In the race of digital evolution, organizations are turning to AI-driven remote monitoring solutions to gain an edge with optimized performance and increased profitability. These advanced employee monitoring tools not only promote enhanced productivity but also claim to offer extensive insights into employee time management, work patterns, and output, empowering managers to make data-based, informed decisions. 

Yet, a more sinister side of such technologies came to light in 2025, one that discriminately affects women, night owls, and disabled employees, raising growing concerns about workplace bias, algorithmic fairness, and digital ethics.

Algorithmic bias in employee monitoring

While artificial intelligence is powerful, it is only as productive and constructive as the data it is trained on. And sadly, former workplace data is full of inherent biases. When these discriminations sync with modern employee monitoring software, the outcome is a digital mechanism, reinforcing obsolete norms and policing those who do not follow them.

Say, if an AI model is consistently trained on data acquired from 9-to-5 workers, single, and able-bodied individuals, it would automatically assume that uninterrupted keyboard logs between 9 AM and 5 PM as high productivity hours. This presumption produces biased reports as it does not align with caregivers clocking in sporadically, or specially-abled employees using adaptive technologies, ultimately flagging as underperformed workers, despite actual contributions being superior or equivalent in quality.

In 2024, the Algorithmic Justice League published a study revealing that about 58% of workplace AI systems failed to accurately encompass atypical behavior, such as the use of assistive technology or irregular work hours. These findings outline the growing legal challenges against accountable developers and employers.

Caregivers: Penalized for flexibility

Caregivers, especially women, juggle between home responsibilities and job duties, requiring flexible work hours. However, employee monitoring software is trained to treat time away from work during working hours as ‘unproductive.’ This inflexible metric failed to consider the wider context of someone’s contributions, particularly in knowledge-based roles.

In 2024, a landmark lawsuit in California involving a class of remote working parents alleged that the company’s monitoring software lowered their productivity scores every instance when they logged off for a short while to change diapers or pick up their child from school. These reduced scores resulted in fewer promotions and increased layoffs, unreasonably affecting parents.

Instead of recognizing actual productivity across diverse time blocks, the AI systems primarily equate work value with presence and availability, a parameter that systematically polices workers with non-linear schedules. This nuance sheds light on workplace bias, creating a chilling effect on employees with the utmost need for flexible work hours.

Disabled workforce: Caught in the algorithm

Most employee monitoring software measures productivity by assessing various inputs like real-time webcam footage, mouse movement, or keystrokes per hour, which can be rather a hostile take for disabled workers. Because someone with a neurological condition may require frequent breaks to refresh, while others may use assistive technology that cannot be registered in traditional monitoring systems.

In 2025, the Equal Employment Opportunity Commission (EEOC) was intensely pressured by disability rights advocates to mandate stricter monitoring standards. In response, the EEOC revised its employer guidelines, stating, “The use of algorithmic tools must not result in disparate impacts on individuals with disabilities, especially where accommodations are warranted but not offered.”

Other than that, there are also many pending lawsuits, including the one where software engineers with arthritis received negative feedback due to a low activity score. While she did accomplish her allocated tasks efficiently and within the deadline, the software imposed a penalty as the system could not assess the speech-to-text input used. Such instances highlight how non-inclusive tools generate systematic challenges, resulting in bias by default.

Night owls: Overlooked and undervalued

Workplace surveillance algorithms do not fit with the schedules of night owls and the asynchronous workforce. This bunch of employees has to or may need to work overtime or till late evenings, all the more if it is in global or remote work settings. But, even the leading monitoring systems are crafted to work around traditional business hours only, failing big time to acknowledge night-time or overtime work as legitimate productivity.

Recently, the Harvard Business School published a report revealing that about 41% of the distributed workforce reportedly work beyond the standard 9-to-5 work schedule. Despite these astonishing numbers, a mere 12% of employee monitoring software platforms consider and offer scheduling customization or supportive and adaptive productivity parameters.

This wide mismatch led to real consequences. In one reported case, a seasoned software developer in India tragically lost his work contract with a US agency when his night-time coding sessions were identified as ‘inactive work periods.’ Sardonically, his work output was way higher than that of his peers, but the AI monitoring lacked the configuration to identify or reward it.

Legal reckoning: Accepting accountability

The ongoing wave of lawsuits is the pacesetter for the brewing regulatory storm surrounding AI monitoring in the workplace. In a major case in 2024, the US District Court permitted parts of a lawsuit against Workday, an HR software company. The suit purported discrimination against new hire candidates based on age, race, and disability, originating from biased AI screening tools.

As scrutiny grows, countries like the Netherlands and Germany are at the forefront of advocating for mandated AI audits for workplace tools. In the US, the Algorithmic Accountability Act 2.0, a new proposed federal legislation, intends to regulate automated decision-making systems and requires transparency and discrimination mitigation strategies from developers and employers alike.

Last thoughts: A step towards a more human-centric future

For a fact, monitoring tools or software are not inherently harmful. It is the current use of them that outlines a troubling disregard for individual diversity. When productivity is compared, and a lower score is shown on the dashboard, it unintentionally dehumanizes work and marginalizes those workers who do not conform to the algorithmic molds.

Companies that repeatedly fail to consider these critical underlying concerns are more likely to face legal repercussions, risking workplace trust, losing talent, and reputational harm in an environment where social responsibility is greatly valued and beyond.

By developing an AI monitoring tool that accommodates flexibility, celebrates diversity, and acknowledges nuance, organizations can turn employee monitoring software into a stimulant for progress and inclusion.