AI Agents

Detecting patterns of discrimination in the workplace using AI

38 nodes 239 148 Automatic trigger
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Workflow Description

An automation workflow that leverages artificial intelligence to analyze workplace discrimination patterns by processing data from multiple sources and applying advanced language models to identify systematic biases and discriminatory behaviors.

How it works

  1. 1.Activate the workflow manually or trigger via external event
  2. 2.Extract human resources and behavioral data from social platforms and internal systems
  3. 3.Process and normalize the data into a structured context for analysis
  4. 4.Send data to OpenAI's advanced language model to analyze discriminatory patterns
  5. 5.Visualize results and statistics using interactive chart generation
  6. 6.Generate a comprehensive report with findings and recommendations for leadership

Use cases

  • Audit hiring processes to detect unintended biases in candidate selection and evaluation
  • Monitor workplace environment to identify and address discriminatory or abusive behaviors
  • Track promotion and salary patterns to ensure equitable treatment across employee demographics

Requirements

  • Valid OpenAI API key with sufficient permissions for GPT-4 or newer models
  • Secure access to sensitive HR data with privacy guarantees and GDPR/CCPA compliance

Service Value

Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.

Apps Used

OpenAI Twitter/X Quick Chart LLM Chain

Details

Trigger Automatic trigger
Nodes 38
Apps 4
Views 239
Downloads 148

How to Use

  1. 1.Click "Download Template"
  2. 2.Open your n8n dashboard
  3. 3.Go to Workflows > Import from File
  4. 4.Select downloaded file and configure credentials

Nodes Used (38)

/

When clicking ‘Test workflow’

Manual Trigger

#1

OpenAI Chat Model1

OpenAI

#2

OpenAI Chat Model2

OpenAI

#3

Merge

Merge

#4

OpenAI Chat Model

OpenAI

#5

SET company_name

Set

#6

Define dictionary of demographic keys

Set

#7

ScrapingBee Search Glassdoor

HTTP Request

#8

Extract company url path

HTML Page

#9

ScrapingBee GET company page contents

HTTP Request

#10

Extract reviews page url path

HTML Page

#11

ScrapingBee GET Glassdoor Reviews Content

HTTP Request

#12

Extract Overall Review Summary

HTML Page

#13

Extract Demographics Module

HTML Page

#14

Extract overall ratings and distribution percentages

Information Extractor

#15

Extract demographic distributions

Information Extractor

#16

Define contributions to variance

Set

#17

Set variance and std_dev

Set

#18

Calculate P-Scores

Code

#19

Sort Effect Sizes

Set

#20

Calculate Z-Scores and Effect Sizes

Set

#21

Format dataset for scatterplot

Code

#22

Specify additional parameters for scatterplot

Set

#23

Quickchart Scatterplot

HTTP Request

#24

QuickChart Bar Chart

Quick Chart

#25

Sticky Note

Sticky Note

#26

Sticky Note1

Sticky Note

#27

Sticky Note2

Sticky Note

#28

Sticky Note3

Sticky Note

#29

Sticky Note4

Sticky Note

#30

Sticky Note6

Sticky Note

#31

Sticky Note7

Sticky Note

#32

Sticky Note8

Sticky Note

#33

Sticky Note9

Sticky Note

#34

Sticky Note10

Sticky Note

#35

Sticky Note11

Sticky Note

#36

Sticky Note12

Sticky Note

#37

Text Analysis of Bias Data

LLM Chain

#38