• DATA
  • ANALYSIS
  • DECISION
  • HUMAN

How to adjust interviewer bias scores with your AI

Connect this MCP to your AI client to mathematically correct skewed interview data. It uses specific coefficients to bring raw scores back to a neutral baseline.

Ask AI about this page

Short answer

How can I use AI to fix biased interview scores?

Your AI applies mathematical coefficients to raw scores to neutralize known interviewer bias. You'll get a set of adjusted scores that better reflect true candidate performance. Here is the breakdown of how it works.

The results of the adjustment.

Where the data lands.

Once the math is applied, your raw data shifts into calibrated metrics.

DATA

Neutralized score sets

The AI uses calculate_score_adjustments to produce a new list of scores. These values account for individual interviewer tendencies.

ANALYSIS

Bias pattern identification

Your agent identifies which interviewers consistently score too high or too low. This helps you spot systemic issues in your hiring process.

DECISION

Fairer candidate rankings

The adjusted scores provide a more accurate leaderboard. You can rank candidates based on corrected data rather than raw, biased numbers.

HUMAN

Final hiring review

The AI provides the math, but you decide if the adjustments make sense. You retain full control over the final hiring decision.

The workflow

What your AI does when the scores arrive.

The AI handles the heavy lifting of the math so you don't have to build custom spreadsheets.

  1. Ingest raw data

    Your AI reads the current interview scores from your provided source. It looks for the raw numbers and the interviewer IDs.

    calculate_score_adjustments

  2. Calculate coefficients

    The agent determines the specific mathematical offset needed for each interviewer. It calculates how much to pull scores up or down to reach a neutral mean.

    calculate_score_adjustments

  3. Apply adjustments

    The AI applies those coefficients to every candidate score. This step transforms the raw data into the corrected dataset.

    calculate_score_adjustments

  4. Present results

    Your agent shows you the original scores alongside the new, adjusted scores. You can then compare the two to see the impact of the correction.

    calculate_score_adjustments

Try it

Copy these to start.

Use these prompts to trigger the adjustment process.

Starting points

These are starting points. Swap out the specific file names or sheet names for your actual data sources.

Accelerator Interview Scoring Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_nMVY83qq4qpDJYgBhxfvvwYmcqHPqbIM9auZ1Clt/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Accelerator Interview Scoring capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "accelerator-interview-scoring-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_nMVY83qq4qpDJYgBhxfvvwYmcqHPqbIM9auZ1Clt/mcp"
    }
  }
}
Copy into chat04

  • Adjust the scores in the 'Q3 Engineering' spreadsheet using the Accelerator Interview Scoring MCP.

  • Apply bias coefficients to the candidate scores found in candidate_evaluations.csv.

  • Look at the interview data in my Google Sheet and calculate the adjusted scores to neutralize interviewer bias.

  • Using the scores from the recent sales interview loop, show me the corrected rankings.

  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Start here

Connect Accelerator Interview Scoring once, then ask.

Just click the link to connect the MCP to your client. Once it's live, you can start asking your agent to run calculations immediately.

Connect Accelerator Interview Scoring to your AI

FAQ

How this task behaves.

  • 01

    Does the AI change my original interview notes?

    No. The AI only calculates new numerical scores based on the existing data. Your original notes remain untouched.

  • 02

    Can the AI automatically update my hiring software?

    No. The AI calculates the adjustments and presents them to you. You must manually move those scores into your hiring platform.

  • 03

    How does the AI know which interviewer is biased?

    It looks at the distribution of scores provided in your data. It identifies outliers who consistently deviate from the group average.

  • 04

    Will this replace my hiring managers?

    No. This is a mathematical tool to help you see the data more clearly. The final decision always stays with the human.

  • 05

    What kind of data do I need to provide?

    You need to provide a list of raw scores and the names or IDs of the interviewers who gave them.

  • More questions about Accelerator Interview Scoring? The Connector page answers them. See everything the Accelerator Interview Scoring Connector can do

Connect Accelerator Interview Scoring to Claude, Cursor, ChatGPT & more