AI incident #10 ·
Kronos Scheduling Algorithm Allegedly Caused Financial Issues for Starbucks Employees
What happened
Kronos’s scheduling algorithm and its use by Starbucks managers allegedly negatively impacted financial and scheduling stability for Starbucks employees, which disadvantaged wage workers.
Only the incident metadata is stored here. The underlying news reports are on the AI Incident Database (CC BY-SA 4.0); use the links above to read them.
News reports (9)
Coverage catalogued by the AI Incident Database. Titles link to the original publisher; the text is not reproduced here.
Who was involved
AI systems implicated
Classification (MIT AI Risk Repository taxonomy)
- Risk domain
- Socioeconomic & Environmental Harms
- Causal entity
- AI
- Intent
- Intentional
- Timing
- Post-deployment
- Harm level
- AI tangible harm event
- Sectors
- accommodation and food service activities
- Countries
- US
Risk entries describing this failure mode
Entries from the MIT AI Risk Repository coded to subdomain 6.2.
- Job loss/losses
"Job loss/losses - Replacement/displacement of human jobs by a technology system, leading to increased unemployment, inequality, reduced consumer spending, and social friction."
- Societal destabilisation
"Societal destabilisation - Societal instability in the form of strikes, demonstrations and other types of civil unrest caused by loss of jobs to technology, unfair algorithmic outcomes, disinformation, etc."
- Societal inequality
"Societal inequality - Increased difference in social status or wealth between individuals or groups caused or amplified by a technology system, leading to the loss of social and community wellbeing/cohesion and destabil...
- Labour exploitation
"Labour exploitation - Use of under-paid and/or offshore labour to develop, manage or optimise a technology system."
- Political instability
"Political instability - Political polarisation or unrest caused by increased inequality, job losses, over- dependence on technology making societies vulnerable to systemic failures, etc, arising from or amplified by the...
- Increased income disparity
"While AI is predicted to bring increased GDP per capita by performing existing jobs more efficiently and compensating for a decline in the workforce, especially due to population aging, the potential substitution of man...
- Economic
"AI is predicted to bring increased GDP per capita by performing existing jobs more efficiently and compensating for a decline in the workforce, especially due to population aging, the potential substitution of many low-...
- Effects on the Workforce
"Rapid advances in LLMs pose three distinct sets of challenges for workers’ incomes (Korinek and Stiglitz, 2019; Susskind, 2023). First, they are likely to accelerate the rate of job turnover and disruption —– affecting...
Related incidents on the AI Incident Database
Linked by AIID editors or by its text-similarity model.
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