HonestyMeter - AI powered bias detection
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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.
Biased language
Using language that is loaded with positive or negative connotations to influence the reader's perception.
Phrases like 'Charles is one of the best and most beloved sportscasters in the history of television' and 'We have the most amazing people, and they are the best at what they do' are examples of biased language.
Suggested Changes
Replace 'Charles is one of the best and most beloved sportscasters in the history of television' with 'Charles Barkley is a well-known sportscaster.'
Replace 'We have the most amazing people, and they are the best at what they do' with 'We have a dedicated team at TNT Sports.'
Unbalanced reporting
Giving more attention or favorable coverage to one side over others.
The article focuses heavily on Charles Barkley and TNT's perspective, with minimal mention of the NBA's side of the story.
Include more information about the NBA's decision to leave TNT and the reasons behind it.
Provide quotes or statements from NBA representatives to balance the coverage.
- 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.