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.
Sensationalism
Use of exciting or shocking stories at the expense of accuracy, to provoke public interest or excitement.
The article discusses the actions of Selena Gomez and Emily Blunt in a manner that seems to exaggerate the significance of their gestures to 'thwart lipreaders.'
Suggested Changes
Provide a more neutral description of the event without implying exaggerated significance.
Appeal to emotion
Attempting to manipulate an emotional response in place of a valid or compelling argument.
The article plays on the emotions of the readers by mentioning how 'the thought of them [Blunt and Krasinski] divorcing threw corners of the internet into turmoil.'
Remove emotionally charged language and stick to factual reporting.
Unsubstantiated claims
Claims that are presented without sufficient evidence or support.
The article refers to 'lipreading experts' and internet speculations without providing concrete evidence for the claims made about the celebrities' conversations.
Clarify that the interpretations by 'lipreading experts' are speculative and not confirmed by the individuals involved.
- 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.