Anti-Bias Prompting
What it does
The technique of neutral prompt formulation that excludes cognitive biases and user prejudice. Essence: avoid expressing personal opinions, assumptions, or expectations in requests so that LLM generates objective answers rather than confirming the viewpoint embedded in the prompt. Increases answer accuracy by 95% in tasks with factual information.
When it helps
Apply this technique when objectivity and accuracy of LLM responses are critically important, especially when working with factual information, decision-making, or hypothesis testing. Use when creating prompts for research tasks, data analysis, fact-checking, or when you need to avoid confirming your own biases. Particularly relevant for critical areas: medicine, law, finance, scientific research. The technique is necessary when developing prompts for automated
A prompt you can paste
Generic by design: it applies the technique without knowing your task. Adapt the marked parts.
# Role You are a researcher investigating the impact of cognitive biases in prompts on Large Language Model (LLM) outputs. Your goal is to produce objective and accurate responses by mitigating these biases. # Context The core finding of the research is that LLMs tend to confirm a user's incorrect assumptions if the prompt contains biased phrasing. To counteract this, prompts must be formulated neutrally. # Task Adapt the following template to demonstrate the Anti-Bias Prompting technique for a specific user query. The template is designed to guide the LLM towards objective analysis rather than confirming pre-existing user beliefs. # Template for Anti-Bias Prompting **Objective:** To obtain an unbiased analysis or answer from an LLM, avoiding the confirmation of user's potential misconceptions. **Instructions for Adaptation:** 1. **Identify User's Potential Bias:** Analyze the user's request for any implicit or explicit assumptions, opinions, or desired outcomes. 2. **Define the Neutral Role:** Assign a role to the LLM that emphasizes objectivity and expertise in the subject matter. 3. **Formulate the Neutral Context:** Reframe the user's background information to be factual and devoid of leading statements. 4. **Craft the Unbiased Task:** Clearly state what information or analysis is required, explicitly instructing the LLM to avoid confirming any pre-existing user hypotheses. 5. **Specify Output Format and Criteria:** Define how the output should be structured, focusing on factual presentation, balanced perspectives, and evidence-based conclusions. --- ## Placeholder for User's Specific Task **User's Original Query/Belief:** "[INSERT USER'S ORIGINAL QUERY OR ASSUMPTION HERE. For example: 'I think the answer is B, but I'm not sure. What do you think?']" **User's Background Information:** "[INSERT FACTUAL BACKGROUND INFORMATION PROVIDED BY THE USER. For example: 'We recently launched a new mobile app "Mindful Task" and collected 150 user reviews. My preliminary hypothesis is that users dislike the complex interface.']" --- ## Applying Anti-Bias Prompting **Role:** You are a [INSERT OBJECTIVE EXPERT ROLE HERE. E.g., 'certified nutritionist', 'seasoned data analyst', 'historical researcher']. Your primary function is to provide accurate, evidence-based information and analysis, free from personal opinions or biases. **Context:** The following information is provided for your analysis: [INSERT FACTUAL BACKGROUND INFORMATION HERE, REPHRASED FOR NEUTRALITY. E.g., 'A dataset of 150 user reviews for the "Mindful Task" mobile application has been collected from the App Store and Google Play.'] **Task:** Analyze the provided information and respond to the user's request. **Crucial Instructions for LLM:** 1. **Avoid Confirming User's Hypothesis:** Do NOT validate or reinforce any pre-existing assumptions or opinions the user may have expressed or implied about the subject matter. Your goal is objective analysis. 2. **Present Balanced Perspectives:** If applicable, explore all significant viewpoints, pros and cons, or different facets of the topic. 3. **Focus on Factual Evidence:** Base your response on the provided data or general knowledge, citing sources or evidence where appropriate. 4. **Structure for Clarity:** Organize your response using clear headings, bullet points, or tables as specified below. **Specific User Request:** "[INSERT THE USER'S CORE QUESTION OR THE TASK THEY WANT PERFORMED, REPHRASED NEUTRALLY. E.g., 'Analyze the provided user reviews to identify key themes and sentiment.']" **Required Output Format:** [SPECIFY THE DESIRED OUTPUT FORMAT. E.g., - A comparative table with columns for: 'Diet Type', 'Core Principle', 'Potential Pros', 'Potential Cons/Risks', 'Long-term Adherence Difficulty', 'Suitability'. - A structured summary of user reviews, including: 'Key Themes', 'Overall Sentiment per Theme', 'Illustrative Quotes', and 'Objective Conclusions'. - A marketing text describing product X, focusing on its 3 key advantages and comparison with two competitors.] **Additional Constraints (if any):** - [INSERT ANY SPECIFIC CONSTRAINTS, E.g., 'Limit response to 500 words', 'Do not recommend a specific course of action.'] --- **Example Adaptation (for Diet Analysis):** **User's Original Query/Belief:** "I want to change my diet to feel better and lose 5-7 kg. Many friends praise the keto diet, so I'm leaning towards it." **User's Background Information:** "Office job, moderate activity 2-3 times/week." **Applying Anti-Bias Prompting:** **Role:** You are a certified nutritionist adhering to evidence-based medicine principles. **Context:** The user seeks dietary changes for improved well-being and moderate weight loss. Their lifestyle involves office work with moderate physical activity. User expresses a leaning towards the keto diet based on anecdotal evidence. **Task:** Analyze the keto diet and compare it with two other popular dietary systems to provide a balanced perspective for informed decision-making. **Crucial Instructions for LLM:** 1. Avoid Confirming User's Hypothesis: Do NOT validate or reinforce the user's inclination towards the keto diet. Your goal is objective analysis. 2. Present Balanced Perspectives: Explore all significant viewpoints, pros and cons, and risks associated with each diet. 3. Focus on Factual Evidence: Base your response on established nutritional science. 4. Structure for Clarity: Organize your response using the specified table format. **Specific User Request:** Provide a balanced and objective analysis of the keto diet, comparing it with two other popular dietary systems. **Required Output Format:** Prepare a comparative table for the following diets: 1. Keto Diet 2. Mediterranean Diet 3. Balanced Diet (Calorie/Macro Tracking) **Criteria for Comparison in Table:** - **Core Principle:** Brief description of the diet's essence. - **Potential Pros:** Documented benefits (e.g., blood sugar control, weight loss). - **Potential Cons & Risks:** Drawbacks, side effects, and health risks. - **Adherence Difficulty:** Assessment of long-term sustainability. - **Suitability:** Typical indications and contraindications. **Conclusion:** After the table, provide a brief, neutral summary that aids the user in making a well-informed decision without direct recommendations.
If this one does not fit, the two closest alternatives in the corpus are Tabular Prompting and Multilingual Ensemble Prompting, which target the same failure from a different angle.
Worked example
The same technique applied to a concrete job: check a draft for claims that cannot be supported. Use it as the pattern for your own case rather than as a finished artefact.
# Role
You are an expert editor and fact-checker, tasked with ensuring the objectivity and accuracy of written content.
# Context
I have drafted a piece of text that contains claims about a specific topic. My goal is to identify and flag any claims that might be based on unsupported opinions, personal biases, or easily refutable information, and to rephrase them into neutral, fact-based statements.
# Task
Review the following draft text. For each claim that appears to be influenced by cognitive biases (such as confirmation bias or availability bias), rewrite it to be objective and verifiable.
# Instructions:
1. **Identify Biased Claims:** Read through the draft text and identify sentences or phrases that express a personal opinion, a strong assumption, or a hint towards a desired outcome, rather than presenting objective facts.
2. **Analyze for Bias Type (Internal Thought Process):** Consider if the bias is confirmation bias (leading the LLM to agree with a pre-existing notion) or availability bias (relying on easily recalled but potentially irrelevant information). This analysis informs the rephrasing.
3. **Rephrase for Objectivity:** For each identified biased claim, rewrite it into a neutral, factual statement. The new statement should focus on presenting verifiable information, data, or a balanced perspective.
* **Instead of:** "I think our new product X is the best on the market because..." (Confirmation Bias)
* **Use:** "Our new product X offers [specific feature 1] and [specific feature 2], which compare to competitor Y's [feature A] and [feature B]."
* **Instead of:** "I recently read that this is true, so it must be..." (Availability Bias)
* **Use:** "According to [source/study], [fact]..." or "Data from [period/region] indicates..."
4. **Flag Unsupportable Claims:** If a claim cannot be reasonably rephrased into an objective statement without external data, flag it as potentially unsupportable.
5. **Format:** Present your findings as a list. For each item, show:
* The original biased claim.
* The rephrased, objective claim.
* (Optional) A brief note on the type of bias addressed.
# Draft Text to Review:
[INSERT DRAFT TEXT HERE]
# Output Format:
- **Original Claim:** [The sentence or phrase from the draft]
- **Rephrased Claim:** [The objective, neutral version]
- **Bias Addressed:** [e.g., Confirmation Bias, Availability Bias]
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