AI Workslop: Identifying Low-Quality AI Content from Coworkers

The Emergence of "Workslop": Low-Quality AI Output

A novel term, “workslop,” has been introduced by researchers from BetterUp Labs and the Stanford Social Media Lab to characterize substandard content produced by artificial intelligence.

Defining Workslop

According to an article recently featured in the Harvard Business Review, workslop is defined as AI-generated material that appears competent but ultimately fails to contribute substantively to the completion of a task.

Impact on AI Investment

The researchers at BetterUp Labs propose that the prevalence of workslop may account for the disappointing results reported by 95% of organizations that have implemented AI technologies.

These organizations have, despite their investment, observed no discernible return.

Characteristics of Workslop

Workslop is often characterized by being unhelpful, lacking essential details, or omitting critical contextual information.

This ultimately leads to an increased workload for other team members.

The Downstream Burden

The researchers emphasize that workslop doesn't simply represent wasted effort; it actively transfers the responsibility for completing the work to others.

Recipients are then required to decipher, rectify, or completely rework the initial AI output.

Prevalence Among Employees

A continuing survey involving 1,150 full-time employees in the United States revealed that 40% had encountered workslop within the last month.

Mitigating Workslop in the Workplace

To prevent the proliferation of workslop, the researchers advocate for workplace leaders to demonstrate deliberate and purposeful AI utilization.

Furthermore, they recommend establishing clear guidelines and standards for AI usage within teams.

Key Recommendations

• Model thoughtful AI use.
• Establish clear norms for AI application.
• Set acceptable use parameters.