Forms of tacit knowledge?

The philosopher-chemist Michael Polanyi was very interested in what he called the "tacit dimension": forms of knowledge that can be performed but not articulated.  The classic example is riding a bicycle, which is almost impossible to put into words, and can only be taught by actually putting someone on a bicycle.  Tacit knowledge is also called know-how, as opposed to know-that, which is knowledge that can be broken down into propositions (The sky is blue, the sea is green, and so on).

Talking to a friend today, I found out something interesting about the forms that this tacit knowledge can take.  Now, typically a skill like tennis or swimming (or riding a bicycle!) isn't forgotten, even when one doesn't do it for a while.  In a sense, this is because this know-how is stored not in terms of linguistic propositions but in our muscles; this is "muscle memory." 

But my friend told me that he once ran 11 miles after a long time and then ended up really sore!  I asked him how  he managed to run that distance after such a long gap.  He said that if you had done that sort of thing before (run long distances, that is), you could always do it again, howsoever long the gap.

This was an interesting claim.  The know-how he was referring to wasn't just the art of running -- although it was that too -- but stamina.  In other words, muscle memory is also about stamina, and not just technique.  I thought that was pretty interesting.

Ranking and Sorting: two forms of cognition

There are two ways of looking at cognition.

1. There is cognitivism which looks at the mind as an information-processing system. In this view, it is thinking, i.e. the ability to play with representations of the world inside the mind, that is all-important.
   
2. Then there is another view, a heterogeneous set of views that is sometimes called the situated action perspective. Some of the proponents of this view would be Phil Agre, Lucy Suchman, Edwin Hutchins, Rodney Brooks and Eleanor Rosch. In this view, it is action that is all-important. Abstract rule-based thinking is but one, and by no means all-important, resource for action. Equally important are our use of tools and artifacts, and our taken-for-granted bodily and social skills. The situated cognition view locates cognition in our interactions with the world rather than in thinking inside the head. Representations are key but they are by no means solely in the head nor do they mirror the world; rather they are resources for action and are embodied in the tools and artifacts that we use for our tasks.

If you know me (or read this blog), you probably know that I find the situated action perspective far more convincing,. I can't, by any means, give any kind of a logical "proof" for it. But I do think it provides a better description of how we do things in our day-to-day life. E.g. in a form I filled out recently, I was asked to rank a list of 16 items. From a cognitivist perspective, this is a "problem" that is "solved" using utility-maximization; what I hope to do in this post is to show the actual processes that I used to rank the alternatives and also to show that these processes are better described as my interactions with certain external representations of the task. These functioned as tools i.e. resources that helped me complete the task. I also hope to show that by transforming the problem from one representation to another, I could have done the task differently (and more easily).

The housing form is shown above and it asks me rank the 16 types of housing available. Each type, as you can see in the figure, is an ordered pair consisting of a residence hall, and a type of apartment. I was supposed to assign ranks from 1 to 16. I could choose not to rank an option (thereby signifying that I wasn't interested). And I could give multiple options the same rank, if I wished.

From the cognitivist perspective, the process by which I actually ended up ranking these options is not very important. Because at an abstract computational level, my actions can be described as a simple case of utility maximization. I have a certain set of preferences (an upper-limit for the rent I am willing to pay, an interest in living with room-mates rather than alone, etc.). Based on this, whatever I do can be described as calculating a value for each option that measures its suitability for me and then ranking the alternatives based on said values.

But consider what actually happened as I was trying to fill up this form.

It was almost impossible to just straightforwardly rank 16 items without messing up. Some of the problems that I ran into were:

1. It was impossible to go through the alternatives one by one and assign them a rank. There were two possibilities.
   1. I could go through option 1, give it a rank, go to option 2, and so on. This would only work if I had worked out all the ranks in my head before-hand (impossible) or if I had worked them out on pen-and-paper (which I hadn't).
   2. I could scan all the alternatives, find the one that I liked the most, give it rank 1, then scan all the remaining alternatives, find the one I liked second-best, give it rank 2. This didn't work because (a) I quickly forgot what rank I was on, (b) I had to keep in mind all the others I had previously ranked (or get them by quickly scanning all alternatives) and finally (c) I just didn't know scanning the alternatives which one I preferred.
      
2. The form did not give all the information that I thought relevant. E.g. there are 2-bedroom or 3-bedroom apartments in certain residence halls which did not have a living room; I wanted to rank these options lower. Then there were options that I just did not prefer i.e. I had a "black-list." I had to flip back-and-forth between this page and the pages describing the apartments in detail so that I would not accidentally rank something in my black-list.
   

In a sense, the problem was this: not only was I trying to rank all the alternatives, I was also evaluating the criteria I was using to do so at the same time. That is, I was creating the "rules" that I would use to prefer one alternative to another in the process of applying them to specific alternatives! Note however that the representation that I had been given to work with -- a list of alternatives along with the possibility of assigning a number i.e. the rank to each -- was not very conducive to what I was doing.

Ultimately I ended up following the strategies below:

1. I first determined a rough order of preference in my mind. E.g. (1) efficiency apartments, (2) 2-bedrooms, (3) 3-bedrooms, (4) 4-bedrooms, and (5) 1-bedrooms. Of course, this wasn't the whole story since there were many exceptions (the black-list) to this preference. But as a rough guess, it was accurate.
2. Then I went through the options one-by-one keeping the above list in mind.
1. So I first went through all the efficiency apartments (there were 4), looked at their particulars (their price, whether they were on my black-list, etc.) and ranked them. If one was in my black-list, I chose not to give it a ranking.
2. Then I went through the 2-bedroom apartments and did the same. I had to keep the last ranking I had assigned in mind. E.g. if I had ranked the efficiency apartments from 1 to 3 (not ranking the one in my black-list), then I had to remember to rank the 2-bedrooms starting with the rank 4. It was crucial to remember this. Because if I forgot, I had to scan the whole list again for the last ranking so far and this was not a fun task. If I mis-remembered, then I would mess up all subsequent rankings. I could have chosen to write this last ranking down to avoid this.
3. And then I had to do the same for all the other types of apartments: 3-bedrooms, 4-bedrooms and 1-bedrooms.
4. One of the reasons why I could do this was because there were no "anomalies" in my choices. E.g. there was no stray 3-bedroom that I preferred to a 2-bedroom. Had that been the case, I would have had to adopt a slightly different strategy. As I was ranking the 2-bedrooms, I would have had to look at the 3-bedrooms as well. And I would have had to look at the 3 and 4-bedrooms together. And so on.
   
3. Once all this was done, I went back to all the alternatives I had not ranked (because they were on my black-list). I had the choice of not ranking them or giving them the last few ranks. Again it was crucial for me to remember the last rank that I had assigned. E.g. if the last ranking was 13, and I had 3 more left, I would assign them to ranks 14, 15 and 16.

Remember that this is a gloss on how I did the task. A narrative that I have constructed by looking back on what I did and trying to be conscious of what I was doing when I did it. It should, by no means, be considered a true account of what I did.

But that said, let's look at this account and see whether it can be reasonably described in terms of rule-following or utility-maximization. The answer is clearly, at some level, yes. But consider the following points:

1. While I did follow a rule (a "heuristic"), at no point did I assign any value for each alternative. Nor did I ever consider all the alternatives together.
2. Instead I used one of my selection criteria to break down the 16 alternatives into 5 groups in decreasing order of preference (efficiencies, 2, 3, 4 and 1-bedrooms). Then I ranked the items in each group. This was far easier to do since each group had only 4 or 5 members.
3. A lot of what I did was, in effect, my way of interacting with the available representation of the problem (in this case, a list whose items could be assigned ranks).

Now consider how much more simple the problem would have been if I had an interface that allowed me to sort the table, rather than rank it, using mechanisms like drag-and-drop.




Or suppose I had made written each alternative on a piece of paper, and then sorted the pieces into a list with my most preferred alternative at the top and the least-preferred one at the bottom. Like so.



This makes the task so much simpler, no?

In effect, this is a transformation of the task: from a ranking task to a sorting task. Computationally, the "problem" remains the same, but this transformation makes it easier to solve. Here is why sorting is easier than ranking:

1. Sorting allows us to focus on a subset of the alternatives without being distracted by the others . E.g. I can focus on whether I prefer an Edgerton 1-bedroom or a Tang 3-bedroom by moving the representations of these alternatives close together and moving all the rest out of my field of vision. This is impossible to do in a static list whose items need to be assigned ranks.
2. Sorting converts the ranking problem into an ordering problem. E.g. once I have arranged alternatives A, B, C in that order and I decide that I prefer C to B, all I need to do is insert C between A and B. The order changes immediately to A, C, B. If I was assigning numbers to A, B and C this same step would involve me having to change the ranks of each one of them.
3. Sorting eliminates any need for memory -- which is the hardest for the mind to do without external representations. E.g. one does not have to remember, say, the last rank that one assigned; instead the representation will itself tell us what the current state of the matter is.

What I write here has similarities both to the distributed cognition hypothesis and the extended mind hypothesis.

Selected References

1. Edwin Hutchins, Cognition in the Wild, New edition. (The MIT Press, 1996).
2. Abigail J. Sellen and Richard H. R. Harper, The Myth of the Paperless Office, 1st ed. (The MIT Press, 2001).
   
3. David Chalmers and Andy Clark, “The Extended Mind,” Analysis 58 (1998): 10-23.
   

Interactive computing systems and the relationship between embodiment and teachability

In this post, I am going to talk about the notion of "embodiment" in human-computer interaction. In particular, I will explain how my understanding of the term has changed and how experiences with teaching my Dad how to use certain programs (Picasa, the Indian Railways online website, etc.) revealed to me another facet of the term: the relationship between the embodiment and teachability of an interactive system. If one wants to teach someone how to perform a certain task on an embodied interactive system, then written instructions (without pictures or visual aids) are almost always insufficient. In other words, one measure of the embodiment of an interactive system can be found by looking at the efficacy of written instructions in helping a novice perform a certain task.

Paul Dourish's "Where the Action is" is possibly one of my favorite books. The book's thesis is that as computers have developed, our interactions with them have changed in nature and have progressively become more "embodied." Dourish divides the history of computer systems into 4 successive time-periods based on the mode of interaction:

• Electrical: To program a computer, one had to rewire its hardware.
• Symbolic: Abstraction was introduced and separated hardware from software. Abstraction meant that coding got progressively simpler: from machine language to assembly language to high-level Fortran-like languages.
  
• Textual: This refers to the development of command-line interfaces. These, for the first time, made interacting with the computer, seem like a "conversation."
• Graphical: Finally, there was the development of the graphical user interface (GUI) with its desktop metaphor and 2-dimensional arrangement of files and icons. The 2-dimensionality of the GUI meant that users were able to exploit "further areas of human ability as part of the interactive experience." This meant the use of faculties such as peripheral attention, pattern recognition and spatial reasoning.

Dourish sees each successive stage as involving more and more of the distinctively "human" capabilities i.e. those skills that are most used in our interactions in our everyday life with other human beings. Embodied interaction, as Dourish defines it, therefore means an interaction that involves more and more of distinctively human skills. These could be bodily skills (like pointing, gesturing, moving, pattern recognition) or social skills (our workplace habits, our everyday assumptions, etc.). In other words, embodied interaction is a move towards integrating more and more of our real-world practices (at home, at work, at play and so on) in our interactions with computing systems.

There is another aspect to embodied interaction that has slowly come to my attention as I have been trying to teach my Dad to use computer software (email, Picassa, certain websites, etc.). It involves what I call its teachability.

Let me give some background. My father worked during a time when computers were not such a ubiquitous part of the everyday work environment. In particular, he worked at a time when there were special people who did computer work -- and therefore not everybody needed to use the computer. More so, the computer was used for what can be called high-tech scientific stuff; it wasn't used at all for the mundane things at work: sending emails/memos, for filling up your time-sheets, submitting vouchers for reimbursement, etc.

Consequently, my Dad never interacted with computers in any sustained way when he worked. But he was certainly aware of them. However this was back in the times when the command-line (Dourish's 3rd stage) was the primary mode of interacting with computers; MS-DOS ruled. When my Dad did start interacting with computers in a sustained way however (primarily to keep in touch with me here in the US), he was dealing with the GUI, a new and much more embodied stage of human-computer interaction.

Consequently he would ask me to write down instructions for him on how to do a certain action. I would agree but I would find the writing of instructions to be extraordinarily hard. Here's an example of what I mean. To copy a file from one directory to another in DOS is a simple command:

Now of course, even here, there are variations. You don't have to specify the directory if you want to copy something from or to the same directory you are in, etc. But the command itself is fairly simple and easy to understand.

Now consider doing the same thing in Windows and there turn out to be quite a few ways to copy a file from one folder to another (drag-and-drop, Edit menu, Context menu). I'm going to consider one of them here, to illustrate its complexity:

Go to the folder you want to copy from. Select the file and copy it (this can be done either by right-clicking the file and selecting "Copy" or by selecting the file and selecting "Copy" from the Edit menu). Then go to your target folder and paste the file there (again, this can be done in two ways, right-clicking in the target folder and selecting "Paste" or selecting "Paste" from the Edit menu).

Just the sheer complexity of what I wrote above makes it clear that in terms of giving written instructions, the command-line interface is far simpler than the GUI and involves less tacit assumptions (the phrases in red font, above).

Talking about the GUI involves an almost taken-for-granted use of metaphors. Consider, for example:

Go to the folder/Be in the folder/Be in some application: Go to a folder implies that the folder is a place. Go in a folder implies that the folder is like a house which you can go inside. I also ask him frequently to be inside some folder or to be inside some application.

Select the file: This is not really a metaphor although it comes up frequently in my discussions with my father. Many times, when I instruct him over the telephone to "select the file," he doesn't get what I mean or asks me whether I mean to left-click or right-click on the file icon. I also frequently ask him to "select the text" (e.g. to copy a hyper-link from Skype to Firefox to open a link that I sent him)

How does one teach people to use embodied interactive systems (GUIs), particularly when they have very little experience with computers, don't use the computer frequently and most important, are distant from us so we can only communicate with them through spoken and written instructions? Some points and observations:

Written instructions without pictures are almost completely useless.

Written instructions with pictures (screen-shots) can be useful.

However, it is best to give verbal instructions especially during the task itself*. That way, your instructions can be followed in real time and you will get immediate feedback about their intelligibility (i.e. whether or not they're understood) and efficacy (whether or not they worked).

Having a shared referenced visual object is even better. Meaning that if you are teaching someone how to use the Indian Railways Ticketing website, it is best to have it open in front of you and to carry out an instruction yourself so that you know exactly what the person you are instructing is looking at. This is easy to do for websites but much harder if you are instructing someone about how to use Picasa or how to copy files from a flash-drive to the hard-disk.

Which leads to the best possible and most embodied form of instructions. Screen-sharing along with a voice communication channel is the best way of all! This way, you know exactly what the other person sees and the instruction itself can be modified depending on how you see it being interpreted. E.g. if you ask someone to copy a file to a certain folder and this doesn't seem to get through, you can immediately supply them with instructions on how to copy files and take them through it step-by-step.

I guess the broader point that I am trying to build to is this: embodied interaction uses many bodily and social skills, and these are almost always tacit; it is hard to translate them into words. Verbal instructions (spoken and written) need to be backed up with visual aids like screen-shots and screen-sharing. Therefore it follows that one rough measure of the embodiment of an interactive system can be found by measuring the efficacy of written and spoken instructions, especially when the student and the teacher are distant, and the student is a novice at using computers.

*Whether your instructions will be remembered is another question.

Is there social science research on the habits of movie-renters?

I've just started exploring the Netflix data -- and want to use it to look into the habits of folks who rent movies regularly. There's a lot of work on collaborative filtering algorithms and other "recommendation" systems that goes on in Computer Science departments.

But does anyone know of any academic work that was done documenting the behavior patterns exhibited by movie-renters? Questions such as:

• Is the renting behavior exhibited by families different from that of individuals?
• How does liking or disliking a movie affect the next movie that person or family rents?
• What role does the social network play? What about advertisements?

Anything that anyone knows will be much appreciated.