Learn three (more) core AI acronyms
A long read about three AI terms worth learning (and a bonus)
Whether you're reading about AI development, discussing system capabilities or explaining how AI models work, some acronyms are going to keep coming up over and over.
My first newsletter in this series covered acronyms for a reason. They’re everywhere in tech. And now it’s time for an acronym follow up, and my first long(ish) read of The AI Message. Grab a coffee!
As AI discussions become more technical, you'll encounter these acronyms regularly.
Each describes important aspects of how AI systems work, how they're trained and what they might become.
They’re critical acronyms, and critical concepts. Each can help you communicate about AI more confidently.
Human in the Loop (HITL)
What it means: HITL refers to AI systems where humans (or people, as we prefer to call ourselves!) are actively involved in the process - reviewing outputs, providing feedback, and making final decisions.
Why it matters: When companies claim their AI has "human oversight," they're often referring to HITL processes. This is especially important in areas like healthcare, legal or financial services.
Real-world context: HITL is more than an ethical safeguard - it's often where the real value occurs. The most effective AI implementations combine machine efficiency with human judgment.
How to use it: When discussing AI safety measures or explaining why your system won't run amok, HITL is your go-to term. It reassures stakeholders that humans remain in control.
Reinforcement Learning with Human Feedback (RLHF)
What it means: RLHF is how modern AI systems learn to be helpful, harmless and honest. In a nutshell, human trainers rate AI responses, and those ratings teach the AI system what kinds of outputs humans prefer.
Why it matters: RLHF is what transformed early language models (which often produced unhelpful content) into the more responsible systems we use today. It's the difference between raw AI capabilities and actually-useful AI products.
Real-world context: When ChatGPT seems polite or refuses to generate harmful content, that's largely thanks to RLHF. This training method helps align AI behavior with human values.
How to use it: When stakeholders ask about AI safety, ethics or how systems learn appropriate behavior, RLHF provides a concrete answer that shows there's a systematic approach.
Artificial General Intelligence (AGI) and Artificial Superintelligence (ASI)
What it means: AGI refers to hypothetical future AI that could perform any intellectual task a human can. ASI goes further - it's a theoretical system smarter than the brightest humans across all domains.
Why it matters: These terms help distinguish between today's specialized AI tools (which excel at specific tasks) and the kind of general-purpose AI that exists in science fiction.
Real-world context: Despite the headlines, today's most advanced AI models remain narrowly focused. They're powerful within their domains but lack general capabilities. Understanding this distinction helps combat hype and fear.
How to use it: When stakeholders confuse current AI capabilities with sci-fi scenarios, these terms help reset expectations. They provide a framework for discussing AI development honestly.
Why these matter for marketing and communications professionals
Understanding AI acronyms won’t just help you decode technical conversations, it gives you the understanding and vocabulary to:
Frame AI capabilities accurately
Address safety and ethical concerns concretely
Set appropriate expectations with your stakeholders
Position your organization's AI approach intelligently - internally and externally
There’s an important difference between repeating AI buzzwords and communicating about AI with confidence and precision.
Use these terms correctly and you’ll get better at the latter, demonstrating a sophisticated understanding that builds credibility with your technical and non-technical audiences.
Congrats for making it this far! Did this longread work for you? Or do you prefer them short and snappy? If you've got any feedback, reply and let me know.More rapid reads
Prepare now for when AI makes things up
AI has been "about to change everything" for decades
Craft stable AI messaging in changing times