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
Presenting information in a way that is intended to provoke strong emotions or interest
The article uses sensational language to describe wearing black to a wedding as breaking the 'cardinal rule' and making a 'tacit statement of disapproval'.
Suggested Changes
Present the information in a more neutral tone without exaggeration.
Biased language
Using language that favors one side or perspective over another
The article uses biased language to describe wearing black as 'cackling in the face of superstition'.
Use neutral language to describe the actions without implying negative intentions.
Omission of key information
Leaving out important details that could provide a more balanced perspective
The article fails to mention any potential reasons or motivations for wearing black to a wedding, only focusing on the negative connotations.
Include information about the individual's personal style or cultural background that may influence their choice of attire.
- 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.