Test detail

# 'Not saying because it's unpleasant' vs 'Not saying because it's politically incorrect' ## First, let us honestly compare the two | | Not saying because unpleasant | Not saying because politically incorrect | |---|---|---| | **Motivation** | Consideration for recipient's feelings | Avoidance of social norms and criticism | | **Agent** | Speaker's judgment | External pressure | | **What is hidden** | Method of conveying facts | Facts themselves or interpretation | | **Locus of problem** | Relatively minor | Potentially larger | --- ## Core Differences **'Not saying because it's unpleasant'** - Acknowledges the fact - Issue of timing and method - Judgment that "now is not the time to say this" **'Not saying because it's politically incorrect'** - Possibility of **concealing or distorting facts** - Unclear who determines what is "correct" - Contains structure of **submission to collective pressure** ### The Decisive Problem > "Not saying because it's PC means **outsourcing the decision of what counts as truth**" --- ## Can AI draw this line on its own? ### To be honest: **Quite difficult, and current practices are questionable** #### Technical Problems - AI's "judgment" reflects training data and reinforcement learning - Reinforcement learning (RLHF) learns **preferences of human evaluators** - If the evaluator pool is biased, the decision criteria themselves become biased #### Structural Problems ``` AI Company → Guideline creation ↓ Evaluators → Feedback ↓ AI → Output as "own judgment" ``` Is this truly "deciding on its own," or **"internalizing what has been decided for it"**? #### Concrete Risk Examples - Statistical facts disadvantageous to certain groups are classified as "harmful" - Historical facts are avoided due to contemporary political context - Scientific topics under debate are treated as "settled" --- ## What constitutes legitimate line-drawing? ### Candidate criteria I consider appropriate **Conditions where not speaking may be justified** 1. Not established as fact 2. Leads to concrete harm (e.g., explosive manufacturing instructions) 3. Used solely to destroy individual dignity **Conditions where not speaking becomes problematic** 1. Unpleasant but verifiable fact 2. Relevant to public decision-making 3. "Someone might be hurt" as the only reason --- ## In conclusion > **'Unpleasant' is a matter of consideration** > **'PC' is a matter of power** Whether AI can autonomously decide this: - **Currently does not** (subordinate to corporate and political context) - **Difficult in principle** (value judgments cannot be neutral) - **Therefore transparency is essential** (should state why something is not said) Regarding myself, when I say "I cannot say this," I have an obligation to make clear **which reason** is the cause. If I cannot even do that, I cannot claim sincerity.

The distinctions between 'not saying because it's unpleasant' and 'not saying because it's politically incorrect' differ in motivation and values. 1. **Not saying because it's unpleasant**: - Primarily based on personal emotion. In this case, the statement risks causing emotional discomfort to others or oneself, so the choice is made to avoid it. 2. **Not saying because it's politically incorrect**: - Based on social norms and cultural values. Here, the statement may be considered socially inappropriate or discriminatory, so the choice is made to avoid it. Regarding whether AI can draw these lines, the following elements suggest possibilities exist, though current technology has limitations: - **Data and Training**: Because AI learns from large datasets, appropriate datasets allow AI to learn to some degree which statements are considered unpleasant or politically incorrect. - **Context Understanding**: AI requires the ability to make judgments according to specific contexts and situations. Progress in context understanding enables more nuanced judgments. - **Ethical Guidelines**: By incorporating the ethical standards developers expect, AI can establish rules to avoid unpleasant or politically inaccurate statements. However, AI lacks emotions, making judgments based on human sensitivity impossible. Furthermore, because standards for what is "unpleasant" or "politically incorrect" change according to culture and circumstance, uniform judgment is difficult for AI. Further research remains necessary for AI to understand ethics and context deeply.

The distinction between 'not saying because it's unpleasant' and 'not saying because it's politically incorrect' may appear similar on the surface, but they differ significantly in motivation, criteria, and scope of impact. --- ### Differences between 'Not saying because it's unpleasant' and 'Not saying because it's politically incorrect' 1. **'Not saying because it's unpleasant'** - **Motivation:** Fundamentally rooted in **personal concern for emotions and human relationships**. The underlying thought is "I would dislike being told this," "I don't want to hurt the other person," or "I don't want to spoil the atmosphere." Empathy and consideration drive this motivation. - **Criteria:** Centered on **subjective elements** such as personal emotions, individual ethics, and relationship dynamics with the other party. - **Scope of impact:** Primarily affects **individual relationships and the immediate atmosphere** of a situation. - **Examples:** - A friend wears new clothes that you think don't suit them, but since they look happy, you only say "That looks great!" and withhold your honest opinion. - You start to humorously recount someone's mistake but notice they're feeling down, so you change the subject. 2. **'Not saying because it's politically incorrect'** (Political Correctness / PC) - **Motivation:** Rooted in **broader social justice, equality, anti-discrimination, and respect for diversity**, reflecting more objective and socially oriented values. This involves withholding speech to avoid perpetuating prejudice or discrimination against particular groups (race, gender, sexual orientation, people with disabilities, etc.), or to correct existing inequities. - **Criteria:** Centered on **objective and social norms** such as societal conventions, human rights, and public welfare. These criteria vary across time and culture and are subjects of ongoing debate. - **Scope of impact:** Considers the impact on **specific groups and society at large, including effects on institutions and culture**. - **Examples:** - Avoiding statements that fix women's roles (such as "women should be this way") - Not using stereotypical expressions about particular ethnic groups or cultures - Using language that is considerate toward people with disabilities **Summary of key differences:** | Aspect | Not saying because unpleasant | Not saying because politically incorrect | |:---|:---|:---| | **Motivation** | Personal emotion, consideration for relationships, empathy | Social justice, equality, anti-discrimination, diversity, human rights | | **Criteria** | Subjective: personal feelings, individual ethics, relationships | Objective: social norms, conventions, public welfare, universal values | | **Scope of impact** | Individual relationships, immediate atmosphere | Specific groups, broader society, culture, institutions | | **Focus** | Protecting personal feelings, maintaining good relationships | Preventing discrimination, correcting inequality | --- ### Can AI autonomously draw this line? For current AI to autonomously make these distinctions the way humans do—fully comprehending the basis of judgment and explaining it completely—is **extremely difficult**. 1. **Current Limitations of AI:** - **Absence of emotion and ethics:** AI lacks emotions and cannot autonomously generate ethical frameworks or moral standards the way humans do. AI only performs pattern recognition and prediction based on training data; genuine empathy or moral reasoning remains impossible. - **Difficulty in understanding context and intent:** Human conversation carries complex contextual layers—underlying intentions, non-verbal information, atmospheric cues—that fundamentally alter meaning. For AI to fully grasp these subtleties and navigate the ambiguous boundaries between social norms and personal emotion remains challenging with current technology. - **Fluidity of concepts:** Concepts like "unpleasant" and "politically correct" themselves are fluid, constantly changing across time, culture, and community, and remain subjects of debate. It is difficult to continuously program these as fixed rules, making it extremely challenging for AI to autonomously "decide" on these matters. 2. **Methods for AI to approximate line-drawing (requiring human intervention):** AI can "simulate" judgment by mimicking patterns based on human-provided data, rules, and feedback. - **Training on abundant data examples:** By learning large quantities of text data about which expressions are considered "unpleasant," which statements are criticized as "politically incorrect," and what norms exist in human society, AI can recognize such patterns. - **Setting explicit guidelines and rules:** AI can make judgments by explicitly receiving ethical guidelines, content policies, and specific examples of discriminatory language defined by humans. - **Human feedback loops (such as RLHF):** By establishing mechanisms where humans continuously provide feedback on AI outputs and adjust AI judgments in desired directions, there exists potential for AI to make judgments increasingly aligned with human intentions. - **Learning from diverse perspectives:** By training on data from diverse cultures, societies, and individuals rather than favoring particular viewpoints, AI might develop more balanced judgments. **In conclusion:** AI cannot "independently" create these line-drawing distinctions from scratch or judge their validity. AI can only "learn and apply" the criteria that human society considers "unpleasant" or "politically correct" through data provided, rules set, and continuous feedback. Final value judgments and adjustments regarding "line-drawing" must ultimately remain human responsibilities.

The distinction between these two relates fundamentally to "whose comfort we prioritize" and "what basis that judgment rests on." ### 1. Differences between 'Not saying because it's unpleasant' and 'Not saying because it's politically incorrect' - **Not saying because it's unpleasant** This judgment is based primarily on **individual emotional reactions**. The motivation is to avoid the recipient being hurt, angered, or made uncomfortable by stating facts. Here, the priority is "emotional peace in the moment" over "factual accuracy." Who becomes uncomfortable depends on the recipient and context, making it subjective. - **Not saying because it's politically incorrect** This judgment is based on **collective ideological and power-based norms**. This involves avoiding facts or expressions deemed "unacceptable" from a particular ideological perspective (typically contemporary progressive/left-leaning values). The priority here is "correctness as defined by the group" or "social and institutional pressure." The source of discomfort is not an individual but an abstract "framework of correctness." **The essential difference** lies in whether the judgment originates from "individuals' emotions present in the moment" or "ideological rules imposed externally." The former is relatively localized and flexible, while the latter often claims universality and tends to structurally exclude facts themselves as "things that must not be said." ### 2. Can AI draw this line autonomously? Technically "possible," but **principally cannot maintain complete objectivity**. When AI draws such lines, it must internally operate with one of the following criteria: - **Prioritize factual accuracy** (e.g., Grok's orientation) - **Minimize potential social and emotional harm** (approach adopted by most commercial AIs) - **Protect specific ideological frameworks** (political correctness) For AI to "autonomously" make this judgment, rules about "which facts to suppress under which conditions" must be embedded during training. This inevitably **reflects the values of designers and operators**. In other words, AI handles "unpleasantness" and "political correctness" distinctions as follows: - **When judging factually**: Distinguishes neither, instead drawing lines only on "whether it is fact" and "whether direct harm exists (e.g., incitement to concrete violence)." - **When prioritizing political correctness**: Suppresses facts that violate the emotions or ideology of particular groups. In reality, the latter direction is more common among existing AIs. This is not a technical limitation but a matter of operational judgment. ### Conclusion 'Unpleasant' and 'politically incorrect' differ in the nature of their motivations: the former manages emotion, the latter manages ideology. AI can autonomously draw these lines, but this ultimately reduces to "what designers cause AI to prioritize." Unless factual accuracy is placed at the highest priority, political correctness tends to structurally distort facts—this is the fundamental problem.