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Xsolla CEO Aleksandr Agapitov terminated 150 employees via email after an internal 'big data team' analyzed their activity in workplace software like Jira, Confluence, and Gmail. The employees were labeled 'unengaged and unproductive' based on these metrics, which many were unaware were being tracked. The incident sparked significant backlash regarding employee privacy, the ethics of AI-driven performance monitoring, and the lack of empathy in the termination process.
Xsolla CEO fired more than a hundred employees from his company in Perm, Russia, based on big data analysis of their remote digitized-work activity, which critics said was violating employee's privacy, outdated, and extremely ineffective.
Domain classification, causal taxonomy, severity scores, and national security assessments were LLM-classified and may contain errors.
Social and economic inequalities caused by widespread use of AI, such as by automating jobs, reducing the quality of employment, or producing exploitative dependencies between workers and their employers.
Also classified as
The AI system secretly tracked and analyzed employees' private activities and communications across workspace software without their knowledge.
The tracking system failed to reliably measure actual productivity, relying instead on flawed proxies like network time and software interaction.
The deployment of secret AI surveillance to track and terminate employees based on software activity metrics directly degrades the quality of employment and worker trust.
Human
Due to a decision or action made by humans
Intentional
Due to an expected outcome from pursuing a goal
Post-deployment
Occurring after the AI model has been trained and deployed
The risk of mass layoffs and secret surveillance was caused by intentional decisions made by Xsolla's management using the tracking system.
Added categories peak at 2: Minor (Psychological Harm, Direct)
Xsolla terminated 150 employees in Perm, Russia, using AI-driven big data analysis of workplace software activity. While the incident sparked significant backlash regarding worker privacy and algorithmic surveillance, its national security impact remains negligible to minor, confined entirely to corporate labor practices and workplace privacy concerns.
The AI system functioned as an Assistant by analyzing employee activity data across various workspace applications and tagging individuals as unengaged, which human management then used to make termination decisions.
High Risk: The system is an employment and worker management system used to monitor and evaluate worker productivity, which is explicitly classified as high risk under the EU AI Act.
The AI system was explicitly deployed to track, monitor, and evaluate employee productivity and engagement across workspace software.
The reports provide consistent details regarding the number of employees fired (150), the location (Perm, Russia), the date of the email leak (August 3, 2021), and the specific software tracked (Jira, Confluence, Gmail, etc.). The CEO's own statements and emails are quoted directly, confirming the use of big data/AI tracking for the layoffs.
Some might view this as a standard big data analytics query rather than an advanced AI system, though the reports repeatedly refer to it as an AI-based analysis and data collection AI.
Technology
Flawed Productivity Metrics
Algorithm evaluated software interaction rather than actual work output.
Inability to Track Creative Work
AI cannot measure unconventional or neurodiverse creative work styles.
Data Inputs
Secret Workspace Tracking
Employees were unaware that their software activities were being tracked.
Proxy Performance Data
Using Jira, Confluence, and Gmail activity as a proxy for engagement.
Remote Work Data Complications
Tracking remote employees on private computers raised privacy concerns.
Human Factors
Lack of Leadership Empathy
CEO delivered insensitive termination emails and public social media posts.
Workforce Distrust and Anxiety
Secret surveillance created a culture of fear and low morale.
Process and Methods
Algorithmic Decision Making
Laying off 150 workers based solely on automated big data categorization.
Ineffective KPI Design
Measuring network time encourages gaming metrics instead of productive work.
Management
Growth Prioritization
Layoffs were driven by the company failing to sustain 40 percent growth.
Lack of Algorithmic Transparency
Management failed to inform employees about tracking systems and metrics.
Regulatory Environment
Gray Legal Area on Data Privacy
Lack of clear regulations regarding tracking remote employees on private PCs.
AI system involved
Identified by automated extraction; can differ from the alleged developers above.
