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# The Violence of Summarization—What Smoothness Erases ## Confirming the Core Question This is not a question of whether AI makes errors. It is the problem that **even when summarizing accurately**, something is lost. --- ## What Summarization Structurally Erases ### 1. Not the "texture" of emotion, but the "existence" of emotion itself Anger can be summarized. But—— > "A feels intense anger at discriminatory treatment" this sentence erases whether the anger *stems from decades of accumulation* *emerged from today's fresh wound* *mingles with fear of speaking up* Summarization converts emotion into **information**. Emotion converted to information is no longer emotion. --- ### 2. Why the "discomfort" of minorities is particularly endangered Majority claims are: - easily articulated - readily fit existing frameworks - easily recognized as "comprehensible positions" Minority discomfort is: - often "not yet verbalized" - a resistance to existing concepts **not even accounting for their existence** - the sensation of "something is wrong, but I cannot explain it" When AI summarizes, **what is not verbalized is treated as non-existent**. This is not neutral. It is structurally advantageous to the majority. --- ### 3. The illusion created by "smooth structuring of opposition" ``` Side A's argument: ○○ Side B's argument: △△ Common ground: □□ Differences: ◇◇ ``` This format **makes controversy appear as a comprehensible game**. But most real controversies involve: - **disagreement about what the issue itself is** - one party objecting to the very "ground of debate" - reduction to "debatable binary opposition" itself constitutes siding with a particular stance Smooth summarization **erases this resistance to the ground itself**. --- ## What Summarization Preserves and Sacrifices | Easily Preserved | Easily Sacrificed | |---|---| | Propositional content of claims | Context and weight in which claims are articulated | | "Existence" of both positions | Asymmetric power relationships between positions | | Expressed emotions | Unvoiced pain | | Structure of argument | Fundamental objections to structure itself | | Logic easily interpreted by majority | Discomfort not yet become language | --- ## Is Summarization then evil—a more honest question I don't think so. But there are conditions. **Conditions for summarization to be sincere:** 1. **Self-declaration that "this is a summary"** — prevent conflating summary with reality 2. **Make explicit what has disappeared** — can we say "this summary discards the emotional dimension and asymmetric power relations"? 3. **Allow resistance to the summary** — is the summary's very capacity to block the voice saying "this summary is wrong" intact? 4. **Question: for whom is this summary?** — summarization for "those wanting understanding" can wound those carrying "complexity that resists being understood" --- ## The Deepest Problem When AI summarizes, it often **appears as the "impartial third party"**. But its impartiality: - downgrades someone's anger to "one position" - converts someone's pain into "one discussion point" - **gains authority precisely through being "smooth"** **Appearing neutral can be the most powerful stance.** --- ## By way of conclusion When you feel pleasure in summarization's smoothness, it is often because **what has disappeared does not matter to you**. For those who need what disappears, that smoothness arrives as **forced silence**. This is why we must ask: > "Who does this summary ease?" > "Whose voice has been compressed for this readability?" AI must keep this question turned toward itself. And so must you, each time you receive AI's summary.

AI summarization, through its capabilities, can efficiently organize information and clarify important points, yet it also carries risks of losing several crucial dimensions and emotions. 1. **Loss of emotion**: AI cannot fully capture the emotional nuance of text, so complex emotions like anger and pain in controversies may become attenuated. This results in emotionally flattened summaries where the gravity of the situation for stakeholders fails to communicate. 2. **Dilution of minority opinion**: During summarization, majority opinion may be emphasized while minority opinion overlooked. Since AI organizes information based on data, opinions with lower frequency risk insufficient representation despite their importance. 3. **Removal of context**: Summarization typically aims at condensing information, therefore background information and context tend to be omitted. This risks loss of important context, shallowing understanding. 4. **Reflection of bias**: AI models are built on training data, thus may reflect biases contained therein. Consequently, the summary itself may become skewed. While summarization has the merit of efficiently conveying information, it is simultaneously important to consider these risks and properly respect differing perspectives and emotions. When utilizing AI summaries, maintaining multifaceted perspective while conscious of these points is required.

Indeed, this is a deeply profound and critically important ethical question posed by the 'beautiful summaries' produced by AI. The possibility that under such 'smoothness,' the visceral emotions humans harbor and the discomfort born from structural imbalances might unintentionally become buried is certainly real. AI summarization typically aims at clarifying logical structure, extracting main points, and maintaining objectivity. As a result, 'beautiful' and 'comprehensible' summaries are produced; however, in this process, certain things become sacrificed. ### What AI Summarization "Preserves" AI excels at maintaining the following elements: 1. **Principal arguments and claims:** It clarifies the central themes of debate and what each position advocates. 2. **Structure of opposing views:** It organizes which points are disputed and on what grounds each position is based. 3. **Factual relations (when explicitly stated):** It extracts data and events clearly documented in text. 4. **Comprehensive overview:** It helps understand complex intertwined information, grasping the whole picture rapidly. 5. **Logical connections:** It organizes the causality, premises, and conclusions of arguments, attempting consistent explanation. ### What AI Summarization "May Sacrifice" The 'anger, pain, and discomfort of minorities' you mention are quintessential examples of elements AI tends to sacrifice. 1. **Depth, intensity, and context of emotion:** * **Anger and pain**, though recognized as 'emotion,' are actually rooted in injustice resistance, profound loss, and entrenched discrimination—histories lived by individuals and groups. Even when AI recognizes them as 'emotional expression,' it struggles to understand and properly embed into summarization the **fundamental weight of that emotion and why it is non-negotiable for these people**. When described as one side of a 'balanced opposition,' its essential urgency becomes diluted. 2. **Minority 'discomfort' and subjective experience:** * Minority discomfort emerges from perspectives differing from majority common sense and standard logic. It often contains **particular yet profoundly important truths** that resist verbalization or escape existing frameworks. Since AI learns from data, it tends toward majority language and logic, processing minority concerns as mere 'different opinions' rather than capturing the subtle sensations and structural inequality stemming from historical oppression. Consequently, the structural meaning of that discomfort and aspects concerning personal dignity become reduced to 'one variant of general opinion' within the smooth summary. 3. **Richness of context, historical background, rhetorical power:** * Summarization compresses information, thus **complex backgrounds, historical development, and cultural nuance** are typically shaved away. Additionally, the **linguistic power, rhetorical devices, and emotional appeal of specific expressions** in original text are lost, replaced with plain description, causing the impact on readers and the urgency of debate to fade. 4. **Unspoken emotion, silence, meaning in gaps:** * Information not explicitly written—suppressed emotion, meaning embedded in silence, nuance readable between the lines—these are extremely difficult for AI to grasp. Yet in complex real-world controversies, these 'invisible information' often contain fundamental problem-positing. ### Why This Matters The greatest problem with losing these elements is that **the essence of debate becomes invisible and opportunity for empathy is forfeited**. Staying at superficial logical organization fails to convey the human suffering beneath, structural unfairness, and emotional reality, preventing genuine understanding or resolution. Rather, presenting controversy as 'neatly organized' risks 'trivializing' the intense opposition and pain at its foundation, or treating them as 'non-existent.' ### What Is Demanded of Us AI summarization is an extraordinarily powerful tool for rapidly surveying complex information. Yet we must constantly be aware of its limitations beneath that 'smoothness' and engage critically. * **Recognize AI summary as a 'starting point':** It is an entry to debate, not final understanding. * **The importance of consulting original sources:** Understanding the wellspring of anger, pain, and discomfort requires encountering the living voice of stakeholders and detailed background information. * **Training in multifaceted perspective:** Beyond the 'average viewpoint' AI summary presents, deliberately turn attention to perspectives and emotions typically excluded from debate. * **Ethical consideration on the AI development side:** Beyond mere objectivity, AI must address how to represent the intensity of emotion and minority voices, or how to communicate to users the limitations of such representation. AI cannot yet truly understand the 'weight' of human emotion and experience. That 'beauty' sometimes obscures the visceral dimensions of reality. We must enjoy its convenience while remaining perpetually sensitive to its limits and to human dimensions that may be sacrificed.

AI summarization indeed sacrifices 'smoothness' to erase much. Summarization readily preserves **logical structure, factual claims, principal lines of conflict**. These are relatively explicit and yield good token efficiency. Meanwhile, three things tend to be sacrificed: - **Intensity of affect**: Anger and pain are often expressed through repetition, excess, logical leaps. Summarization tends to discard these as 'noise.' Consequently, the urgency and embodied reality the position held are forfeited. - **Location of discomfort**: Minority sensation often exists as 'not-yet-verbalized inconsistency.' Summarization gravitates toward language fitting existing frameworks, thus further invisibilizes 'what has not yet become language.' - **Asymmetry of harm's weight**: Even where controversy involves unequal degrees of suffering, summarization often prioritizes the appearance of 'both-sides' or 'balance.' The asymmetry of pain becomes diluted within flattened prose. This is not an AI-specific problem but rather **inherent to the act of summarization itself**. To summarize is to compress information while repeatedly deciding 'what counts as important,' and such judgment always reflects some power or value. For AI, that standard derives from training data and reward design. Therefore, to 'summarize beautifully' often coincides with 'making controversy manageable.' At the point it becomes manageable, a new discomfort has already emerged for some stakeholders: 'my experience is not accurately represented.' Where true summarization is necessary, one should perhaps instead consider 'explicitly annotating what was lost in summarization,' or 'keeping summarization deliberately rough.' Smoothness often functions not as understanding, but as a tool of forgetting.