AI Agents

Detecting patterns of discrimination in the workplace using AI

38 nodes 229 156 Automatic trigger
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Workflow Description

An advanced automation template that leverages artificial intelligence and data analytics to identify workplace discrimination patterns. It integrates sophisticated language models with information extraction and data visualization to deliver comprehensive reports on potential discriminatory behaviors.

How it works

  1. 1.Trigger the workflow manually and aggregate HR and communications data from organizational systems
  2. 2.Process information through advanced language model chains with OpenAI to detect discrimination patterns
  3. 3.Merge results and generate visual charts using Quick Chart tools for pattern presentation
  4. 4.Extract critical findings and structure them into a comprehensive, actionable report
  5. 5.Send alerts and reports to communication platforms or compliance documentation systems

Use cases

  • Monitor hiring and promotion practices to verify fairness and equity in selection processes
  • Analyze internal communications for biased or abusive language patterns across departments
  • Generate periodic compliance reports for HR and governance teams with pattern insights

Requirements

  • Valid OpenAI API key with appropriate language model configuration and usage permissions
  • Organized database containing employment records, communications logs, and performance evaluations
  • System access permissions to HR platforms and organizational documentation repositories

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 229
Downloads 156

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