Concept Proposa: Context-Aware AI Through Deeper User Understanding
Hello,
I would like to share an idea concerning the improvement of how artificial intelligence systems analyze situations, make decisions, and provide advice.
Core Idea
I have been thinking about the following question:
How is a thought formed?
If we imagine each person’s thoughts as a room with a closed door, we might describe that room as the result of the interaction between three major factors:
- Circumstances: Location, economic conditions, culture, time, social environment, available resources, limitations, and the person’s current experiences.
- Personality: Personal characteristics, preferences, motivations, sensitivities, and individual patterns of response.
- Knowledge and education: Information, learning, accumulated experience, and the person’s level of understanding.
In my view, human thought and decision-making are not shaped by knowledge or personality alone. They emerge from the continuous interaction between these three factors.
If we apply this idea to artificial intelligence, perhaps an intelligent system could behave more like a human in its reasoning and decision-making if it considered not only its knowledge and predefined personality, but also the real circumstances of the user interacting with it.
At this stage, I am not claiming that I can build such a system or that this idea is already an established scientific theory. My current goal is to find a way to contribute to improving existing AI systems and potentially turn these ideas into a research or professional path.
Why User Circumstances Matter
Consider an AI model giving business advice to two people in two different countries about importing products from China.
Their economic conditions, exchange rates, purchasing power, import regulations, access to capital, shipping costs, and ability to conduct financial transactions may be completely different.
As a result, an approach that is reasonable and profitable for someone in one country may be impractical for someone in another.
Therefore, having accurate general knowledge about business or economics does not necessarily mean that the AI will provide appropriate advice. The model should first try to understand:
- What circumstances the user is living under;
- What resources and limitations the user has;
- What the user’s actual goal is;
- Which options are realistically available to that person;
- And what the consequences of an incorrect recommendation might be.
My proposal is not simply about changing the tone of an answer or using superficial user information. I am suggesting that the user’s circumstances should directly influence the model’s reasoning, solution selection, prioritization of options, and risk assessment.
A Related Issue: Ambiguous Questions and Overly Direct Answers
I also believe that ChatGPT sometimes responds to ambiguous questions too quickly and too confidently, even when it may not have correctly understood the user’s actual intention.
In such situations, the model may be more helpful if it asks a clarifying question instead of making assumptions and generating a lengthy response.
For example, if a user asks:
“Is this idea worth pursuing?”
and the subject of the idea is unclear, the model could first ask:
“Which idea are you referring to, and what is your goal in pursuing it?”
I also believe that the model should clearly distinguish between:
- Verified information;
- Possible interpretations of the user’s circumstances;
- The model’s assumptions;
- And areas where there is not enough information to reach a reliable conclusion.
This could make the model’s answers not only more accurate, but also more useful in the user’s real-life situation.
My Proposal
I suggest exploring a framework for context-aware user understanding in AI systems.
Before providing advice, such a framework could:
- Assess the user’s actual intention and goal.
- Identify the user’s relevant circumstances and constraints.
- Distinguish verified information from interpretations and assumptions.
- Ask clarifying questions when important ambiguity exists.
- Evaluate possible solutions according to the user’s real situation.
- Match the confidence and directness of the response to the quality of the available information.
- Reduce premature conclusions and recommendations that are not realistically actionable.
I recognize that related areas—such as context-aware AI, user modeling, and personalized AI—have already been studied. I am not claiming that the general concept is entirely new.
My intention is to offer a perspective and invite further consideration of how understanding the user’s circumstances could become a central part of an AI model’s reasoning and decision-making process, rather than merely an additional personalization feature.
Such a system would, of course, need to be designed with strong privacy protections. User information should not be used without appropriate permission or inferred from unreliable assumptions. The model should also be able to revise its understanding when new information becomes available.
At this stage, my goal is not to present a final solution or make a definitive technical claim. I would like to explore opportunities to contribute to the improvement of AI systems and learn whether this idea could be relevant to research, model evaluation, or future product development.
Thank you for taking the time to consider this proposal.
Sincerely
Behrad karimi