Studies of the impact of the media on people have not produced stable results

Great read tonight: Studying the New Media by Howard Becker (Qualitative Sociology, Vol. 25, No. 3, 2002).

The author focuses here on the studies about the “impact of the media on people”, the sort of stuff you see popping up in the press on a regular basis (be it about tv, video-games, comic-books or the interwebs). Becker shows that these studies have not produced stable results, because they operate with an unrealistic view of people. He describes how inaccurate the “impact” paradigm is and the fact it never produced any solid findings about the good or bad effects of XXX (where XXX stands for arts experience/TV/video-games, etc.):

“The idea that you could isolate a unique influence of such a thing as TV or movies or video games is absurd on the face of it. Social scientists, operating under the best conditions, have enough trou- ble demonstrating causal relations between any two variables—to tell the truth, I don’t think they ever do, just maybe hint at it. Studying the effect of a commu- nication medium which operates in the middle of ordinary social life, with all its complications, is not working under the best conditions, and the demonstration of cause and effect is, practically speaking, impossible.
(…)
The “impact” approach improperly treats the public as an inert mass which doesn’t do anything on its own, but rather just reacts to what is presented to it by powerful (usually commercial) organizations and the representatives of dominant social strata.“

He exemplifies how “the image of an inert, passive mass audience is a gross empirical error” with various cases where other researchers had shown that “ordinary people” aren’t passive: TV-viewing (where “users” explored imaginatively the possibilities of adult relationships), the creation of internet website, or the writing of homosexual pastiches of the Star Trek stories or pornography:

“One of the first uses of any new communication technology has always been to make pornography. Photography was no sooner invented in the mid-nineteenth century than people were using it to make and distribute dirty pictures. (…) I’m talking about the “amateurs” in this field, of whom there have always been a lot. (…) In other words, pornography is a major area of use of digital technology by ordinary folks.“

Why do I blog this? reflecting on past paradigms and approaches I used to be taught.

The Reflective Practitioner by Donald Schön

The Reflective Practitioner: How Professionals Think in Action by Donald Schön was a good summer read. The book was highly relevant to me for two reasons: (1) the case studies themselves were interesting (especially the architect one, which is related to my interest in design), (2) Schön’s objective, which was about setting an epistemology of practice that place “technical problem solving within a broader context of reflective inquiry, shows how reflection-in-action may be rigorous in its own right, and links the art of practice in uncertainty and uniqueness to the scientists’ art of research“.

To some extent, what I appreciated in this book was that the author recast the notions of research and practice in novel ways. This was important to me as I constantly try to rethink my own stance. Actually, this is what happen when I state that I am a researcher although I left academia or that I avoid mentioning any “academic discipline” next to the term “researcher”. Besides, having a BSc in biology, an MSc in Human-Computer Interaction from a psychology department and a PhD in in Human Computer Interaction from a computer sciences department doe not really help here.

Schön basically shows that the world cannot be split in two categories such as practitioner and researchers, on p. 308-309

“Clearly, then, when we reject the traditional view of professional knowledge, recognizing that practitioners may become reflective practitioners in situations of uncertainty, instability, uniqueness, and conflict, we have recast the relationship between research and practice. For on this perspective, research is an activity of practitioners. It is triggered by features of the practice situation, undertaken on the spot, and immediately linked to action.“

This activity that we calls “reflective research” can be discriminated into four types:

1. Frame analysis: the study of the way in which practitioners frame problems and roles.
2. Repertoire building research: accumulating and describing description and analysis of images, category schemes, cases, precedents and exemplars to be brought to unique situations
3. Research on fundamental methods of inquiry and overarching theories: discover how the process of recognition and restructuring works by examining episodes of practice to enter into a way of seeing, restructuring and intervening which they may wish to make their own.
4. The study of reflection-in-action: research done by practitioners triggered by features practice situation, undertaken on the spot and is immediately linked to action.

Later on in the book, he confronts the epistemology of technical rationality (research produces abstract theories that could be useful to solve problem, applied in practice) and what he calls an “epistemology of practice” which is more inductive and substitute “problem solving” by “problem setting/spotting”:

“In real-world practice, problems do not present themselves to practitioners as givens. They must be constructed from the materials of problematic situations that are puzzling, troubling, and uncertain. In order to convert a problematic situation to a problem, a practitioner must do a certain kind of work. He must make sense of an uncertain situation that initially makes no sense.
“

What is important in this piece is also the critique of the technical rationality. Inherited from Positivism, the model of practice for lots of professions has the one of the Engineer. The practitioner’s question (“How ought I to act?”) becomes a scientific question and answers could be derived through scientific theories. Schön criticizes this through the book and I won’t enter into the details here. What is interesting to me is the part about how the technical rationality often leads to the “mystique of technical expertise”, the sort of wizardry some folks impose on others, showing that “they know (and you don’t)”. Schön as a good take on this:

“The idea of reflective practice leads, in a sense both similar to and different from radical criticism, to a demystification of personal expertise. It leads us to recognise that for both the professional and counter professional, special knowledge is embedded in evaluative frames which bear the stamp of human values and interest. It also leads us to recognize that the scope of technical expertise is situations of uncertainty, instability, uniqueness, and conflict. When research-based theories and techniques are inapplicable, the professional cannot legitimately claim to be expert, but only to be especially well prepared to reflect-in-action“

Which leads him to state some tips about how to judge a claim without being an expert. I like them a lot and think they should be used more often (p301):

• “judge the man rather than his knowledge”. Challenge him and see how he responds to challenge. Look how he responds to challenge. Look for the combination of confidence and humility, advocacy of a position, and openness to inquiry which is characteristic of reflective competence.
• Use your own ignorance. Do not be afraid to admit ignorance, ask for help in understanding and expect to get it.
• Ask for sources of risk. Push for the limits of the other’s confidence. Ask what risks are attendant on a proposed course of action.
• Seek out more than one view. Assume that is is normal and legitimate to compare practitioners’ approaches to a problem. Use multiple meetings to build up a sense of the proper questions to ask and the criticisms of a particular approach that need to be answered”

Finally, a great part of my interest has been devoted to the description of the “reflection-in-action” process per se, or how practitioner do what they do. Schön’s contribution here consists highlighting the “fundamental structure of professional inquiry”

He explains how the first step is about identifying the problem (“There is a problem in finding the problem“) where the practitioner has “a reflective conversation” with the situation at hand: “The practitioner conducts an experiment in reframing the problematic situation (…) judges his problem-solving effectiveness in terms of an objective function“. At this point, the person does not really know what the solution to the problem will be (nor that the problem is soluble) but the frame imposed on the situation is one that lends itself to a method of inquiry in which he/she has confidence. Nevertheless, Schön lists a set of question employed to evaluate the fitness of the frame:

• Can I solve the problem I have set?
• Do I like what I get when I solve this problem?
• Have I made the situation coherent?
• Have I made it congruent with my fundamental values and theories?
• Have I kept inquiry moving?

Then, there are two possibilities when it comes to “solving the problem”. On the one hand, the practitioner can bring past experience, familiar categories. This is close to analogical reasoning/case-based reasoning as described by cognitive psychologists. On the other hand, he/she “conduct” and experiment, that he refers to as “a game with the situation” which is done through hypothesis-testing. In the context of design, this corresponds to what he calls “move experiment”: iterations that are evaluated and serve as a basis for generating new solutions. He insists also on the fact that this move experiment is an “interaction of making and seeing”, which is an important characteristic of design. This notion of experiment is described in thorough details by Schön because he wants to show the differences with what the model of technical rationality implies when it comes to “experiments”. In the case of practitioners’ work, there are three types of experiments that correspond to 3 types of reflection-in-action:

• Explorative experiments, which follows a “What if?” logic: “when action is undertaken only to see what follows, without accompanying predictions or expectations“
• Move-testing, which implies an intention on the part of the practitioner
• Hypothesis-testing, that corresponds to the traditional notion with formulated hypothesis consisting of different variables. Unlike move-testing hypothesis-testing is much more complex and analytical.

And what are the consequences of such experiments? let’s get back to the book because the phrasing here is REALLY important:

“When a move fails to do what is intended and produces consequences considered on the whole to be undesirable, the inquirer surfaces the theory implicit in the move, criticizes it, restructures it, and tests the new theory by inventing a move consistent with it. The learning sequence, initiated by the negation of a move, terminates when new theory leads to a new move which is affirmed.
(…)
Other theories of action or models might also account for the failure of the earlier move and the success of the later one. But in the practice context, priority is placed on the interest in change and therefore on the logic of affirmation. It is the logic of affirmation which sets the boundaries of experimental rigor.“

With this quote, I end here this chaotic review because it circles back to I started to discuss at the beginning: the different definition of rigor for practitioner. I am pretty sure I will now used this quote (and material) to discuss practitioners’ work with my student. I found it strikingly revealing and highlight the difference of attitude between academics and professionals.

Why do I blog this? lots of excerpts and quotes here but this blog is my notepad, the place where I reference this sort of material for futures enquiries. The place where my frame are being built and where futures moves are being hypothesized.

Of course, there are tons of others theories of knowledge and problem solving, some coming from cognitive psychologies, others from management sciences. However, I find interesting to read Donald Schön’s approach given its proximity to different practitioners’ field and its peculiar theoretical stance.

People interested in this book may also have a glance at Dan Saffer’s extensive review as it uncovers interesting connection with designers’ work.

City legibility and ambient informatics

Reading “City of Bits: Space, Place, and the Infobahn” (William J. Mitchell) during the holidays, I ran across that quote:

“we are beginning to know and use cities in new ways. Long ago, the urban theorist Kevin Lynch pointed out the fundamental relationship between human cognition and urban form – the importance of the learned mental maps that knowledgeable locals carry about inside their skulls. These mental maps, together with the landmarks and edges that provide orientation within the urban fabric, are what make a city seem familiar and comprehensible. But for us artificially intelligent cyborgs, the ability to navigate through the streets and gain access to city resources isn’t all in our heads. Increasingly we rely on our electronic extensions – smart vehicles and hand-held devices, together with the invisible landmarks provided by electronic positioning – to orient us in the urban fabric, to capture and process knowledge of our surroundings, and to get us where we want to go.“

Why do I blog this? Except the “cyborg/intelligent” rhetoric that I don’t parse and acknowledge, that quote is quite interesting and it echoes with recent readings such as what Greenfield and Shepard describes in “Urban Computing and Its Discontents” or the work of Anthony Townsend that I mentioned the other day. This is interesting as I am interested in how urban computing (will) affect cities, especially how location-aware applications or networked objects would change city life (the “user experience” of city sounds pretty lame here).

The link between Lynch’s work about the legibility of cities and urban computing is of great interest to me as it resonates with my background in cognitive sciences. To some extent, it boils down to this simple question: “how people take decisions about what they do in an urban environment?”: how do people navigate through streets and avenues, how do they choose specific points of interest, how do they change their path, etc. Kevin Lynch provided some answers about this, showing how mental representation of space is built based on urban elements such as paths, edges, districts, nodes, and landmarks. For instance, he showed how specific angles of elements in a city allow for easier way-finding, or how people position their head and body in relation to their environment in navigation determine their navigation. The reason why this is interesting is that Lynch’s work is a bit less mentalist as the dominant model in cognitive sciences: people’s decision can be based both on mental representation (very cognitive) AND situated elements of space (less cognitive). On top of that, you can add the fact that mental maps can be built upon situated elements…

Anyway, back to Mitchell’s quote, electronic flows of information and representation can modify and affect the decision process I just described. However, I am still missing elements about this, more detailed accounts of the interlinkages between cognition/urban forms and urban computing.

Information management techniques and other species

Ann Blair (from Harvard University), in her review of “Glut: Mastering Information Through the Ages” (by Alex Wright):

Wright draws from sociobiology the suggestion that evolution has favoured the development of particular human cognitive behaviours in managing information, such as the drive to classify and the emotional attachment to symbols. He turns for confirmation to anthropologist Donald Brown’s notion of human universals and notes the particular importance of the ice age that began some 40,000 years ago in forcing humans to interact more closely, thus stimulating the development of drawing and symbolic objects. Wright argues that this “ice age information explosion brought humanity to the brink of literacy”.
(…)
The historical perspective of Glut is admirable: Wright neither assumes a linear progress nor makes unwarranted claims about the novelty or the indebtedness of current technologies to earlier ones. He doesn’t try to predict what the lasting impacts of the Web will be, but notes that the Internet facilitates the formation of small, self-organized communities that have the potential to undermine large hierarchical structures. In this way, he suggests that human culture may no longer be moving unidirectionally as was once thought, towards coalescence into larger entities, but rather multidirectionally.

Why do I blog this? it echoes with old memories of undegrad biology courses, this is interesting to me in terms of “traces of interactions” that can be collected and processed. These traces, intentional or not, explicity disclosed or not, are the basis of new types of interactions that can help building regulation systems, games, information management dashboards, etc. There should be some interesting things to draw out of that book regarding the evolutions of this over time and species.

Judith Donath on “signals”

Signals, Truth, Design is the upcoming book of Judith Donath which deals with the social dynamics of the “mediated world” (i.e. email, forums and other communication supported by the Internet) and how to design it. To do so, the author use the “signaling theory” as a framework to describe how:

“most of the things we want to know about each other – one’s identity,
status, and intentions – are qualities that are not directly observable. Instead, we rely on signals, which are indicators of these hidden qualities, in order to comprehend the world around us. (…) Signaling theory explains what makes some signals more reliable than others are.“

She applies it to some more specific topics such as deception, identity, reputation or impression formation.
Why do I blog this? this topic is a bit different than what I am interested in, but awareness (as provided by mutual location-awareness tools) can be perceived as a “signal”. This “signal” concept sparked some discussion during my PhD defense when one of the reviewer wondered about why employing this “old” metaphor, very tight to the Shannon-model of communication. The argument was about showing that it’s still relevant, I’d be curious to know how this book approach the signal notion using the biology background.

Difficulty in 3D perception

A Survey of Design Issues in Spatial Input by Ken Hickley, Randy Pausch, John C. Goble, and Neal Kassell (1994), Proc. ACM UIST’94 Symposium on User Interface Software & Technology, pp. 213-222.

Even though the paper is a bit old, it gives a comprehensive summary of the design issues regarding spatial input, especially regarding the perception of 3D. The authors describes
how users have difficulty understanding three-dimensional space, based on user studies.

“ Anyone who has tried to build a stone wall knows how difficult it is to look at a pile of available stones and decide which stone will best fit into a gap in the wall. There are some individuals, such as experienced stone masons, who have become proficient with this task, but most people simply have to try different stones until one is found that fits reasonably well. In general, people are good at experiencing 3D and experimenting with spatial relationships between real-world objects, but we possess little innate comprehension of 3D space in the abstract. People do not innately understand three dimensional reality, but rather they experience it.
(…)
Previous interfaces have demonstrated a number of issues which may facilitate 3D space perception, including the following: Spatial references, Relative gesture vs. absolute gesture
Two-handed interaction, Multisensory feedback, Physical constraints“

Why do I blog this? looking for references about how 3D is experienced. Why? because this topic is back again (with the SL frenziness) and that I often find myself in situations where I have to explain why 3D s problematic. It’s quite interesting because it engages me in reading old paper from 10-15 years ago, as if everyone forgot the research that has been done.

Online play to tackle tough computational problems

There’s an intriguing piece in Science news about using the power of online gaming to address big computational challenges such as language translation, refining online search, locating objects in images, etc. The point is to use the time, the energy and the mass of players to solve problems and collect data: “turning playtime to profit”. Moreover, the researchers realize that computers are good at certain things but less at others, hence the idea of tapping into “human brainpower”.

Some examples described on the ACM Technews:

“One example is the ESP Game developed by von Ahn, in which two players come up with words to describe an image, and are awarded points when the words match; in this way, images can be creatively labeled to facilitate easier Web searching. Players are encouraged to choose more creative, less obvious descriptive terms by being restricted from using certain words. Training computers to determine the location of an image of an object is the goal behind Phetch, another game of von Ahn’s in which players search for images that fit certain descriptions in a scavenger hunt scheme. One player or narrator types out a description of an image chosen from a database at random, and then several other players or seekers find the image by using a built-in browser; points are awarded to the narrator every time a search is carried out successfully, while the first seeker to find the image gets points and assumes the role of narrator for the next image. Von Ahn’s latest game, Verbosity, is founded on the concept of building a database of common-sense facts through gameplay. In Verbosity, one player is given a word and presents hints about the word to another player in the form of sentences with blanks where words should go. Von Ahn says all his games have a time limit because he wants participants to play faster and thus generate more data.“

New rules of solving problems

(Via Dr Fish), An article from mechanical engineering magazine (by Kathryn Jablokow) addresses the new rules for solving problems nowadays. Although it’s written for engineers, there are some pertinent elements for other domains. Some excerpts:

“The number of problems we each can solve alone is getting smaller. Not only are there more problems than any one person can handle, but no one person has the brainpower to cover—on his or her own—the wide
range of knowledge and expertise that is so often required
(…)
To gather all the knowledge we need to solve complex problems, we know that we must collaborate. Working together is no longer optional. Paradoxically, in order to collaborate and solve problems effectively, we need to know even more—and about different things.”

The article then describes a very cognitive-centric vision of problem solving (“problem solving level (…) problem solving style”). It’s however very pragmatic and it gives interesting insights about to apply this with some concrete examples/stories. I won’t enter into much details here but it’s basically about problem solving, Adaption-Innovation theory, which states that people differ in their innate preferences for structure in problem solving. Very polemical but the examples are intriging.
Why do I blog this? some good thoughts about collaborative problem solving and design.

Paper for CSCL 2007

Our paper “Partner Modeling Is Mutual”, Sangin, M., Nova, N. Molinari, G and Dillenbourg, P for the CSCL 2007 conference (Computer Supported Collaborative Learning) has been accepted.

The paper, that one may categorize as belonging to cognitive science research, basically described our empirical research about how the modeling of partners’ intentions is a mutual process. This research stems from a project we carried out at the lab for the Swiss Research National Fundation.

Abstract: Collaborative learning has been hypothesized to be related to the cognitive effort engaged by co-learners to build a shared understanding. The process of constructing this shared understanding requires each team member to build some kind of representation of the behavior, beliefs, knowledge or intentions of other group members. This contribution reports interesting findings regarding to the process of modeling each other. In two empirical studies, we measured the accuracy of the mutual model, i.e. the difference between what A believes B knows, has done or intends to do and what B actually knows, has done or intends to do. In both studies, we found a significant correlation between the accuracy of A’s model of B and the accuracy of B’s model of A. This leads us to think that the process of modeling one’s partners does not simply reflect individual attitudes or skills but emerges as a property of group interactions. We describe on-going studies that explore these preliminary results.

What a news: Neural ‘extension cord’ developed for brain implants:

A “data cable” made from stretched nerve cells could someday help connect computers to the human nervous system. The modified cells should form better connections with human tissue than the metal electrodes currently used for purposes such as remotely controlling prosthetics. (…) Tests have already shown that electrical signals can be transmitted in both directions along the cord.
(…)
Christopher James, who works on brain-computer interfaces at Southampton University, UK, gives the work a cautious welcome. “This approach does sound like a good idea,” he says. “Although directly attaching electrodes to the brain has been shown to work, the long term effects are not known”.

Why do I blog this? I find intriguing the emphasis on invasive brain-computer interfaces. Though it’s often not necessary (EEG could be another solution as mentionned in the article), there seems to be a conspicuous fascination towards plugging stuff into one’s body.