Natural Language Processing (NLP) is an ever-growing interest across various organizations. NLP is a component of artificial intelligence that specifies a computer’s ability to understand human language in its spoken or written form. Organizations such as Amazon, Google, Microsoft, and other tech-savvy companies have been utilizing this technology for years, but for most companies this is a new interest they’ve started to leap into – often making decisions without doing the proper research.
Three typical reasons why an organization might want to pursue Natural Language Processing:
1. The want to say that they have NLP capability. “Google and Amazon are using it, so we should, too!”
2. Organizations have so much data that they feel that they need to use it. Most HR business engagements generate a high volume of natural language (i.e., recruitment, surveys, appraisals, interviews), but the majority is unstructured data.
3. They have a specific problem that they want to solve.
These all may seem like equally valid reasons, but the best reason is the third bullet: to identify a specific problem to solve within the organization. NLP can offer new approaches to answering key organizational questions and can add efficiencies to processes.
Examples of NLP projects:
Reducing assessor and interview time through the automation video interviews using NLP.
Classify and rank resumes according to their core skills and experience.
Identifying common problem areas within an organization through employee engagement surveys.
Reducing administrative work such as form-filling, data entry, and other routine tasks that require time, manpower, and money.
When choosing to use NLP there are risks to consider:
Legally: Be aware of any legal regulations regarding employee or candidate assessment and data protection. The stringency of these regulations can vary by location (for example, the US and Europe happen to have very strict laws). Additionally, ensuring that the NLP practices being used are valid and defensible, particularly in hiring decisions.
Ethically: It’s important to be transparent with individuals about what type of data is being collected, especially if organizations are using this data as part of hiring criteria. Organizations need to be up front with their employees and applicants on what their data is being used for.
NLP should not be thought of as a replacement for human involvement and judgment, but should be used to bolster human decisions as an initial level of filtering within the recruitment process. Computers have not evolved enough to be able to detect nuances in human language like sarcasm, ambivalence, passive-aggressiveness, or regional norms, which can give intuitive insights into a person’s personality.
As technology evolves it’s important to be well-informed as it may affect your organization. Organizations often want to keep up with the Joneses (i.e., the Amazons and Googles of the world), but just because the technology is available doesn’t necessarily mean every organization out there should use it. It's important to do your research and identify risks before jumping into any AI technology.