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.
Appeal to emotion
The article uses emotive language to engage the reader with the theory.
Phrases like 'optimistic light has started shining' and 'pack a punch' are used to evoke an emotional response from the reader.
Suggested Changes
Use neutral language to describe the theory without emotional connotations.
Confirmation bias
The author expresses personal agreement with the theory, which may lead readers to give it undue weight.
The author states, 'I’m a big fan of this theory, and I would not be shocked at all if it’s how Costner’s character exits the show.'
Present the theory without personal endorsement to maintain objectivity.
- 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.