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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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.
Making predictions or claims without sufficient evidence.
The article predicts a 1-2 win for Cote d'Ivoire and suggests betting tips such as 'Cote d'Ivoire to win' and 'Over 2.5 goals' without providing concrete evidence or analysis to support these claims.
Provide statistical analysis or expert opinions to support the predictions.
Clearly state that the predictions are speculative and based on available data.
Using emotional appeal to influence the reader's perception.
The article uses phrases like 'eke out a narrow win' which can evoke an emotional response rather than presenting an objective analysis.
Use neutral language to describe the potential outcomes of the match.
Focus on factual data and avoid emotionally charged language.
- 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.