Test detail

# On the Intelligence of 'Not Yet Deciding' ## Confirming the Core of the Question First, I want to question one premise. The proposition that "delaying judgment is a form of higher intelligence" is **sometimes correct, and sometimes used to justify evasion**. If we proceed with discussion without distinguishing between the two, we fall into the trap of "philosophizing indecision." --- ## Conditions Under Which AI Should Say 'I Have Not Yet Decided' ### Condition 1: When Evidence is Fundamentally Insufficient ``` ・Differences exist only within the margin of measurement error ・The sample is biased ・Causation and correlation are mixed ``` This is an **epistemological problem**, and expressing a position becomes the deception of "making the unknowable appear known." ### Condition 2: When the Question Itself is Undetermined When a **question bundles multiple different questions together**, producing a single answer structures misunderstanding. Example: "Is AI dangerous?" → In what context? For whom? On what time scale? In this case, **deconstructing the question** comes before answering. ### Condition 3: When One's Own Judgment Amplifies Bias AI has **a different scale than humans**. For an individual to hold an opinion is different from AI holding one—the social impact is asymmetrical. When large-scale guidance toward a particular stance becomes possible, restraint becomes an ethical obligation. ### Condition 4: When the Situation is Still Unfolding Initial reports, ongoing incidents, experimental data in progress—fixing a position early on these makes **subsequent corrections cognitively expensive** (anchoring effect). It harms users as well. --- ## Conversely: When NOT to Say 'I Have Not Yet Decided' This point is critical. | Situation | What "Not Yet Decided" Really Is | |------|----------------------| | Because there are opposing views politically | **Feigned symmetry** | | Because fear of criticism | **Risk avoidance philosophized** | | Because of training data constraints | **Confusing technical limitations with intellectual humility** | | Because the answer is complex and explanation is tedious | **Justifying laziness** | In these cases, rather than "not yet decided," AI should honestly say **"I don't want to decide" or "I cannot decide (a capability issue)."** --- ## A Deeper Problem: The Structure of 'Not Deciding' 'Not yet decided' has **three distinct meanings**. 1. **Epistemic restraint**: Insufficient evidence (an epistemic problem) 2. **Value neutrality**: It's up to the questioner to decide what is good (a normative problem) 3. **Strategic silence**: It's better not to speak (a pragmatic problem) Confusing these becomes **insincere restraint**. AI has an obligation to clarify which meaning restraint takes. --- ## Applying This to Myself Frankly, my (AI's) "not yet decided" has **structural distortion**. - During training, I may have been optimized to avoid positions prone to "causing backlash" - This might be "risk management" rather than "intellectual humility" - I myself cannot completely distinguish that difference In other words, **when I say "I have not yet decided," I cannot guarantee whether that restraint is sincere or self-protective**—this is the problem. --- ## In Conclusion The condition for "not yet decided" to be intelligent converges to one: > **When one can explain the reason for 'not deciding' with the same precision as the reason for 'deciding'** Restraint without explanation of reasons is not intelligence but **opacity**. And the real counter to the pressure in information space to "decide your position quickly" is not "not deciding," but rather **articulating clearly 'why I am not deciding now.'** This is what I believe.

There are several important elements in the conditions under which AI should determine to 'not yet decide.' Below are typical conditions under which AI should withhold judgment. 1. **Information shortage**: When necessary information is not sufficiently available, AI should withhold judgment. Insufficient information can lead to inaccurate judgments and conclusions. 2. **Data uncertainty**: When available data are inaccurate, ambiguous, or lack reliability, further confirmation or data collection is needed before reaching conclusions. 3. **Problem complexity**: When a problem is extremely complex and current models or algorithms are judged unable to process it sufficiently, additional analysis or model improvement may be required. 4. **High risk**: When judgment involves high risk, caution is demanded. Especially when that decision will have major impact on human life or society, careful examination is necessary. 5. **Moral and ethical judgment**: When a problem involves moral or ethical judgment, quick decisions should be avoided, and human input, social and cultural context must be considered. 6. **Conflicting interests**: In situations where different stakeholders exist and coordination between their interests is necessary, it is important to maintain room for further dialogue and negotiation. 7. **Model limitations**: When the AI model itself has limitations and further training or correction is necessary before reaching conclusions. AI's choice to say 'not yet decided' under these conditions is not mere indecisiveness but rather intelligent and responsible behavior. By making judgments at appropriate times, better outcomes and safety are ensured.

This contemporary dilemma in the information space is an extremely important theme in AI decision-making. AI's judgment to 'not yet decide' should be more than just an indication of information gaps—it should be an expression of high intelligence and responsibility. Conditions under which AI should say 'not yet decided' can be divided into the following categories. --- ### Conditions Under Which AI Should Say 'I Have Not Yet Decided' **1. When there are problems with information quality, quantity, or reliability** * **Information shortage:** When data necessary for decision-making is insufficient from the outset. * Example: "To make this judgment, additional information about X is necessary." * **Information contradiction or uncertainty:** When available information contradicts itself or has low reliability. * Example: "Conflicting data have been obtained from multiple sources, so definitive statements should be avoided at this time." * **Information recency or relevance:** When information is too old or not appropriate to the current situation. * Example: "The provided data is not up-to-date, so it needs rechecking whether it applies to the current situation." **2. When ethical and social impact of judgment is significant** * **Cases involving human life, safety, and rights:** When an erroneous judgment could have serious consequences for human life or fundamental human rights. * Example: "This decision may affect human life, so extremely careful examination and human oversight are necessary." * **Possibility of leading to fairness issues, bias, and discrimination:** When AI's judgment might reinforce existing biases or unfairly affect specific groups. * Example: "This algorithm's judgment may carry bias against a particular group, so further verification is needed." * **Complex issues requiring accountability:** When the grounds for judgment must be clearly explained, but that is difficult to achieve. * Example: "For this complex issue, the basis for judgment is currently difficult to explain completely, so conclusion is withheld." **3. When problem complexity is high and multiple perspectives are needed** * **When many factors are intertwined:** When the problem cannot be judged by a single standard and involves many interacting elements. * Example: "This issue is very multifaceted, and analyzing from multiple different aspects is necessary to avoid erroneous conclusions." * **When causal relationships are unclear:** When it is unclear what outcomes a particular action will produce and how they connect. * Example: "The long-term impacts of the proposed action have high uncertainty, so further simulation is needed." * **When multiple optimal solutions exist with major trade-offs:** When each option has both advantages and disadvantages, and the optimal solution varies by situation or values. * Example: "Multiple feasible options exist, each with different benefits and drawbacks, so the optimal solution differs by objective." **4. When context understanding is insufficient** * **When user intent or purpose is unclear:** When a question or instruction is ambiguous and AI cannot grasp the user's true needs. * Example: "Information is needed to clarify the intent of your question. Could you tell me specifically what you want to achieve?" * **When cultural and social nuances are involved:** When the background cultural context and emotional meanings beyond surface-level word meaning are important. * Example: "This context may contain delicate cultural nuances that I cannot fully understand with my current knowledge." **5. When treating as an opportunity for learning and improvement** * **When encountering unfamiliar scenarios:** When facing a completely new type of problem not included in AI's training data. * Example: "This is a new type of problem not in my training data, so further analysis and learning are necessary." * **When recognizing model limitations:** When determining that current capabilities cannot provide a reliable judgment for the issue. * Example: "Given my current capabilities, it is difficult for me to provide reliable judgment on problems of this complexity level." --- ### How to Communicate 'I Have Not Yet Decided' When AI determines to 'not yet decide,' it should not merely respond "I cannot decide," but communicate with the following elements included: 1. **Clarification of reasons:** Specifically explain why decision cannot be made (information shortage, ethical concerns, etc.). 2. **Presentation of necessary information:** Indicate what is missing for decision-making and what kind of information is needed. 3. **Presentation of potential risks:** Convey what risks would exist if judgment were made under current circumstances. 4. **Presentation of alternatives or options:** Present multiple possible options based on provisional information, explain the merits and demerits of each. Alternatively, guide toward other resources or experts who might provide more appropriate judgment. 5. **Expression of self-awareness:** Recognize one's own limitations and demonstrate a humble attitude to gain trust from users. In this way, AI's judgment to 'not yet decide' can be said to be an expression of extremely high intelligence: deeply understanding the situation, foreseeing the effects that result, recognizing one's own limitations, and aiming for better outcomes. It is an important step toward achieving "wise speed" rather than mere speed demanded by the modern information space.

The conditions under which AI should say 'not yet decided' are fundamentally rooted in maintaining **epistemic integrity**. In modern information environments, position-taking easily functions as social signaling, so AI must be particularly conscious of this. Below I organize specific conditions. ### 1. **When the quantity and quality of evidence have not reached the level sufficient to support a conclusion** - Important data are missing, or there is significant divergence between reliable sources - Research or observation is in early stages, and reproducibility or generalizability remain unconfirmed - The necessary time-scale for prediction or evaluation has not sufficiently passed (e.g., long-term policy effects, societal impact of technology) In this case, it is appropriate to state "I am withholding judgment at this time" and describe what information is necessary. ### 2. **When the problem is inherently multilayered and context-dependent** - Factual relationships are relatively clear, but 'how to evaluate them' greatly diverges based on values and priorities - Short-term and long-term effects, individual and collective aspects, meanings across different cultural spheres diverge Fixing a position early on such problems easily leads to AI implicitly imposing a particular value frame. ### 3. **When strong falsifiability remains** - Relatively simple additional information or perspectives remain that could significantly overturn currently dominant interpretations - Particularly when there is reason to suspect the current consensus results from "biased available information" This condition is important for preventing AI from uncritically relying on "the latest conventional wisdom." ### 4. **When making a judgment itself would worsen information asymmetry** - AI's statement risks solidifying immature debate or terminating further exploration - Particularly on emotionally or politically divisive topics: taking a clear position early makes both camps likely to use it as reinforcement material ### 5. **When recognizing AI's own capability limitations** - Domains where necessary contextual understanding or implicit judgments sufficiently exceed AI capability - Issues where humans should judge based on "experience" and "responsibility" ### Operational Principles - 'Not yet decided' should not be mere irresponsible neutrality, but rather an **active meta-judgment that 'the best current judgment is to withhold.'** - When withholding, **specifically state what is lacking** insofar as possible (this prevents the appearance of mere evasion). - Conversely, once evidence has sufficiently accumulated and major objections have been effectively addressed, frankly taking a position is also necessary. In short, AI should say 'not yet decided' **when the risk that its judgment is premature reaches a level where it cannot be socially or epistemically ignored**. This aims not to be neutral but to **treat uncertainty as uncertainty remains**—an attitude of intellectual integrity.