March 10, 2025 | By Ben Tannenbaum

What Does "Asking an AI" Really Mean? Demystifying AI Responses

When you ask ChatGPT a question, what are you really getting? According to AI researcher and former Tesla AI Director Andrej Karpathy, it's not the mystical wisdom of an artificial superintelligence—it's something much more human.

"People have too inflated sense of what it means to 'ask an AI' about something... Instead of the mysticism of 'asking an AI', think of it more as 'asking the average data labeler' on the internet." — Andrej Karpathy
Person searching on a computer, representing the human effort behind AI responses
Person searching on a computer, representing the human effort behind AI responses

The One-Hour Search Equivalence

Based on our analysis of AI responses and human research patterns, we've found that a typical ChatGPT response is roughly equivalent to what an average human would discover after one hour of search.

This insight fundamentally changes how we should view AI assistance—not as magical or omniscient, but as a significant time-saving tool that compresses human-level research into seconds.

Understanding the Three Key Components

👤 Average Human
  • Not an expert or specialist in the field
  • Lacks domain-specific training or experience
  • No access to specialized knowledge databases
  • Limited ability to evaluate source credibility
⏱️ One Hour
  • Sufficient time to gather basic information
  • Enough to understand fundamental concepts
  • Limited time for cross-referencing or verification
  • Insufficient for deep analysis or synthesis
🔍 Search
  • Primarily surface-level information gathering
  • No access to paywalled content or databases
  • Limited ability to follow citation trails
  • No specialized search techniques or tools

Karpathy's insight helps explain both the impressive capabilities and the limitations of today's AI systems. When you ask ChatGPT a question, you're not tapping into some mystical AI consciousness—you're essentially getting a compressed version of what an average person would find if they spent an hour researching your question online.

The Human Foundation of AI Responses

Large language models like ChatGPT are trained primarily through a process that Karpathy describes as "imitation on data from human labelers." These models learn patterns from vast amounts of human-written text and are then refined through human feedback.

This training approach means that AI responses are fundamentally limited by the quality and breadth of human knowledge they've been exposed to. As Karpathy puts it, "You're not asking some magical AI. You're asking a human data labeler. Whose average essence was lossily distilled into statistical token tumblers that are LLMs."

Deep Research vs. Basic Search

If a standard ChatGPT response equates to an average human's one-hour search, then what would constitute "deep research"? Based on our analysis, deep research would be equivalent to an average human spending ten or more hours on a topic—still limited by human capabilities, but with significantly more depth and breadth.

This is why specialized AI models fine-tuned on specific domains can outperform general models in those areas—they're essentially mimicking humans with more specialized knowledge.

The Role of Human Feedback

The quality of AI responses is directly tied to the quality of human feedback during training. When companies like OpenAI use Reinforcement Learning from Human Feedback (RLHF), they're essentially having human evaluators rate different AI responses, teaching the model which types of answers humans prefer.

Karpathy notes that this process is "just barely RL" (reinforcement learning), suggesting that current AI systems are still heavily dependent on human guidance rather than learning independently through trial and error.

Implications for AI Users

Understanding AI responses as compressed human research has several important implications:

  1. Appropriate expectations: AI can provide quick, human-level summaries but shouldn't be expected to deliver expert-level insights in specialized domains.
  2. Complementary expertise: AI works best when paired with human expertise that can evaluate and contextualize its responses.
  3. Efficiency gains: The primary value of AI is compressing hours of human research into seconds—an enormous efficiency gain even with limitations.
  4. Critical evaluation: Users should apply the same critical thinking to AI responses as they would to information from an average internet researcher.

The Value Proposition

Despite these limitations, the value proposition of AI is extraordinary. Getting the equivalent of an hour of human research in seconds represents a massive productivity multiplier. For many everyday questions and tasks, this level of assistance is more than sufficient.

The key is understanding what you're getting—not superhuman intelligence, but extremely efficient access to average human knowledge.

Looking Forward

As AI systems continue to evolve, we may see models that better approximate expert-level knowledge in specific domains. However, Karpathy's insight suggests that these systems will still fundamentally reflect human knowledge and capabilities, just at a higher level of specialization.

For brands looking to optimize their presence in AI responses, this understanding is crucial. The goal isn't to appeal to some mysterious AI algorithm, but to ensure your brand is well-represented in the human knowledge that AI systems draw upon.

At Aiso, our approach to AI optimization is built on this fundamental understanding of how AI systems work. We help brands ensure they're properly represented in the knowledge base that AI systems access, maximizing visibility in AI responses by focusing on the human foundation of AI knowledge.

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About Aiso

At Aiso, we help brands optimize their presence in AI responses. Our platform analyzes millions of ChatGPT conversations to understand how users interact with AI and what they're searching for. With ChatGPT dominating approximately 90% of LLM traffic, we focus on helping brands maximize their visibility where it matters most. Our research into transactional search patterns provides unique insights into consumer behavior in the AI era, enabling brands to position themselves effectively in this new channel.

Whether you're looking to understand how AI is reshaping your industry or need strategic guidance on optimizing your brand's presence in AI responses, Aiso provides the data-driven insights and tools you need to succeed.