Incident 10: Kronos Scheduling Algorithm Allegedly Caused Financial Issues for Starbucks Employees

Description: Kronos’s scheduling algorithm and its use by Starbucks managers allegedly negatively impacted financial and scheduling stability for Starbucks employees, which disadvantaged wage workers.

Tools

New ReportNew ReportNew ResponseNew ResponseDiscoverDiscover
Alleged: Kronos developed an AI system deployed by Starbucks, which harmed Starbucks employees.

Incident Stats

Incident ID
10
Report Count
10
Incident Date
2014-08-14
Editors
Sean McGregor, Khoa Lam

CSET Taxonomy Classifications

Taxonomy Details

Full Description

The staff scheduling tool used by Starbucks has led to staff working hours volatile and erratic schedules. Some store managers use a scheduling software, Kronos, to optimize scheduling and cut labor costs, however Starbucks refuses to accept or deny using Kronos.

Short Description

Issues with Starbucks worker's schedules may be linked to a staffing software, Kronos.

Severity

Negligible

Harm Type

Psychological harm

Location

Global

Named Entities

Starbucks, Kronos

Technology Purveyor

Starbucks

Beginning Date

2015-01-01

Ending Date

2015-01-01

Near Miss

Unclear/unknown

Intent

Unclear

Lives Lost

No

Infrastructure Sectors

Food and agriculture

GMF Taxonomy Classifications

Taxonomy Details

Known AI Goal

Market Forecasting, Scheduling

Potential AI Technology

Regression, Diverse Data

Known AI Technical Failure

Underspecification

Potential AI Technical Failure

Tuning Issues, Misconfigured Aggregation

Variants

A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.

Similar Incidents

By textual similarity

Did our AI mess up? Flag the unrelated incidents