With the digitization of work, the amount of data companies collect about their employees has increased dramatically. The trend has been compounded by information from wearable devices and, during the pandemic, remote work and personal information like vaccination status.
Ethical use of data about employees should focus on dignity, according to a new research brief from the MIT Center for Information Systems Research. This means making sure data use helps employees achieve their goals and receive appropriate recognition. Focusing on dignity also improves data management, the researchers found, and also allows leaders to reinforce their regard for employees.
Researchers Dorothy E. Leidner, Olgerta Tona, Barbara H. Wixom, and Ida A. Someh analyzed interviews with people who had participated in one of 52 different artificial intelligence projects at 48 companies, and later reviewed 22 of the projects that had significant use of employee data.
While workforce analytics have traditionally been led by the human resources department, companies are starting to use employee data in new ways, they found. One company analyzed anonymous employee badge information, Wi-Fi connection activity, and other factors to learn more about building occupancy. That information helped the organization save millions of dollars in heating and cooling costs.
But using employee data could also lead to outcomes that are negative for employees — such as using historical data to alter or eliminate work tasks or treating employees like objects to be managed, rather than people. Existing data privacy regulations don’t provide the proper guidance for employers using employee data, the researchers write, in part because those regulations don’t address the ethical complexity of an employer/employee relationship.
Instead, companies need to develop an acceptable data use capability, which includes legal, regulatory, and ethical considerations for using data of all kinds. To make sure dignity is at the core, companies should:
Know the kinds of employee data
Employers often gather five types of employee data, the researchers found, which are often interrelated. This information is combined in various ways — with data about customers, operations, and products, for example, as well as with external data.
Who data describes employees who are performing work. This has evolved from employee demographics, contact information, and information about salary and benefits to include things like social media connections and biometric information from wearable devices.
What data describes employee work activities. This includes online activities such as internet searches and keyboard actions, as well as digitized offline behavior such as work logs, video surveillance, and call center transcripts.
Where data describes employee whereabouts, such as physical location and spatial movement. This has become more precise with the addition of wearable devices, mobile tracking, and smart factories and buildings.
When data describes the timing of employee activities and related outcomes. This could include milestones of a work day or a task, or a complex time series with events assembled from usage logs, mobile devices, sensors, and transactions.
Why data has historically described tacit employee knowledge, including expertise and logic. With digitization and work automation, organizations have information about what employees know, how they form judgments or make decisions, and how they feel. For example, AI training data often includes employee feedback about model outcomes; in this way, employees’ experiences and judgments can help improve model performance.
Consider three types of employee dignity
Organizations tend to use employee data to learn more about employee workforce activity and to communicate insights to employees or others inside or outside of the organization. As data is being used, the researchers advise leaders to consider employee dignity on three fronts.
Behavioral dignity, which provides employees with resources to achieve their goals and meet organizational expectations. Employee data can help companies create training and support resources and develop a transparent performance evaluation system. Employee data can also threaten behavioral dignity: If, for example, data gathered is concealed from employees, used to manipulate employees or set unrealistic goals, or if employees are being judged based on data that an employee doesn’t see or know is being gathered.
Meritocratic dignity, which ensures individuals receive appropriate acknowledgement for their contributions. Companies can use employee data to identify exceptional contributions and determine the ways in which individuals contribute to group goals. On the negative side, employee data could be used to compare employees and manipulate behavior, or companies could fail to acknowledge an employee’s contribution.
Inherent dignity, which means individuals are treated with respect regardless of their status. At the workplace, this means helping employees feel accepted and included in organizational matters. Employee data can be used to make work tasks more appealing and to identify and remedy bias in the workplace, for example. To maintain inherent dignity, companies should involve employees in decisions about what data is gathered and used and inform employees about what data is being captured and get their consent. Inherent dignity is threatened when companies reuse data for purposes beyond established consent, ignore contextual factors and other influences that impact work performance, or fail to inform employees about the capture of employee data or gain consent.
How to gauge whether dignity is core to your company’s data use
The CISR researchers said companies can take stock of their employee data use by asking the following questions:
- What employee data is in use?
- Are employees aware of the data being captured, and do they consent to its use? Do they have options about what data is gathered?
- Do employees see their own data, and do they benefit from insights derived from it?
- Do employees understand how and why their data benefits the organization and them personally?