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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Against ACA Subsidies
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.
Using charged or dismissive language to sway opinion.
The article refers to the Affordable Care Act as the '(Un)Affordable Care Act' and describes the subsidies as a 'financial crime of generational warfare.'
Use neutral language when referring to the Affordable Care Act.
Avoid using terms like 'financial crime' and instead present factual information about the subsidies.
Using emotional language to persuade the audience.
The article describes the subsidies as 'bankrolling Bill and Shelly’s 30-year retirement' and 'driving young Americans further into debt.'
Provide data and statistics to support claims about the impact of subsidies.
Avoid emotionally charged language and focus on objective analysis.
Selecting data that supports a specific viewpoint while ignoring data that contradicts it.
The article highlights the income of Bill and Shelly but does not provide a comprehensive view of how subsidies affect different income groups.
Include a broader range of examples to show how subsidies impact various income levels.
Present data on both the benefits and drawbacks of the subsidies.
- 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.