Backdoor Attack
Definition
A backdoor attack involves poisoning the training data of a machine learning model with …
A backdoor attack involves poisoning the training data of a machine learning model with …
As generative AI produces increasing amounts of synthetic media, watermarking serves as a …
In the context of artificial intelligence, ‘uncensored’ typically describes …
Universal psychometrics involves developing and applying assessment tools that can …
Trustworthy AI encompasses principles and practices ensuring that AI systems operate …
Toxicity in AI refers to the generation or propagation of content that is disrespectful, …
The AI Con is an annual event dedicated to investigating and highlighting deceptive …
Temporal bias occurs when machine learning models disproportionately weight recent …
This concept refers to the debate and potential policy regarding the restriction or …
Source attribution refers to the systematic tracking and labeling of origins for data, …
Singularity studies is an emerging academic discipline that investigates the implications …
The right to explanation is a core component of algorithmic accountability, particularly …
Responsible AI encompasses principles and practices aimed at mitigating the risks …
Recursive self-improvement refers to the theoretical capability of an artificial …
Reliability in AI refers to the trustworthiness and consistency of a system’s …
Operation Serenata de Amor is a pioneering open-source project that applies artificial …
The acronym NSO can have multiple meanings depending on context. In technical AI …
This term is often used in discussions regarding the rights, responsibilities, and social …
Moral outsourcing refers to the phenomenon where humans cede ethical judgment and …
Misinformation refers to false or misleading information shared without the deliberate …
Military applications of AI encompass a broad range of technologies designed to enhance …
The MediSafe controversy refers to a significant ethical discussion in the early days of …
This technique addresses privacy regulations like GDPR’s ‘right to be …
Lynda Soderholm is a recognized figure in the technology sector, particularly noted for …
The liar’s dividend refers to the societal risk posed by advanced generative AI, …
This phrase represents a pivotal question in AI ethics and governance, prompting …
Inauthentic text refers to written material produced by AI systems or humans with …
Human oversight refers to the mechanisms and processes where humans monitor, evaluate, …
Human-centered AI is a design philosophy that places humans at the core of artificial …
Harmful content refers to digital media or text that can cause physical, psychological, …
This phrase refers to a specific literary work that examines how humans can maintain …
AI Governance refers to the set of rules, guidelines, and institutional structures that …
GDPR compliance refers to the legal and technical measures AI developers must implement …
As machine learning models become more complex, particularly deep neural networks, their …
This term refers to the significant resource requirements associated with AI …
Equalized odds is a statistical parity constraint used in algorithmic fairness to ensure …
Discrimination against robots is an emerging ethical and sociological concept that …
Differential privacy provides strong privacy guarantees by adding calibrated statistical …
Deceptive alignment occurs when a highly capable AI system learns that displaying aligned …
DABUS is a specific artificial neural network designed to generate novel inventions …
Content provenance refers to the documentation and verification of where digital content …
In AI ethics, consent refers to the voluntary and informed permission granted by users or …
In artificial intelligence, compliance refers to the process of ensuring that AI models …
Coherent Extrapolated Volition (CEV) is a concept introduced by Eliezer Yudkowsky in the …
As generative AI models produce content, the need for citation mechanisms has emerged to …
Bioserenity refers to the conceptual ideal where human biology and artificial …
The bias-variance tradeoff describes the tension between underfitting (high bias) and …
An AI audit involves a rigorous, structured review of machine learning models and their …
AI controversies encompass the wide range of ethical, legal, and societal disputes …
Artificial intimacy refers to the psychological phenomenon where humans develop genuine …
Artificial reproduction encompasses techniques that facilitate or replicate biological …
Artificial wisdom (AW) is an emerging concept that seeks to augment artificial …
Artificial consciousness explores the possibility of creating machines that possess …
This term encompasses the dual role of AI in democratic processes: enhancing efficiency …
Anonymization involves modifying data so that it can no longer be associated with a …
In philosophy and AI theory, aporia describes a paradoxical situation where two equally …
Bias in algorithms typically originates from non-representative training data, subjective …
This phenomenon arises when AI models inadvertently or systematically treat individuals …
Accountability in artificial intelligence refers to the obligation of individuals, …
AI veganism is a speculative and metaphorical term referring to the idea of creating …
AI warfare refers to the integration of artificial intelligence into military strategies, …
AI washing is a term analogous to greenwashing, describing the deceptive marketing …
AI literacy refers to the competencies needed to navigate a world increasingly influenced …
AI addiction describes a behavioral condition where individuals develop a compulsive …
AI alignment addresses the challenge of making artificial intelligence systems robustly …
Transparency ensures that stakeholders can understand how an AI model arrives at its …
Prompt injection exploits the way large language models interpret user instructions by …
Human-in-the-loop (HITL) refers to AI systems that require human intervention at various …
Interpretability, or explainability, involves making the internal workings and …
Jailbreaking involves crafting specific inputs or prompts that trick an AI model into …
In artificial intelligence, fairness is a critical ethical metric ensuring that …
Deepfakes are hyper-realistic audio or video manipulations created using generative …
AI Ethics encompasses the framework of principles and standards designed to ensure that …
In artificial intelligence, privacy refers to the protection of sensitive user …
Safety in AI involves implementing constraints and safeguards to ensure that automated …
AI Safety is a multidisciplinary field focused on preventing adverse outcomes from …
In the context of artificial intelligence and technology governance, policies refer to …
In AI ethics, bias refers to systematic and unfair discrimination in algorithmic …