Everything about Computer-supported Collaboration totally explained
Computer-supported collaboration (CSC) research focuses on technology that affect groups, organizations communities and societies, for example
voice mail,
text chat. It grew from
cooperative work study of supporting people's work activities and working relationships. As net technology increasingly supported a wide range of recreational and social activities, consumer markets expanded the user base, more and more people were able to connect online to create what researchers have called a
Computer Supported Cooperative World which includes "all contexts in which technology is used to mediate human activities such as communication, coordination, cooperation, competition, entertainment, games, art, and music" (from CSCW 2004).
Scope of the field
Focused on output
The subfield
computer-mediated communication deals specifically with how humans use "computers" (or
digital media) to form, support and maintain relationships with others (social uses), regulate information flow (instructional uses), and make decisions (including major financial and political ones). It doesn't focus on common work products or other "collaboration" but rather on "meeting" itself, and on
trust. By contrast CSC is focused on the output not the character or emotional consequences of meetings or relationships.
The difference between "communication" and "collaboration".
Focused on contracts and rendezvous
Unlike communication research which focuses on trust,
computer science which focuses on
truth and
logic, CSC focuses on
cooperation and
collaboration and
decision making theory, which are more concerned with
rendezvous and
contract. For instance,
auctions and
market systems, which rely on
bid and ask relationships, are studied as part of CSC not usually as part of communication.
The term CSC emerged in the 1990s to replace the terms
workgroup computing (which emphasizes technology over the work being supported and seems to restrict inquiry to small organizational units) or
groupware (which became a commercial
buzzword and was used to describe many badly designed systems) and
computer supported cooperative work (the name of a conference) seems only to address research into experimental systems and the nature of workplaces and organizations doing "work" as opposed to play or war).
Collaboration isn't software
Two different types of software are sometimes differentiated
Base technologies like
netnews,
email,
chat and
wiki could be described as either "social" or "collaborative". Those who say "social" seem to focus on so-called "
virtual community" while those who say "collaborative" seem to be more concerned with
content management and the actual output. While software may be designed to achieve closer social ties or specific deliverables, it's hard to support collaboration without also enabling relationships to form, and hard to support a social interaction without some kind of shared co-authored works.
May include games
Accordingly, the differentiation between social and collaborative software may also be stated as that between "play" and "work". Some theorists hold that a
play ethic should apply, and that work must become more game-like or play-like in order to make using computers a more comfortable experience. The study of
MUDs and
MMRPGs in the
1980s and
1990s led many to this conclusion which is now not controversial.
True multi-player
computer games can be considered a simple form of collaboration, but only a few theorists include this as part of CSC.
Not just about "computing"
The term
social computing is used mostly at
IBM to describe the field, in an attempt to invoke existing social conventions or contexts as opposed to technological attributes: the use of e-mail for maintaining social relationships, instant messaging for daily microcoordination at one's workplace, or weblogs as a community building tool. Most researchers argue that these are all forms of
collaboration not forms of "computing", making this variant term an
oxymoron: whatever is "social" about software it isn't the "computing" aspect. The term hasn't caught on much beyond IBM.
However, the relatively new areas of evolutionary computing, massively-parallel algorithms, and even "artificial life" explore the solution of problems by the evolving interaction of large numbers of small actors, or agents, or decision-makers who interact in a largely unconstrained fashion. The "side-effect" of the interaction may be a solution of interest, such as a new sorting algorithm; or there may be a permanent residual of the interaction, such as the setting of weights in a neural network that has now been "tuned" or "trained" to repeatedly solve a specific problem, such as making a decision about granting credit to a person, or distinguishing a diseased plant from a healthy one. Connectionism is a study of systems in which the learning is stored in the linkages, or connections, not in what is normally thought of as content.
This larger definition of "computing", in which not just the data, or the metadata, or the context of the data, but the computer itself is being "processed" makes the term "social computing" have a whole different meaning. The repeated use of the "
blogosphere" to process daily news has a "side-effect" of building up linkage maps, trusted sources, RSS aggregator feeds, etc., so that the overall system is, in some sense, learning how to do something better, more rapidly, and more easily.
In control systems theory, it has been shown that closed-loop feedback systems are vastly more robust than open-loop system. The blogosphere has been criticized for having "echos" or repeatedly cycling certain ideas, but the upside is that there are simultaneous closed-loop feedback paths across a wide spectrum of distance and time-constants. These issues of computability and algorithm-order are classic computer-science issues and, in that sense, social computing is again a legitimate "computing" subject, even if it involves flexible collaboration as part of the "hardware". An analogy might be to imagine a "computer" built entirely of field-programmable gate-arrays, where not just the data and the program itself can be modified in flight (as in LISP, where programs and data are indistinguishable), but the hardware and logic and rules of operation also can be modified real-time during a "computation."
If the collaboration is over a large distance and many time-zones, the system will probably encounter significant differences in
context between the components, resulting in a whole new set of design and support problems and behaviors, especially misunderstanding of what is taken as implicit or obvious by different collaborators, and therefore not explicitly stated. Such differences may be cultural, geographic, hierarchical, etc. For example, when Hurricane Katrina hit the US in Fall, 2005, there were substantial collaboration and communication difficulties between Federal, State, and local officials. A significant portion of those difficulties were classic issues that very frequently result from attempts to collaborate over a distance, and from people at one level in an organization trying to collaborate with people at an entirely different level of an organization, with each group having different meanings to what "the problem" is that's being addressed and what time-scale is relevant. Computer-supported collaboration research includes academic research into how to minimize, or at least recognize that class of problem in collaboration and take it into account. Similar problems may occur if a conversation or collaboration occurs when it's a work day at one site or in one country, and already a week-end or holiday in another site, and the parties have different levels of stress and focus. These problems are analogies to "flame wars", the abrupt hostility that has been observed to occur when e-mail is used for a conversation, when the parties are no longer getting direct feedback from watching each other's body language.
A final difference between computer-supported collaboration and classic "computing" is that a computer typically remains a closed system, focusing only on what is already "inside the box", and only dealing with it in an abstract or mental fashion. Collaboration that occurs over a significant period of space and time shares properties of "active vision", where the actions possible are more than just analyzing an incoming TV image of an object of interest, but include walking over to the object, picking it up, turning it over, smashing it open, etc. The collaborating "units" are human beings, typically, who remain partly involved in the collaboration, and partly both sensing and actively changing the world around them. A collaborative discussion of baking cookies could include a period in which participants left the room to actually bake such cookies and try them out. A collaborative discussion of politics could include actually voting and changing the political landscape. This inclusion of both active sensors and active "effectors" is again a difference from "computing" that, at a minimum, makes this field at least as complex as "robotics".
Also, as stated earlier, generally a computer is unaltered by the program it's running or the data it's processing; but a collaboration of people and groups is typically substantially and permanently altered by the nature of problems it works on, the enjoyment or frustration with the working process, and the outcome of the work. This lasting residual "side-effect" or "effect" of one "cycle" of the collaboration then may alter the way in which the collaboration tool is use for the next "cycle", as people learn how to use this new method, so short-term, single-session or single-problem studies of collaboration tools may be very misleading as to what the longer-term outcomes may be. Imagine that your desktop computer, after a while, decided it didn't really like to do word-processing any more and preferred to work on addition, and that every time you tried to write e-mail the computer stopped mid-course to become obsessed with doing word-counts. Analogous behaviors in CSC, as with "game-theory", make studying almost any system or design problem frustratingly complicated: either the problems involved seem to be "toy" problems that are doable but unrealistically simple, or the problems become so complex that analysis is impossible.
A "computer" doesn't generally care whether the answer to a problem is "5" or "25", "yes" or "no," but humans involved in a group decision-making process may care very much about the outcome, and the various answers can have winners and losers with potentially very high stakes. At a minimum, this introduces substantial bias into the analysis of any data, as people will tend to selectively see facts that support the conclusions they personally prefer. In a collaboration within a single hospital between multiple clinicians, mediated by an "electronic medical record", there may actually be a substantial amount of dispute and negotiation going on among, say, a group focusing on treating diabetes and another group focusing on treating congestive heart failure. The "collaboration" may actually be much more of a "competition" to frame and define the problem in terms that result in favorable outcomes. Again, this makes CSC design work far more complicated than simply trying to get a group of sensors or computers to share data and work together correctly. In fact, in some cases, participants may have a strong vested interest in the status quo and prefer as an outcome that the "problem" not be solved. A
successful CSC system, in their minds, would be one that prevented the solution of the problem supposedly being addressed collaboratively, perhaps while giving a misleading appearance of cooperative effort. This factor complicates research into whether a CSC system is well-designed or not.
For example, in some countries national political elections could be viewed, abstractly, as heavily technology-mediated (and "computer supported") processes, including information distribution, discussion, debate, and an outcome resolution process - yet there may not be a unanimous opinion as to whether this process "works" or "is broken." It is difficult to improve or redesign a system if people can't even agree on whether the system works now or not. The implications of this is that CSC systems are inextricably embedded in social contexts and have to simultaneously address a specific problem, plus the issue of whether collaboration this way increases the ability to address future problems, plus the issue of what really defines which problems need to be addressed in the first place and the relative priority of those problems.
And, not only is there difference and potential competition between parties across organizational and cultural and geographic dimensions -- opinions on all those subjects may differ, and generally will differ, even within any given organization at different hierarchical levels. What works for workers may not work for management. What works for middle-management may not work for upper-management. What works for management may not work for the stockholders. What works for the company may not work for the country. A CSC system has to handle not just "content processing" but also "context processing" in that sense, sorting out the different nested and overlapping value-laden reference frames as well as the data and "the explicitly identified problem" within those reference frames. Part of this is a very abstract technical problem, faced by researchers in distributed artificial intelligence, in getting, say, 20 different surveillance robotic vehicles to talk to each other and compare notes - which is in itself a hard problem. Add to that complexity a new factor that, say, each of the robots has a hidden agenda and isn't being totally honest about what it shares.
If the preceding discussion gives the impression that CSC problems are extraordinarily hard to solve, that's correct. In fact, they've been described as "wicked" problems, not only because they're immensely complicated when addressed, but because they look so simple from the outside and are generally under-appreciated. For example, building a disaster-response communication system is vastly more complex than just getting a unified frequency for different agencies to use to communicate with each other, because the words, meanings, contexts, values, and agendas all also have to be communicated and resolved, across space, across time, across a 14 level hierarchy from the national leader to the front-line responder.
The view of a scene from an infection-control specialist's viewpoint and from a military or police viewpoint may suggest exactly opposite actions regarding "rounding up people and concentrating them at the stadium." The ability of a CSC system to facilitate wise decisions and action in that sort of situation might require the type of action described by the Harvard Negotiation Project in the book "Getting to Yes", where "positions" have to be abstracted to "interests", perhaps repeatedly, until a level is reached at which agreement and a common ground can be found between groups that appear, on the surface, to be hopelessly deadlocked. It is an open research question as to what features of a CSC system could simply allow that type of discussion to occur, let alone facilitate it. Very high bandwidth and multiple "back-channel" communication pathways have often proven to be helpful. Apparently very simple things, such as sufficient magnification and resolution on video screens to be able to actually see another person's eyes clearly, can have a dramatic effect on the ability of a system to support trust-building and collaboration at a distance.
Requires protocols
Communication essential to the collaboration, or disruptive of it, is studied in CSC proper. It is somehow hard to find or draw a line between a well-defined process and general human communications.
Reflecting desired
organization protocols and
business processes and
governance norms directly, so that regulated communication (the collaboration) can be told apart from free-form interactions, is important to collaboration research, if only to know where to stop the study of work and start the study of people.
The subfield CMC or computer-mediated communication deals with human relationships.
Basic tasks
Tasks undertaken in this field resemble those of any social science, but with a special focus on
systems integration and
groups:
Discover the multidisciplinary nature of computer supported cooperative work
Discuss experiences with technologies that support communication, collaboration, and coordination
Understand behavioral, social, and organizational challenges to developing and using these technologies
Learn successful development and usage approaches
Anticipate future trends in technology use and global social impacts
Analyze CMC systems and interaction via social software
Design CMC systems to facilitate desirable outcomes
Apply CMC analysis and visualization tools
Find uses of video conferencing, if any
Apply social ergonomics
Work environment design and A/V considerations
Improve audio and video encoding - from grainy thumbnails to HD
Improve and integrate common video conferencing tools
Analyze work processes, for example with the support of video monitoring
Deploy and evaluate systems for use in particular work contexts
Take theoretical perspectives to fieldwork, dealing with social complexity.
Performing observational studies
Work in commercial and industrial settings, domestic environments and public spaces
Problems of method, communication and comprehension in collaborations between ethnographer and system developer are also of special concern.
CSCW 2004 tutorials
listed all of the above as desirable skills to know.
Mainstream research
A 2004 list of "coordination and communication technologies" includes: » "Innovations and experiences with Intranets, the Internet, WWW"
"Innovative installations: CSCW and the arts" » "Innovative technologies and architectures to support group activity, awareness and telepresence"
"Social and organizational effects of introducing technologies" » "Theoretical aspects of coordination and communication"
"Methodologies and tools for design and analysis of collaborative practices", for example social network analysis » "Ethnographic and case studies of work practice"
"Working with and through collections of heterogeneous technologies" » "Emerging issues for global systems"
Plenary addresses on Open Source Society and Hacking Law' suggest a bold, civilization-building, ambition for this research.
Less ambitiously, specific CSC fields are often studied under their own names with no reference to the more general field of study, focusing instead on the technology with only minimal attention to the collaboration implied, for example video games, videoconferences. Since some specialized devices exist for games or conferences that don't include all of the usual boot image capabilities of a true "computer", studying these separately may be justified. There is also separate study of e-learning, e-government, e-democracy and telemedicine. The subfield telework also often stands alone.
Early research
The development of this field reaches back to the late 1960s and the visionary assertions of Ted Nelson, Douglas Engelbart, Alan Kay, Glenn Gould, Nicholas Negroponte and others who saw a potential for digital media to ultimately redefine how we work. A very early thinker, Vannevar Bush, even suggested in 1945 As We May Think.
Numbers
The inventor of the computer "mouse", Douglas Engelbart, studied collaborative software (especially revision control in computer-aided software engineering and the way a graphic user interface could enable interpersonal communication) in the 1960s. Alan Kay worked on Smalltalk, which embodied these principles, in the 1970s, and by the 1980s it was well regarded and considered to represent the future of user interfaces.
However, at this time, collaboration capabilities were limited. As few computers had even local area networks, and processors were slow and expensive, the idea of using them simply to accelerate and "augment" human communication was eccentric in many situations. Computers processed numbers, not text, and the collaboration was in general devoted only to better and more accurate handling of numbers.
Text
This began to change in the 1980s with the rise of personal computers, modems and more general use of the Internet for non-academic purposes. People were clearly collaborating online with all sorts of motives, but, using a small suite of tools (LISTSERV, netnews, IRC, MUD) to support all of those motives. Research at this time focused on textual communication, as there was little or no exchange of audio and video representations. Some researchers, such as Brenda Laurel, emphasized how similar online dialogue was to a play, and applied Aristotle's model of drama to their analysis of computers for collaboration.
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