AI has the ability to write resumes, review resumes, write LinkedIn profiles, review profiles, write employee reviews, or assess candidates for potential future performance. However, an analytical model is only as good as the data we feed it, and the decisions are only as good as the training data.
We know that HR data is inherently incomplete, changes year to year, and is a reflection of the manager and HR team more than the employee. Despite these known shortfalls of candidate and employee data, HR teams continue to move forward with the application of AI for more business processes associated with all aspects of recruiting, resume review, employee review, and organizational planning.
Employees have begun to explore using AI for job interviews, as an additional component to review language and word use in conversation. This aligns with the increased use, by HR teams, of tools to automate the recruiting process. While this can provide high efficiency for the company, it is often at the expense of the candidate's experience. But these early days have already shown that these AI solutions can manifest the worst of human behavior if not properly deployed and monitored.
The negative outcomes that are seen with applying AI to HR recruiting, resume review, and hiring processes can include:
- Language & Translation - Many AI tools leverage English as their first language of training, while many candidates often have languages other than English as their primary spoken and written language. This can create a bias against candidates who may have the necessary skills to execute the role successfully but communicate in different ways.
- Educational Bias - People learn in many ways through different channels and institutions. Modern AI tools do not have the ability to interpret someone's educational background beyond the basics of traditional college programs and degrees. Impactful employees today will showcase their lifelong learning through non-traditional methods including online classes, certifications, participation in community groups, and giving back through speaking at events.
- Missing Future Potential - Modern AI tools for reviewing resumes are focused on a candidate's past accomplishments. While this can be effective for like-for-like evaluation against job levels or roles, they miss candidates who show high potential to thrive in different roles when given the right opportunity and enablement. Organizations that leverage more human engagement in the process have a higher chance of spotting candidates with high potential in future roles.
- Tone of Communication - Someone's tone of communication is a reflection of their upbringing, education, mentoring, and experiences. AI solutions do not have the ability to distinguish between someone's written tone and how they will communicate when engaged in conversation and discussion. Only an experienced interviewer or hiring manager can make this determination.
- Following a Process versus Defining a Process - Defining a business process requires a higher level of creativity and critical thinking than executing a previously defined process. Many AI-driven HR tools will evaluate a candidate's work to date which can be following established processes with limited room to improve them. Successful HR teams will ensure that a candidate’s critical thinking skills are also exercised during the recruiting process.
I know and accept that AI-powered tools will continue to be adopted by HR teams. The efficiencies that these tools bring within an organization are hard to ignore, especially at a time when a single job posting can have hundreds of applicants creating a large number of resumes a recruiter must review and make a determination about.
My advice, if you are an HR professional, is to be cautious and always think of the candidate's experience through your own resume, experiences, and career goals. The technology is not there yet to easily identify and respond to bias. We must ensure the human component is not removed from tools that review resumes and make candidate recommendations. Human engagement ensures that bias does not affect interviewing and hiring decisions, that AI vendors receive real-world feedback on ways to improve and candidates have an engaging experience where they have a full opportunity to showcase their experience to your organization.
