AI can be hugely helpful in an HR context, but there are challenges employers should be aware of. Cowden Associates’ President Elliot Dinkin explores how companies can use AI in human resources and what potential problems could arise.
As more employers are exploring the use of artificial intelligence (AI) in human resources activities such as hiring, retirement planning and benefits enrollment, employers must be aware of the potential hazards and unintended consequences of utilizing this technology. Clearly, AI can lead to a more robust and personalized communication process through its usefulness in highlighting particular areas of interest and helping employees make informed and logical decisions tied to their individual relevant factors.
By embracing AI data capabilities, specifically in predictive and analytical nature, HR departments can make potentially more informed recruiting and performance decisions. For example, employers can use data to determine where to distribute resources and find employees with relevant skill sets. Data can also influence existing staff to better understand factors that increase or decrease productivity by evaluating new methods of workflow, similar to employees on a production floor many years ago.
There are challenges with this and precautions need to be considered and taken. Companies must develop policies, procedures and monitoring systems to attempt to reign in any potential real or perceived issues with using this new technology.
Benefits Decision-Making
Is AI appropriate for all types of benefits decision-making?
AI can be a great asset for helping employees make complicated benefits decisions. Systems may be established to react to employee responses to a set of questions in order to generate guidance, such as for:
Life insurance and disability – Most companies provide a core amount of coverage tied to a group policy. However, often choices of alternate levels of coverage, including offering dependent life, are provided. Using programming and responses to a series of questions will form guidance on these topics, balancing a variety of considerations, such as the level of coverage outside of the company, medical conditions and cost.
Medical/Rx, dental and vision – Making complex decisions can requires extensive data and related information in order to make an informed election. AI creates decision-matrix solutions to aid in the process.
Retirement planning – Similarly, making decisions using all relevant information, from current pay, current living expenses and other benefit choices, would be of particular interest.
AI can be a beneficial tool for improving the annual open enrollment process, as it can build upon prior data with current updates that may shed light on other areas that may have been missed.
From a compliance and tracking perspective, employers who use AI to assist employees in making decisions should fully disclose this. Additionally, emphasize that answers to questions are based upon each employee’s individual answers to a variety of questions, combined with programming and the use of algorithms. Although emotional factors are not included, there could be biases built into the programming that trigger responses based upon the programmer. This can be problematic, because women and minorities are underrepresented in the technology field. Accordingly, AI should be introduced as a tool, but with careful consideration among other tools available to help employers and employees.
Talent Acquisition
Is AI an appropriate tool for employers to handle talent acquisition, including initial screening decisions?
How many resumes do HR and/or recruiters routinely receive? How much time is allocated for this process? Clearly, AI may assist in managing this initial function and directing mundane tasks to an automated search process using algorithms in a cost-effective manner.
AI carries with it tremendous potential as a solid support tool, but not as the only tool, and employers should develop best practices:
Hiring and screening – consistent with the above, unintended consequences may occur:
- According to the Bureau of Labor Statistics, employment growth in computer science and engineering jobs is more than double the national average; however, women and minorities continue to be underrepresented.1
- AI in the workplace may also expose companies to potential violations related to age discrimination, as the law prohibits age-based discrimination against applicants or employees age 40 or over. The use of AI in the workplace to streamline certain activities could result in a disparate impact on an older workforce and potentially expose a company to discrimination claims.
- Legislation will create other roadblocks. For example, in early August 2019, the Illinois legislature unanimously passed the Illinois Artificial Intelligence Video Interview Act; if enacted, it will regulate the increasing use of algorithms, so-called “interview bots” and other forms of AI to analyze applicants’ facial expressions, body language, word choices and vocal tones during video interviews. 2
Best Practices for Using AI
Prior to implementing AI, consider the creation of policies and procedures addressing the following:
- In the decision-making process, employers should not rely exclusively on AI; some of the best (and worst) hiring decisions have been made without the use of this technology.
- Before implementing AI in any aspect of HR, carefully document the process, including the factors used in creating the algorithms.
- For hiring and screening processes, implement a review process, such as full and falseinclusion/exclusion tests of those selected and not selected. For example, 10 resumes selected for the next step in the recruiting process should be examined (if this is a statistically relevant data point) to determine if, in fact, they are worthy of the next step. Similarly, 10 resumes rejected should be examined to determine if the rejection was proper. It may be worthwhile to conduct this on a “blind” basis without indication of acceptance or rejection.
Conclusion
As AI and other data management techniques are implemented throughout an organization, companies must realize that a data-driven culture is here, regardless of role. With this understanding, organizations will need to develop an approach to handle the influx of real-time information and its potential uses. This approach could alter work culture and may require restructuring and the subsequent focus on time, money and workforce. Keep in mind: A data-driven lens provides a systematic routine, absent any emotions. It would appear that a complete, 100 percent data approach is unreasonable, considering how successful companies and people have performed historically absent these tools.
AI has significant benefits across all facets of an organization, but those benefits come with risk. An awareness of both aspects is critical for any company.
nsf.gov/statistics/2017/nsf17310/static/downloads/nsf17310-digest.pdf
Elliot Dinkin is president and CEO of 
