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 sensational language to provoke interest at the expense of accuracy.
The title of the article and the description of the exchange between Daniels and Smith are sensationalized to draw in readers.
Suggested Changes
Use a more neutral title and avoid sensational language when describing the exchange.
Biased language
Language that is partial or prejudiced towards one side.
The article uses biased language when describing Smith's comments as 'jabs' and 'lazy,' which implies a negative connotation without providing a balanced view.
Describe the comments factually without using language that implies judgment.
Ad hominem attacks
Attacking the character of the person rather than addressing the substance of their argument.
The article includes the Pelicans organization's mocking of Smith's athletic skills, which is an ad hominem attack rather than a response to his criticism of Williamson.
Remove personal attacks and focus on the substance of the criticism and responses.
- 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.