我的征尘是星辰大海。。。

The dirt and dust from my pilgrimage forms oceans of stars...

-------当记忆的篇章变得零碎，当追忆的图片变得模糊，我们只能求助于数字存储的永恒的回忆

作者:黄教授

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从是的大臣看懂人类求知

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原始脚本

四维认知象限，从是大臣看懂人类求知、 AI 交互与认知永恒悖论。
是大臣里一段政务博弈。
一句评价马斯克的，You don't know what you don't know。
一套经典四维认知模型，能够统一解释官僚信息博弈、大模型运行逻辑，以及人类长久以来求索真理的底层困境。
我们依靠各类工具从已知奔赴未知，可一条天然的认知悖论始终横亘在所有求知行为前方。
一、影子是大侦探里无解的信息闭环，整部剧集的核心冲突。
本质是一场认知博弈。
一边是代表求知者、决策者的大臣，另一边是手握全部信息、等同于信息工具的常务政务秘书。
二者存在明确规则约束。
秘书有义务如实回答大臣提出的每一个问题，不能刻意编造谎言。
但他拥有天然的信息选择权。
绝不会主动披露隐患、补充盲区、提醒风险。
由此形成无法挣脱的闭环悖论，项目缺陷、资金漏洞、制度弊病全部记录在成堆公文与附件中。
信息客观上完全对大臣开放，可想要获知隐藏的真相，前提是提出精准对应的问题。
大臣困于自身认知边界。
根本意识不到自己存在哪些未知，自然无法抛出触及核心的疑问。
海量报告堆满桌面，关键信息藏在委婉话术与冗余文本之间。
即便全部文件可供查阅，决策者也极易入宝山而空手回。
掌握全局信息的秘书只被动应答，不问不补。
不会主动拓宽提问者的思考维度。
这套交互逻辑和当下人与 AI 人与搜索引擎的相处模式高度相似。
AI 如同数字化的政务秘书。
人类则始终受自身认知局限束缚，而衡量这一困境的核心框架正是四层认知象限。
二、核心框架。
四层认知象限清晰定义全文统一四组认知状态的内涵。
这是所有分析的基础。
One  you know what you know  知其所知，自身完全掌握，可随时调取。
能熟练运用的知识，是一切思考、提问、探索唯一的起点。
To you know what you don't know 知其所不知。
清晰察觉自身存在认知缺口，主动意识到自身短板，进而生出提问、求证、学习的内在动力，是主动向外探索的关键状态。
Three You don't know what you know 不知其所知。
答案、资料、相关经验客观存在于公开网络、文档、记忆之中。
自身拥有获取渠道，却因各类阻碍无法识别、调取、内化，坐拥资源却难以利用。
For  you don't know what you don't know 不知其所不知，最隐蔽、最难自行突破的深层盲区。
人完全无法意识到某类规律、风险、领域的存在，连探索防备的念头都不会产生。
它既是人滋生傲慢、止步不前的根源，也是 AI 产生幻觉的底层诱因。
三、角色对照。
政务秘书与 AI。
共享同一套被动逻辑。
一、信息载体的共性，被动应答，不主动拓界。
政务秘书和人工智能具备完全一致的行为特征。
仅依据外界输入作出回应，无主动拓宽使用者认知的内在驱动力。
二者掌握完整的底层信息，隐藏风险与逻辑细节远超使用者认知范围。
却只会针对明确提问输出内容，不会主动补充提问框架以外的维度、矛盾与隐患。
早年航天从业者评价创业者时那句。
你不知道你不知道的事，正是在描述典型的不知其所不知状态。
从业者只掌握表层商业逻辑，对行业数十年沉淀的隐性工程风险毫无概念。
在盲区中盲目试错。
对应到 AI 领域，幻觉现象同样源于第四层认知困境。
模型没有内置区分有无对应事实的自检机制。
训练目标要求持续生成通顺文本。
即便知识库不存在相关真实信息，它也无法感知自身空白，只能依靠词语统计关联编造看似合理的内容。
和人类困于盲区，便主观笃定一切尽在掌握，底层逻辑相通。
二、人类作为求知者，天然受认知框架束缚所有人的提问范围。
永远局限于自身已有的，知其所知。
完全超出个人认知框架的风险维度与真相，不会转化为具体问题，信息工具自然不会给出对应解答。
就像剧中大臣只能围绕直观的预算问题发问，却想不到体系冗余才是亏损根源。
普通人使用 AI 时，也只会基于固有认知提出单一视角的问题。
工具不会自发补齐用户未曾设想的隐性矛盾，这是人机交互中无法绕开的先天局限。
四，消解终极盲区。
两条并行的求知路径，我们求索真理，压缩不知其所不知的范围。
仅有两条相辅相成的可行路径，不存在第三条捷径。
人类全部科学实践、学习、成长都依托二者运转。
路径一，向外开拓，抵达，知其所不知，直面未知，主动求证，这是科学实验、社会实践、个人成长的主流路径。
现实挫折、预判与事实的偏差、不同观点的碰撞，会让人直观察觉到自身存在大量空白，原本看不见的盲区转化为清晰可攻克的问题。
落实在人机交互中，便是带着明确的疑问向 AI 搜索引擎求助，定向弥补已知的短板。
落实在个人成长层面，则是在试错受挫后，放下主观傲慢，主动开启学习。
这条路径的核心价值是把完全隐形的深层盲区。
转化为可定向探索的明确未知，直接缩小不知其所不知的边界。
路径二，向内挖掘，破解不知其所知。
盘活存量信息互联网数据库大模型存储着人类绝大多数存量知识。
理论上所有人都可自由调取，但多数人依旧入宝山空手回。
三重客观阻碍无法消除。
第一，信息过载与话术遮蔽，有效内容混杂海量冗余修饰文本，筛选成本极高。
第二，知识存在链式依赖。
想要理解复杂结论，必须先掌握全套前置基础。
工具只能搬运文本，无法跳过完整学习链条，直接赋予理解能力。
第三，真假信息混杂共存，搜索引擎。
AI 无法自主完成逻辑校验与真伪辨别，分辨、验证、纠错，只能依靠人的主观思辨。
书籍、老师、 AI 搜索引擎，都只是打捞存量知识的工具，能够降低检索门槛，却无法替代人完成吸收、内化、实践。
正所谓师傅领进门，修行在个人。
单纯填鸭式灌输只能形成浅层条件反射，真正掌握知识离不开使用者自身的主观能动性。
这条路径的核心价值是唤醒客观存在却无法取用的存量信息，避免重复探索已有答案，减少无效试错。
五、核心结论。
任何工具都无法替代人类完成完整认知闭环。
搜索引擎、大模型、实验仪器、书本、师长。
全部属于被动型信息工具，拥有三个恒定特质。
一、工具仅遵循使用者指令运行，不会主动突破对方的认知边界。
无法自发提醒隐藏盲区。
二、工具可以整理信息、拆解原理、应答疑问，但真伪鉴别、逻辑推演、内化运用、落地检验。
只能依靠人脑独立完成。
三、 AI 能大幅降低检索答疑的时间成本，却无法破解本源悖论，看不见的盲区不会生成提问。
缺少基础认知便无法消化现成答案。
任何人任何主体都不可能彻底消除不知其所不知。
世界持续存在未被观测、未被记录的全新规律。
盲区只能无限压缩，无法完全根除。
六、收尾。
人类文明永恒的求索循环，从低等生物无意识的生存试错，到人类有意识的主动求真。
一切智能主体的认知迭代遵循统一循环。
起点局限于知其所知，向外分支，遭遇现实偏差，察觉自身短板。
进入知其所不知，通过学习求证，将未知转化为自身已知向内分支，借助各类信息工具破解不知其所知，盘活闲置存量知识两条路径持续循环，不断挤压。
不知其所不知的边界。
千万年来，人类探索世界、迭代文明、追寻真理，本质就是持续压缩深层盲区的漫长过程。
这也是我们从有限已知不断突破，从必然王国走向自由王国的旅途。
认清所有信息工具的被动属性，守住人脑独立思辨、主动吸收的核心作用。
主动接纳自身存在局限，善用工具挖掘存量真知，审慎校验一切外来信息，便是这套四维认知模型带给我们最核心的启示。

修正脚本

四维认知象限，从《是，大臣》看懂人类求知、 AI 交互与认知永恒悖论。
《是，大臣》里一段政务博弈。
一句评价马斯克的，You don't know what you don't know。
一套经典四维认知模型，能够统一解释官僚信息博弈、大模型运行逻辑，以及人类长久以来求索真理的底层困境。
我们依靠各类工具从已知奔赴未知，可一条天然的认知悖论始终横亘在所有求知行为前方。
一、这正是《是，大臣》里无解的信息闭环，整部剧集的核心冲突。
本质是一场认知博弈。
一边是代表求知者、决策者的大臣，另一边是手握全部信息、等同于信息工具的常务政务秘书。
二者存在明确规则约束。
秘书有义务如实回答大臣提出的每一个问题，不能刻意编造谎言。
但他拥有天然的信息选择权。
绝不会主动披露隐患、补充盲区、提醒风险。
由此形成无法挣脱的闭环悖论，项目缺陷、资金漏洞、制度弊病全部记录在成堆公文与附件中。
信息客观上完全对大臣开放，可想要获知隐藏的真相，前提是提出精准对应的问题。
大臣困于自身认知边界。
根本意识不到自己存在哪些未知，自然无法抛出触及核心的疑问。
海量报告堆满桌面，关键信息藏在委婉话术与冗余文本之间。
即便全部文件可供查阅，决策者也极易入宝山而空手回。
掌握全局信息的秘书只被动应答，不问不补。
不会主动拓宽提问者的思考维度。
这套交互逻辑和当下人与AI、搜索引擎的相处模式高度相似。
AI 如同数字化的政务秘书。
人类则始终受自身认知局限束缚，而衡量这一困境的核心框架正是四层认知象限。
二、核心框架。
四层认知象限清晰全面定义了四组认知状态的内涵。
这是所有分析的基础。
One  you know what you know  知其所知，自身完全掌握，可随时调取。
能熟练运用的知识，是一切思考、提问、探索唯一的起点。
Two you know what you don't know 知其所不知。
清晰察觉自身存在认知缺口，主动意识到自身短板，进而生出提问、求证、学习的内在动力，是主动向外探索的关键状态。
Three You don't know what you know 不知其所知。
答案、资料、相关经验客观存在于公开网络、文档、记忆之中。
自身拥有获取渠道，却因各类阻碍无法识别、调取、内化，坐拥资源却难以利用。
Four you don't know what you don't know 不知其所不知，最隐蔽、最难自行突破的深层盲区。
人完全无法意识到某类规律、风险、领域的存在，连探索防备的念头都不会产生。
它既是人滋生傲慢、止步不前的根源，也是 AI 产生幻觉的底层诱因。
三、角色对照。
政务秘书与 AI。
共享同一套被动逻辑。
一、信息载体的共性，被动应答，不主动拓界。
政务秘书和人工智能具备完全一致的行为特征。
仅依据外界输入作出回应，无主动拓宽使用者认知的内在驱动力。
二者掌握完整的底层信息，隐藏风险与逻辑细节远超使用者认知范围。
却只会针对明确提问输出内容，不会主动补充提问框架以外的维度、矛盾与隐患。
早年航天从业者评价创业者时那句：
你不知道你不知道的事，正是在描述典型的不知其所不知状态。
从业者只掌握表层商业逻辑，对行业数十年沉淀的隐性工程风险毫无概念。
在盲区中盲目试错。
对应到 AI 领域，幻觉现象同样源于第四层认知困境。
模型没有内置区分有无对应事实的自检机制。
训练目标要求持续生成通顺文本。
即便知识库不存在相关真实信息，它也无法感知自身空白，只能依靠词语统计关联编造看似合理的内容。
和人类困于盲区，便主观笃定一切尽在掌握，底层逻辑相通。
二、人类作为求知者，天然受认知框架束缚，所有人的提问范围永远局限于自身已有的知其所知。
完全超出个人认知框架的风险维度与真相，不会转化为具体问题，信息工具自然不会给出对应解答。
就像剧中大臣只能围绕直观的预算问题发问，却想不到体系冗余才是亏损根源。
普通人使用 AI 时，也只会基于固有认知提出单一视角的问题。
工具不会自发补齐用户未曾设想的隐性矛盾，这是人机交互中无法绕开的先天局限。
四、消解终极盲区。
两条并行的求知路径，我们求索真理，压缩不知其所不知的范围。
仅有两条相辅相成的可行路径，不存在第三条捷径。
人类全部科学实践、学习、成长都依托二者运转。
路径一，向外开拓，抵达知其所不知，直面未知，主动求证，这是科学实验、社会实践、个人成长的主流路径。
现实挫折、预判与事实的偏差、不同观点的碰撞，会让人直观察觉到自身存在大量空白，原本看不见的盲区转化为清晰可攻克的问题。
落实在人机交互中，便是带着明确的疑问向 AI 搜索引擎求助，定向弥补已知的短板。
落实在个人成长层面，则是在试错受挫后，放下主观傲慢，主动开启学习。
这条路径的核心价值是把完全隐形的深层盲区，转化为可定向探索的明确未知，直接缩小不知其所不知的边界。
路径二，向内挖掘，破解不知其所知。盘活存量信息。互联网、数据库、大模型存储着人类绝大多数存量知识。
理论上所有人都可自由调取，但多数人依旧入宝山空手回。
三重客观阻碍无法消除。
第一，信息过载与话术遮蔽，有效内容混杂海量冗余修饰文本，筛选成本极高。
第二，知识存在链式依赖。
想要理解复杂结论，必须先掌握全套前置基础。
工具只能搬运文本，无法跳过完整学习链条，直接赋予理解能力。
第三，真假信息混杂共存，搜索引擎、AI 无法自主完成逻辑校验与真伪辨别，分辨、验证、纠错，只能依靠人的主观思辨。
书籍、老师、 AI 搜索引擎，都只是打捞存量知识的工具，能够降低检索门槛，却无法替代人完成吸收、内化、实践。
正所谓师傅领进门，修行在个人。
单纯填鸭式灌输只能形成浅层条件反射，真正掌握知识离不开使用者自身的主观能动性。
这条路径的核心价值是唤醒客观存在却无法取用的存量信息，避免重复探索已有答案，减少无效试错。
五、核心结论。
任何工具都无法替代人类完成完整认知闭环。
搜索引擎、大模型、实验仪器、书本、师长，全部属于被动型信息工具，拥有三个恒定特质。
一、工具仅遵循使用者指令运行，不会主动突破对方的认知边界。
无法自发提醒隐藏盲区。
二、工具可以整理信息、拆解原理、应答疑问，但真伪鉴别、逻辑推演、内化运用、落地检验，只能依靠人脑独立完成。
三、 AI 能大幅降低检索答疑的时间成本，却无法破解本源悖论，看不见的盲区不会生成提问。
缺少基础认知便无法消化现成答案。
任何人任何主体都不可能彻底消除不知其所不知。
世界持续存在未被观测、未被记录的全新规律。
盲区只能无限压缩，无法完全根除。
六、收尾。
人类文明永恒的求索循环，从低等生物无意识的生存试错，到人类有意识的主动求真。
一切智能主体的认知迭代遵循统一循环：起点局限于知其所知，向外分支，遭遇现实偏差，察觉自身短板，进入知其所不知，通过学习求证，将未知转化为自身已知；向内分支，借助各类信息工具破解不知其所知，盘活闲置存量知识。两条路径持续循环，不断挤压不知其所不知的边界。
千万年来，人类探索世界、迭代文明、追寻真理，本质就是持续压缩深层盲区的漫长过程。
这也是我们从有限已知不断突破，从必然王国走向自由王国的旅途。
认清所有信息工具的被动属性，守住人脑独立思辨、主动吸收的核心作用。
主动接纳自身存在局限，善用工具挖掘存量真知，审慎校验一切外来信息，便是这套四维认知模型带给我们最核心的启示。

英文翻译

Four-dimensional cognitive quadrant: Understanding humanity's quest for knowledge, AI interaction, and the eternal paradox of cognition through *Yes, Minister*.

A political bargaining scene in *Yes, Minister*.  
A comment on Musk: "You don't know what you don't know."  
A classic four-dimensional cognitive model that can uniformly explain bureaucratic information games, the operational logic of large models, and the deep-seated predicament of humanity’s long-standing pursuit of truth.  
We rely on various tools to move from the known to the unknown, yet a natural cognitive paradox always stands before all acts of seeking knowledge.

I. This is precisely the inescapable information loop in *Yes, Minister*, the core conflict of the entire series.  
It is essentially a cognitive game.  
On one side is the minister, representing the seeker of knowledge and the decision-maker; on the other is the Permanent Secretary, who holds all the information and acts as an information tool.  
There are clear rules governing both parties.  
The Secretary is obliged to truthfully answer every question posed by the minister and cannot deliberately fabricate lies.  
But he has the natural right to choose what information to disclose.  
He will never proactively reveal hidden risks, fill in blind spots, or alert to dangers.  
This creates an inescapable closed-loop paradox: project flaws, funding gaps, and institutional deficiencies are all recorded in piles of documents and appendices.  
Objectively, the information is fully accessible to the minister, but to uncover the hidden truth, he must first ask precisely targeted questions.  
The minister is trapped by his own cognitive boundaries.  
He is fundamentally unaware of what he does not know, and thus cannot raise questions that touch the core.  
Massive reports pile up on the desk, with key information hidden between euphemistic language and redundant text.  
Even if all files are available for review, the decision-maker can easily "enter the treasure mountain and return empty-handed."  
The Secretary, who holds the complete picture, only responds passively and does not supplement without a question.  
He will not actively expand the questioner’s thinking dimensions.  
This interaction logic is highly similar to the current mode of interaction between humans and AI or search engines.  
AI is like a digital Permanent Secretary.  
Humans are always constrained by their own cognitive limitations. The core framework for measuring this dilemma is precisely the four-layer cognitive quadrant.

II. The core framework.  
The four-layer cognitive quadrant clearly and comprehensively defines the meanings of four groups of cognitive states.  
This is the foundation of all analysis.  
One: You know what you know — Knowing what you know, fully mastered and can be retrieved at any time.  
Knowledge that can be skillfully applied is the only starting point for all thinking, questioning, and exploration.  
Two: You know what you don’t know — Knowing what you don’t know.  
Clearly aware of cognitive gaps, actively recognizing one’s own shortcomings, thereby generating intrinsic motivation to question, verify, and learn — a key state for active outward exploration.  
Three: You don’t know what you know — Not knowing what you know.  
Answers, materials, and relevant experiences objectively exist in public networks, documents, and memory.  
You have access channels but cannot identify, retrieve, or internalize due to various obstacles — sitting on resources but unable to use them.  
Four: You don’t know what you don’t know — Not knowing what you don’t know. The most hidden and hardest blind spot to break through on one’s own.  
A person is completely unaware of the existence of certain patterns, risks, or domains, and does not even generate the thought of exploring or guarding against them.  
It is both the root of human arrogance and stagnation, and the underlying cause of AI hallucinations.

III. Role comparison.  
The Permanent Secretary and AI share the same passive logic.  
1. The commonality of information carriers: passive response, no proactive boundary expansion.  
The Permanent Secretary and artificial intelligence have identical behavioral characteristics.  
They only respond based on external input, without an intrinsic drive to actively broaden the user's cognition.  
Both hold complete underlying information, with hidden risks and logical details far beyond the user’s cognitive scope.  
Yet they only output content in response to specific questions, without proactively supplementing dimensions, contradictions, or risks outside the question’s framework.  
The early aerospace practitioner’s comment on entrepreneurs — "You don’t know what you don’t know" — is precisely describing the typical state of not knowing what you don’t know.  
The practitioners only grasp surface-level business logic, with no concept of the implicit engineering risks accumulated over decades in the industry.  
They blindly trial-and-error in blind spots.  
Corresponding to the AI domain, the phenomenon of hallucination also stems from the fourth-layer cognitive predicament.  
The model has no built-in self-check mechanism to distinguish whether corresponding facts exist.  
The training objective requires continuous generation of coherent text.  
Even if the knowledge base contains no relevant real information, it cannot perceive its own gaps, relying only on statistical correlations of words to fabricate seemingly reasonable content.  
This is fundamentally the same as humans, who, trapped in blind spots, subjectively believe everything is under control.

2. Humans, as seekers of knowledge, are naturally bound by cognitive frameworks. All people’s questioning scope is forever limited to their own "you know what you know."  
Risk dimensions and truths completely beyond an individual’s cognitive framework will not be transformed into specific questions, and information tools will naturally not provide corresponding answers.  
Just as the minister in the drama can only ask questions around intuitive budget issues but cannot imagine that systemic redundancy is the root cause of losses, ordinary people using AI will only raise single-perspective questions based on their inherent cognition.  
The tool will not spontaneously fill in implicit contradictions the user never envisioned — this is an inherent limitation in human-computer interaction that cannot be bypassed.

IV. Dissolving the ultimate blind spot: Two parallel paths of seeking knowledge.  
We seek truth to compress the scope of "not knowing what you don’t know."  
There are only two complementary viable paths, no third shortcut.  
All of humanity’s scientific practice, learning, and growth rely on these two paths.  
Path one: Outward exploration, reaching "you know what you don’t know." Face the unknown, actively seek verification. This is the mainstream path of scientific experiments, social practice, and personal growth.  
Real-world setbacks, deviations between predictions and facts, and collisions of different viewpoints allow people to intuitively perceive large gaps in themselves. Previously invisible blind spots transform into clear, solvable problems.  
In human-computer interaction, this means turning to AI or search engines with specific questions to purposefully fill known shortcomings.  
In personal growth, it means, after trial and error and setbacks, letting go of subjective arrogance and actively initiating learning.  
The core value of this path is converting completely hidden deep blind spots into clearly targeted unknowns, directly reducing the boundary of "not knowing what you don’t know."  
Path two: Inward excavation, cracking "you don’t know what you know." Revitalize existing information. The internet, databases, and large models store the vast majority of humanity’s accumulated knowledge.  
Theoretically, everyone can freely access it, but most still "enter the treasure mountain and return empty-handed."  
Three objective obstacles are insurmountable.  
First: Information overload and rhetorical obscuration. Effective content is mixed with massive redundant decorative text, making filtering costs extremely high.  
Second: Knowledge has chain dependencies. To understand a complex conclusion, you must first master the entire prerequisite foundation. Tools can only transfer text; they cannot skip the complete learning chain and directly grant understanding.  
Third: True and false information coexist. Search engines and AI cannot autonomously perform logical verification or truth discernment — distinguishing, verifying, and correcting errors rely solely on human subjective reasoning.  
Books, teachers, AI, and search engines are merely tools for retrieving existing knowledge. They can lower the barrier to searching, but cannot replace humans in absorbing, internalizing, and practicing.  
As the saying goes, "The master leads you to the door; cultivation depends on yourself."  
Simple rote灌输 only creates shallow conditioned reflexes. True mastery of knowledge depends on the user’s own subjective initiative.  
The core value of this path is awakening objective but inaccessible existing information, avoiding redundant exploration of already-known answers, and reducing ineffective trial and error.

V. Core conclusion.  
No tool can replace humans in completing the full cognitive loop.  
Search engines, large models, experimental instruments, books, and teachers are all passive information tools with three constant characteristics:  
1. Tools only operate according to user instructions and will not actively break through the user’s cognitive boundaries. They cannot spontaneously alert to hidden blind spots.  
2. Tools can organize information, break down principles, and answer questions, but truth discernment, logical deduction, internalization, application, and empirical testing must be completed by the human brain independently.  
3. AI can greatly reduce the time cost of searching and answering, but it cannot solve the fundamental paradox: invisible blind spots do not generate questions. Without basic cognition, ready-made answers cannot be digested.  
No person or entity can completely eliminate "not knowing what you don’t know."  
The world continuously contains new patterns that have not been observed or recorded.  
Blind spots can only be infinitely compressed, never completely eradicated.

VI. Conclusion.  
The eternal cycle of human civilization’s quest: from the unconscious trial and error of lower organisms to humanity’s conscious pursuit of truth.  
The cognitive iteration of all intelligent entities follows a unified cycle: starting from "you know what you know," branching outward, encountering real-world deviations, perceiving one’s own shortcomings, entering "you know what you don’t know," transforming the unknown into known through learning and verification; branching inward, using various information tools to crack "you don’t know what you know," revitalizing idle existing knowledge. The two paths continuously cycle, constantly squeezing the boundary of "you don’t know what you don’t know."  
For thousands of years, humanity’s exploration of the world, iterative civilization, and pursuit of truth have essentially been a long process of continuously compressing deep blind spots.  
This is also our journey from limited known breakthroughs, from the realm of necessity to the realm of freedom.  
Recognizing the passive nature of all information tools, upholding the core role of the human brain’s independent reasoning and active absorption, actively accepting one’s own limitations, using tools to excavate existing true knowledge, and carefully verifying all external information — these are the most central revelations this four-dimensional cognitive model brings us.