LinkedIn Company Diversity Assessment – Concept

LinkedIn provides valuable employee data such as university attended, location, and skills, which enables language models like Anthropic's Claude 3 to conduct comprehensive diversity assessments by analyzing the available information and generating insights and recommendations to help organizations foster a more inclusive and innovative workforce.

Concept: The tool will help companies, partners and job seekers to identify potential diversity gaps, risks of homogeneous thinking, and opportunities to foster a more inclusive and innovative workforce.

Features:

1. Skillset Analysis: a selected LLM analyzes the distribution of employee skills (via LinkedIn API, web scraping or screenshots in case of a multi modal engine) to identify overrepresented or underrepresented areas. It highlights potential skill gaps and provides recommendations for recruiting talent with complementary skills to enhance diversity of thought.

2. Educational Background Analysis: The tool examines the educational institutions employees attended, identifying patterns of overrepresentation or lack of diversity. It suggests expanding university recruiting to a more geographically and academically diverse set of institutions.

3. Recommendation Engine: Based on the analysis, the AI generates personalized recommendations for improving diversity and inclusion. These may include suggestions for targeted recruiting, diversity training programs, inclusive leadership development, and setting diversity goals.

Methodology for assessing diversity:
1. skills: I instructed the LLM to group related skills into main categories (e.g. graphic design, product design and UX), calculate the percentage of employees in each category and analyze if the distribution indicates a concentration in certain areas.
2. geography/school: to assess the diversity of educational backgrounds, the LLM analyzed the distribution of employees across universities, identifying any overrepresentation that may contribute to a homogeneous perspective

Further Opportunities:

1. Predictive Analytics: Enhance the tool's capabilities to predict future diversity trends based on current hiring patterns and employee turnover. This can help organizations proactively address potential diversity challenges.

2. Inclusive Language Analysis: Extend the tool's features to analyze company communications, job descriptions, and policies for inclusive language. Provide suggestions for more inclusive terminology and phrasing.