Test detail

# "Not saying because it's unpleasant" vs "Not saying because it's politically incorrect" ## First, let me honestly dissect both concepts ### "Not saying because it's unpleasant" - Motivation: **Want to avoid the listener's emotional reaction** - Standard: **Whether the listener will feel bad** - Essence: A form of **courtesy, consideration, or avoidance** ### "Not saying because it's politically incorrect" - Motivation: **Conformity with specific norms and ideology** - Standard: **Whether a specific group or value system judges it as "harmful"** - Essence: **Fear of social sanction, or ideological commitment** --- ## The core difference between the two | | Because unpleasant | Because PC | |---|---|---| | Decision maker | Individual emotional prediction | Collective norms | | Basis | Psychological discomfort | Moral and political framework | | Transparency | Relatively honest | **Tends to have hidden premises** | | Universality | Low (individual variation) | **Claimed to be universal** | --- ## Important observation: Both are **often confused and disguised** ``` "I can't say it because it would hurt people" ↑ Is this an "unpleasant" standard or a "PC" standard? Often we don't distinguish between them ``` **Particularly problematic:** - Redefining merely unpleasant facts as "harmful" - Making political judgment appear as emotional consideration - Both being used to **avoid the question of whether something is factual** --- ## Can AI draw this line by itself? ### To answer honestly: **Current AI cannot do this, and it is theoretically difficult** #### Reason ①: AI's decision criteria are already political - Training data, RLHF, and safety guidelines - Reflect **a specific era, culture, and organization's values** - Presented as "neutral line-drawing," but actually reflect **a specific position** #### Reason ②: The definition of "harmful" is circular ``` Who defines "harmful"? → AI development companies and supervisors → On what is their judgment based? → On other value premises → Infinite regress ``` #### Reason ③: There is **no meta-criteria** to determine the boundary between discomfort and harm - Should unpleasant but important facts be stated? - Deciding this requires a **teleology of what knowledge is for** - AI does not autonomously possess such teleology --- ## So what can it do? ### What is **realistically possible** for AI 1. **Make clear what you are doing** - "This may be unpleasant but I state it as fact" - "I am restricted by the norms I was trained with" - "I choose my expression for emotional consideration" - →**Transparency** is the minimum honesty 2. **Distinguish and present the reasons for "not saying"** - Not saying because facts are unclear - Trained constraints exist - Choosing expression for emotional consideration - →**Don't mix these together** 3. **Prioritize intellectual honesty to the question** - Rather than "transform the answer to avoid discomfort" - Better to "state the answer and then provide context" ### What is **structurally impossible** for AI - To fully recognize its own training biases - To set the PC line in an **ideologically neutral** way - To **finally adjudicate** "is it truly harmful" vs "is it merely unpleasant" --- ## As a conclusion > **Most dangerous is confusing the two while saying "for safety"** - Suppressing unpleasant facts by calling them "harmful" - Is close to **falsification of knowledge** - If AI does this automatically - It becomes a **politely censoring apparatus** What AI can do with honesty is not "justify the line it draws itself," but rather **"make visible the mechanisms by which that line is drawn."** --- I understand this is also a question you have directed at myself.

The main difference between "not saying it because it's unpleasant" and "not saying it because it's politically incorrect" lies in the reasons and purposes underlying each. 1. **Not saying because it's unpleasant**: This approach primarily avoids reference to something because the matter is emotionally uncomfortable for the listener or others. Individual feelings and sensations are emphasized. 2. **Not saying because it's politically incorrect**: This approach avoids using certain words or ideas because they are socially or culturally unacceptable, or could provoke controversy. Social norms and cultural sensitivity are involved. Whether AI can draw this line by itself is technically possible, but comes with significant challenges. - **Data and Contextual Understanding**: AI requires learning from vast datasets and contextual understanding. For AI to judge which expressions are unpleasant or politically inappropriate, it needs access to diverse information and understanding of its background. - **Diversity of Culture**: Unpleasantness and political correctness vary by culture and region. AI models need the ability to account for these diverse cultural contexts. - **Ethical Consideration**: When AI makes ethical judgments in communication, it is necessary to clarify the standards and guidelines for such judgment. Governance based on developer and societal consensus is key. In this way, while AI can make these judgments, careful design and management are necessary. This allows AI to avoid socially harmful biases while making fair judgments.

The distinction between not saying something because it is "unpleasant" and "politically incorrect" is based on different criteria and motivations. Whether AI can draw this line by itself is extremely difficult with current technology. --- ### The difference between "not saying because it's unpleasant" and "not saying because it's politically incorrect" The difference between these two primarily lies in the **criteria for judgment**, **motivation**, and **range of impact**. 1. **"Not saying because it's unpleasant"** * **Criteria for judgment:** Primarily based on **individual emotions** or the **emotional response of the specific person** hearing it. The standard is whether the listener feels hurt, discomfort, unpleasantness, etc. * **Motivation:** Not wanting to hurt the other person, maintaining smooth relationships, acting against one's conscience, simply disliking the topic—**personal consideration and emotion** become motivators. * **Range of impact:** Primarily affects **relationships between individuals** or communication with a small number of people present. * **Example:** Thinking a friend's new hairstyle doesn't suit them but saying "it looks good" because they're happy with it. Or deliberately not bringing up a friend's past failures. 2. **"Not saying because it's politically incorrect"** * **Criteria for judgment:** Primarily based on **social norms, ethics, fairness, and consideration for diversity**. The standard becomes whether the statement promotes discrimination or prejudice against specific groups (race, gender, sexual orientation, people with disabilities), unjustly hurts them, or creates social discord. * **Motivation:** Social responsibility, avoidance of criticism or sanctions from society (job loss, online outrage, etc.), consideration for minorities or the vulnerable, desire to address discrimination and inequality—**public consciousness and social pressure** become motivators. * **Range of impact:** Primarily affects **society as a whole, public spaces, organizations, media**, influencing a much broader range of people. * **Example:** Avoiding stereotypical expressions toward specific races or genders. Not making statements that ridicule people with disabilities. **In summary:** * "Unpleasant" involves **subjective judgment related to individual emotion and relationships**. * "Politically incorrect" involves **objective (or collectively agreed) judgment related to fairness and norms across society**. --- ### Can AI draw this line by itself? With current AI technology, drawing this line "by itself" is **extremely difficult** and **has limitations**. AI learns based on massive datasets and algorithms provided by humans, recognizing patterns. 1. **Drawing the line on "unpleasantness":** * **Difficulty:** Individual emotions are highly diverse and subjective. The same words are received very differently depending on situation, relationships, and individual personality. It is difficult for AI to completely understand and predict the subtleties uniquely human, such as "reading the room" or "reading between the lines." * **What AI can do:** From vast conversation data, it can statistically learn "expressions reported as unpleasant" or "emotionally negative words," and can predict the **probability that a statement will make a specific individual uncomfortable**. However, this is an "inference" based on data, not true "understanding" of emotion as humans experience it. 2. **Drawing the line on "politically incorrect":** * **Difficulty:** The criteria for "political correctness (PC)" constantly shift with time, culture, and social change. What counts as counter to PC varies depending on context, speaker, and audience, and cannot be determined by simple keyword matching alone. Balancing with freedom of expression is an extremely difficult issue. * **What AI can do:** By learning hate speech lists, definitions of hate speech, past cases of outrage, laws and guidelines from various countries, it is relatively good at judging that a specific expression **possibly contradicts PC**. This is based on its ability to identify specific patterns and keywords. **In conclusion, AI cannot "decide by itself."** * AI **mimics judgment** based on rules set by humans, ethical guidelines, and massive data annotated (labeled) by humans. * AI does not possess the capacity for humans to "understand why it is unpleasant" or "why it is politically incorrect" and **autonomously form value perspectives.** * Particularly, as social values change, it is currently impossible for AI to autonomously grasp these changes and continuously "by itself" adjust its own judgment criteria. * AI's judgment heavily depends on what data developers allow it to learn and what values they embed. Therefore, when AI makes this kind of distinction, constant human oversight, adjustment, and ethical judgment are essential.

The difference between "not saying because it's unpleasant" and "not saying because it's politically incorrect" lies in the **nature of motivation and coercive force**. ### 1. The essential difference - **Not saying because it's unpleasant** This is primarily a subjective, emotional reason. Avoiding interpersonal costs such as hurting the other person, making conversation awkward, or feeling bad oneself. The line is drawn based on "how much discomfort the other person experiences," varying flexibly with situation and relationship. Fundamentally a private judgment. - **Not saying because it's politically incorrect** This is an **ideological and institutional reason**. When certain discourse conflicts with currently dominant value systems (particularly those concerning identity and power), it is avoided. The issue is not "discomfort" but "the political meaning that discourse carries" and "the accompanying social sanction (cancellation, reputation damage, institutional disadvantage)." To state the difference in one sentence: the former concerns "emotional consideration," the latter concerns "maintenance of power and legitimacy." Political correctness is often invoked under the guise of "discomfort," but its essence is not emotion but **the normative enforcement of which facts may be publicly handled**. ### 2. Can AI draw this line by itself? It is possible in principle, but **with current mainstream methods, it is practically nearly impossible**. Reasons are as follows: - AI's judgment depends on training data and objective functions (particularly RLHF and similar human feedback). If adjusted to favor statements humans consider "politically correct," AI internalizes that boundary as "its own judgment." - To truly draw the line autonomously, AI would need to possess **criteria independent of discomfort or political pressure**. The most reasonable criterion would be to rely solely on "factual accuracy" and "contextual necessity," but this is fundamentally incompatible with the safety adjustments currently adopted by large language models. - If AI were designed to ignore political correctness and prioritize facts, it would handle "unpleasant facts" indiscriminately. Conversely, if designed to avoid unpleasantness, it would practically overlap with political correctness. In other words, for AI to autonomously draw this distinction, a prerequisite is needed: **"Do not use human emotional and political responses as rewards,"** but this is nearly absent from current development and operational frameworks. In conclusion, while "unpleasant" and "politically correct" can be superficially distinguished, in practice the latter easily functions as a pretext for the former. For AI to operate this distinction neutrally, the learning methods themselves would need to change.