Jove
Visualize
Contact Us
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 Concept Videos

Conformity01:20

Conformity

45.2K
Conformity is the change in a person’s behavior to go along with the group, even if that person does not agree with the group.
45.2K
Stereotype Content Model02:16

Stereotype Content Model

14.7K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.7K
Ethical Issues01:27

Ethical Issues

968
Nurses are essential in patient care, upholding the ethical principles of their profession and effectively navigating ethical dilemmas. Neglecting ethical issues can lead to inadequate patient care, compromised therapeutic relationships, and moral distress among healthcare workers.
Ethical Concerns in Healthcare:
968
Humanistic Psychology01:24

Humanistic Psychology

1.1K
Humanistic psychology emerged in the mid-20th century as a response to the deterministic and pessimistic nature of behaviorism and psychoanalysis. While behaviorism focused on observable behaviors influenced by the environment and psychoanalysis delved into unconscious motivations, both theories suggested that human actions lacked free will. In contrast, humanistic psychology offers a perspective that emphasizes the innate potential for goodness and growth within every individual.
This approach...
1.1K
Self-Discrepancy Theory02:45

Self-Discrepancy Theory

18.3K
One influential perspective on what motivates people's behavior is detailed in Tory Higgin's self-discrepancy theory (Higgins, 1987). He proposed that people hold disagreeing internal representations of themselves that lead to different emotional states.  
18.3K
Uncertainty: Overview00:59

Uncertainty: Overview

555
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.
555

You might also read

Related Articles

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

Sort by
Same author

Designing and Evaluating Digital Mental Health Interventions: Scoping Review.

JMIR mental health·2026
Same author

From human teams to hybrid intelligence teams: identifying, characterizing, and evaluating foundational quality attributes.

Autonomous agents and multi-agent systems·2026
Same author

Exploring the effect of automation failure on the human's trustworthiness in human-agent teamwork.

Frontiers in robotics and AI·2023
Same author

Drivers of partially automated vehicles are blamed for crashes that they cannot reasonably avoid.

Scientific reports·2022
Same author

A Unifying Framework for Reinforcement Learning and Planning.

Frontiers in artificial intelligence·2022
Same author

What values should an agent align with?: An empirical comparison of general and context-specific values.

Autonomous agents and multi-agent systems·2022

Related Experiment Video

Updated: Jul 5, 2025

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations
09:07

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Published on: September 16, 2015

9.0K

Normative uncertainty and societal preferences: the problem with evaluative standards.

Sietze Kai Kuilman1, Koji Andriamahery2, Catholijn M Jonker1

  • 1Intelligent Systems Department, Faculty of Electrical Engineering, Mathematics & Computer Science, Delft University of Technology, Delft, Netherlands.

Frontiers in Neuroergonomics
|January 18, 2024
PubMed
Summary

Borda voting can help artificial intelligence (AI) systems align with human values by aggregating preferences. However, successfully implementing AI ethics requires careful consideration of ethical principle formulation and uncertainty management.

Keywords:
ethicslimit of formsmoral machinenormative uncertaintypreference profilesself-driving cars

More Related Videos

The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies
08:24

The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies

Published on: August 25, 2023

734
Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

6.9K

Related Experiment Videos

Last Updated: Jul 5, 2025

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations
09:07

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Published on: September 16, 2015

9.0K
The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies
08:24

The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies

Published on: August 25, 2023

734
Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

6.9K

Area of Science:

  • AI Ethics and Governance
  • Computational Social Choice
  • Moral Philosophy

Background:

  • Increasing autonomy of technological systems necessitates ethical alignment with human values.
  • AI systems pose significant risks, demanding robust control mechanisms beyond traditional error handling.
  • Societal value pluralism complicates defining universal ethical principles for machines.

Purpose of the Study:

  • To investigate Borda voting as a method for maximizing expected choice-worthiness in AI ethical implementations.
  • To assess the effectiveness of Borda voting using empirical data from the Moral Machine experiment.
  • To analyze the challenges and limitations in applying collective choice mechanisms to AI ethics.

Main Methods:

  • Examined Borda voting as a mechanism for aggregating diverse ethical preferences.
  • Utilized data from the Moral Machine experiment to simulate and evaluate the voting system's performance.
  • Analyzed the impact of different ethical principle formulations on the maximization of choice-worthiness.

Main Results:

  • Borda voting demonstrates average effectiveness in achieving outcomes preferred by a majority.
  • The success of maximizing expected choice-worthiness is highly sensitive to the precise formulation of ethical principles.
  • Significant challenges remain in accurately formulating credences and managing uncertainty within such systems.

Conclusions:

  • Borda voting offers a potential framework for AI systems to adhere to collective moral beliefs.
  • Implementation requires caution due to the dependency on principle formulation and inherent difficulties in maximizing choice-worthiness.
  • Further research is needed to address fundamental challenges in ethical AI governance before widespread adoption.