Media Manipulation and Bias Detection
Auto-Improving with AI and User Feedback
HonestyMeter - AI powered bias detection
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Nikki Haley
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.
The use of language that is not neutral and shows a preference for one side over another.
Examples of biased language in the article include phrases such as 'Trump seethed over her decision to continue her campaign', 'Trump instead sounded annoyed', 'Trump’s age, his verbal miscues', 'Trump is a loser', 'Trump’s mental competency'.
Use neutral language when describing the actions and characteristics of the individuals involved.
Attacking an opponent's character or personal traits rather than their arguments or stance.
The article contains ad hominem attacks such as 'Trump is a loser', 'Trump’s mental competency'.
Focus on the individuals' arguments and actions rather than their personal traits.
Statements or claims made without any evidence or proof.
The article contains unsubstantiated claims such as 'Trump is the only Republican in the country who Joe Biden can defeat'.
Provide evidence or sources to back up any claims made.
- 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.