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!
None (sides are presented roughly equally in the limited visible text)
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 a sympathetic or value-laden phrase without full context can subtly influence readers’ perception of a party’s intentions.
The line: "Construction firm owner says it was dealing with the IRD ‘in good faith’ but managed to sell to a new Canadian owner prior to the application." Issues: - The phrase "in good faith" is the company’s characterization of its own conduct and is presented without any IRD response or independent verification. - The contrast with "but managed to sell to a new Canadian owner" could imply either clever avoidance or legitimate business continuity, depending on reader interpretation, but no additional facts are provided to clarify.
Attribute and qualify the claim clearly, and add balancing context if available. For example: "The construction firm’s owner said the company had been dealing with IRD ‘in good faith’. IRD has not publicly commented on that characterisation."
Add factual detail instead of relying on a value-laden phrase. For example: "The owner said the company had been in regular contact with IRD about its tax arrears and had proposed a repayment plan."
Clarify the timing and legal relevance of the sale to the Canadian owner, and avoid implying intent without evidence. For example: "The company was sold to a Canadian owner before IRD filed its liquidation application. It is not yet clear what impact, if any, the sale will have on the liquidation proceedings."
Leaving out important context that would help readers fully understand the situation can bias interpretation, even if the statements that are included are accurate.
The article states: "NZ Build Group will head to the High Court facing liquidation proceedings owing $6.16 million in tax debt. Inland Revenue filed for the liquidation ... following a statutory demand for an outstanding $5.01m..." but does not, in the visible portion, explain: - Over what period the tax debt accumulated. - Whether there were previous repayment arrangements or defaults. - IRD’s position or comments on the company’s claim of dealing "in good faith". Given the paywall, this may be covered later in the full article, but in the visible text alone, readers get a partial picture.
Add brief neutral context about the history of the tax debt, if known. For example: "The tax debt relates to unpaid GST and PAYE obligations accumulated between [years], according to court documents."
Include IRD’s response or note its absence. For example: "IRD declined to comment while proceedings are before the court" or "IRD said it had made multiple attempts to secure payment before filing for liquidation."
Clarify the nature of the sale to the Canadian owner (asset sale vs share sale, timing relative to the debt, and any regulatory oversight) to avoid speculative inferences.
- 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.