|
Items in cart [0] |
Questions? Call 888-624-8373 |
| Copyright © 2009. National Academy of Sciences. All rights reserved. Terms of Use and Privacy Statement |
Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter.
Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 131
Page 131
B
Position Papers Submitted by
Workshop Participants
OCR for page 132
OCR for page 133
Page 133
Research On Information
Technology Impacts
Paul Attewell
Graduate School and University Center, City University of New
York
A few comments about past impact research are appropriate at the
outset, because there are some important issues that ought to be
considered before moving on to new topics and research priorities.
We made some intellectual mistakes in the past that we can avoid
repeating in the future. Since some of the workshop participants
are new to this area of study, I think it would be helpful to lay
out some of these issues.
Because technological change in information technology
applications has been so rapid during the last 25 years, there has
been a constant temptation to turn away from studies of current
outcomes of existing information technologies and instead turn
toward a kind of futurology or speculative stance about what might
be the case in the future. Examples are found in the agenda for
this workshop, where topics are articulated such as: "How will the
nature of the employment contract change? … What will be the
impact on K-12?" The future is important, and these kinds of
questions are valid, but this stance has had some unfortunate
implications for impact research in the past. Among these are the
following:
• A tendency to support the development of
theoretical models to predict what will
be or might
be the case, rather than pursue empirical
studies of what actually is happening now. Since theorizing tends to be cheaper
than data collection, this has tended to skew funding toward the
former, and has often given this field a rather speculative feel.
But speculation, even by very smart people, has often been far off
the mark.
• A tendency to fund studies of "cutting-edge"
applications, which tend to be located in large, dynamic (and
resource-rich) firms, or superior schools, rather than looking at
the kind of "ordinary" IT that is in place in average workplaces
and ordinary schools—the point being that what one observes in
the largest, most resource-rich, and most committed settings is
not a good predictor of
the typical effects of a technology in the larger world. (In the
field of program evaluation there is a parallel phenomenon known as
the demonstration effect: innovative programs are shown to work well initially in
well-supported demonstration projects but then prove much less
effective when widely implemented in more
OCR for page 134
Page 134
ordinary settings.) Studying
cutting-edge applications in cutting-edge firms, schools, or
universities is fascinating, but this is not the most rigorous
approach to understanding how technological change is affecting the
larger population of organizations and people. It tends to result
in unrealistic scenarios.
• A tendency to direct money into prototyping new
applications, and to rely on the authors of the prototype to do the
impact assessment or performance evaluation themselves or not do an
evaluation at all. This has occurred all over the "computer
assisted cooperative work" field, as well as in the field of
educational software. It is naive to expect that people who toil
over developing new technology can provide an objective assessment
of its performance, yet this approach dominates research. There is
no equivalent in IT research of the "double blind" study, and
replication is rare. Perhaps this is one arena in which engineers
and social scientists could collaborate: if federal funders
insisted that all prototype and development projects include an
arm's-length performance assessment, this would be a major step
forward.
• A tendency to discount findings that demonstrate
negative or null impacts of IT as being intellectually
uninteresting on the grounds that such impacts simply reflect early
versions, or start-up problems, which will disappear when the next
generation of machinery or software comes online. Studies indicate
that there are large discontinuance/abandonment/non-use rates for
important and much-hyped IT products. (Examples are Kemerer's
recent studies of abandonment of fourth-generation software
development tools and Detroit's ripping out advanced automated
manufacturing from some plants.) Users of "what if" decision-tools
have been found to use them mechanistically even when shown that
they are producing inferior decisions. Computer searches of
databases using current methods have been shown to generate large
numbers of bad hits, and also to miss large numbers of relevant
items.
If IT impact research were a normal social science discipline,
such striking findings would be viewed as important scientific
puzzles, unleashing a stream of follow-up research seeking insights
into human-computer interactions implied by these failures. By and
large this has not occurred, because of a widespread mentality that
says that any problems with IT that impact studies unearth are
simply minor implementation issues and will be overcome by the next
generation of technology. This mentality reminds me of the
anthropologist Evans-Pritchard's studies of Azande witchcraft.
Whenever he contrived to show African believers in witchcraft that
casting a spell/curse on someone did not work in a concrete case,
the believers were unshaken, retorting that of course witchcraft
worked, but that the spell had been performed poorly in this case.
IT does work, but impact research should spend much more
time looking at the many settings in which it works very
differently than intended, and should mine these cases, as well as
the successes, in order to understand the full picture.
OCR for page 135
Page 135
• One of the most common findings in prior IT impact studies has
been that outcomes are far from uniform across all kinds of
settings and contexts. In earlier years we looked for the
impact of IT on (say) organizational centralization, and scholars
tended to hew to one end or the other of a bipolar spectrum:
centralization versus decentralization; upskilling or
deskilling; job destroying versus job creating. What scholars
found, in almost every case, was that this was an unproductive way
to conceptualize the issue. One almost always found evidence of
both extremes of outcomes/impacts as well as many points in between
(see Attewell and Rule, 1989). We finally realized that we were
asking the wrong question. We should have asked, In what contexts
does outcome A typically predominate, and in what contexts does
outcome B tend to prevail, and when does one see A and B in equal
measure? We found that a technology does not usually have an
impact. The context or setting in which the same technology is used
often produces strikingly different "impacts." This phenomenon has
been discussed in terms of "Web Models" (Kling), or "structural
contingency theory" (Attewell), or Robey's ''Plus Ca Change" model.
All imply that we fully appreciate the role of context in
technology outcomes, and that we therefore expend sufficient
research effort to measure the context, and to delineate its
interactions with the technology. If we fail to do this, we return
to the old "black box" paradigm, that is, attempting to measure
only the input (say, a particular software program) and the outcome
(say, kids' test scores) without bothering with the context (the
classroom, the kids' family backgrounds) or the causal mechanisms.
Black box research on impacts often discovered "inconsistent"
outcomes across studies but proved unable to show why there was so
much variation, because it neglected to measure the contextual
variables that were moderating the effects of the input upon the
output. For example, the old paradigm would phrase a research
question so as to ask whether or not home PCs would improve kids'
school performance. In contrast, research within the current
contextual paradigm would ask under what conditions having PCs at
home affects students' school outcomes. A piece of my own work has
indicated, for example, that having a home PC currently has a
minimal effect on the school performance scores of poor and
minority kids but is associated with substantial positive effects
on the school performance of kids with high socioeconomic status
(SES), when other factors are controlled for (Attewell and Battle,
1997). Race and class/SES, in this example, prove to be very
important contextual features moderating the impact of home PCs on
school performance.
• Workshop organizers should be aware that because of the last
three decades of research and the importance of context as
discussed above, many distinguish ed scholars of technology avoid
the term "technology impact." Using this term in framing the
question would be viewed by some of them as indicating an ignorance
of the body of scholarship in technology studies. For them, the
term "impact" connotes a kind of technological determinism that is
very dated and
OCR for page 136
Page 136
widely discredited. Personally, I am not so averse to the term
"impact," but I do agree with their larger point about avoiding
models based on simple technological determinism.
Distilling these arguments into positive recommendations: (1)
future research should pursue empirical studies of existing
technologies in real settings, as distinct from speculative or
purely theoretical exercises; (2) care should be taken to include
representative organizations/settings, not just cutting-edge or
high-tech ones; (3) studies of unintended consequences of IT, such
as failures and discontinuance, are important for what they tell us
about these technologies and about the process of change more
generally. Researchers should be interested in the full range of
"impacts"—intended and unintended; (4) projects aimed at
developing technology prototypes should routinely include a
performance assessment or evaluation, and the latter should be
conducted at arm's length from the former; (5) contextual variables
should be studied rigorously, and their moderating effects on
technology outcomes should be a major part of inquiry; (6) we
should reconceptualize what we are doing as social and economic
studies of computing and communications technologies rather than
technology impact studies, and try to avoid technological
determinism.
To move to the request about specific areas for research, here
are some suggestions:
1. The "productivity paradox," in my opinion, remains an
important and unresolved issue. However, I suggest that we should
move beyond dichotomous thinking (Does information technology have
a payoff, or not?) and ask, In what areas/applications/settings do
we see payoffs and in what areas don't we, and why? What mechanisms
can be identified that attenuate potential payoffs, and how do we
measure them? What interactions and contexts explain variation in
productivity outcomes?
2. Skills. There is anecdotal evidence that the range in
performance levels in computer-related work is greater than that
found in noncomputerized tasks. In other words, the gap between
skilled and mediocre users is larger in computer-related work. This
suggests that skills in computer work are less well diffused, or
are shared less than in other kids of tasks. We need research on
what constitutes skilled versus unskilled performance in computer
work of various kinds, and a better understanding about why so many
of us make mediocre use of these tools.
3. Teenagers. I suspect that personal computers are changing
the lives of teenagers more than most other age cohorts, and that
is both an opportunity and a concern. Computerized communication
affords powerful opportunities for social affiliation (e.g.,
Sproull and Faraj, 1995) and for playing with identity, both
preoccupations of adolescence. There have already been studies that
suggest that teenagers are spending less time watching TV and more
on the Web. There are a
OCR for page 137
Page 137
host of policy issues surrounding their use. But
our knowledge base of how young people are using the Web, and what
they are getting out of it, is too sparse.
4. Education. As a researcher I find the literature on
educational computing quite maddening. There are exciting claims of
accelerated learning using computerized tools, but the research
rarely gets replicated, and even the most lauded programs (e.g.,
the algebra tutor at Carnegie Mellon) never seem to cross into
public use, in part because these prototypes are built on UNIX
platforms in esoteric languages. As a result the field does not
progress in a cumulative manner. There is clearly room for a
serious review and analysis of the state of the art in educational
software, and for research on the barriers to future progress of IT
in education. Universal access to the Web is the only area I know
that has received systematic treatment.
OCR for page 138
Page 138
What If All Information Were
Readily
Available To All?
Joseph Farrell
Department of Economics, University of California, Berkeley
Rapid improvements in information technology raise two grand
issues. First, are we moving toward a world in which, to a
reasonable approximation, all "information" (not, of course, the
same as knowledge) is readily available to all, or are there major
obstacles in the way that may prevent us from getting to that
point? For instance, is there no such thing as "all information"
relevant to a particular topic? Are standards problems,
intellectual property rights problems, database search limitations,
or other issues likely to bound us well away from that "all
information available" state?
Second, if we do get to that state, what will it be like? Much
of today's employment consists of clumsily dealing with
information. Will the demands of more information be greater or
less? If the problem gets "solved" rather than just increasingly
addressed, what are the other main things that need to be done in
an advanced society—in other words, what will today's
information manipulators do instead?
OCR for page 139
Page 139
Critical Issues Relating To Impacts
Of
Information Technology: Areas For Future
Research And Discussion
Alexander J. Field
Santa Clara University
There are several key issues that concern me as a scholar.
First, as an economic historian and as someone who looks
retrospectively as well as prospectively, I believe we face a major
issue involving the archiving of data. There are two main issues.
People say about magnetic media that it lasts 5 years or until it
wears out, whichever comes first. That is probably a bit
pessimistic. But even if the media persist, what about the
input-output devices? It is getting more and more difficult to find
a 5.25-inch drive, and woe to him or her who has data on 8-inch
floppies! Tape backups are sometimes even worse. New backup
software is sometimes not backwards compatible, so that one needs
old copies of backup software as well as a compatible tape drive in
order to restore data. We need mechanisms to ensure the
retrievability of records that previously would have been stored as
printed records. This issue is at least as important for individual
records (both personal and professional) as for those pertaining to
the corporation or organization as a separate legal entity.
Whatever media are used, we need them to be at least as durable and
stable as microfilm. Ideally these media should be relatively
inexpensive, and equipment to read and/or write on them should be
standardized and widely accessible. Will individual and private
enterprise be sufficient to ensure retrievability? Is there an
externality in terms of ensuring access that would warrant
government subsidy or intervention in this area, perhaps as part of
the activity of the National Institute of Standards and
Technology?
A second issue: As a scholar I look forward to tremendous
opportunities in terms of the archiving of old journal runs. This
has an enormous potential capital savings impact (consider the
linear feet of bookshelves in faculty offices that might be
liberated). I look forward to being able to access 100-year runs of
journals such as the American Economic Review, from CD-ROM
or over a network through software such as Adobe Acrobat (thus text
is searchable). I see this as less important for books and
monographs (where being able to read through an entire volume,
which presumably has some coherence) will still be desirable.
Nevertheless, the ability to search the text of scholarly
monographs would be useful. The cost of converting newly published
material to this form will be small, since most of it now exists in
machine readable form before it goes to be typeset. The real
challenge will be older works. There is a potential for
enormous
OCR for page 140
Page 140
efficiencies here in terms of research libraries and scholarly
research. But who will pay? Is there a role for the Library of
Congress? Can we get to the point that interlibrary loan involves
the simple downloading of a large file? Will scholars assemble
libraries of CD-ROMs attached to personal computers? Will they
invest in juke boxes so that the disks are available and
retrievable when needed? (CD-ROMs can be as inconvenient as the
computers were prior to the advent of hard disks—one can never
seem to find the disks when one needs them, and their smaller size
renders them more vulnerable to misplacement than books.) Or will
the material be available through servers in libraries or over
commercial networks? Obviously, copyright issues are relevant for
recently published works, but I am interested in materials for
which copyright is no longer relevant. How will this affect the
publishing business?
Finally, let me comment on ways in which new instructional
technologies will affect the craft of teaching. I believe firmly
that advances in information technology will play an important role
in complementing rather than eliminating traditional
classroom instruction. The advent of television and the video tape
recorder were both heralded as sounding the death knell of
traditional instruction. There is no evidence that this has
occurred, nor that recent advances will have this effect either,
any more than computers have eliminated the use of paper or
videoconferencing facilities have spelled the demise of the 747.
The effective instructor acts in a complex mixture of roles. In one
role the instructor is a supplier of services to students
(particularly when they are enrolled in course work beyond the age
of compulsory schooling laws). In terms of this relationship
students are in a real sense customers. But the effective
instructor occupies another role as well—as, in a sense, a
supervisor of students, and plays a role in motivating,
encouraging, evaluating, and developing students that is totally
foreign to the service provider-customer model. For any topic there
will always be a small percentage of prospective students with the
necessary background, motivation, and self-discipline to learn from
self-paced workbooks or computer-assisted instruction. For the
majority of students, however, the presence of a live instructor,
will, in my view, continue to be far more effective than a
computer-assisted counterpart in facilitating positive educational
outcomes, just as for most work relationships, a live supervisor is
going to be more effective than a computer replacement.
The most important impact of information technology will likely
occur in increasing the productivity of the hours students spend
outside of the classroom. Several years ago many universities,
including my own, built computer classrooms with networked
computers for every one or two students. While these have proved
effective for training in the use of various kinds of software, in
most cases they proved disastrous for standard classroom
instruction. The computers created line-of-sight obstacles between
the instructor and students, and students could sometimes not
resist the temptation to play computer games during class time. In
some instances such labs have been ripped out. Nor am I persuaded
that
OCR for page 141
Page 141
the increasing use of presentation software on average improves
the efficacy of classroom communication. The dimming of lights and
the focusing of attention on an overhead screen distracts attention
away from the facial expression and body language of an instructor,
which gives away two of the most powerful benefits of live
instruction. Expensive overhead cameras that convert documents to a
video feed currently have lower resolution than standard overhead
projectors.
The greatest potential for new information technology lies in
improving the productivity of time spent outside the classroom. The
norm of accrediting agencies is 2 hours' outside work for 1 hour in
class. Making syllabi, solutions to problem sets, and, where
copyright law will permit, assigned reading materials available on
an inter- or intranet offers tremendous convenience. E-mail and
more sophisticated groupware vastly simplify communication between
students and faculty and among students who may be engaged in group
projects and face enormous logistical challenges in setting up
group meeting times.
OCR for page 152
Page 152
Questions For Research
Jeffrey K. MacKie-Mason
Department of Economics, and School of Information, University
of Michigan
What is currently known? What questions need to be
addressed?
Costs are falling exponentially for technologies built primarily
with silicon and sand: computing cycles and bandwidth. The decline
in data storage costs would also seem remarkable but for the
comparison.
Almost, but not quite the same thing: technological progress in
these areas is accelerating. (Possible research question: Is it?
How is it measurable?) Ignoring cost, remarkable new things are
possible each year. (A thousand IBM 360s connected with RS-232
cables would not a parallel-processing supercomputer have
made.)
We have a long history of adapting to falling costs and
technological progress. But we are not well adapted to such fast
change. In the context of our history and institutions—social,
political, cultural, at least—such rapid advancement is
deviant. Deviancy threatens existing institutions.
Institutions (conventions; standard practices; social, business,
and political norms) evolve to deal with problems that undermine
the ideal of a competitive market equilibrium: positive
externalities (standardization), public goods (government
provision), and transaction costs (default rules, social
conventions). But when relative costs and technological
opportunities change rapidly, the problems that the institutions
solved are no longer the same.
Problems are changing rapidly, but institutions change slowly
and reluctantly. New problems, old institutions: things break, or
progress is delayed. Examples:
• International spectrum allocation: need for global bandwidth
reservations for low earth orbit satellites and other wireless
networks.
• Governance of the Internet: need for assignment of domain names
and Internet protocol numbers, routing policy, content control.
• International banking and currency control.
• International taxation, currently largely source-based: Where is
cyber activity taking place? How easy will income shifting to find
a low-tax-rate base become?
OCR for page 153
Page 153
• Church, school, and other local community institutions being
challenged as core communications channels for shared values,
culture, and social norms. Rise of disembodied, asynchronous
"community" (e-mail, Usenet, special interest groups). Paradox of
improved communications channels increasing balkanization?
So, at least one set of fundamentally important questions for
research involves looking beneath specific impacts to uncover the
institutional structures, assumptions, and rigidities that are
becoming dysfunctional, and then considering how to facilitate the
transition to new institutions that are likely to accommodate the
effects of exponential decreases in the costs of sand and
silicon.
• What government core institutions underlie market interventions,
subsidy and tax policies, and trade policies? What educational
structures? What legal institutions?
• What do we take for granted about intellectual property (before
we get to the question of protection)?
• What mechanisms for establishing trust, evaluating,
authenticating, and providing assurance underlie conventional
commerce, and how can a system of trust be evolved for electronic
commerce?
• What law applies to artificial agents who participate in
information exchange? What socially acceptable policies exist for
dealing with deadly threats to the public health like outbreaks of
Level IV computer viruses (Ebola-PC, Ebola-Mac)?
• What does universal service mean? When should government treat
emergent network services with large potential positive network
externalities as public goods that should be subsidized?
• Good advice: Assume CPU cycles and bandwidth are free. What
then?
What will be useful methods to determine answers to such
questions?
The cycle of change strains some traditional methods. It is hard
to get data from "natural experiments" on which generalizable
hypotheses can be tested. For example, Internet congestion seems to
be a problem. Various approaches to allocating scarce, easily
congested resources have been proposed, including different types
of usage-sensitive pricing. Lots of concern: Will this increase
information inequality? Squelch creative explosion of Internet
applications? Slow adoption? Chase away independent, voluntary
provision of content in exchange for industrialized creation and
control of mass-market content? Some fundamental research
questions: How much consumer surplus is lost due to congestion?
(How much does waiting "hurt"? What applications are we not getting
to use because they can't tolerate unpredictable congestion, and
how much are those worth to us?) How would different classes of
users respond to usage-sensitive pricing (if it constituted a small
fraction of their consumption
OCR for page 154
Page 154
budget)? Thus, would be benefits (of less congestion in current
services, and new services enabled with guaranteed quality of
service) outweigh the adverse effects on adoption rate and social
externalities of communication, reduced innovation, change in
content, change (not necessarily increase!) in information
inequality?
To answer these questions, we might normally run consumer demand
studies to estimate user valuation of various service qualities at
different prices, looking for natural experiments to assess the
value of social externalities.
The problem: no data! And even as data start to become
available, the data-generating process is nonstationary
(stationarity is a prerequisite for classical statistical
estimation and analysis): new services are introduced, users are on
a learning curve, participation externalities are riding up the
adoption curve. Example: How much do we learn about future Internet
demand if we study pre-WWW demand? And if we wait to observe,
strong network externalities and resulting standardization may lock
us into policies and standardized solutions that are inefficient,
inflexible, and limiting (e.g., Wintel architecture; the "mistakes"
of QWERTY and VHS standards). The traditional pace of research and
institutional adaptation is too slow.
Possible implication: Social science research may need to do
more field and lab experimentation, rather than waiting around for
the real world to toss up natural experiments.
There may also have to be some merger between traditional social
science and engineering methodologies—some attempt to learn
from results that are not fully general, developed, and rigorously
tested following a modernist hypothesis testing method. Thus, look
to find—and design—systems, policies, and institutions
that "just work." Think about how to make them work better, without
clinging too tightly to the "optimality" paradigm. Internet litmus
test: "running code that works."
Likewise, traditional conceptual structures may need
reworking.
Many observers—but not economists for the most
part—have suggested that "traditional economics is dead," that
there is a "new" economics of information. Yet the "special"
features of information problems are familiar in economics: high
fixed costs plus low variable costs, congestion externalities,
positive network externalities, and tipping. What may be new is
that several of these become simultaneously significant, and for a
greater, more essential share of exchange. We are used to thinking
of these and designing policies for them as special cases.
Nonetheless, we should not blithely discard hard-won principles.
For example, some would have it that soon bandwidth will no longer
be scarce: it will be infinite (effectively) and free. Not by the
laws of physics, of course. Has anything ever become infinite and
free? No, just relatively less scarce. It seems still very useful
to study the relative scarcity of different resources—silicon,
sand, labor, creativity, attention—and to focus on how
relative scarcity is changing.
OCR for page 155
Page 155
Where the change in scarcity is occurring is where the
opportunities and problems lie. The end of scarcity is a red
herring.
A few areas on which to focus research:
• Information warfare: survivability of communications networks
(civilian as much as military); institutions and policies for
response to transnational terrorism and criminality (that uses or
attacks information infrastructure);
• Artificial agent economies: how to harness the efficiency,
stability and robustness of competitive economies for real-time
management and control of complex systems (electric grids,
telecommunications networks, smart highways, spread-spectrum
bandwidth allocation); and
• Evaluation and social filtering: the economics of attention,
trust, and reputation. Funding models for information and
information services, and their effect on the creation and
distribution of content.
OCR for page 156
Page 156
Electronic Interactions
Paul Resnick
AT&T Laboratories
The Internet offers new opportunities both to support and to
study interactions among people who do not know each other very
well. I believe that recommendations, trust, reputations, and
reciprocity will play important roles in such interactions and thus
deserve attention from interdisciplinary research teams.
There are interesting topics in all stages of commercial
interactions, from search processes to negotiation to consummation
of transactions:
• Recommendations and referrals can help people to find
interesting information and vendors. There is a need for continued
research on techniques for gathering and processing recommendations
(this is sometimes called collaborative filtering). Compilation of
"grand challenge" data sets of recommendations would help this
field advance.
• The structure of negotiation protocols and the availability of
information about past behavior of participants will affect the
kinds of outcome that are possible. Economists have theoretical
results regarding many simplified negotiation scenarios, but there
is a need for interdisciplinary research to apply and extend these
results to practical problems of protocol design.
• Finally, in the transaction consummation phase, much effort has
focused on secure payment systems. Some transactions, however,
require a physical consummation (mailing of a product, for example)
and hence must rely on trust in some form. Research can explore the
role of reputations in creating trustworthy (though not completely
secure) contract consummation. Such transactions may also have
lower transaction costs than secure payment systems, even in the
realm of purely electronic transactions.
Noncommercial electronic interactions also offer many
interesting opportunities. Electronically mediated interactions are
visible and available for analysis in a way that face-to-face
interactions typically are not. For example, "softbots" could scour
the Web to create various graphs of relations between people and
information resources. Social network theorists have already
devised a number of techniques for analyzing such graphs. One
possible application would be to hypothesize about and then analyze
the credibility of information sources in
OCR for page 157
Page 157
various parts of a social network. Another possible application
of network analysis would be to analyze the flow of reciprocity (or
gift exchange, as Esther Dyson put it) and perhaps devise ways to
increase a social network's level of reciprocity.
In the last couple of years, I have become particularly
interested in the concept of social capital, as articulated by
James Coleman, Robert Putnam, and others. Social capital is a
resource for action that inheres in the way a set of people
interact with each other. I'm still struggling for various ways to
connect this concept to specific research questions and projects.
Some of the ideas above are born from those struggles, and I'd
welcome any project ideas or new ways of thinking about these
problems.
OCR for page 158
Page 158
Social Impact Of Information
Technology
Frank Stafford
University of Michigan
A great deal of attention has been given to new information
technology as the main empirical force changing the wage structure
and giving rise to wage inequality. Yet something on the order of
skill-biased technical change is usually given no formal
representation. The theory that could actually explain the changing
wage structure is some type of unbalanced growth model. In fact the
theory that could apply is not too hard to imagine. It is a closed
economy "trade" model with "biased" technical change (Johnson and
Stafford, 1998). Skilled and unskilled workers produce different
goods. Suppose that there are three goods. Throughout, skilled
workers produce Good A (professional services, most obviously), and
less skilled workers produce Good C (including basic retailing).
Initially, let us suppose that there is a large Good B sector, such
as manufacturing and some other services, produced by less skilled
workers. Then the new technology appears. It improves the ability
of skilled workers to produce the Good B output, previously the
domain of the less skilled workers.
What in general will happen to the equilibrium when this
skill-biased technological progress occurs? The average real wage
will rise, but the skilled workers will get more than 100 percent
of the benefit, implying that the real wage of less skilled workers
will fall. In contrast, if the new technology had allowed the
skilled workers to be more productive at their traditional
specialty (Good A), then the real wage of all workers would have
risen.
A model of this simple sort would go a long way in organizing
thought about some of the patterns reported in the literature on
changing wage structure. Skilled workers have been substituted for
less skilled workers in many Organisation for Economic Cooperation
and Development manufacturing industries, for example. In that
(Good B) industry there has been a rise in the ratio of
nonproduction to production workers, and overall growth in
manufacturing productivity has been strong. In contrast, high-skill
service-sector (Good A) productivity growth has been generally
slow. One need only think of higher education and legal services
(and possibly medicine) as cases in point. The terms of trade
within the domestic economy could be defined as the prices of goods
produced by skilled workers and others. The price of the Good B
sector has fallen because of biased technical change, and as
additional less-skilled workers become available to produce
more
OCR for page 159
Page 159
traditional Good C products such as retail services, they
experience deteriorating terms of (internal) trade. For some
countries with rather little trade, such as the United States, the
closed-economy aspect of such a framework is most empirically
relevant. For other countries, such as Japan, both trade and
external as well as internal technological effects will be
important to incorporate in an assessment of wage pressures.
Consider the price of tuition and the price of routine health
care assistance provided by home health care aides. Data from the
Bureau of Labor Statistics wage series show the latter to have been
falling below the level of inflation since 1973. On a more
optimistic note, if the new technology can be applied to improve
the productivity of skilled workers in their traditional domains,
both skilled and unskilled workers would be better off. The new
information technology is so far helping the nonmarket productivity
of skilled workers: use of the Internet will be providing a huge
array of services via the household sector. Data available to study
this aspect of technical change are close to nonexistent. The real
standard of living may come to depend more on the nonmarket sector.
We have developed a methodology for studying the value of nonmarket
output though the use of time-use diary data, based on a grant from
the National Science Foundation in the mid 1970s and early 1980s.
We are currently studying the access of children under the age of
12 to information technology with time-use diaries both in the home
and in schools. The data are being collected as a special
supplement to the Panel Study of Income Dynamics, funded by the
National Institute of Child Health and Human Development. Copies of
our instruments are available at
<http://www.umich.edu/˜psid/>.
OCR for page 160
Page 160
The Uncalming Effects Of Digital
Technology
Mark Weiser
Xerox Palo Alto Research Center
The important waves of technological change are those that
fundamentally alter the place of technology in our lives. What
matters is not technology itself, but its relationship to us.
In the past 50 years of computation there have been two great
trends in this relationship: the mainframe relationship and the PC
relationship. Today the Internet is carrying us through an era of
widespread distributed computing toward one of ubiquitous
computing, characterized by deeply imbedding computation throughout
the world. Ubiquitous computing will require a new approach to
fitting technology to our lives, an approach we call "calm
computing." Calm computing is not a natural result of increased use
of technology—in fact unbridled digital technology naturally
decreases calm.
Imagine the following experiment; or if you are brave, try it.
Find two empty cardboard toilet paper tubes, and tape them over
your eyes so that you are looking out through them. You now have no
view up, down, left, or right, only a narrow cone of view straight
in front. Now walk. What happens? You have lost the flow of
information from the periphery into the center, and have only the
center. Everything that you see is a surprise, because it just pops
in without warning. Your head must constantly swivel or you will
trip, run into things, miss people passing you, and generally
bumble.
If you wear toilet paper tubes for a few hours you will feel
exhausted and highly anxious. Your head will have been constantly
swiveling to try to partially compensate for the lack of peripheral
vision. You will feel overloaded with all the work you did to keep
up with your world. You will be emotionally drained by all the
surprises when things popped into view and when you had to
compensate for the unexpected.
Wearing toilet paper tubes is like living in the digital age,
where the feeling of exhaustion is called "information overload."
Digital technology, like toilet paper tubes, tends to deliver
information with a set of biases. These biases push us toward the
center of our awareness and tend to leave out the essential
periphery that helps us make sense of and anticipate the world
around us. More and more of the economy and business and life are
mediated through digital technology. If we lose the periphery, we
may be smarter about whatever is right in front
OCR for page 161
Page 161
of us, but stupid to the point of ignorance about what is nearby
but out of sight behind the toilet paper tube.
Proper action has always meant keeping the periphery and center
in balance. The center is the domain of conscious, symbolic thought
and action. The periphery is the domain of flow, of context, of
intuition, and of understanding. The center is the domain of
explicit knowledge of what to do, the periphery the domain of
knowing how to do it. Take away either of these and near paralysis
results.
There are 10 biases in today's digital technology that
contribute to unbalancing center and periphery. These are saying,
homogenizing, stripping, reframing, mono-sensing, deflowing,
defamiliarizing, "uglying," reifying, and destabilizing.
1. Saying names the tendency of digital technology to make
everything explicit.
2. Homogenizing is the delivery of digital information at an ASCII
monotone that puts all information into the same pigeonhole.
3. Stripping is the loss of social context and frame that
frequently comes with digital transmission.
4. Reframing results because there is always a social context and
frame, and after stripping, a confusing or illegitimate context may
result.
5. Mono-sensing is the emphasis on the eye over all other senses,
reducing our inputs, our style, and our intelligence.
6. Deflowing is the loss of the context that lets us enter the
"flow state" of greatest intelligence and creativity, and so
reduces our anticipation and history.
7. Defamiliarizing is the loss of familiar social practices as we
try to work and live on the net.
8. "Uglying" names, with an ugly word, the uncomfortable feeling
with which the low state of design in digital technology leaves
us.
9. Reifying results when implicit practices are cast in stone,
removing the white space that lets anything work, as when a company
puts all its processes online.
10. Destabilized is our emotional state after buffeting from all the
above.
The above add up to a bias toward the center, and away from the
periphery.
Understanding the power of balance between focus and periphery,
and caring about both, can be a tremendous source of advantage in
the digital age. Digital technology, through its homogeneous,
ubiquitous, and voluminous provision of information, can enable an
even richer periphery for action. The danger comes if we believe
that only focus is effective. Trying to focus on the increasing
volume of bits can overwhelm us, and we can badly misuse our full
intelligence by ignoring attunement, community, and peripheral
awareness. The opportunity for focus is greater than ever before,
but only if we recognize that there is no focus without periphery,
there is no center without a surround. If we can stay in balance,
we can expect a world of greater satisfaction and
effectiveness.
OCR for page 162
Representative terms from entire chapter:
digital technology
