Amid rapidly evolving digital landscapes, data and AI have become essential tools in human resource (HR) management, but these advancements are both promising and perplexing for HR professionals. Leveraging data can help HR departments make decisions and lead to a better understanding of employee behavior. If companies want to give HR teams access to a treasure trove of information, they need to think about regulatory compliance as well as ethical and privacy considerations.
At the same time, artificial intelligence (AI) offers the opportunity to streamline HR processes, but it also introduces another set of challenges. In this article, we’ll explore the biggest pitfalls and problems of AI and data-driven HR and give you some ways to compensate for some of these problems.
The HR data dilemma: compliance, ethics and protection
With the rise of data collection, organizations must navigate a complex maze of regulations in order to stay compliant. HR departments must comply with data protection laws, including HIPAA, CCPA, and GDPR. And compliance isn’t just important from a legal perspective: it’s also essential for maintaining trust with employees and stakeholders. Failure to comply may result in financial penalties and reputational damage.
HR teams must also ensure that their use of data remains within their company’s ethical boundaries. Transparency is paramount in data processing, especially when it comes to personal information. Organizations must ensure that employees understand what data is collected, how that information is used, and how confidentiality will be protected.
Data breaches are commonplace in today’s digital age. The consequences of HR data breaches can be devastating. Compromised data can expose people to identity theft and break down trust between an organization and its employees. Organizations must continually refine their strategies to keep data secure and ensure data integrity.
AI Ethics and Transparency in HR
AI introduces huge potential within HR, but just like data, AI presents many challenges for departments to think about.
As AI systems become increasingly involved in employee interaction and decision-making, ethical implications are becoming a major concern. Intelligent machines are increasingly used to make decisions within HR, and these decisions impact workers.
Amazon, for example, used algorithms to track fulfillment center workers, leading to automated layoffs. Every organization seeking to implement AI should establish an “ethics board” that examines these types of issues and their impact on artificial intelligence initiatives.
Transparency around AI is another crucial issue. Just as it is important to understand the underlying logic of human decisions, it is equally important to be able to see the logic behind AI-powered the decisions. HR professionals must be able to explain the reasoning and decision-making process used by machines. Organizations should strive for transparency to build trust and alleviate fears around the use of AI.
Another important challenge is the environmental toll of AI. AI systems consume a lot of energy and businesses need to consider their environmental footprint when planning data-driven and AI-enabled HR initiatives.
AI also depends on blank data. Inaccurate or impure data can lead to faulty AI-based decisions, negating the benefits that AI could otherwise bring to human resource management. Organizations can use these metrics to evaluate their data:
● Consistency — all data should be recorded and collated in the same way.
● Accuracy — Data must be free of errors.
● Uniqueness – Each data element must be unique and duplicates must be eliminated.
● Validity — Each record or data element must be fit for its intended use.
● Timeliness — Data should be relevant to when it was collected.
● completeness — Data should capture as much as possible the total availability of data on a particular topic.
Every HR professional should be aware of the delicate balance between the potential and pitfalls of data and AI in HR.