Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Kjersti Flaa
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.
Phrases like 'resorted to something unlawful' and 'just so selfish' are used to describe Reynolds's actions, which are subjective and judgmental.
Use neutral language to describe Reynolds's actions, such as 'Reynolds admitted to leaking the footage, which he had previously denied.'
Using emotional language to sway the audience's opinion.
Statements like 'could potentially have ended up in a very expensive lawsuit' and 'let the others be under suspicion' are designed to evoke a negative emotional response towards Reynolds.
Present factual information without emotional language, such as 'The leak led to an investigation by the studio.'
Giving more weight to one side of the story.
The article heavily focuses on Flaa's criticism of Reynolds without providing a balanced view or Reynolds's perspective.
Include statements or responses from Reynolds or his representatives 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.