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
The article uses sensational language to describe the situation.
Ariana Grande and Ethan Slater’s relationship has been marred with controversy since whispers of their romance began – and the singer’s fans are now well and truly rinsing her new beau over his recent snap.
Suggested Changes
Use neutral language to describe the situation.
Biased language
The article uses biased language to express opinions about Ethan Slater's costume.
It’s fair to say fans were a little creeped out by the picture, which we really hope (and suspect) has something to do with the play…
Use neutral language to express opinions.
Cherry-picking data
The article selectively includes negative comments from fans without providing a balanced view.
While some came to Ethan’s defense and pointed out, ‘He’s in character for a role in a play…’ this didn’t stop people being weirded out by the image.
Include a balanced view of both positive and negative comments from fans.
- 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.