Notes on 《How the Mind Works》Ch.4 —— The Mind's Eye

In this chapter, steven explores how vision turns retinal depictions into mental descriptions.

The definition of vision: a process that produces from images of the external world a description that is useful to the viewer and not cluttered with irrelevant information.
What description means here is: mental symbol, and the mental propositions that capture the spatial relations among objects.

Correspondence problem in stereo vision: matching up the marks in one eye with their counterparts in the other.

In order to solve the matchup in mind, there are 3 built-in assumptions about the world we evolved in plus constraint satisfaction:

1. every mark in the world is anchored to one position on one surface at one time.
2. a dot in one eye should be matched with no more than one dot in the other.
3. matter is cohesive and smooth.

Constraint-satisfaction technique: make tentative guesses and hash it out among themselves until a global solution emerges

Stereo vision is a mixture of nature and nurture:

• different forms of stereoblindness suggest is is genetically determined
• stereo vision is not present at birth, and it can be permanently damaged in children or young animals if one of the eyes is temporarily deprived of input or disrupted by experience.

A visual system make us see the most probable state of the world given the retinal images via probability theory -- Bayes' theorem（贝叶斯方法）: assigning a probability to a hypothesis based on some evidence. That is, the odds favoring one hypothesis over another can be calculated from just two numbers for each hypothesis:

1. prior probability（先验概率）: how confident are you in the hypothesis before you even look at the evidence? （假设本身独立的可能性大小）
   
2. likelihood（相似度）: if the hypothesis were true, what is the probability that the evidence as you are seeing it now would have appeared?

How we see the world around us:

1. We see only what is in front of our eyes; the world beyond the perimeter of the visual field and behind the head is known only in a vague, almost intellectual way.
2. We see surfaces, not volumes.
3. We see in perspective.
4. We don't immediately see "objects".
5. We see in two and a half dimensions. Depth is whimsically downgraded to half a dimension because it does not define the medium in which visual information is held (unlike the left-right and high-low dimensions)

In order to access the visual information properly, Reference frames are inextricable.

• rentina's frame: allow us to judge the location via compensating for movements of the head and body.
• world-aligned reference frame: allow us to judge the genuine angles and extents of the matter outside our skin.
• the inner ear's frame: allow us to judge the direction of gravity

Motion sickness is triggered by the mismatch signals sent from the retina's frame and inner ear's frame.

Several theories used in shape recognition:

1. geon theory (by Irv Biederman):
• geon is simple geometric part of objects. ( Like protons and electrons making up atoms)
• Geons can be assembled into objects with a few attachment relations like "above", "beside", "parallel" etc. (These relations are defined in a frame of reference centered on the object not the visual field)
• Geons are combinatorial, like grammar. (an object is not the sum of its geons but depends on their spatial arrangement;) 24 types of geon, 15 different sizes and builds, 81 ways to join them.
• Left hemisphere: has the ability to recognize and imagine shapes defined by arrangments of geons.
• Right hemisphere: to measure whole shapes like taller or shoter, nearer or distanter.
2. multiple-view theory: people create a separate memory file for every orientation in which an object commonly appeared.
3. mental-rotation theory: people rotate shapes in their minds. When a shape appeared at a new, unfamiliar orientation, the farther it would have to be rotated to be aligned with the nearest familiar view, the more time people took.

When to use which theory for shape recognition:

• when a shape's sides are not too different, geon theory is used.
• when the shape is more complicated, multiple-view theory is used.
• When the shape appears at an unfamiliar orientation, mental-rotation theory is used.

What is mental image for:

• A mental image is a pattern in the 2 and 1/2 -Dimension sketch that is loaded from long-term memory rather than from the eyes.
• Mental imagery is the engine that drives our thinking about objects in space.
• Mental imagery help creative people to "see" the solution to a problem.
• Images drive the emotions as well as the intellect.

Thinking in images engages the visual parts of the brain.

• the Perky effect: holding a mental image interferes with seeing faint and fine visual details.
• Mental images of lines can affect perception just as real lines do: they make it easier to judge alignment and can even induce visual illusions.

Thinking in images has some limitations:

• Images are fragmentary.people cannot reconstruct an image of an entire visual scene.
• images are slaves to the organization of memory.
• images cannot serve as our concepts, nor can they serve as the meanings of words in the mental dictionary.

Notes on 《How the Mind Works》Ch.3 —— Revenge of Nerds

In this chapter, Steven mainly explains how the human mind evolve over eons in the light of natural selection and distinguishs the evolutionary theory from other plausible theories.

Evolution is about ends, not means; Intelligence isn't for every species because:

• organisms don't evolve toward every imaginable advantage.
• An organism that devotes some of its matter and energy to one organ must take it away from another.
• Organs evolve only when their benefits outweigh their costs.

Based on this premise, it explains why some creatures do not evolve a humanlike brain:

1. the brain is bukly, which makes people more vulnerable.
2. the brain needs energy. 2% weighted brain need to consume 20% energy and nutrients.
   
3. the brain take time to learn to use.
4. simple tasks can be slow.
   

Rickard Dawkins's evolutionary theory v.s Directed/Adaptive mutation:

• mutations are indifferent overall to the benefits they confer on the organism. (a cornerstone of the scientific worldview)
  
• mutations can not respond to organisms' needs in general.
  

The Baldwin effect: learning can guide evolution. The sustained behavior of a species or group can shape the evolution of that species.

Four traits make our ancestors easier to evolve better powers of causal reasoning:

1. vision: depth perception and color vision together have pushed the primate brain into splitting the flow of visual information into two streams: a "what" system, for objects and their shapes and compositions, and a "where" system, for their locations and motions. The human mind grasps the world—even the most abstract, ethereal concepts—as a space filled with movable things and stuff.
2. group living:
   
1. several advantages:
• protect themselves better
  
• foraging efficiency
• the benefit of the knowledge and the benefit of whatever it can get in trade for the knowledge.
2. Group living could have set the stage for the evolution of humanlike intelligence in two ways:
1. the value of having better information is multiplied
2. The other way in which a group can be a crucible of intelligence is that group living itself poses new cognitive challenges.
3. the hand and fully upright posture
4. hunting: provides sporadic packages of concentrated nutrients so that we could afford our expensive brains, can be traded for other resouces.
   

Inglish_10/11/09

mise en scene: 上演; 舞台调度; 导演; 布景和道具
we need more than a terse mise en scene to make our way around the world.

spell out: 讲清楚; 清楚地说明
I want to spell out the case for this foundational idea.

bric-a-brac: 小古董; 小古玩
Living things are not just pretty bits of bric-a-brac, but do amazing things.

nuts and bolts: 基本要素, 基础部分，
The evolution of information processing has to be accomplished at the nuts-and-bolts level by selection of genes that affect the brain-assembly process.

If You Knew —— 《My Sister's Keeper》

想找的，不过是一个可以流泪的借口。
　　
当泪水真的涌出，心中涌起更多的，是思念，是孤寒，是哀伤，是惘然，是苦涩，是痛切......
　　
If you knew......
　　
Something in your eyes, makes me wanna lose myself
Makes me wanna lose myself, in your arms
There's something in your voice, makes my heart beat fast
Hope this feeling lasts, the rest of my life
　　
If you knew how lonely my life has been
And how long I've been so alone
And if you knew how I wanted someone to come along
And change my life the way you've done
　　
It feels like home to me, it feels like home to me
It feels like I'm all the way back where I come from
It feels like home to me, it feels like home to me
It feels like I'm all the way back where I belong
　　
A window breaks, down a long, dark street
And a siren wails in the night
But I'm alright, because I have you here with me
And I can almost see, through the dark there is light
　　
Well, if you knew how much this moment means to me
And how long I've waited for your touch
And if you knew how happy you are making me
I never thought that I'd love anyone so much
......
　　
If you knew something would last longer than you thought they would.
If you knew......

Notes on 《How the Mind Works》Ch.2 —— Thinking Machine

This chapter mainly deals with 2 questions:

What makes intelligence possible?

Two meanings of "intelligence": aptitude and rational, humanlike thought.

The characteritics of intelligence:

• To make decisions "rationally," by some set of rules (applying a set of operations that reduce the difference.)
• Wanting and pursuing something in the face of obstacles (specifying a goal)
• To use the rational rules to attain the goal in different ways, depending on the obstacles to be overcome. (assessing the current situation to see how it differs from the goal)

Intelligence does not come from a special kind of spirit or matter or energy but from a different commodity, information. Information is a correlation between two things that is produced by a lawful process (as opposed to coming about by sheer chance).

2 properties glued together in the entity we call a symbol:

1. carries information
2. causes things to happen.

The computational theory of mind is the hypothesis that intelligence is computation, which demystified mentalistic terms.

• Beliefs are inscriptions in memory
• desires are goal inscriptions
• thinking is computation
• perceptions are inscriptions triggered by sensors
• trying is executing operations triggered by a goal.

The computational theory of mind also rehabilitates once and for all the infamous homunculus.

1. Homunculi don't duplicate entire the talents they are rung in to explain, instead, a team or committee of relatively ignorant, narrow-minded, blind homunculi to produce the intelligent behavior of the whole.
2. A representation is a set of symbols corresponding to aspects of the world, and each homunculus is required only to react in a few circumscribed ways to some of the symbols.

How a symbol in a mind can mean something:

• a symbol is connected to its referent in the world by our sense organs.
• the unique pattern of symbol manipulations triggered by the first symbol mirrors the unique pattern of relationships between the referent of the first symbol and the referents of the triggered symbols.
• Together the causal and inferential roles of a symbol determine what it represents.

Human brain uses at least four major formats of representation:

1. visual image: like a template in a two-dimensional, picturelike mosaic.
2. phonological representation: a stretch of syllables that we play in our minds like a tape loop. This stringlike representation is an important component of our short-term memory. Phonological short-term memory lasts between one and five seconds and can hold from four to seven "chunks."
3. grammatical representation: nouns and verbs, phrases and clauses, stems and roots, phonemes and syllables, all arranged into hierarchical trees.
4. mentalese: the language of thought in which our conceptual knowledge is couched, the medium in which book's content or gist is captured

Minds is a special case of modular, hierarchical design in all complex systems.Complex systems are hierarchies of modules because only elements that hang together in modules can remain stable long enough to be assembled into larger and larger modules.

Neural networks is more like everything-connected-to-everything network, which sometimes called auto-associator, has five nifty features:

1. a reconstructive, content-addressable memory.
2. use a preponderance of mutually consistent pieces of information to override one unusual piece. "graceful degradation" helps deal with noisy input or hardware failure,
   
3. do a simple version of the kind of computation called constraint satisfaction.
4. ability to generalize automatically.
5. learn from examples, where learning consists of changes in the connection weights.

Two laws governing the thought of the association of ideas (associationism: 观念联想论):

1. contiguity: ideas that are frequently experienced together get associated in the mind. Thereafter, when one is activated, the other is activated too.
   
2. resemblance: when two ideas are similar, whatever has been associated with the first idea is automatically associated with the second.

Five feats giving human thought its distinctive precision and power, but they are the problems for associative network:

1. individuality: neural network has problem to distinguish individuals with identical properties from classes, but human mind can.
2. compositionality: the ability of a representation to be built out of parts and to have a meaning that comes from the meanings of the parts and from the way they are
   combined. Compositionality is the quintessential property of all human languages. Human thoughts are assembled out of concepts; they are not stored whole.
3. quantification (or variable-binding): It arises from a combination of the first problem, individuals, with the second, compositionality. Our compositional thoughts are, after all, often about individuals, and it makes a difference how those individuals are linked to the various parts of the thought. Hooking up concepts to their roles is not enough. Logicians capture these distinctions with variables and quantifiers.
4. recursion: the ability to embed a proposition inside another proposition bestows the ability to think an infinite number of thoughts. Unless neural networks are specially assembled into a recursive processor, they cannot handle our recursive thoughts.
5. People think in two modes, that is, fuzzy and crisp versions of the same category can live side by side in a single head.
   

• People can form fuzzy stereotypes by uninsightfully soaking up correlations among properties, taking advantage of the fact that things in the world tend to fall into clusters
• People can also create systems of rules—intuitive theories—that define categories in terms of the rules that apply to them, and that treat all the members of the category equally.

When the "ideas" were replaced by stimuli and responses, associationism became behaviorism.

What makes consciousness possible?

Different meanings/interpretations of consciousness:

• intelligence:
  
• self-knowledge: an intelligent being can have information about is the being itself.
• access to information: this meanings embraces Freud's distinction between the conscious and the unconscious mind. That is: the mass of information processing in the nervous system falls into two pools:
  
1. One pool, which includes the products of vision and the contents of shortterm memory, can be accessed by the systems underlying verbal reports, rational thought, and deliberate decision making.
   
2. The other pool, which includes autonomic (gut-level) responses, the internal calculations behind vision, language, and movement, and repressed desires or memories (if there are any), cannot be accessed by those systems.
• sentience: subjective experience, phenomenal awareness, raw feels, first-person present tense. The main features of this sense of consciousness: sensory awareness, focal attention, emotional coloring, and the will.

Any intelligent agent incarnated in matter, working in real time, and subject to the laws of thermodynamics must be restricted in its access to information because information has costs:

• space: the hardware to hold the information.
• time:Solving a problem in a hundred years is, practically speaking, the same as not solving it at all.
• resources:Information processing requires energy. working brain tissue calls more blood its way and consumes more glucose.

Access-consciousness has four obvious features:

1. we are aware, to varying degrees, of a rich field of sensation: colors, shapes, sounds, smells, the pressures and aches etc.
• Our immediate awareness seems to tap the intermediate levels, does not exclusively tap the lowest levels of sensations and the highest level of representation, either.
2. portions of this information can fall under the spotlight of attention, get rotated into and out of short-term memory, and feed our deliberative cogitation.
3. sensations and thoughts come with an emotional flavoring: pleasant or unpleasant, interesting or repellent, exciting or soothing.
4. an executive, the "I," appears to make choices and pull the levers of behavior.

Notes on 《How the Mind Works》Ch.1 —— Standard Equipment

The rationale for reverse-engineering living things comes from Charles Darwin.

• In forward-engineering, one designs a machine to do something;
  
• in reverse-engineering, one figures out what a machine was designed to do. Psychology is engineering in reverse.

Evolutionary psychology brings together two scientific revolutions:

1. the cognitive revolution of the 1950s and 1960s: helps us to understand how a mind is possible and what kind of mind we have.
2. evolutionary biology of the 1960s and 1970s: helps us to understand why we have the hnd of mind we have.

How to connect the ethereal world of meaning and intention, the stuff of our mental lives, with a physical hunk of matter like the brain? The computational theory of mind resolves the question:

• beliefs and desires are information, incarnated as configurations of symbols
• The symbols are the physical states of bits of matter
• symbols bump into symbols, one belief give rise to another belief, eventually, the bits of matter bump into bits of matter connected to the muscles, and behavior happens.
• the content of brain activity lies in the patterns of connections and patterns of activity among the neurons.
• Minute differences in the details of the connections may cause similar-looking brain patches to implement very different programs.
• The same basic neural tissue embodies all of these programs

The mind is not a general problem solver. The mind has to be built out of specialized parts because it has to solve specialized problems.

To say that the mind is an evolutionary adaptation is not to say that all behavior is adaptive in Darwin's sense. Because:

1. selection operates over thousands of generations.Our brains are adapted to that long-vanished way of life, not to brand-new agricultural and industrial civilizations.
2. Our minds are designed to generate behavior that would have been adaptive, on average, in our ancestral environment, but any particular deed done today is the effect of dozens of causes.

The gene-centered theory of evolution does not imply that the point of all human striving is to spread our genes.

• Our goals are subgoals of the ultimate goal of the genes

• our goals are about health and lovers and children and friends.
• gene's goals are replicating themselves.
• By making us enjoy life, health, sex, friends, and children, the genes reach their goal
  

The three supposed implications of an innate human nature are wrong:

1. an innate human nature implies innate human differences, this is no implication at all.
2. if our ignoble motives are innate, they can't be so bad after all. (It is the naturalistic fallacy, that what happens in nature is right.). Happiness and virtue have nothing to do with what natural selection designed us to accomplish in the ancestral environment. They are for us to determine.
3. Blaming bad behavior on our genes, to understand is not to forgive.
   

Many computational faculties engineered by natural selection is our best hope for a grasp on how the mind works that does justice to its complexity.

Inglish_04/11/09

cozy up to: 奉承(拉拢, 取悦)
J. T. thought Venkatesh was crazy, literally—a university student wanting to cozy up to a crack gang?

out of place:不在适当的位置; 不合适的, 不相称的, 不恰当的

He felt so out of place there—like a white man working at Afro Sheen headquarters, he liked to say—that he quit.

ripple effect: 连锁反应
The Butterfly Effect is the theory that a small action in one place may have a ripple effect that creates a dramatic action in another place

bona fide: 真实的; 有诚意的

It offered a set of bona fide heroes rather than simply a dearth of villains.

pecking order： 长幼尊卑制度, 权势等级

Nobody wants to be at the bottom of the pecking order.

willy-nilly：不管愿不愿意的；乱糟糟的

If something happens to you willy-nilly, it happens whether you like it or not.
If someone does something willy-nilly, they do it in a careless and disorganized way, without planning it in advance.

to wit：那就是说; 即; 就是

He will leave at the end of term, to wit 30 July.

Thinking By Numbers —— 《Freakonomics》

我是抱着较大的期望读这本《Freakonomics》的，既因为它与最近我所追看的剧集《数字追凶》和两本行为经济学读物不无相关，也因为Malcolm Gladwell的推荐。看完之后，坦白说，有点失望。一方面，此书所陈述的所谓的离经叛道、有悖于传统思维的观点，没能如宣称的那般让我大跌眼镜，另一 方面，它也没能如一些书评人所言，像一本一流的侦探小说一样让我屏住呼吸。总体而言，该书讲故事比不上Gladwell的精彩和张驰有致，论信息量，又不 如《摇摆》姐妹篇的密集丰富。当然，它的亮点也不容置疑，就是Steven Levitt的巧思妙问和细致的数字解读方式。

读的时候，我时不时会想起《数字追凶》的片首语：

We all use maths everyday!

To predict weather, to tell time, to handle money. But maths is more than formulas and equations, It's logic, it's rationality.

We also use maths to analyze crime, review patterns, predict behaviours.

It's all about numbers. Using numbers we can solve the biggest mysteries we know.

当Steven Levitt运用大量的数据遴选出芝加哥教育系统中的“黑羊”老师时，当他揭示了日本相扑运动员比赛中作弊的模式时，当他求证出房地产经纪人并不会为他们 的客户达成最好的协议时, 当他自问自答了为什么毒品贩子还会和父母一起住在救济屋里时，当他推算出70年代流产的合法化才是美国90年代犯罪率显著下降的原因时，我的脑海中常常会 浮现出腼腆的 Charles在加州大学的教室黑板上运笔如飞、在自家车库的资料堆里冥思苦想、在FBI透明会议室的白板前对着一脸茫然的探员口若悬河的画面。看来，才识渊博的学者放下身段，走出象牙塔，走进世俗世界，跨领域合作研究，已是一种不可抵挡的潮流。无巧不巧 的是，号称经济学界的“印第安纳琼斯”的Steven，他的研究兴趣之一也聚焦在犯罪领域，区别是他手持的是经济学理论武装起来的解剖刀：从小处着手，剥 开现象的表层，在数字中寻找隐含规律，仔细辨析相关性和因果关系，冷眼解读事物的本质。

也许正如两位合作者所宣扬的，掀起了”苹果橘子经济学“热潮的这本书，致力于为我们提供一种独特的视角和另类的解释，来理解这个社会究竟是如何运行的、并试图破解那些平时根本无法破解的迷团。而这一切，都基于他们所提出的5个基本点：

1. incentives are the cornerstone of modern life
   
2. the conventional wisdom is often wrong
   
3. Dramatic effects often have distant, even subtle, causes.
   
4. "Experts" use their informational advantage to serve their own agenda.
   
5. Knowing what to measure and how to measure it makes a complicated world much less so.-- There is nothing like the sheer power of numbers to scrub away layers of confusion and contradiction.
   

归根结底，一旦找到合适的切入点，看似复杂无序的世界，会变得简单清晰起来。

P.S 此书第三章节还可观看Steven Levitt在TED关于毒品贩子为什么是个糟糕行业的风趣生动的演讲。

Addendum: A new post "When data and decision collide" from Seth Godin questions well how we should react when facing counter-intuitive data-driven findings, which I think sort of related to the points of this book.

Inglish_01/11/09

slam dunk: 很有把握, 肯定会发生的事情;a very impressive act;

Always keep in the back of your mind that no evidence will be a slam dunk that gets the job done conclusively.

mug shot: 嫌疑犯照片; a photograph of sb's face kept by the police in their records to identify criminals.

Tomkins, it was said, could walk into a post office, go over to the “Wanted” posters, and, just by looking at mug shots, tell you what crimes the various fugitives had committed.

airy-fairy: 不切实际的，天马行空的

Many explanations of behavior have an airy-fairy feel to them because they explain psychological phenomena in terms of other, equally mysterious psychological phenomena.

lingua franca: 混合语，a common language used by speakers of different languages

tease out: 梳理, 拣选出 If you tease ot information or a solution, you succeed in obtaining it even though this is difficult.

The key to measuring the Weakest Link voting data is to tease out a contestant’s playing ability from his race, gender, and age.

quid pro quo:赔偿; 报复

The most logical explanation is that the wrestlers made a quid pro quo agreement。

Save Me!

Another day passed, a new month begins, life stays the same......

I sat beneath the fall of tears as salt as yours, hearing the sighing years. I lied there drearily, wondering how I can find the peace in my mind, how long I could keep my sanity......

I can hear the voice wuthering from my deepest heart: my beloved, come back, save me, please. Days and nights, they drive me crazy......



How I wish I could hear you again, How I wish I could whisper to you again, How I wish I could hold you again, How I wish I could lie in your arms again, How I wish......

I wish for the millionth time......