Data Essentials to Empower AI Recruitment
AI can help a recruiter find the right person for the right organization at the right time. Imagine that. Getting connected with the exact job you’re suited to at the precise moment in time that’s right for you and the employer. That’s a big promise.
This is what Ken Lazarus, CEO of Scout Exchange, a platform for marketplace recruiting, told HR Technologist when asked how smart recruitment technologies are transforming talent acquisition.
Corporations like Amazon have already experimented with their own AI recruitment tool, albeit unsuccessfully, because of the skewed data the AI engine received. This caused the engine to demonstrate bias towards female candidates. While an Amazon spokesperson has categorically stated that this tool was never used by Amazon recruiters to evaluate candidates, and this tool was eventually abandoned, this experiment forces us to consider the type and quality of data that AI-powered recruitment tools require to deliver unbiased results.
What are the 3 Data Essentials of AI-Powered Recruitment?
The more data you feed AI tools, the better the result you will get, say the experts. The quality of the data, however, is equally important. Let’s look at the three data essentials of AI-powered recruitment.
1. Data Collection
The ideal data set for AI recruitment engines is a combination of historical and current data. This data can be obtained from two sources: internal (i.e., an organization’s internal historical data) and external (current data available online on the skills/qualifications needed for a job). However, numerous data touchpoints are essential to ensure bias-free candidate screening. Relying on one set of data that, for example, focuses on candidate expressions in their video interviews to decide if they are suitable for a job may cause inherent bias without allowing them a chance to be evaluated fully or fairly.
Internal data: Historical data can be found in an organization’s HRIS system.
This includes but is not limited to:
- Employee tenure
- Employee compensation
- Periodic employee evaluations
- Employee appraisal details indicating their performance