Reportedly Faulty AI Transcription Threatens Integrity of Genoa Bribery Probe

Laws on record for this risk area

Policy angle: Classified under Misinformation (False or misleading information) in the MIT AI Risk Repository taxonomy; 5 instruments on record cover this risk area.

• India DPDP Act India · Partially applicable · binding
• Law on Artificial Intelligence (2025) Kazakhstan · Adopted · binding
• Law No. 132/2025 on artificial intelligence Italy · In force · binding
• EU AI Act European Union · Partially applicable · binding
• Texas Responsible AI Governance Act (TRAIGA) Texas (United States) · In force · binding

Matched from the record's risk category and country to the instruments in effect recorded here: a law listed covers the area, which is not a finding that it applies to this incident. A reviewer can correct the match in the repository (data/external/incident_overrides.yaml).

News reports (1)

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

1. 13 Jun 2024
   The judicial system underestimates the errors of automatic transcription

   ilpost.it · Il Post

Who was involved

Alleged deployer

Judiciary Of Italy

Alleged developer

Unnamed Automated Transcription Software Developer

Alleged harmed party

Roberto Spinelli, Paolo Emilio Signorini, Italian General Public, Giovanni Toti, Genoa Prosecutor'S Office

Classification (MIT AI Risk Repository taxonomy)

Risk domain

Misinformation

Risk subdomain

3.1 False or misleading information

Causal entity

AI

Intent

Unintentional

Timing

Post-deployment

Harm level

—

Sectors

—

Countries

—

Risk entries describing this failure mode

Entries from the MIT AI Risk Repository coded to subdomain 3.1.

• Pursuing Consistent Context

  "LLMs have been demonstrated to pursue consistent context [129]–[132], which may lead to erroneous generation when the prefixes contain false information. Typical examples include sycophancy [129], [130], false demonstra...

  Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

• Defective Decoding Process

  In general, LLMs employ the Transformer architecture [32] and generate content in an autoregressive manner, where the prediction of the next token is conditioned on the previously generated token sequence. Such a scheme...

  Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

• Noisy Training Data

  "Another important source of hallucinations is the noise in training data, which introduces errors in the knowledge stored in model parameters [111]–[113]. Generally, the training data inherently harbors misinformation....

  Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

• Untruthful Content

  "The LLM-generated content could contain inaccurate information"

  Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

• Hallucinations

  "LLMs generate nonsensical, untruthful, and factual incorrect content"

  Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

• Faithfulness Errors

  "The LLM-generated content could contain inaccurate information" which is is not true to the source material or input used

  Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

• Factuality Errors

  "The LLM-generated content could contain inaccurate information" which is factually incorrect

  Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

• Knowledge Gaps

  "Since the training corpora of LLMs can not contain all possible world knowledge [114]–[119], and it is challenging for LLMs to grasp the long-tail knowledge within their training data [120], [121], LLMs inherently posse...

  Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

Incidents in the same risk subdomain

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• 10 Apr 2026South Africa Draft National AI Policy Reportedly Included Fictitious References Believed to Be AI Hallucinations
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