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Kronos Scheduling Algorithm Allegedly Caused Financial Issues for Starbucks Employees

9 news reports Synced from source · record last edited 5 Sep 2026

In brief

An AI system built by Kronos and deployed by Starbucks allegedly harmed Starbucks employees.

Risk domain
Socioeconomic & Environmental Harms Increased inequality and decline in employment quality
Occurred
Coverage
9 reportsAug 2014 - Jun 2016

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.

Laws that address this harm

Policy angle: Classified under Socioeconomic & Environmental Harms (Increased inequality and decline in employment quality) in the MIT AI Risk Repository taxonomy; 5 recorded instruments address this use case in the United States.

Matched from the record's risk domain and country to the instruments recorded here. A reviewer can correct the match in the repository (data/external/incident_overrides.yaml).

News reports (9)

Titles link to the original publisher; report text is not reproduced here.

  1. Working Anything but 9 to 5
    nytimes.com · Jodi Kantor
  2. For some Starbucks workers, job leaves bitter taste
    cbsnews.com · Alain Sherter
  3. After A Wave Of Bad Press, This Controversial Software Company Is Making Changes
    buzzfeednews.com · Caroline O'Donovan
  4. Kronos shift scheduling software a grind for Starbucks worker
    searchhrsoftware.techtarget.com · News Writer
  5. THE GRIND: Striving for Scheduling Fairness at Starbucks
    populardemocracy.org · Aditi Sen, Carrie Gleason
  6. Starbucks vows to do more to ease barista schedules
    money.cnn.com · Aaron Smith
  7. ​Is Starbucks shortchanging its baristas?
    cbsnews.com · Aimee Picchi
  8. How Starbucks started taking their schedules seriously…and why you should too
    quinyx.com · Tommy Tonkins
  9. The Seattle Times: Starbucks says its scheduling practices have improved
    fairworkweek.org · Fair Workweek Initiative

Who was involved

Alleged deployer
Starbucks
Alleged developer
Kronos
Alleged harmed party
Starbucks employees

AI systems implicated

Enterprise AI systemsAlgorithmic management systems

Classification (MIT AI Risk Repository taxonomy)

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.

  • Labour exploitation

    "Labour exploitation - Use of under-paid and/or offshore labour to develop, manage or optimise a technology system."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • 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."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • 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...

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • 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."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • 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...

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • 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-...

    The Rise of Artificial Intelligence - Future Outlooks and Emerging Risks (Allianz2018)

  • 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...

    The Rise of Artificial Intelligence - Future Outlooks and Emerging Risks (Allianz2018)

  • 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...

    Foundational Challenges in Assuring Alignment and Safety of Large Language Models (Anwar2024)

Linked by editors or by text similarity in the source dataset.

Incidents in the same risk subdomain

All incidents in this subdomain

Source record: incident #10 on the AI Incident Database · all 9 reports