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Amazon Flex Drivers Allegedly Fired via Automated Employee Evaluations

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

In brief

An AI system built by Amazon and deployed by Amazon Flex allegedly harmed Amazon Flex employees and Amazon Flex drivers.

Risk domain
Socioeconomic & Environmental Harms Increased inequality and decline in employment quality
Occurred
Coverage
5 reportsJun 2021

What happened

Amazon Flex's contract delivery drivers were dismissed using a minimally human-interfered automated employee performance evaluation based on indicators impacted by out-of-driver's-control factors and without having a chance to defend against or appeal the decision.

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.

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 (5)

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

  1. Fired by Bot at Amazon: ‘It’s You Against the Machine’
    bloomberg.com · Spencer Soper
  2. Amazon is using algorithms with little human intervention to fire Flex workers
    arstechnica.com · Tim De Chant
  3. War veteran fired from Amazon for automated email with no chance to defend himself
    explica.co · Explica
  4. Amazon Flex Fires Employees by Software Algorithm
    olhardigital.com.br · Rafael Queiroz
  5. Amazon Is Using Algorithms And A.I. To Terminate Flex Drivers By E-mail
    jalopnik.com · Lawrence Hodge

Who was involved

Alleged deployer
Amazon Flex
Alleged developer
Amazon
Alleged harmed party
Amazon Flex employees Amazon Flex drivers

AI systems implicated

Algorithmic management systems

Classification (MIT AI Risk Repository taxonomy)

Causal entity
AI
Intent
Intentional
Timing
Post-deployment
Harm level
—
Sectors
—
Countries
—

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 #111 on the AI Incident Database · all 5 reports