Jove
Visualize
Contact Us

Related Concept Videos

Distribution Reliability and Automation01:25

Distribution Reliability and Automation

93
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
93
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.5K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
5.5K
Quality Assurance01:19

Quality Assurance

108
Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
108
Uncertainty: Overview00:59

Uncertainty: Overview

454
In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
454
Actuarial Approach01:20

Actuarial Approach

44
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
44
Ethical Standards I01:25

Ethical Standards I

759
The American Nurses Association (ANA) created and implemented the first nationally accepted Code of Ethics for Nurses with Interpretive Statements. The Code of Ethics is a living document regularly updated by the ANA and establishes an ethical standard that is non-negotiable for nurses in all roles and settings.
The Code of Ethics provisions outline the nurse's duty to the patient, the healthcare team, the profession, and society. The Code's fundamental principles include advocacy,...
759

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Comparison of time series and mechanistic models of vector-borne diseases.

Spatial and spatio-temporal epidemiologyยท2022
See all related articles
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: May 14, 2025

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.0K

TAI-PRM: trustworthy AI-project risk management framework towards Industry 5.0.

Eduardo Vyhmeister1, Gabriel G Castane1

  • 1Insight Centre of Data Analytics, University College Cork, Cork, Ireland.

AI and Ethics
|May 12, 2025
PubMed
Summary

The TAI-PRM framework integrates ethical considerations into AI risk management for manufacturing, moving towards Industry 5.0. This approach ensures the development and deployment of trustworthy AI systems by addressing societal and human-centric needs.

Keywords:
Artificial IntelligenceFMEAIndustry 5.0Risk ManagementTrustworthy AI

More Related Videos

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
06:18

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm

Published on: October 20, 2022

2.0K
Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios
06:02

Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios

Published on: October 6, 2020

2.2K

Related Experiment Videos

Last Updated: May 14, 2025

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.0K
The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
06:18

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm

Published on: October 20, 2022

2.0K
Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios
06:02

Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios

Published on: October 6, 2020

2.2K

Area of Science:

  • Manufacturing Technology
  • Artificial Intelligence Ethics
  • Risk Management

Background:

  • Industry 4.0 heavily relies on AI for automation and data processing.
  • Transitioning to Industry 5.0 necessitates integrating human-centric and societal dimensions into AI development.
  • Existing AI practices require ethical considerations to be blended with standards and risk management.

Purpose of the Study:

  • To introduce the TAI-PRM framework for managing risks associated with AI artefacts in manufacturing.
  • To incorporate ethical considerations as hazards within risk management processes.
  • To enable the development and deployment of trustworthy AI in the manufacturing sector.

Main Methods:

  • Developed the TAI-PRM framework, building upon Failure Mode and Effect Analysis (FMEA) and ISO 31000.
  • Identified ethical considerations as hazards impacting system processes and sustainability.
  • Applied the framework in an EU project focused on AI for Digital Twins in manufacturing.

Main Results:

  • The TAI-PRM framework effectively identifies and tracks failure modes in AI artefacts.
  • The framework aids users in managing ethical risks related to AI deployment.
  • Validation in an EU project demonstrated the framework's utility for trustworthy AI in manufacturing.

Conclusions:

  • The TAI-PRM framework provides a structured approach to managing ethical risks in AI for manufacturing.
  • Integrating ethical considerations into risk management is crucial for Industry 5.0.
  • The framework supports the creation of reliable and human-centric AI systems in industrial settings.