TITLE PAGE
Author: Laurence Press
Title: Press, L., Systems for Finding People
Journal of Organizational Computing, 2(3&4), 303-314 (1992).
Affiliation:
Professor, Computer Information Systems, California State
University at Dominguez Hills
Email: lpress@venera.isi.edu
Running head: Finding People
Keywords:
organizational culture, participation, collaboration,
computer-supported cooperative work
ABSTRACT
Finding a previously unknown person with the skills and knowledge to
answer a question or perhaps to collaborate with is an effective use
of a computer-mediated communication (CMC) system. This article
discusses two aspects of systems for finding people, system
architectures and organizational implications.
The architectures considered are special interest groups, centralized
servers, and decentralized systems. The organizational implications
are the value to organizations of people-finding systems, management
incentives for individuals to participate in them, and participation
in the absence of apparent incentives.
The deployment and improvement of people-finding and other CMC systems
will bestow a marginal advantage upon cooperative individuals and
organizations with cooperative cultures. As a result, CMC may
marginally alter organizational and human nature, nudging us in the
direction of a time when nice guys finish first.
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Systems For Finding People
How do we use computer networks? Early proposals for networks
envisioned remote login as the key application (Marill & Roberts,
1966). As early networks became reality, electronic mail, file
transfer, and access to remote databases were added to the list of
applications (Roberts & Wessler, 1970).
Information retrieval has turned out to be of great value, and today
many use computers to retrieve structured and unstructured information
from local and public databases. Cuadra (1989) lists over 2,000 on-
line databases, and MIS departments often open data files to members
of their organizations. While such structured information is of
obvious value, it is used primarily for operational tasks like order
processing and billing or for relatively specialized tasks like
literature or legal-precedent search.
Unstructured data may contain valuable information, but locating
relevant items is difficult. Visions of the future such as the
"personalized newspaper" at the MIT Media Lab, Brand (1988) promise
that artificially-intelligent agents will one day find relevant
unstructured information for us, and Malone, Grant, Turbak, Brobst,
and Cohen (1987) have experimented with a system in which simple,
rule-based agents search for relevant semistructured messages
(containing fixed fields and text), but such systems are not yet in
general use.
While information retrieval and access to remote computation are of
value, electronic mail, or more generally computer-mediated
communication (CMC) has turned out to be the most common application
to date. CMC is now accomplished over a worldwide matrix of connected
computer networks and conferencing systems (Quarterman, 1990).
We can consider two types of CMC transaction: mail messages for a
specific person and queries in which you are trying to meet a
previously unknown person with skills or knowledge you need. In the
former case, you may or may not know the email address of the person
you wish to communicate with. If you do not, the Internet has several
systems for finding addresses. If the person's name and host are
known, the Finger protocol (Harrenstien, 1977) or a message to the
system postmaster may be used. If not, "white pages" services such as
Whois (Harrenstien, 1985), Knowbot (Droms, 1990), and NetFind
(Schwartz & Tsirigotis, 1991) may help.
The focus of this article is the second case, where you do not know in
advance who you are looking for. In my own experience, CMC enables me
to "meet" someone new who helps me with my work at least once a week.
(I know of a married couple who met on a bulletin board system and
understand that Compuserve has a regular listing of "cupcakes" --
couples that met on Compuserve). Therefore, I am more interested in
an agent or system which can help me find relevant people than one
which retrieves addresses or information.
This article discusses two aspects of systems for finding people,
system architectures and organizational implications. The next
section presents three alternative architectures: special interest
groups and centralized and decentralized systems. That is followed by
a discussion of organizational implications.
SYSTEM ARCHITECTURES
We can think of the problem of finding a person who can provide
information or collaboration as follows: the information seeker (or
an agent) formulates and submits a query, hoping there are system
members capable of providing a useful reply. Ideally, the system
would locate each member who could provide unique information
regarding the query, and no others.
Three possible approaches to this problem are: posting a query to a
subset of the system members who voluntarily participate in a special
interest group (SIG) such as a teleconference, mail list or USENET
News group, a centralized person server which matches a query against
profiles of system members, and a decentralized system in which system
member's agents screen queries to determine their relevance.
Special Interest Groups
The first of these, posting a query to a SIG, is common today. System
members identify themselves as being likely to have information on a
topic by joining the SIG. When a user posts a query, it is broadcast
to all members of the SIG, each of whom decides how to respond to it.
While widely used, SIG systems pose some problems.
When a query is submitted, system resources are used in making each
member of the SIG aware of it. Next, each SIG member spends time
screening the query. The screening time might be as little as reading
a header line and deciding not to read further, or it might mean
reading the entire query. Some subset of the SIG members then respond
to the query, which again takes their time and system resources.
In the ideal case, there would be only one response, and it would be a
complete, exact answer to the query; however, that is seldom achieved.
There may be no response, which is appropriate if no system member is
able to answer the query, but inappropriate if there is a member who
could answer, but does not see the query or does not read it. There
may also be multiple, redundant responses. I recently posted a query
to a news group asking for source code for a data compression
algorithm, and received essentially the same answer from 8 people.
For seven of these, the time they took to formulate replies, the
system resources needed to deliver them, and the time I spent reading
them were wasted.
The situation is analogous to type I and II errors in statistical
hypothesis testing -- the system can err by not finding a person who
could answer the query or by finding several people who provide
redundant information, wasting time and resources. Of course, queries
with a single correct answer like "what is size of the national debt"
or "who is the purchasing manager at the XYZ Company" are not typical.
In general, queries will have more complex, open-ended answers, so
replies fall on a continuum from completely relevant and unique to
partially redundant to fully redundant. In the case of a single-
answer query, there can only be one useful reply; in the case of more
complex queries, the relevance of a reply depends upon both it's
content and the time at which it is received.
Centralized Person Servers
The second approach to the problem of finding a person to answer a
query is a centralized person server (see Figure 1). A query is sent
----- insert figure 1 about here ----
to the server, which identifies system members likely to have
information or skills relevant to the query. Let us consider several
architectural alternatives.
The server could either be designed to automatically pass the query on
to the member(s) exceeding a system or query-specific relevance
threshold, or it could pass their descriptions back to the requester,
along with an explanation of why they were selected.
In the latter case, the user could consider the selections, optionally
request more information on the suggested correspondents or perform
further queries, and finally contact people at his or her discretion,
cutting the time spent on irrelevant queries and replies, but
requiring more of the requester's time. Given the current state of
the art of procedures for determining relevance, and the requester's
knowledge of the request, I would expect this approach to be superior
to one which fully automated the matching of queries and people. In
nearly all cases, a centralized server would be more efficient than a
SIG; however, it could be more prone to "type I" errors, in which
relevant system members do not see the query, depending on the design
of both systems and the behavior of system members.
The server must have access to profiles of the interests, skills and
experience of the system members as well as a procedure for
determining the likely relevance of a member to a given query. Note
that the profiles need not necessarily be stored on the same machine
as processes the queries. A network enables resource discovery
(Schwartz, 1991), in which one machine automatically searches or
queries others. Examples of systems using this architecture are the
Knowbot and NetFind, mentioned above, and Archie (Deutsch, Emtage, &
Heelan, 1992) which compiles a list of files available for anonymous
access using the Internet File Transfer Protocol.
A profile could be as simple as a set of keywords, or it could include
semistructured documents similar to resumes or bibliographies, or it
could include the full text of documents written by the members. The
design of profiles would be a function of the application context. In
a large public network, only keyword identifiers with a short
biography might be feasible. The keywords would be searched for
matches with the query, and the user would scrutinize the biographies
in deciding who to contact. (At one time IBM had a system for the
selective dissemination of information (SDI), in which members
automatically received copies of magazine and journal articles as a
function of self-defined keyword lists). If the system were serving a
single organization, it might be feasible to utilize structured and
semistructured information in evaluating query relevance, for example,
locating "any person with contacts in the XYZ company."
A wide range of options exists for search procedures and query
formats. A simple system could be built using current document
retrieval software with boolean keyword queries matched against
keyword profiles or fields in a structured or semi-structured profile.
A more ambitious system might search an inverted file of terms used in
free-format profiles or of documents prepared by members.
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Simple search software would merely decide that there is or is not a
match between each query and system member, while other software might
rank the relevance of each member relative to a query. In the former
case, the search could continue until a specified number of matches
were found, in the latter case, it would find all members exceeding a
threshold of relevance or it would rank them all. Free-format
queries, for example finding people who have written documents similar
to others or people with skill similar to others, can be processed by
large computers. For example, Stein (1991) describes wide-area
information servers (WAIS) which handle such queries on Connection
Machines and Dumais, Furnas, Landauer, Deerwester, and Harshman (1988)
describe latent semantic analysis, a computationally intensive metric
for distance between documents.
Clients and servers may be decoupled by adhering to query protocols
which are emerging as standards. Three candidates are the WAIS
protocol, SFQL, and CD-RDx. The WAIS protocol extends the NISO Z39.50
protocol developed for library catalog queries, and it is being used
and developed by an active group of Internet-based researchers (Lynch,
1991; anonymous, 1990). SFQL (structured Full-Text Query Language)
extends SQL, and it grew out of the need to query heterogeneous
aircraft documentation distributed on CD-ROM (Shapiro, Diamantopoulos
& Cotton, 1991). It is being developed at the request of the Air
Transport Association. CD-RDx is being developed at the request of
the Information Handling Committee of the CIA (anonymous, 1991).
Their goal is to enable government agencies to share data.
Existing information retrieval and database management software can be
adapted to the task of finding people, and there have been a few
trials. The WAIS approach was tested for finding consultants with
specified expertise at the KPMG Peat Marwick consulting firm (Kahle &
Medlar, 1991). Streeter and Lochbaum (1988) describe the application
of latent semantic analysis in a similar system at Bellcore. The
California State University System is experimenting with a system for
locating consultants from among faculty members, and Cartermill's BEST
North America and BEST Great Britain are commercial databases
including information on faculty and graduate students at 106 North
American and all British universities (S. B. Hesson, personal
communication, January, 1992).
A more flexible, object-oriented approach would also be possible. In
this case, each profile would be encapsulated with methods for
assessing its own relevance relative to a query. An object-oriented
approach would allow flexibility in the definition of profiles since
heterogeneous descriptions could be accommodated. An object-oriented
approach would also lend itself to parallel processing, with multiple
profiles evaluating their relevance to a query simultaneously. New
software and techniques would have to be developed for an object-
oriented system, and it would probably not be possible (or necessarily
desirable) to devise a single metric of likely relevance for all
classes of profile.
A Decentralized Approach
The object-oriented approach to a central server brings us close to
the third alternative, a decentralized system in which member's
filters or agents examine queries to determine whether or not to make
them known to their owner. This can be thought of as an extension of
the centralized, object-oriented architecture with the methods for
determining relevance executing in a process (probably running on a
personal workstation) associated with each member. It is different;
however, in that the decision to present or not present a query to a
given member is made locally, without knowledge of the relative
relevance of the query to other members. It also requires that
communication resources be used in presenting a query to each agent
and there is the likelihood of "type II" errors, with several
redundant replies to a query. On the other hand, the agent screening
queries will run in the background, using otherwise idle resources.
A version of a system such as this could probably be implemented using
an experimental system like the Information Lens (Malone et al. 1987).
With Information Lens, semistructured messages may be addressed to
"anyone." Each system member defines rule-based agents which screen
these messages. This mechanism can be used to screen messages and to
classify those which are accepted for reading. The rules are written
by the user, and they operate on information in the fixed-field
portion of a semi-structured message. Since the message formats are
extensible and users write their own rules, it should be possible for
users to define rules which incorporated self descriptions. Queries
sent to "anyone," would be checked by the potential recipient's agent
using the self-description rules. The agent would screen out queries
which its user would probably not be able to answer. It might also be
possible to implement rules which categorized queries as to the
likelihood with which they could be answered. Whether with
Information Lens or another system, it should be possible to implement
query screening agents. As in a centralized system, an object-
oriented approach could facilitate heterogeneous self-descriptions and
screening methods.
Of the three approaches to finding people who can answer a query, only
SIG systems are in wide use today, and in spite of their costs and
tendency to make errors, they are valuable. There have also been a
few experiments with centralized systems, and the technology is
available to deploy others. Assuming such systems could be built
brings us to organizational issues. The following section discusses
the value to organizations of people-finding systems, incentives for
individuals to participate in them, and participation in the absence
of apparent incentives.
ORGANIZATIONAL IMPLICATIONS
An organization often benefits from cooperative, internal CMC as
outlined above. In every transaction someone "gives away" information
and someone else "gets" it. The organization is enriched because both
members have the information, and they know of each other. If person
A posts a query, and person B is able to answer it completely and does
so, the organization will be better off if the value of the answer to
A is greater than the cost of supplying it. If the query/response
system were perfect, and only B saw and replied to the query, then the
"profit" to the organization would be the value of the information to
A less the communication cost and the cost of B preparing the reply.
Of course the system will not be perfect. As we saw above, there are
communication costs and, more important, the system may cause several
people to read the query, and several people may prepare and submit
redundant answers, which will have to be read. To the extent that
this happens, the system is inefficient. Such occurrences are
analogous to friction in a mechanical system.
In spite of of their relatively high "friction," SIG systems are
proliferating and many people find them worthwhile. As SIG systems
improve and person servers are implemented, efficiency will increase,
making CMC still more valuable for the organization. Other new
communication technology and infrastructure will have the same effect.
As the cost of cooperation decreases, organizations with a high
propensity to cooperate will enjoy an increasing competitive
advantage, thus economic selection will tend to favor the survival of
organizations which develop an ethic or value system favoring
cooperation.
While organizations will benefit from increased cooperation, what
about the individuals in them? Why should person B reply to person
A's query? Does person B even have an incentive to make his or her
qualifications known to the system -- won't doing so mean being
bothered to read queries and taking time to answer them? Person A
might even be a competitor of person B. Perhaps misinformation would
be in B's best interest. The situation is analogous to the "tragedy
of the commons" in which it "pays" for an individual to abuse or over
use common resources like grazing land, lakes, or the atmosphere
(Hardin, 1968).
Incentives to Participate
In the face of possible disincentives for individuals to participate,
management has several options. Profit sharing and other mechanisms
which reward group rather than individual performance increase the
value of participation to individuals. Rewarding group performance
has a secondary effect of increasing the emphasis on cooperation in
the general organizational culture, further increasing the propensity
to participate. This indirect effect can be amplified by using hiring
practice, training, executive communication, and other techniques to
increase the general value placed upon cooperation in the culture of
the organization (Schein, 1984).
Management also has the prerogative to exercise its authority to
mandate participation, making it part of an employee's job and
monitoring compliance. The effectiveness of group rewards and
attempts to produce a cooperative culture will be strongest in
difficult economic times, when the organization is threatened and
individuals have relatively few alternatives.
Changing organization structure, for example, by flattening it, may
also have some influence on participation. The effect of organization
structure (the topology of communication channels) on propensity to
communicate has been investigated in small group experiments by
Bonacich and Schneider (personal communication, January, 1990). It is
also possible to create economic markets within and among
organizations, by paying royalties or consulting fees. Perhaps the
first suggestion along these lines was Nelson (1973), which proposed
the Xanadu Network, a hypertext publishing and conferencing system
supported by a system of copyright and royalty payments. Potential
consulting fees are the incentive to participate in the Cartermill
systems mentioned above.
Participation without Incentives
While management actions such as these may be needed to overcome a
reluctance to participate, there are also many examples of seemingly
irrational cooperation or altruism. This section examines possible
causes of this behavior.
One framework for explaining it is offered by Maslow (1954) who
postulates an hierarchy of needs: physiological, safety, social,
esteem, and self-actualization. A person may be preoccupied by a
lower level need, but as it becomes satisfied, its importance
diminishes as the next level moves into focus. People with
unsatisfied physiological or safety (security) needs, would be less
likely to take the time to respond to a query than those who were
focused on higher needs. If you are insecure in your job, you might
not be willing to spend time helping a coworker without explicit
credit or compensation.
Higher level needs, for example for esteem, explain some apparently
uneconomic contributions. As any aspiring poet can tell you,
unpublished information does not yield esteem. Voluntarily submitting
a description of your skills and experiences to a person server would
afford an opportunity to achieve esteem as would answering queries.
Frequent contributors to public SIG discussions, such as those on
USENET, gain esteem by becoming known among to SIG members.
From the point of view of someone posting a query, anonymity might be
desired in order to prevent erosion of social status. For example,
Karabenick (1987) has found evidence that in an academic setting,
people are more likely to request help if they may do so anonymously,
presumably in order to hide their ignorance, and Stodolsky (1989)
suggests that mechanisms to protect expression, for example anonymity
or psuedonymity, where each member has one, and only one pseudonym,
might encourage information sharing.
However, information contributions which bestow neither economic
advantage nor social status are common on today's SIG systems. These
might be explained as a recognition of long-run economic calculations.
For example, Kenner (1989) recounts an anecdote in which someone on
the BIX network helps him with a problem and he passes the favor along
by helping someone else. He explains this altruism as follows:
[Members of the BIX Network] routinely exchange services for
free. It's the regnant assumption that, whether I can ever be
of service to [the person who is assisting me], I can surely
be of service some other time to somebody, and these pooled
favors level out.
But why doesn't the tragedy of the commons stop one from contributing?
When Kenner sees a query which he can answer, it is still locally
irrational for him to do so. While some may use Kenner's
rationalization, others may find themselves contributing without being
able to explain why -- it just feels right.
The evolution of apparently irrational altruism has been studied in
depth by biologists, who may offer some clues. We often have
difficulty giving rational, symbolic explanations for skills and
concepts which are critical to survival. Perhaps this is because
surviving members of our species learned these concepts in a pre-
verbal era. For example, everyone can differentiate between living
from non-living entities, yet "life" is difficult or impossible to
define. Similarly, to some people, at some times, cooperation, taking
the time to answer a query on BIX, might just "feel right." Lovelock
(1979) states that what feels right may be genetically determined:
It may be that we are also programmed to recognize
instinctively our optimal role in relation to other forms of
life around us. When we act according to this instinct in
our dealings with our partners in Gaia, we are rewarded by
finding that what seems right also looks good and arouses
those pleasurable feelings which comprise our sense of
beauty.
Biology offers theories which might explain the evolution of
altruistic feelings and hence behavior. One is the theory of kin
selection, in which "a gene which causes its carrier to perform an act
which puts it at risk may nevertheless increase in frequency if the
result of that act is to help relatives of the actor, who may carry
identical copies of the gene" (Maynard-Smith, 1982). For example,
animals are known to give warning calls when a predator is near, at
their own peril. Sherman (1977) has studied this phenomenon in ground
squirrels, and after testing six alternative hypotheses to explain it,
concludes that of the six, the warning of kin is the most important
and perhaps only function of these calls. Could it be that the
feeling which leads to cooperative behavior among individuals within
an organization is a case of misguided kin selection, evoked by
contact in the workplace and common organizational symbols and
culture?
There are also evolutionary theories explaining reciprocal altruism
among unrelated individuals. Risky, cooperative behavior has been
observed in unrelated animals, for example, by Packer (1977), and
modeled using game theory in Axelrod and Hamilton (1981) and Axelrod
(1984).
Axelrod and Hamilton analyzed the Prisoner's Dilemma game and showed
that a strategy which involves some cooperation (instead of always
defecting) is evolutionarily stable if the game is repeated many
times, the players recognize each other, and the probability that they
will play each other in a subsequent game is sufficiently high, given
the payoff matrix. One such strategy is tit-for-tat (TFT), in which
the player always cooperates on his or her first encounter with an
opponent, and thereafter does whatever the opponent did on the
previous encounter, i. e., begin cooperatively, but immediately
retaliate for a defection and reward a return to the cooperative fold.
Axelrod invited game-theory experts and amateurs from around the world
to participate in a computer-simulation contest for such strategies,
and TFT won, even though the other strategies were computationally
more complex. (The TFT algorithm required only 5 lines of code while
the 62 other entries ranged from 6 to 152 lines).
Axelrod and Hamilton speculate that uncertainty as to whether others
were relatives (kin selection) could get the cooperative ball rolling.
Furthermore, they show that once TFT is established, it will resist
intrusion by an all-defection strategy. Gregory (1982) notes a TFT-
like pattern in the behavior of people in clan-based societies with
gift-exchange economies. Gift exchange establishes a relationship
between the participants, with a gift establishing a debt that has to
be repaid.
TFT did not defeat any competing strategy, but its total score was
highest. Axelrod states that "TFT won the tournament, not by beating
the other player, but by eliciting behavior from the other player
which allowed both to do well," and goes on to give examples from
every day life (business, arms control, etc.) where such behavior
works to everyone's benefit.
Simon (1991) also offers an evolutionary theory of motivation to join
organizations and work without shirking. As partial explanation for
such cooperative, often altruistic behavior, he speculates on the
evolution of a tendency to balance self-assertiveness with docility,
where being docile is "to be tractable, manageable, and above all
teachable." Simon reasons that a degree of docility would on the
average increase fitness, and hence be selected for.
If there is some instinctively felt propensity to cooperate, we would
expect that propensity to be stronger in some individuals than others.
We would also expect it to be felt more strongly at some times of life
than others, due both to circumstance and maturation. Achieving
material success could pave the way for altruism, and it may also come
more easily at certain stages in life, just as sexual maturation or
the ability to acquire language have a well defined place in the life
cycle. (Also, as pointed out by Axelrod and Hamilton, older
individuals would have lower probability of encountering others in the
future, shifting their game-theoretic assessment).
Lovelock suggested that we may be genetically programmed to recognize
beauty, and we may also be genetically programmed, to varying degrees,
to cooperate. Helping someone who posts a query on a computer network
might feel good because that feeling tends to propagate your genes.
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CONCLUSION
CMC infrastructure is proliferating rapidly, lowering the cost of
communication and cooperation. One way CMC systems are used is to
find previously unknown people who can provide information or
expertise. We discussed three general architectural alternatives for
building such systems. Of these, SIGs are already in wide use, and
the technology is available to deploy systems using centralized
servers.
While this form of cooperation benefits the organization, it may not
benefit the individuals in the organization. We outlined several
management options for increasing individual's incentive to
participate. We also discussed reasons people may participate without
incentives -- to gain status or because it was part of their
instinctive nature.
Individuals, organization, and tools co-evolve. We shape our tools
and they shape us. Imagine organizations without the clock, electric
light, telephone, or automobile. Tools also change our individual
nature. At the point where a tool is pervasive and no longer noticed,
our sub-conscious self has changed. We perceive our environment
differently, therefore we are different. If the propensity to
cooperate has a genetic component, and CMC bestows a marginal
advantage upon individuals and organizations that cooperate, we might
expect some evolutionary pressure in favor of cooperation. Perhaps
CMC will marginally alter organizational and human nature, nudging us
in the direction of a time when nice guys finish first.
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Person
Server
Z D D D D D D D D D D D D D ? query Z D D D D D D D D D D D D D ?
3 3 D D D D D D D D D D D D D D >3 3
3 User with 3 3 Matching 3
3 Query 3 matches 3 Procedure 3
3 3 <D D D D D D D D D D D D D D 3 3
@ D D D D D D D D D D D D D Y @ D D D D D D B D D D D D D Y
^
3
3
Z D D D D D D A D D D D D D ?
3 3
3 Member 3
3 Profiles 3
3 3
@ D D D D D D D D D D D D D Y
Figure 1. A Person Server. A query is matched against member
profiles, and the user is informed of the identity and characteristics
of members likely to posses relevant information. Alternatively, the
system could automatically forward the query to matching members. In
an object-oriented system, the matching procedure would be
encapsulated with the profile.
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