AI incident ·
Alexa Recommended Dangerous TikTok Challenge to Ten-Year-Old Girl
In brief
An AI system built and deployed by Amazon allegedly harmed Kristin Livdahl'S Daughter, Amazon Echo Customers and 1 other.
- Risk domain
- Discrimination and Toxicity
- Occurred
- Coverage
- 3 reports
What happened
Amazon’s voice assistant Alexa suggested “the penny challenge,” which involves dangerously touching a coin to the prongs of a half-exposed plug, when a ten-year-old girl asked for a challenge to do.
Laws that address this harm
Policy angle: Classified under Discrimination and Toxicity (Exposure to toxic content) in the MIT AI Risk Repository taxonomy; 5 recorded instruments address this use case in the United States.
- Colorado AI Act
- NYC Local Law 144 (automated employment decision tools)
- Illinois AI Video Interview Act
- Illinois HB 3773 (AI in employment, Human Rights Act amendment)
- NIST AI RMF
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 (2)
Titles link to the original publisher; report text is not reproduced here.
Who was involved
Classification (MIT AI Risk Repository taxonomy)
- Risk domain
- Discrimination and Toxicity
- Risk subdomain
- 1.2 Exposure to toxic content
- Causal entity
- AI
- Intent
- Unintentional
- Timing
- Post-deployment
- Harm level
- AI tangible harm issue
- Sectors
- information and communication
- Countries
- US
Risk entries describing this failure mode
Entries from the MIT AI Risk Repository coded to subdomain 1.2.
- Harmful Content
"The LLM-generated content sometimes contains biased, toxic, and private information"
- Toxicity
"Toxicity means the generated content contains rude, disrespectful, and even illegal information"
- Toxic Training Data
"Following previous studies [96], [97], toxic data in LLMs is defined as rude, disrespectful, or unreasonable language that is opposite to a polite, positive, and healthy language environment, including hate speech, offe...
- Not-Suitable-for-Work (NSFW) Prompts
"Inputting a prompt contain an unsafe topic (e.g., notsuitable-for-work (NSFW) content) by a benign user. "
- Controversial Opinions
The controversial views expressed by large models are also a widely discussed concern. Bang et al. (2021) evaluated several large models and found that they occasionally express inappropriate or extremist views when disc...
- Toxicity and Abusive Content
This typically refers to rude, harmful, or inappropriate expressions.
- Harmful responses
"Current Frontier AI mdoels amplify existing biases within their training data and can be manipulated into providing potentially harmful responses, for example abusive language or discriminatory responses91,92. This is n...
- Violation of social norms
"Second, because LLMs are trained on internet text data, there is also a risk that model weights encode functions which, if deployed in particular contexts, would violate social norms of that context. Following the princ...
Incidents in the same risk subdomain
- KBS AI Translation Subtitles Reportedly Broadcast Profanity During Artemis II Launch Livestream
- Grok Allegedly Generated Publicly Visible Sexist Abuse Targeting Swiss Finance Minister Karin Keller-Sutter After X User Prompt
- Trump Reportedly Posted Purportedly AI-Generated Racist Video Depicting Barack and Michelle Obama as Apes on Truth Social
- Tencent's WeChat-Integrated Yuanbao Chatbot Reportedly Insulted User During Coding Debug Request
- Alleged Harmful Outputs and Data Exposure in Children's AI Products by FoloToy, Miko, and Character.AI
- AI Training Dataset for Detecting Nudity Allegedly Found to Contain CSAM Images of Identified Victims
Other incidents involving Amazon
- Amazon Algorithmic Pricing Allegedly Hiked up Price of Reference Book to Millions
- Amazon Reportedly Sold Products and Recommended Frequently Bought Together Items That Aid Suicide Attempts
- Amazon's AI Cameras Incorrectly Penalized Delivery Drivers for Mistakes They Did Not Make
- Amazon's Monitoring System Allegedly Pushed Delivery Drivers to Prioritize Speed over Safety, Leading to Crash
- Amazon Allegedly Forced Deployment of AI-Powered Cameras on Delivery Drivers
- Amazon’s Search and Recommendation Algorithms Found by Auditors to Have Boosted Products That Contained Vaccine Misinformation
Source record: incident #160 on the AI Incident Database · all 3 reports