inaccurate, we encourage you to submit feedback , helping us enhance the accuracy and reliability of HonestyMeter and contributing to media transparency.
Using language that unfairly favors one side over another.
The phrase 'Biden’s seismic July 21 decision' uses dramatic language that could influence readers' perception of the event.
Replace 'seismic' with 'significant' to maintain a neutral tone.
Using an authority figure's opinion to support an argument without presenting evidence.
The article quotes Trump campaign’s top pollster Tony Fabrizio without providing evidence to support his claims about Harris' 'honeymoon phase.'
Include data or examples to support Tony Fabrizio's claims.
Using specific sources that support one side while ignoring others that may provide a different perspective.
The article primarily cites Bloomberg News/Morning Consult polls, which may not represent the full spectrum of available data.
Include data from other reputable polling sources to provide a more balanced view.
- This is an EXPERIMENTAL DEMO version that is not intended to be used for any other purpose than to showcase the technology's potential. We are in the process of developing more sophisticated algorithms to significantly enhance the reliability and consistency of evaluations. Nevertheless, even in its current state, HonestyMeter frequently offers valuable insights that are challenging for humans to detect.