Purported AI-Generated Video Reportedly Depicts Illegal Tiger Sales in Bagerhat, Bangladesh

Laws that address this harm

Policy angle: Classified under Misinformation (False or misleading information) in the MIT AI Risk Repository taxonomy; 5 recorded instruments address this use case.

• 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 domain and country to the instruments recorded here. 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. 1 Jul 2025
   This video of an alleged tiger market in Bangladesh is a deepfake created using AI

   factly.in · Murshid, Factly

Who was involved

Alleged deployer

Unknown Social Media Accounts

Alleged developer

Google

Alleged harmed party

General Public Of Bangladesh, Conservationists In Bangladesh, Wildlife Authorities In Bangladesh

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)

• 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)

• Untruthful Content

  "The LLM-generated content could contain inaccurate information"

  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

• 12 May 2026Nonfiction Book 'The Future of Truth' Reportedly Included AI-Generated and Misattributed Quotations
• 6 May 2026Claude Console Reportedly Generated Phantom Legal Quotations in Trump Layoffs Court Filing
• 21 Apr 2026Purportedly AI-Enhanced Images of Iranian Women Protesters Were Reportedly Spread With Unverified Execution Claims
• 10 Apr 2026South Africa Draft National AI Policy Reportedly Included Fictitious References Believed to Be AI Hallucinations
• 8 Apr 2026Purportedly AI-Generated Image Reportedly Misled Daejeon Authorities Searching for Escaped Wolf Neukgu
• 17 Mar 2026Gemini and Grok Reportedly Misidentified Authentic Minab School-Strike Graveyard Photo as Unrelated Disaster Imagery

Other incidents involving Unknown Social Media Accounts

• 7 Feb 2024Alleged Deepfake Audio of Imran Khan Calls for Election Boycott, Misleading Pakistan Voters