Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Kenyan Drake
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 emotionally charged language to elicit an emotional response from the audience.
"It’s been an incredible ride," "I’ve loved the journey — the wins, the moments big and small, the comradery, the energy, all of it […] Ready to enjoy a little retirement and see where the next chapter takes me."
Replace emotionally charged language with neutral descriptions, e.g., 'Drake reflected on his career and expressed readiness for retirement.'
Making claims without providing evidence or sources.
"It felt like the right time," Drake told NFL insider Josina Anderson. "I love the game, but I don’t love the business. I’m at peace with the decision. I’m healthy and ready to start the next chapter of my life."
Provide more context or evidence for Drake's feelings about the business side of the NFL, e.g., 'Drake cited specific experiences that led to his disenchantment with the business aspects of the NFL.'
- 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.