Media Manipulation and Bias Detection
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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.
Use of exciting or shocking stories at the expense of accuracy, to provoke public interest or excitement.
The focus on Bianca Censori's revealing outfit and the description of it as 'like looking at an X-ray' is sensationalist.
Provide a more neutral description of the event and avoid focusing on sensational aspects of the attire.
Language that is biased or contains value judgments.
Terms like 'knows how to turn heads' and 'left little to the imagination' are value-laden and not neutral.
Use neutral language to describe the individuals and the situation without implying judgment.
Attempting to induce an emotional response in place of a valid or compelling argument.
The article attempts to evoke curiosity and possibly disapproval by highlighting the reactions of 'parents with children' to Bianca's outfit.
Stick to factual reporting without attempting to evoke an emotional response from the reader.
- 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.