AIMC Topic: Deception

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Can robots lie? A posthumanist approach to robotic animals and deceptive practices in dementia care.

Journal of aging studies
Robotic animals are designed to resemble real, living animals, but at the same time, dementia care guidelines and policies often emphasize the value of transparency in relation to robots-people should not be led to believe that robots have capacities...

Prescribed performance adaptive neural event-triggered control for switched nonlinear cyber-physical systems under deception attacks.

Neural networks : the official journal of the International Neural Network Society
In this paper, the design of an adaptive neural event-triggered control scheme for a class of switched nonlinear systems affected by external disturbances and deception attacks is presented. In order to address the effects caused by unknown disturban...

Detecting deception with artificial intelligence: promises and perils.

Trends in cognitive sciences
Rapid advancements in artificial intelligence (AI) have driven interest in its potential application for lie detection. Unfortunately, the current approaches have primarily focused on technical aspects at the expense of a solid methodological and the...

Role play with large language models.

Nature
As dialogue agents become increasingly human-like in their performance, we must develop effective ways to describe their behaviour in high-level terms without falling into the trap of anthropomorphism. Here we foreground the concept of role play. Cas...

Deception detection with machine learning: A systematic review and statistical analysis.

PloS one
Several studies applying Machine Learning to deception detection have been published in the last decade. A rich and complex set of settings, approaches, theories, and results is now available. Therefore, one may find it difficult to identify trends, ...

Protecting world leaders against deep fakes using facial, gestural, and vocal mannerisms.

Proceedings of the National Academy of Sciences of the United States of America
Since their emergence a few years ago, artificial intelligence (AI)-synthesized media-so-called deep fakes-have dramatically increased in quality, sophistication, and ease of generation. Deep fakes have been weaponized for use in nonconsensual pornog...

Recursive Minimum-Variance Filter Design for State-Saturated Complex Networks With Uncertain Coupling Strengths Subject to Deception Attacks.

IEEE transactions on cybernetics
In this article, the recursive filtering problem is investigated for state-saturated complex networks (CNs) subject to uncertain coupling strengths (UCSs) and deception attacks. The measurement signals transmitted via the communication network may su...

IAT faking indices revisited: Aspects of replicability and differential validity.

Behavior research methods
Research demonstrates that IATs are fakeable. Several indices [either slowing down or speeding up, and increasing errors or reducing errors in congruent and incongruent blocks; Combined Task Slowing (CTS); Ratio 150-10000] have been developed to dete...

Leveraging Computational Intelligence Techniques for Defensive Deception: A Review, Recent Advances, Open Problems and Future Directions.

Sensors (Basel, Switzerland)
With information systems worldwide being attacked daily, analogies from traditional warfare are apt, and deception tactics have historically proven effective as both a strategy and a technique for Defense. Defensive Deception includes thinking like a...

Event-Triggered Output Feedback Synchronization of Master-Slave Neural Networks Under Deception Attacks.

IEEE transactions on neural networks and learning systems
The problem of event-triggered synchronization of master-slave neural networks is investigated in this article. It is assumed that both communication channels from the sensor to controller and from controller to actuator are subject to stochastic dec...