Skip to Content
logologo
AI Incident Database
Open TwitterOpen RSS FeedOpen FacebookOpen LinkedInOpen GitHub
Open Menu
Discover
Submit
  • Welcome to the AIID
  • Discover Incidents
  • Spatial View
  • Table View
  • List view
  • Entities
  • Taxonomies
  • Submit Incident Reports
  • Submission Leaderboard
  • Blog
  • AI News Digest
  • Risk Checklists
  • Random Incident
  • Sign Up
Collapse
Discover
Submit
  • Welcome to the AIID
  • Discover Incidents
  • Spatial View
  • Table View
  • List view
  • Entities
  • Taxonomies
  • Submit Incident Reports
  • Submission Leaderboard
  • Blog
  • AI News Digest
  • Risk Checklists
  • Random Incident
  • Sign Up
Collapse

Incident 346: Robots in Japanese Hotel Annoyed Guests and Failed to Handle Simple Tasks

Description: A number of robots employed by a hotel in Japan were reported by guests in a series of complaints for failing to handle tasks such as answering scheduling questions or making passport copies without human intervention.

Tools

New ReportNew ReportNew ResponseNew ResponseDiscoverDiscoverView HistoryView History

Entities

View all entities
Alleged: unknown developed an AI system deployed by Henn na Hotel, which harmed Henn na Hotel guests and Henn na Hotal staff.

Incident Stats

Incident ID
346
Report Count
5
Incident Date
2016-06-15
Editors
Khoa Lam
Applied Taxonomies
MIT

MIT Taxonomy Classifications

Machine-Classified
Taxonomy Details

Risk Subdomain

A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
 

7.3. Lack of capability or robustness

Risk Domain

The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
 
  1. AI system safety, failures, and limitations

Entity

Which, if any, entity is presented as the main cause of the risk
 

AI

Timing

The stage in the AI lifecycle at which the risk is presented as occurring
 

Post-deployment

Intent

Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
 

Unintentional

Incident Reports

Reports Timeline

Incident Occurrence+4
Robot Hotel Loses Love for Robots
Robot Hotel Loses Love for Robots

Robot Hotel Loses Love for Robots

wsj.com

Robots Ruin Robot Hotel

Robots Ruin Robot Hotel

gizmodo.com

Japan’s robot hotel lays off half the robots after they created more work for humans

Japan’s robot hotel lays off half the robots after they created more work for humans

theverge.com

Hotel sacks half of its robot staff for being bad at their jobs

Hotel sacks half of its robot staff for being bad at their jobs

independent.ie

Japan’s Henn na Hotel fires half its robot workforce

Japan’s Henn na Hotel fires half its robot workforce

hotelmanagement.net

Robot Hotel Loses Love for Robots
wsj.com · 2019

SASEBO, Japan—Yoshihisa Ishikawa’s one-night stay at a robot-staffed hotel in western Japan wasn’t relaxing.

He was roused every few hours during the night by the doll-shaped assistant in his room asking: “Sorry, I couldn’t catch that. Coul…

Robots Ruin Robot Hotel
gizmodo.com · 2019

Hotel owner Hideo Sawada said he wanted to run “the most efficient hotel in the world” by staffing it almost exclusively with robots. According to a new report, however, the hotel has laid off more than half of its bots for being inefficien…

Japan’s robot hotel lays off half the robots after they created more work for humans
theverge.com · 2019

It turns out that even robots are having a tough time holding down a job. Japan’s Henn-na “Strange” Hotel has laid off half its 243 robots after they created more problems than they could solve, as first reported by The Wall Street Journal.…

Hotel sacks half of its robot staff for being bad at their jobs
independent.ie · 2019

A high-tech hotel in Japan has been forced to lay off half of its robot staff after finding they were incompetent and created more work for humans.

he robots were introduced partly as a novelty and partly to reduce the need for human staff …

Japan’s Henn na Hotel fires half its robot workforce
hotelmanagement.net · 2019

Japan’s Henn na Hotel, which first opened in 2015 with a staff of robots, has cut its robotic workforce after the experience failed to reduce costs or workload for its employees.

The hotel, which is located in Nagasaki, will reduce its 243-…

Variants

A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.

Similar Incidents

By textual similarity

Did our AI mess up? Flag the unrelated incidents

Robot kills worker at German Volkswagen plant

Robot kills worker at German Volkswagen plant

Jul 2014 · 27 reports
Security Robot Drowns Itself in a Fountain

Security Robot Drowns Itself in a Fountain

Jul 2017 · 30 reports
Female Applicants Down-Ranked by Amazon Recruiting Tool

Female Applicants Down-Ranked by Amazon Recruiting Tool

Aug 2016 · 33 reports
Previous IncidentNext Incident

Similar Incidents

By textual similarity

Did our AI mess up? Flag the unrelated incidents

Robot kills worker at German Volkswagen plant

Robot kills worker at German Volkswagen plant

Jul 2014 · 27 reports
Security Robot Drowns Itself in a Fountain

Security Robot Drowns Itself in a Fountain

Jul 2017 · 30 reports
Female Applicants Down-Ranked by Amazon Recruiting Tool

Female Applicants Down-Ranked by Amazon Recruiting Tool

Aug 2016 · 33 reports

Research

  • Defining an “AI Incident”
  • Defining an “AI Incident Response”
  • Database Roadmap
  • Related Work
  • Download Complete Database

Project and Community

  • About
  • Contact and Follow
  • Apps and Summaries
  • Editor’s Guide

Incidents

  • All Incidents in List Form
  • Flagged Incidents
  • Submission Queue
  • Classifications View
  • Taxonomies

2024 - AI Incident Database

  • Terms of use
  • Privacy Policy
  • Open twitterOpen githubOpen rssOpen facebookOpen linkedin
  • 300d90c