Another approximation incorporates new computational mechanisms tosubstitute adequately for social mechanisms or to provide for new social issues(Hollan & Stornetta, 1992).

First-order approximations, to adopt a metaphor from fluid dynamics, aretractable solutions that partially solve specific problems with knowntrade-offs.

Similarly, an educational perspective would argue that programmers andusers should understand the fundamental nature of the social requirements.

CSCW’s science, however, must centralize the necessary gap between whatwe would prefer to construct and what we can construct. To do this as a practi-cal program of action requires several steps—palliatives to ameliorate the cur-rent social conditions, first-order approximations to explore the design space,and fundamental lines of inquiry to create the science. These steps should de-velop into a new science of the artificial. In any case, the steps are necessary tomove forward intellectually within CSCW, given the nature of the social–tech-nical gap.

Ideological initiatives include those that prioritize the needs of the peopleusing the systems.

Simon’s (1969/1981) book does not address the inevitable gaps betweenthe desired outcome and the means of producing that outcome for anylarge-scale design process, but CSCW researchers see these gaps as unavoid-able. The social–technical gap should not have been ignored by Simon.Yet, CSCW is exactly the type of science Simon envisioned, and CSCW couldserve as a reconstruction and renewal of Simon’s viewpoint, suitably revised. Asmuch as was AI, CSCW is inherently a science of the artificial,

At a simple level,CSCW’s intellectual context is framed by social constructionism andethnomethodology (e.g., Berger & Luckmann, 1966; Garfinkel, 1967), systemstheories (e.g., Hutchins, 1995a), and many large-scale system experiences (e.g.,American urban renewal, nuclear power, and Vietnam). All of these pointed tothe complexities underlying any social activity, even those felt to be straightfor-ward.

Yet,The Sciences of the Artificialbecame an an-them call for artificial intelligence and computer science. In the book he ar-gued for a path between the idea for a new science (such as economics orartificial intelligence) and the construction of that new science (perhaps withsome backtracking in the creation process). This argument was both charac-teristically logical and psychologically appealing for the time.

The HCI and CSCW research communitiesneed to ask what one might do to ameliorate the effects of the gap and to fur-ther understand the gap. I believe an answer—and a future HCI challenge—is toreconceptualize CSCW as a science of the artificial. This echoes Simon (1981)but properly updates his work for CSCW’s time and intellectual task.2

As Heilbroner (1994) and other researchers have argued, technological tra-jectories are responsive to social direction. I make the case that they may alsobe responsive to intellectual direction.1Indeed, a central premise of HCI isthat we should not force users to adapt.

The coevolutionary form of this argument is that we adapt resources in theenvironment to our needs. If the resources are capable of only partial satisfac-tion, then we slowly create new technical resources to better fit the need.

A second argument against the significance of the gap is historically based.There are several variants: that we should adapt ourselves to the technology orthat we will coevolve with the technology.

A logically similar argument is that the problem is with the entire vonNeumann machine as classically developed, and new architectures will ame-liorate the gap. As Hutchins (1995a) and others (Clark, 1997) noted, the stan-dard model of the computer over the last 30 years was disembodied, separatedfrom the physical world by ill-defined (if defined) input and output devices.

First, it could be that CSCW researchers merely have not found the properkey to solve this social–technical gap, and that such a solution, using existingtechnologies, will shortly exist.

Theproblem, then, was centered by social scientists in the process of design. Cer-tainly, many studies in CSCW, HCI, information technology, and informa-tion science at least indirectly have emphasized a dichotomy betweendesigners, programmers, and implementers on one hand and the social ana-lyst on the other.

In particular, concurrency control problems arise when the software, data,and interface are distributed over several computers. Time delays when ex-changing potentially conflicting actions are especially worrisome. ... Ifconcurrency control is not established, people may invoke conflicting ac-tions. As a result, the group may become confused because displays are incon-sistent, and the groupware document corrupted due to events being handledout of order. (p. 207)

Moreover,one of the CSCW findings was that such categorization (and especially howcategories are collapsed into meta-categories) is inherently political. The pre-ferred categories and categorization will differ from individual to individual.

Because some of the idealization must be ignored to pro-vide a working solution, this trade-off provides much of the tension in anygiven implementation between “technically working” and “organizationallyworkable” systems. CSCW as a field is notable for its attention and concern tomanaging this tension.

Incentives are critical.

People not only adapt to their systems, they adapt their systems to theirneeds

There appears to be a critical mass problem for CSCW systems

The norms for using a CSCW system are often actively negotiatedamong users.

Visibility of communication exchanges and of information enableslearning and greater efficiencies

eople prefer to know who else is present in a shared space, and they usethis awareness to guide their work

Exceptions are normal in work processes.

Members of organizations sometimes have differing (and multiple)goals, and conflict may be as important as cooperation in obtaining is-sue resolutions (Kling, 1991). Groups and organizations may not haveshared goals, knowledge, meanings, and histories (Heath & Luff,1996; Star & Ruhleder, 1994).

One finding of CSCW is that it is sometimes easier and better toaugment technical mechanisms with social mechanisms to control,regulate, or encourage behavior (Sproull & Kiesler, 1991)

because people of-ten lack shared histories and meanings (especially when they are indiffering groups or organizations), information must berecontextualized to reuse experience or knowledge. Systems often as-sume a shared understanding of information.

Yet, systems often have considerable difficulty han-dling this detail and flexibility.

Social activity is fluid and nuanced, and this makes systems techni-cally difficult to construct properly and often awkward to use.

March and Simon’s (1958; Simon, 1957) limited rational actormodel underlies CSCW

I also arguelater that the challenge of the social–technical gap creates an opportunity to re-focus CSCW as a Simonian science of the artificial (where a science of the arti-ficial is suitably revised from Simon’s strictly empiricist grounds).

In summary, they argue that human activity is highly flexible,nuanced, and contextualized and that computational entities such as informa-tion sharing, roles, and social norms need to be similarly flexible, nuanced, andcontextualized.

Thesocial–technical gapis the divide between what we know we must support sociallyand what we can support technically. Exploring, understanding, and hopefullyameliorating this social–technical gap is the central challenge for CSCW as afield and one of the central problems for human–computer interaction.

The facsimile was printed on Factum Arte”s purpose-built flatbed printer (figure 34). This is based on an Epson Pro 9600 digital printer. The printer uses pigment inks in seven colors (cyan, light cyan, magenta, light magenta, yellow, black and light black). The bed is fixed, and the print heads move up and down the bed on linear guides. The movement of the heads is accurate to a few microns, and their height can be adjusted during printing. This made it possible to print the image in pigment onto gesso-coated canvas. The gesso coating, a mixture of animal glue, calcium carbonate, and precipitated chalk, used no metal oxides. The texture on the surface of the 16-ounce Irish flax was made from flax fibers and threads mixed with gesso. Due to its history Le Nozze di Cana has a complex and unusual surface. To reproduce this appearance, each piece of canvas was coated with a layer of animal glue, a layer of gesso and fibers, and then two layers of gesso. Acetate sheets printed with the Phase One photographic data were used, with a pin registration system, to ensure accurate placement of the texture on the prepared canvas. Each panel was then printed twice in perfect register. The first layer to be printed was the information recorded on the Phase One photographs. The second layer was the scanner data. The overprinting resulted in accurate color matching and a control of the tonal values of the painting. The entire image was divided into printing files, with io centimetres of overlap. The printed panels were varnished with a satin Golden acrylic varnish with UVLS (an ultraviolet filter)

Factum Arte built a non-contact color scanning sys tem that uses a large format CCD and integrated LED lights. The system records at a scale of i s i at a maximum resolution of i,2oo dots per inch (dpi). The scanning unit is mounted on a telescopic mast, which is operated by an air pump and can accurately position the scanning unit on the vertical axis.

Not only were his subjects idiosyncratic, but his style was poetic, aphoristic, dra~atic, and colorful.

I began to wonder if by merely assessing the mechanistic aspects of cataloging work we were missing out on an opportunity to include broader social concepts in our assessment and planning processes

TECHNICAL DEBT: A lot of new code is written very very fast, because that’s what the intersection of the current wave of software development (and the angel investor / venture capital model of funding) in Silicon Valley compels people to do. Funders want companies to scale up, quickly, and become monopolies in their space, if they can, through network effects — a system in which the more people use a platform, the more valuable it is. Software engineers do what they can, as fast as they can. Essentially, there is a lot of equivalent of “duct-tape” in the code, holding things together. If done right, that code will eventually be fixed, commented (explanations written up so the next programmer knows what the heck is up) and ported to systems built for the right scale — before there is a crisis. How often does that get done? I wager that many wait to see if the system comes crashing down, necessitating the fix. By then, you are probably too big to go down for too long, so there’s the temptation for more duct tape. And so on.

Instead of thinking of technical debt as yesterday’s work that I failed to do, I think of it as tomorrow’s feature I can have today

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