Incident #173·AI Safety & Failures

AI Tools Failed to Sufficiently Predict COVID Patients, Some Potentially Harmful

July 30, 20211 reportsView on AIID

Explainability

Description

AI tools failed to sufficiently predict COVID patients, some potentially harmful.

Actors

Alleged Deployers

unknown

Alleged Developers

unknown

Harmed Parties

doctors
covid-patients

Classification

Risk Domain

AI Safety & Failures

Risk Subdomain

7.3. Lack of capability or robustness

MIT Risk Profile

HumanUnintentionalPost-deployment

Topics

Explainability

Source

Related Incidents (AI Safety & Failures)

View all →

#545

Chatbot Tessa gives unauthorized diet advice to users seeking help for eating disorders

May 2023

#57

Australian Automated Debt Assessment System Issued False Notices to Thousands

Jul 2015

#34

Amazon Alexa Responding to Environmental Inputs

Research Papers on This Topic

View all →

Concrete Problems in AI Safety

3,612 citationsJun 2016

A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI

2,338 citationsJul 2019

Representation Engineering: A Top-Down Approach to AI Transparency

1,499 citationsOct 2023

Explainable artificial intelligence (XAI) in deep learning-based medical image analysis

1,178 citationsJul 2021

Mitigation Tools

Tools related to this risk domain, via shared responsible AI topics.

Open Source

View all →

lime

marcotcr/lime

Lime: Explaining the predictions of any machine learning classifier

⭐ 12,100

facets

PAIR-code/facets

Visualizations for machine learning datasets

⭐ 7,374

interpret

interpretml/interpret

Fit interpretable models. Explain blackbox machine learning.

⭐ 6,788

captum

Source Reports(1 total)

Hundreds of AI tools have been built to catch covid. None of them helped.

technologyreview.com· Jul 2021

Description

Actors

Classification

Topics

Source

Related Incidents (AI Safety & Failures)

Research Papers on This Topic

Mitigation Tools

Open Source

Source Reports(1 total)

Commercial