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
CLICK ANY SECTION TO GIVE FEEDBACK, IMPROVE THE REPORT, SHAPE A FAIRER WORLD!
Jaguar Land Rover
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.
Exaggerating or sensationalizing events to attract attention.
The headline 'Russian ‘terror attack’ to cost car giant $4bn' uses sensational language by labeling the cyber attack as a 'terror attack', which may not be accurate.
Use more neutral language in the headline, such as 'Cyber attack linked to Russia costs car giant $4bn'.
Making claims without sufficient evidence.
The article states that 'Russia is suspected of being behind the cyber attack' without providing concrete evidence or sources to substantiate this claim.
Provide evidence or credible sources to support the claim of Russian involvement.
Use language that indicates uncertainty, such as 'allegedly' or 'reportedly', if evidence is not available.
Using language that unfairly favors one side over another.
The article uses phrases like 'crippling electronic attack' and 'brought the company to its knees', which may imply bias against the alleged attackers.
Use more neutral language to describe the impact of the cyber attack, such as 'significant electronic attack' or 'caused major disruptions'.
- 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.