Artificial Intelligence (AI) and Synthetic Media are tools that organizations can use to create, secure, and verify digital content. Here is an overview of this advancing technology, plus a glossary of the most common acronyms in the overlapping fields of AI, cybersecurity, and digital trust.

 

What Is Artificial Intelligence (AI)-Generated Content?

AI-generated content is material developed by an AI model. The content could be written, visual, or audio. This content can include media that has been altered or synthesized in some way based on specific inputs or prompts.

 

What are some AI-generated content examples? 

  • AI-generated content includes AI-written blog posts and product descriptions, automatically generated videos or ads, and AI-generated music or art.
  • AI voice assistants and virtual presenters

 

Why is AI-generated content Important?

AI-generated content enables faster creativity, personalization, and productivity. It also presents challenges to authenticity, IP, and trust in digital communication.

 

AI content

 

What Are Deepfakes?

Deepfakes are a type of synthetic media in which artificial intelligence is used to replace or manipulate the likeness of an individual, usually a video or voice recording, making it appear that they said or did something they did not. Typically created with deep neural networks trained to analyze and replicate facial movements, speech, and gestures. The result is a very realistic forgery.

 

How are deepfakes used legitimately?

Movie production, special effects, education, parody, or digital restoration.

 

How are deepfakes abused? 

To spread disinformation, steal identities, and launch social-engineering attacks.

 

How do Deepfakes Impact Cybersecurity?

Deepfakes are an emerging vector for phishing, business email compromise (BEC), and impersonation attacks and make solutions for detection, verification, and digital trust frameworks critical.

 

Deepfake

 

What Is Synthetic Media?

Synthetic media is any text, image, video, or audio content that is written, altered, or generated with the help of artificial intelligence (AI). Instead of being recorded or authored by people alone, synthetic media is written by machine learning models like generative adversarial networks (GANs) and diffusion models.

Synthetic media can be used to create realistic people, voices, and places that look, sound, and act like the real thing. It makes it difficult to determine what is real or manufactured.  

 

Why Do People Use Synthetic Media?

Synthetic media can be used for many applications and benefits, such as driving creative production, marketing automation, accessibility features, training simulations, and more. But it can also have harmful or malicious uses, like privacy, misinformation, and cybersecurity, when used for deception or impersonation.

What are Examples of Synthetic Media?

  • Text: Articles, scripts, or chatbot responses written by large language models like GPT.
  • Images: AI-generated art or product images made with diffusion models like DALL·E, Midjourney.
  • Audio: Voice cloning, text-to-speech, or AI-generated music.
  • Video: Deepfakes, digital avatars, or virtual simulations.
  • Mixed-Media Experiences: Interactive or multi-modal AI-generated content that combines several of the above.

 

AI synthetic

 

AI GLOSSARY

AI and Machine Learning Terms

AI (Artificial Intelligence): Computer technology that mimics human intelligence, like logical reasoning, learning, pattern detection, and perception.

AGI (Artificial General Intelligence): An AI with the ability to perform any intellectual task that a human can (Goal of far-future AI).

ML (Machine Learning): Computer systems that can learn and improve from data without being explicitly programmed to do so.

DL (Deep Learning): Machine learning algorithms that use a neural network to teach a computer to recognize patterns in complex data.

NN (Neural Network): A type of AI modeled on the neural network connections in the human brain, and used to recognize patterns and predict outcomes.

LLM (Large Language Model): AI systems like GPT-5, Gemini, Claude, trained on diverse text datasets to understand and write human-like language.

NLP (Natural Language Processing): A form of AI that can understand, interpret, and generate human language (used for chatbots, summaries, voice interfaces, etc. ).

RAG (Retrieval-Augmented Generation): A process that augments generative AI output with information from other sources for more accurate and contextualized answers.

 

Synthetic Media and Generative AI Terms

Synthetic Media: Digital media (text, audio, image, or video) that has been computer-generated or altered using AI (Used for marketing, training, simulation, but weaponized for deepfakes and disinformation if abused).

AIGC (Artificial Intelligence-Generated Content): Artificially generated media or text written by an AI model based on a human-written prompt.

GAN (Generative Adversarial Network): A type of neural network architecture with two components trained to outdo each other to generate realistic synthetic data (Deepfakes).

VAE (Variational Autoencoder): A type of generative AI that learns a compressed representation of data to generate new synthetic samples.

Diffusion Model: A type of generative AI algorithm that creates images by reversing a noisification process (DALL·E, Midjourney, Stable Diffusion).

DF (Deepfake): Highly realistic synthetic video and audio created using AI models to imitate the likeness and voice of a target person (Deepfakes).

TTS (Text-to-Speech): AI software used to convert written text into a spoken voice.

STT (Speech-to-Text): A speech recognition AI used to transcribe speech into written text.

V2V (Voice-to-Voice): Software that transforms one person’s voice into another person’s voice while retaining tone and intention (Voice Cloning).

 

AI Development & Infrastructure Terms

API (Application Programming Interface): A software interface that allows programs or different AI models to interact with each other.

GPU (Graphics Processing Unit): A hardware chip that can be configured for AI to make machine learning calculations more quickly.

TPU (Tensor Processing Unit): A chip architecture designed by Google for machine learning applications.

MLOps (Machine Learning Operations): Best practices for planning, developing, deploying, and monitoring the performance of AI models at scale.

AIOps (AI for IT Operations): Tools that apply AI analytics to optimize and secure IT operations.

 

AI Safety, Ethics, and Governance Terms

XAI (Explainable Artificial Intelligence): AI that is transparent about its inputs, outputs, and decision-making rationale.

RAI (Responsible AI): Frameworks for implementing AI technology safely, fairly, and with accountability.

AIGov (AI Governance): Policies that provide an ethical foundation for AI development, model and data compliance, and security controls.

C2PA (Coalition for Content Provenance and Authenticity): A self-regulatory industry standard that supports AI-generated media provenance.

EU AI Act: The EU’s official artificial intelligence regulatory framework.

 

Cybersecurity & Synthetic Media Risk Terms

BEC (Business Email Compromise): A type of cybercrime that targets enterprise executives, with criminals now using AI voice or video deepfakes for this type of spearphishing.

CTEM (Continuous Threat Exposure Management): A cybersecurity process that evaluates and prioritizes exploitable vulnerabilities on an ongoing basis across the enterprise.

EASM (External Attack Surface Management): A digital risk management process that continuously uncovers and secures all of an organization’s attack surfaces and digital footprint.

SOC (Security Operations Center): A team that collaborates in real time to identify, monitor, and respond to cybersecurity threats.

IAM (Identity and Access Management): Security controls that ensure systems and individuals have only the access they are permitted.

Political Deepfakes Incidents Database (PDID): A collection of politically salient deepfakes, encompassing synthetically-created videos, images, and less-sophisticated `cheapfakes.’ 

 

SEO and AI Search Terms

SEO (Search Engine Optimization): The practice of optimizing a website to rank better in search results for queries.

AEO (Answer Engine Optimization): The practice of optimizing content to better appear in AI-powered search or overview tools (Google AI, Bing Copilot, Perplexity, etc. ).

EEAT (Experience, Expertise, Authoritativeness, Trustworthiness): Google’s content-quality evaluation framework — important for AI and cybersecurity content.

SERP (Search Engine Results Page): The list of web pages that a search engine or AI-powered overview returns in response to a query.

 

Additional AI and Synthetic Media Terms

HITL (Human in the Loop): A reference to artificial intelligence systems that require human interaction at certain points in their training or decision-making process.

DAIR (Data and AI Responsibility): Principles that outline responsible and secure AI and data practices.

SAI (Synthetic Artificial Intelligence): A nascent concept for using synthetic data and generative AI together to power fully artificial ecosystems.

XR (Extended Reality): An umbrella term for AR (Augmented Reality), VR (Virtual Reality), and MR (Mixed Reality) immersive digital experiences.

 

Review Your Security Risks.

 

 

References

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