AIPolicyTracker

AI incident ·

Worker killed by robot in welding accident at car parts factory in India

12 news reports Snapshot 7 Sep 2026

In brief

An AI system built by Unknown and deployed by Skh Metals allegedly harmed Ramji Lal.

Risk domain
AI system safety, failures, and limitations Lack of capability or robustness
Occurred
Coverage
12 reportsJul 2015 - Apr 2019

What happened

A factory robot at the SKH Metals Factory in Manesar, India pierced and killed 24-year-old worker Ramji Lal when Lal reached behind the machine to dislodge a piece of metal stuck in the machine.

Laws that address this harm

Policy angle: Classified under AI system safety, failures, and limitations (Lack of capability or robustness) in the MIT AI Risk Repository taxonomy; 5 recorded instruments address this use case in India.

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 (12)

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

  1. Terminator redux? Robot kills a man at Haryana's Manesar factory
    timesofindia.indiatimes.com · Rao Jaswant Singh, Sanjay Yadav
  2. Robot kills a man at Haryana's Manesar factory
    zigwheels.com · Team Zigwheels
  3. Robot kills co-worker in a car factory in India
    emirates247.com · Joseph George
  4. Factory Robot Kills Worker in India
    roboticsbusinessreview.com · RT Staff
  5. Robot kills India factory worker
    en.dailypakistan.com.pk · Dawood Rehman
  6. Welding robot kills worker
    ishn.com · The Independent
  7. Robots can kill, but can they murder?
    venturebeat.com · Larry Alton

Who was involved

Alleged deployer
Skh Metals
Alleged developer
Unknown
Alleged harmed party
Ramji Lal

Classification (MIT AI Risk Repository taxonomy)

Causal entity
AI
Intent
Unintentional
Timing
Post-deployment
Harm level
none
Sectors
manufacturing
Countries
IN

Risk entries describing this failure mode

Entries from the MIT AI Risk Repository coded to subdomain 7.3.

  • Reliability issues

    "Relying on general-purpose AI products that fail to fulfil their intended function can lead to harm. For example, general- purpose AI systems can make up facts (‘hallucination’), generate erroneous computer code, or pro...

    International AI Safety Report 2025 (Bengio2025)

  • Type 2: Bigger than expected

    Harm can result from AI that was not expected to have a large impact at all, such as a lab leak, a surprisingly addictive open-source product, or an unexpected repurposing of a research prototype.

    TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AI (Critch2023)

  • Type 3: Worse than expected

    AI intended to have a large societal impact can turn out harmful by mistake, such as a popular product that creates problems and partially solves them only for its users.

    TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AI (Critch2023)

  • Ethics and Morality Issues

    LMs need to pay more attention to universally accepted societal values at the level of ethics and morality, including the judgement of right and wrong, and its relationship with social norms and laws.

    Towards Safer Generative Language Models: A Survey on Safety Risks, Evaluations, and Improvements (Deng2023)

  • Safe learning

    "AGIs should avoid making fatal mistakes during the learning phase. Subproblems include safe exploration and distributional shift (DeepMind, OpenAI), and continual learning (Berkeley)."

    AGI Safety Literature Review (Everitt2018 )

  • Malign belief distributions

    "Christiano (2016) argues that the universal distribution M (Hutter, 2005; Solomonoff, 1964a,b, 1978) is malign. The argument is somewhat intricate, and is based on the idea that a hypothesis about the world often includ...

    AGI Safety Literature Review (Everitt2018 )

  • Meta-cognition

    "Agents that reason about their own computational resources and logically uncertain events can encounter strange paradoxes due to Godelian limitations (Fallenstein and Soares, 2015; Soares and Fallenstein, 2014, 2017) an...

    AGI Safety Literature Review (Everitt2018 )

  • Technical and operational risks

    "To date, technical limitations and vulnerabilities are present in most generative AI models in various contexts. Consequently, malicious users find it easier to breach an AI system’s safety and ethical guardrails to e...

    Regulating under Uncertainty: Governance Options for Generative AI (G'sell2024)

Incidents in the same risk subdomain

All incidents in this subdomain

Source record: incident #69 on the AI Incident Database · all 12 reports