Media Manipulation and Bias Detection
Auto-Improving with AI and User Feedback
HonestyMeter - AI powered bias detection
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Vivek Ramaswamy
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 sensational language to provoke interest at the expense of accuracy.
The article uses phrases like 'became the butt of a joke' and 'provocative headline' which may sensationalize the situation.
Use neutral language to describe the situation without implying a value judgment.
Language that is partial or prejudiced towards particular views or groups.
Terms like 'disgusted by this tired ‘joke’' and 'disgusting,' 'despicable,' and 'racist' reflect a strong bias in the language used to describe the reactions to the Babylon Bee's article.
Present reactions from both sides in a balanced manner without using charged language.
Attributing a statement or action to someone without proper substantiation.
The article suggests that Ramaswamy is positioning himself as Trump's adviser and potentially aiming for the No. 2 spot in the White House without providing clear evidence for these claims.
Clarify the source of the claim or present it as an opinion rather than a fact.
- 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.