Undoubtedly, artificial intelligence can write convincing essays, design beautiful logos, and answer long-winding questions about anything under the sun. But while it's eloquent, does it really understand context? Josh Adler, Melanie Mitchell, and Douglas Rushkoff, three artificial intelligence specialists, share their views on whether artificial intelligence understands context or not.

According to the specialists, artificial intelligence does an excellent job at recognizing form, but not substance. Modern AI can predict the next word in a sentence with stunning precision, but it has no idea what that sentence actually means. "If you dig deep, you realize that AI doesn't actually carry context forward," mentions entrepreneur Josh Adler. "Every time you interact with it, it rereads everything that came before and reprocesses it from scratch. Therefore, it's not holding meaning, it's reconstructing it."

Artificial Intelligence Doesn't Understand Context

Melanie Mitchell, who's spent decades studying how humans reason by analogy, calls this the defining limitation of machine learning. "A pile of narrow intelligences will never add up to a general intelligence," she said. Until machines can learn to make analogies, they won't understand the world the way we do, she adds.

Author and entrepreneur Josh Adler takes that idea and pushes it further. "Humans don't need to replay every single memory before making a decision," he says. "We compress experience and act from intuition. AI doesn't know how to do that, it just re-reads the transcript." Furthermore, Douglas Rushkoff frames it as a cultural problem rather than a technical one. According to him, AI are machines that simulate dialogue, but are stripped of context. To him, AI reflects the same logic as modern markets, endless output detached from meaning.

Artificial Intelligence Doesn't Really Understand Context

Context, in simple human terms, is a living sense of continuity. It's how we know what matters in a conversation and what doesn't. As humans, we forget, generalize, and move forward. Machines can't do this.

Mitchell points out that even large language models, with their billions of parameters, still treat text as simply statistics. Adler likens it to "talking to someone with perfect recall but no awareness." The system remembers everything, but it can't decide what's important for itself. It's fast, articulate, and fundamentally hollow.

The Illusion of Intelligence

Part of AI's appeal is that it sounds extremely intelligent. It writes fluently, reasons convincingly, and occasionally even surprises us.

However, according to the specialists, coherence doesn't always mean comprehension. "When you talk to an AI," Josh Adler adds, "you're not talking to something that understands you. You're talking to something that's excellent at echoing you."

That echo, Mitchell warns, can sound more human than it actually is. Because language models mirror patterns from human data, their output triggers our instinct to project understanding. We imagine intention where there's only probability.

What Real Understanding Would Look Like

For all three specialists, the next frontier of AI isn't scale, but its structure. True understanding will require machines that can hold semantic state: internal representations that persist, evolve, and prioritize meaning.

"Context isn't something you can bolt on after the fact," Josh Adler says. "It has to be built into the system's way of thinking. A memory that updates, not resets."

Artificial Intelligence Limitations: Memory, Emotion, and Self-Reference

The shared conclusion: understanding isn't computation, it's compression. It's the ability to hold experience in motion, not replay it line by line as done by AI.

"AI doesn't live in time," Josh concludes. "It scrolls through it." Until that changes, machines will keep producing language that sounds profound but lacks the memory, emotion, and self-reference that make meaning real. AI's intelligence is impressive, but the awareness is still largely missing.