Media Manipulation and Bias Detection
Auto-Improving with AI and User Feedback
- Objectivity Score
- Objectivity Score
- Objectivity Score
- Objectivity Score
- Objectivity Score
- Objectivity Score
Media Manipulation and Bias Detection
Auto-Improving with AI and User Feedback
HonestyMeter - AI powered bias detection
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Prosecution
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 language that leans towards one side of the argument.
Phrases like 'finally did right by Felishia Caraway-Mudd' and 'pedaling poison' suggest a bias towards the prosecution's perspective.
Use neutral language such as 'admitted responsibility' instead of 'finally did right by'.
Replace 'pedaling poison' with 'distributing drugs' to maintain neutrality.
Using emotional language to sway the reader's opinion.
The statement 'allowing her family to move forward without having to relive this tragedy' appeals to the reader's emotions.
Focus on the factual outcome of the plea without emotional language, such as 'The guilty plea concludes the legal proceedings.'
- 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.