Book Response #6: Ethnographic Articles

Book Response #5: Emotional Design vs Design of Everyday Things

Emotional Design
     By: Donald Norman

Assignment #1: 5 Examples of Good and Bad Design

Book Response #4: Design of Everyday Things - Chapters 5, 6, 7 + Overview

The Design of Everyday Things
      By: Donald A. Norman

Response to Chapter 5:

To Err is Human
  Slips
    Types of Slips
      Capture Errors
      Description Errors
      Data-Driven Errors
      Associative Activation Errors
      Loss-of-Activation Errors
      Mode Errors
    Detecting Slips
    Design Lessons from the Study of Slips
  Mistakes as Errors of Thought
    Some Models of Human Thought
      Connectionist Approach
  The Structure of Tasks
    Wide and Deep Structures
    Shallow Structures
    Narrow Structures
    Nature of Everyday Tasks
  Conscious and Subconscious Behavior
    Explaining Away Errors
    Social Pressure and Mistakes
  Designing for Error
    How to Deal with Error - and How NOT To
    Forcing Functions
  A Design Philosophy

Response to Chapter 6:

  The Design Challenge
    The Natural Evolution of Design
      Forces that Work Against Evolutionary Design
      The Typewriter: A Case History in the Evolution of Design
    Why Designers Go Astray
      Putting Aesthetics First
      Designers are Not Typical Users
      The Designer's Clients May Not Be Users
    The Complexity of the Design Process
      Designing for Special People
      Selective Attention: The Problem of Focus
    The Faucet: A Case History of Design Difficulties
    Two Deadly Temptations for the Designer
      Creeping Featurism
      The Worshipping of False Images
    The Foibles of Computer Systems
      How to do Things Wrong
      It's Not Too Late to Do Things Right
      Computer as Chameleon
        Explorable Systems: Inviting Experimentation
        Two Modes of Computer Usage
        The Invisible Computer of the Future

Response to Chapter 7:

  User-Centered Design
    Seven Principles for Transforming Difficult Tasks into Simple Ones
      Use Both Knowledge in the World and Knowledge in the Head
        Three Conceptual Models
        The Role of Manuals
      Simplify the Structure of Tasks
        Keep the Task much the Same, but Provide Mental Aids
        Use Technology to make Visible what would otherwise be Invisible, thus Improving Feedback and the Ability to Keep Control
        Automate, but keep the Task much the Same
        Change the Nature of the Task
        Don't Take Away Control
      Make Things Visible:  Bridge the Gulfs of Execution and Evaluation
      Get the Mappings Right
      Exploit the Power of Constraints, both Natural and Artificial
      Design for Error
      When All Else Fails, Standardize
        Standardization and Technology
        The Timing of Standardization
    Deliberately Making Things Difficult
      Designing a Dungeons and Dragons Game
      Easy Looking is Not Necessarily Easy to Use
    Design and Society
      How Writing Method Affects Style
        From Quill and Ink to Keyboard and Microphone
        Outline Processors and Hypertext
      Home of the Future: A Place of Comfort or a New Source of Frustration

Response to the Book in General:

Book Response #3: Design of Everyday Things - Chapters 2, 3, 4

The Design of Everyday Things
      By: Donald A. Norman

Response to Chapter 2:

      In this chapter, Norman first discusses how people typically blame themselves when making errors which results in a repeating cycle of inability to avoid error.  These errors often arise from misinterpreting actions throughout everyday life, either as a result of learned assumptions or through incorrect conceptual models built on observations of a poor system image.  He goes on to mention that human always have to justify their actions, and that it usually leads to blaming something other than ourselves for the occurring error.  This reinforces the feeling of helplessness in users that are unable to correct their construed mental model, leading to further failure.  I really enjoyed the way he depicted the slippery slope of helplessness because often times I feel desperately helpless after making the same stupid mistake over and over.  He goes on to break down exactly how people analyze their actions, noting seven precise steps, though I agree with him that typically steps are skipped when they shouldn't be.  Unfortunately he gives the impression that it is quite trivial to span the gulf of execution and evaluation when I personally believe that these can also be attributed to user incompetence.  Why does a user need a light to know if a tape has been inserted into the VCR when they can just lift the flap and check?  This boarders on the line of added complexity with little benefit to the general user.

Response to Chapter 3:

     What I gathered from this chapter is that the precision of human actions do not solely depend on the knowledge stored in the head of that person doing the action.  Typically, for routine tasks, I do them without even thinking about them, but I always had the belief that the knowledge was in my subconscious.  I rationalized that even though I wasn't actively thinking of what I was doing while I was doing it, there was always some little spot hidden away in my brain that told me "I've seen this happen like that before, so doing this should lead to that", but I felt it was more a reference book on how to do things I've done before (like looking up a word in a dictionary), and didn't view it as though my brain had a list of guidelines gathered over the years that led me reason and deduce new actions (like creating a grammatically correct sentence vs. just stringing words together from the dictionary).  Norman obviously spends a lot of time doing Introspection, and over the past year or two I have thought considerably more about how my thoughts are constructed.  I find the four reasons that precise knowledge is not needed is very important for designers to consider.  In addition, I really liked the way Norman broke down the way memories are kept into arbitrary things (rote memorization), meaningful relationships (grouping), and explanations (derived).  I find that I typically try to fully understand something while trying to memorize it, therefore when I have to recall the fact I can explain the reasoning behind it.  I do this because my ability to memorize random things is very poor!

Response to Chapter 4:

     I really enjoyed reading this chapter because it brought to my attention the reasoning behind actions, especially in social situations.  Although most people wouldn't see the correlation immediately, I feel like I try to approach social situations in the same manner I would approach a piece of machinery.  Also, when trying to learn how new things are supposed to work, I find myself highly interested in the constraints and often have found myself telling friends that I prefer to learn things by 'shading in the grey areas'.  This means that I try to identify what the object in question can and cannot be used for in a general sense.  This is probably why in class I typically ask questions that progress the discussion instead of having the professor repeat himself.  If the professor's reply, a new constraint, goes against what I previously understood, I try to clarify instead of just accepting the reply as fact.  Once, in 7th grade I accidentally made my Math Teacher leave the room from embarrassment because she kept saying a negative number times a negative number results in a negative number, which just isn't true.  I kept arguing that it was a positive number, oblivious to her visible feedback that she wanted to move onto the next question.  In regards to the doors and switches, often I pull instead of push or vice versa but I don't even think about the mistake, and move on, but I often have no issues with switches because I explore them in a very systematic manner.

Book Response #2: Chinese Room Thought Experiment

Minds, Brains, and Programs
     By:  John R. Searle

Response to Published Article:

     Searle argues that instantiating a program (running one to accomplish a specific task) does not lead to a computer that 'understands' the information it is processing.  He uses a specific example of a Turing Test using a Chinese story in which the 'being' inside the room answers questions to.  He states that if it were an English speaking man in the room that used a set of rules to transcribe Chinese characters received as input into appropriate Chinese characters as output would not actually understand Chinese.  This goes directly against the views of functionalism and computationalism which state that the mind is an information processing system operating on formal symbols.  Searle approaches this argument by clarifying that information processing does not actually mean one understands the information.  To demonstrate this, I would point to the fact that I have had classes in the past where it is easy to deduce the answer to a question based on another question that is of the same format, but occasionally I find myself struggling to determine the cause, which is to say I don't truly understand the material.

     This brings up another point by Searle, which is that simulation shouldn't be considered the same as duplication.  Behaviorism and operationalism classify objects by how they appear or act, but Searle points out that you wouldn't confuse a human and a dog just because they both eat food.  He argues that creating a strong AI needs to be viewed as creating some sort of meta-program that happens to function like a mind in the framework of a brain.  Since strong AI implies understanding and intentionality, strong AI cannot form from the simulation of just one instantiation of understanding, but would rather form from the creation of another instantiation of the mind, but not in the construct of the brain.

     So this leads back to the Chinese Room example, where Searle tries to boil it down to the fact that if there is an English speaker in the room who actually does understand the Chinese story the way another Chinese speaker would, then the original English speaker must also be a Chinese speaker.  Searle chose Chinese and English as the examples because the languages are so dramatically different, but for the argument at hand, I'd prefer to call it the Language Room.  This means that if the original machine in the room is seen as understanding a language not native to itself, then it must have been able to learn that language.  It also means that we will never get a strong AI just by trying to mimic understanding of something in particular, but that a strong AI can only be developed by creating something that understands in general and can therefore be instantiated to understand something in particular.

Book Response #1: Design of Everyday Things - Chapter 1

The Design of Everyday Things
     By:  Donald A. Norman

Response to Chapter 1:

     In the book The Design of Everyday Things, Norman discusses the phycological aspects of designing everyday objects properly to ease user interaction.  After reading the preface to the book, I felt that Norman was going to talk more about the design process, but after reading the first chapter I get the impression that his intention is to go over the reasons for which people attempt to interact with objects and how the design process can be tailored to suit such elementary interaction.  He raises quite a few great points regarding the principles of great design which are listed below.  One thing I noticed though, throughout reading his multiple examples of poor design, was that I am typically less burdoned by poor design.  I rarely push doors that should be pulled, and have never had much trouble with any telephone system even though he makes a few examples out to be horrendously contrived.

• Visibility
• Using natural signals to convey the mapping between intended actions and actual operations.
• Mapping
• Shows the relationships between actions and results, between the controls and their effects, and between the system state and what is visible.
• Affordance
• The percieved and actual fundamental properties of a device that determine how to properly operate the device.
• Feedback
• Full and continuous feedback regarding the current state as a result of a particular action.
• Conceptual Models - Formed largely by interpreting the devices perceived actions and its visible structure.
• Design Model - The designer's conceptual model of how the user should perceive the system.
• User's Model - Mental model developed through interaction with the system.
• System Image
• The actual visible part of the device to the user.