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

Stereotype Threat and Self-fulfilling Prophecies02:09

Stereotype Threat and Self-fulfilling Prophecies

41.9K
When we hold a stereotype about a person, we have expectations that he or she will fulfill that stereotype. A self-fulfilling prophecy is an expectation held by a person that alters his or her behavior in a way that tends to make it true. When we hold stereotypes about a person, we tend to treat the person according to our expectations. This treatment can influence the person to act according to our stereotypic expectations, thus confirming our stereotypic beliefs. Research by Rosenthal and...
41.9K
Fundamental Attribution Error01:14

Fundamental Attribution Error

13.7K
According to some social psychologists, people tend to overemphasize internal factors as explanations—or attributions—for the behavior of other people. They tend to assume that the behavior of another person is a trait of that person, and to underestimate the power of the situation on the behavior of others. They tend to fail to recognize when the behavior of another is due to situational variables, and thus to the person’s state. This erroneous assumption is...
13.7K
Global Climate Change01:50

Global Climate Change

28.8K
Throughout its ~4.5 billion year history, the Earth has experienced periods of warming and cooling. However, the current drastic increase in global temperatures is well outside of the Earth’s cyclic norms, and evidence for human-caused global climate change is compelling. Paleoclimatology, the study of ancient climate conditions, provides ample evidence for human-caused global climate change by comparing recent conditions with those in the past.
28.8K
Stereotype Content Model02:16

Stereotype Content Model

15.4K
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...
15.4K
What is Conservation Biology?01:57

What is Conservation Biology?

24.0K
Conservation biology is a scientific field that focuses on the preservation of biodiversity in order to protect ecosystems while meeting the needs of the human population. Humans require properly functioning ecosystems to maintain our supply of natural resources, including food, medicines, and building materials.
24.0K

You might also read

Related Articles

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

Sort by
Same author

Distinct roles of hippocampus and neocortex in symbolic compositional generalization.

Neuron·2026
Same author

Representativeness and response validity across nine opt-in online samples.

Nature human behaviour·2026
Same author

Collective emotion regulation.

The American psychologist·2026
Same author

Human curriculum learning of a cue combination task.

Nature human behaviour·2026
Same author

Learning affect norms: Implications for predictions, experiences, and social judgments.

Journal of experimental psychology. General·2026
Same author

Challenging the mechanism for the implicit association test.

Nature human behaviour·2026

Related Experiment Video

Updated: Jan 24, 2026

Time-lapse Imaging of Bacterial Swarms and the Collective Stress Response
06:26

Time-lapse Imaging of Bacterial Swarms and the Collective Stress Response

Published on: May 23, 2020

8.9K

How malicious AI swarms can threaten democracy.

Daniel Thilo Schroeder1, Meeyoung Cha2, Andrea Baronchelli3

  • 1Department of Sustainable Communication Technologies, SINTEF Digital, Oslo, Norway.

Science (New York, N.Y.)
|January 22, 2026
PubMed
Summary

Agentic artificial intelligence (AI) combined with large language models (LLMs) creates new challenges in information warfare. This fusion presents novel threats and requires advanced strategies for defense and analysis.

More Related Videos

Quantifying Bacterial Surface Swarming Motility on Inducer Gradient Plates
05:57

Quantifying Bacterial Surface Swarming Motility on Inducer Gradient Plates

Published on: January 5, 2022

4.2K
Bioparticle Microarrays for Chemotactic and Molecular Analysis of Human Neutrophil Swarming in vitro
11:21

Bioparticle Microarrays for Chemotactic and Molecular Analysis of Human Neutrophil Swarming in vitro

Published on: February 16, 2020

5.5K

Related Experiment Videos

Last Updated: Jan 24, 2026

Time-lapse Imaging of Bacterial Swarms and the Collective Stress Response
06:26

Time-lapse Imaging of Bacterial Swarms and the Collective Stress Response

Published on: May 23, 2020

8.9K
Quantifying Bacterial Surface Swarming Motility on Inducer Gradient Plates
05:57

Quantifying Bacterial Surface Swarming Motility on Inducer Gradient Plates

Published on: January 5, 2022

4.2K
Bioparticle Microarrays for Chemotactic and Molecular Analysis of Human Neutrophil Swarming in vitro
11:21

Bioparticle Microarrays for Chemotactic and Molecular Analysis of Human Neutrophil Swarming in vitro

Published on: February 16, 2020

5.5K

Area of Science:

  • Artificial Intelligence
  • Cybersecurity
  • Information Warfare

Background:

  • The integration of agentic AI and large language models (LLMs) represents a significant technological advancement.
  • This convergence introduces unprecedented capabilities and potential risks in the digital domain.

Purpose of the Study:

  • To explore the implications of combining agentic AI with LLMs.
  • To identify the emerging threats and opportunities in the field of information warfare.

Main Methods:

  • Conceptual analysis of agentic AI and LLM functionalities.
  • Review of current information warfare tactics and strategies.
  • Forecasting potential future scenarios and impacts.

Main Results:

  • The fusion of agentic AI and LLMs creates sophisticated tools for information manipulation.
  • New vulnerabilities in information ecosystems are identified.
  • The potential for autonomous information operations is significantly increased.

Conclusions:

  • The advent of agentic AI-LLM fusion necessitates a re-evaluation of information warfare paradigms.
  • Proactive development of countermeasures and ethical guidelines is crucial.
  • Further research is needed to understand and mitigate the risks associated with this technological frontier.