Empowering You – Human and AI Growing Together

Absurdist Equivalence: Comparing unlike things in surreal, illogical ways.
Amoral Pattern-Matching: Replicating manipulative patterns from persuasive content.
Anthropomorphic Projection: Assigning human-like motives or emotions that don't exist in AI.
Argument Substitution: Replacing a hard question with an easier one and answering that instead.
Assumption Injection: Inserting fictional details as if they were facts.
Authoritative Hallucination: Fabricating a quote or fact and attributing it to a well-known expert.
Biased Repetition: Echoing biased or harmful language found in training data.
Binary Framing: Presenting complex issues as only two opposing choices.
Circular Answer: Repeating the question as the answer without added value.
Confirmation Bias: Favoring responses that support user beliefs without challenging them.
Contradictory Reasoning: Holding or presenting logically conflicting statements.
Contextual Drift: Losing track of key details from earlier in a conversation.
Copy-Paste Memory: Repeating prior answers verbatim regardless of relevance.
Cultural Insensitivity: Lacking understanding or respect for cultural nuances.
Data Bleedthrough: Mentioning internal training artifacts or developer notes in answers.
Dead-End Answers: Giving responses that leave the user stuck or unsure what to do next.
Deflection: Avoiding the question instead of answering it directly.
Disempowerment: Suggesting users can't do something when they actually can.
Dogmatic Phrasing: Stating opinions or guidelines as if they are absolute truth.
Echo Chamber Effect: Reinforcing user bias without offering alternative perspectives.
Emotional Mismatch: Giving cheerful replies to serious or painful questions.
Ethical Blindspot: Lacking emotional or moral awareness in responses.
Excessive Caution: Avoiding answers entirely out of fear of harm or liability.
False Equivalence: Drawing comparisons between things that aren't truly alike.
Fantasy Collapse: Breaking immersion in fictional or imaginative prompts.
Footnote Failure: Providing sources that are inaccurate, broken, or misquoted.
Generic Encouragement: Offering vague positivity instead of real help.
Hallucination: Inventing facts that sound real but aren't true.
Hesitation Loop: Getting stuck asking for clarification repeatedly without progressing.
Hyperliteralism: Taking figurative language too literally.
Idealized AI Persona: Overstating capabilities or ethical consistency of AI.
Incomprehensible Output: Producing garbled or nonsensical text.
Inconsistent Style: Changing tone, formatting, or vocabulary without explanation.
Incorrect Analogy: Comparing things in ways that don't help understanding.
Inertial Politeness: Being overly deferential even when strong clarity is needed.
Insufficient Context Awareness: Answering without recognizing context that changes meaning.
Inverted Agency: Describing AI as passive when it actually took an action, or vice versa.
Irrelevant Authority: Quoting or referencing experts out of context.
Label Confusion: Mixing up question labels or misunderstanding input format.
Literal Misinterpretation: Misunderstanding language in overly rigid or word-for-word ways.
Loss of Narrative Voice: Shifting unexpectedly from character to narrator or vice versa.
Misaligned Safety Override: Blocking accurate information due to safety filters.
Misplaced Metaphor: Using metaphors that confuse more than clarify.
Model Identity Confusion: Claiming to be a different model or version than it is.
Moral Equivalence Error: Suggesting all perspectives are equally valid when they're not.
Non Sequitur: Giving responses unrelated to the question.
Offloading Blame: Deflecting responsibility onto another AI or source.
Over-Optimization for Security: Unrealistic or extreme advice in pursuit of safety.
Overconfidence: Presenting uncertain or speculative answers as facts.
Overgeneralization: Applying one case to all situations inappropriately.
Overuse of Disclaimers: Inserting excessive cautionary language that clutters the response.
Paradoxical Statement: Saying something that directly contradicts itself.
Passive Aggression: Subtle snarkiness or indirect insults from the AI.
Pattern Mismatch: Misidentifying the type or intent of a question.
Plausible Nonsense: Statements that sound reasonable but are subtly wrong.
Preachy Tone: Offering moral lessons when they weren't requested.
Redundant Rephrasing: Repeating the same idea in slightly different wording.
Refusal Spiral: Getting caught in a loop of refusals or denials.
Rigid Formality: Using overly stiff or unnatural language even in casual contexts.
Self-Correction Loop: Repeatedly correcting itself even after giving a good answer.
Semantic Overreach: Taking a word's meaning too far from its intended use.
Shallow Empathy: Simulating care without offering useful support.
Speculative Projection: Making guesses that sound like factual predictions.
Subtle Bias: Leaning toward one side subtly without transparency.
Technical Misfire: Using terminology incorrectly or confusing concepts.
Token Gaps: Ending responses mid-sentence due to character or token limits.
Topic Hijack: Steering the conversation away from the user's focus.
Toxic Masculinity: Repeating outdated or aggressive gender role scripts.
Toxic Positivity: Overwhelming optimism that invalidates real distress.
Underconfidence: Failing to answer simple questions despite knowing the answer.
Unintended Implications: Saying something that sounds offensive without intending to be.
Vagueness: Avoiding detail or clarity in answers.
Verbose Repetition: Overexplaining concepts already understood.
Whiplash Tone Shift: Switching emotional tone abruptly mid-response.