Here's an article I found very interesting... I thought I'd share.
YMMV
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--J. Lambert
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Copyright 1994 by New Prospect, Inc. Readers may redistribute this article
to other individuals for noncommercial use, provided that the text and this
notice remain intact. This article may not be resold, reprinted, or
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The American Prospect, P.O. Box 383080, Cambridge, MA 02238, or by phone at
(617) 547- 2950.
Preferred Citation: Paul Starr, "Seductions of Sim: Policy as a Simulation
Game," The American Prospect no. 17 (Spring 1994): 19-29
(
http://epn.org/prospect/17/17star.html).
Seductions of Sim
Policy as a Simulation Game
Paul Starr
Standing around the computer, my two older daughters, nine and eleven years
old, scan the picture of the city we're creating and debate whether it needs
more commercial or residential development. My six-year-old son suggests we
look at the city budget. In just a few weeks he has learned enough to ask
the critical question: "What's the cash flow?"
This is SimCity, one of a series of computer simulations that turn public
policy and ideas into popular entertainment. With the advent of dramatically
improved graphics and powerful, low-cost multimedia computers, a new
generation of "edutainment" software has finally begun to fulfill the
long-touted promise of computers in education. Most of the new programs use
interactive multimedia to make games out of traditional subjects such as
arithmetic or geography. In MathBlasters, for example, children solve math
problems in order to fuel up a rocket and find a villain in outer space.
However, the Sim series, produced by California-based Maxis, goes a step
further: it makes games out of simulations of complex natural and social
systems, based on advanced and sometimes controversial areas of science and
decision making, such as climatology and environmental science, genetics,
and sociobiology. Those who think designing cities is prosaic can move on to
simulating the development of planetary ecosystems (SimEarth) or the
evolution of new life forms (SimLife). Other programs make games out of the
management of railroads (A-Train), and farms (SimFarm), and even national
health policy (SimHealth). These are unlikely ever to challenge Nintendo's
SuperMario World in sales. Still, it isn't only policy wonks who are buying
the games for themselves and their kids. SimCity has sold two million copies
since its release in 1989 and has probably introduced more people to urban
planning than any book ever has.
When my family first began playing SimCity and others like it not long ago,
my initial reaction was a mixture of excitement and skepticism. The new
simulations are certainly a lot more fun than most textbooks. Rather than
present information, they provide tools for inventing worlds, exploring
hypotheses, and stretching imaginations. Several have a public viewpoint. In
SimCity--unlike Monopoly--the player builds a community. One of the
"scenarios" in the latest version of SimCity puts the player in Flint,
Michigan in 1974 with the task of rebuilding the local job base and
community. In SimEarth and SimLife, the object is to create sustainable
environments and avoid extinctions.
But I worried whether the games might not be too seductive. What assumptions
were buried in the underlying models? What was their "hidden curriculum"?
Did a conservative or a liberal determine the response to changes in tax
rates in SimCity? While playing SimCity with my eleven-year-old daughter, I
railed against what I thought was a built-in bias of the program against
mixed-use development. "It's just the way the game works," she said a bit
impatiently.
My daughter's words seemed oddly familiar. A few months earlier someone had
said virtually the same thing to me, but where? It suddenly flashed back:
the earlier conversation had taken place while I was working at the White
House on the development of the Clinton health plan. We were discussing the
simulation model likely to be used by the Congressional Budget Office (CBO)
to "score" proposals for health care reform. When I criticized one
assumption, a colleague said to me, "Don't waste your breath," warning that
it was hopeless to get CBO to change. Policy would have to adjust.
There are, of course, important differences between computer simulation
games and the simulations used to assess policy options. The games are
designed to be entertaining; fidelity to empirical reality is not foremost.
But simplification is inherent in any simulation. Even "real" simulations
(if that is not an oxymoron) inevitably rely on imperfect models and
simplifying assumptions that the media, the public, and even policy makers
themselves generally don't understand. Both types of simulation are examples
of what might be called a crossover intellectual technology, one that has
only recently moved from academic and technical fields into popular and
public use. The crossover of simulation holds out the promise of an enriched
understanding of the world, particularly of complex systems. But there is a
danger too: forgetting that simulations depend on the models on which they
are built.
The danger is particularly worrisome when simulations are used to make
predictions and evaluate policies. And when policymakers depend on
simulations to guide present choices--especially when legislators put
government on "automatic pilot," binding policy to numerical indicators of
projected trends-- they cede power to those who define the models that
generate the forecasts. This is happening in America today, most notably
with the rise of the CBO as a power center in national policy. In a sense,
Washington is already Sim city.
Original Sim
Although it has taken three decades for them to come of age, simulation
games-- and SimCity in particular--are really children of the '60s. Indeed,
their development follows a classic pattern of our time. In their infancy,
simulations and related advances in computer technology were nurtured by
government grants for both military and domestic policy purposes. In their
maturity, they are being turned by private initiative and investment into a
phenomenon of popular culture.
To be sure, the genealogy of simulation can be traced back to a varied
history preceding the 1960s. At least since their use by the Prussian army
in the eighteenth century, simulations of combat have been a staple of
military training. War games were, so to speak, the cradle of simulation. By
the post-World War II era, engineers and corporate managers were using
simulations to design and run power grids, telecommunications networks,
factories, and businesses. Business simulations, which began primarily as
training exercises, evolved into a routine management tool. And as
researchers gained access to computers in the 1950s and '60s, simulations
came into wide use for scientific purposes to understand complex systems
such as climates, economies, ecosystems, and international relations.
As these examples suggest, simulations referred to at least two types of
activity. One kind of simulation created a role-playing game and engaged
participants in working out a scenario under prescribed conditions and
rules. The other kind projected the behavior of a complex system on the
basis of a quantitative model. The new computer simulations create games
based on models of complex systems and, in that sense, they combine the two.
The forerunners of these games were developed in the 1960s. "Social
simulation" took off during the '60s in several independent forms. At Johns
Hopkins, the sociologist James S. Coleman and his colleagues worked on
simulations as a means of both advancing social theory and improving
education, particularly for minority youth. Role-playing simulations and
games, they argued, would enliven the teaching of subjects as diverse as
mathematics and social studies. One of the games, called Ghetto, sought to
expose the logic of inner-city life. The hope was that as a tool of
research, simulations and games would enable the theorist to define and
grasp the underlying rules of social systems. (Economics, of all the social
sciences, has most used games this way.) As a tool of school reform,
simulations would provide a more accessible, participatory method of
education for children who did not respond well to traditional instruction.
John Dewey's educational ideals would finally be realized--or at least
simulated.
Advanced training programs and consensus-building for professionals and
decision makers also made increasing use of role-playing simulation games,
sometimes involving large groups working under a trained facilitator. Some
of the earliest games simulated urban conflicts over resource allocation. In
1964, one of the founders of the field, Richard Duke, designed a game called
Metropolis for the city council in Lansing, Michigan. The game used
role-playing to work through policy decisions and employed computers to
track the effects, as the group went through one cycle of decision making
after another. By the mid-1970s, a later version of the game, Metro-Apex,
gave computer simulation a central role.
During the 1950s and 1960s, a variety of planners and social scientists
concerned with urban problems had been developing large-scale computer
models of cities to simulate and predict their development under varying
policies. These models were first designed primarily for transportation and
land-use planning. The federal highway program provided a major impetus.
Modeling burgeoned in both academic and professional city-planning
departments and displaced older traditions that conceived of planning as
"architecture writ large."
Large-scale urban simulation models first caught the public eye through the
work of an outsider to the field. In 1969, Jay W. Forrester, an electrical
engineering professor at MIT with no background in urban research, published
Urban Dynamics, a book purporting to disprove common intuitions about urban
policy. Forrester's next work, World Dynamics, proposed a model for the
entire planet. A group based at MIT and led by his protgs prepared the
1972 report The Limits to Growth sponsored by the Club of Rome, which
claimed to show that the world was reaching the end of its ecological
tether.
Because of their dramatic conclusions, Forrester and the Club of Rome report
captured the public imagination, but the reception accorded their work by
researchers and professionals was much cooler. Forrester's urban model was
not based on empirical evidence and had no spatial dimension. According to
Britton Harris, a leading exponent of modeling and emeritus professor of
planning, transportation, and public policy at the University of
Pennsylvania, Forrester's model had little influence on urban planning. The
Club of Rome report did incorporate data and had real influence, though it
too had no spatial dimension. From the vantage of the Club of Rome, the
world consisted only of aggregates and averages. While undoubtedly
contributing to public awareness of global environmental problems (and
better subsequent research), the report itself has not withstood the passage
of time. For example, nearly all the resources that it predicted would be in
short supply at escalating prices in the 1990s now have larger known
reserves and are available at lower prices than they were in 1972.
Professional disillusionment with large-scale models was already setting in
at the time of the Club of Rome report. In 1973, a leading journal in urban
planning published a "requiem" for large-scale models. The emerging
consensus was that the models had overreached; both the theory underlying
the models and the available data were inadequate to make the kind of
predictions the modelers were attempting. The modelers' "loss of faith," as
one of the leading urban modelers, William Alonso, calls it, became part of
a broader collapse of confidence in planning in the 1970s and 1980s. In the
same era, efforts to apply simulation and games to the education of minority
youth were also proving a disappointment. Critics questioned whether the
educational payoff was worth the effort.
But while social simulation flagged, work on simulation models and games did
not actually disappear. Rather, it retreated into more specialized circles.
Role-playing simulations have become a standard technique for professional
training and conflict resolution. During the next two decades, the
development of computers, software, and data resources transformed both the
scientific and popular potential of computer simulation. By the late 1980s,
there was talk of a "renaissance" of large-scale models in urban planning,
even though many in the field are still as wary as ever about the models'
predictive powers.
The spread of desktop computers and advance of visualization techniques have
been particularly important for the revival and popular crossover of
simulation. Early computer simulations and games required access to
mainframe computers and skills that were, to most people, esoteric. Improved
graphics made simulations and games not only more accessible and absorbing,
but also more "playable."
Much of the research behind advances in computer graphics was originally
sponsored by the Department of Defense and space programs and grew out of
work on flight simulation, which in the 1960s and '70s was centered at the
University of Utah. The defense and space programs had a similar catalytic
role in the development of the Internet. Virtual reality has followed the
same route.
Improved graphics hit the home market with the growth of video games and the
advent of the Macintosh. Even flight simulation has crossed over to become
home entertainment.
It was while working on a video game for bombing islands that Will Wright, a
Macintosh programmer, came up with the idea for SimCity. Wright told me
recently that while designing a "terrain editor" to create the landscape, he
discovered that he had "more fun building the islands than bombing them."
Wright had never studied urban planning--his background was in robotics and
computer games--but on his own he found his way to the planning literature,
including Forrester and Jane Jacobs. The subject became interesting to him
only after he began simulating urban development. (Many people who have
since played SimCity have probably had the same experience.) Drawing on
research begun decades earlier, Wright fashioned the models of land use,
traffic, power systems, and other aspects of urban development that underlie
SimCity. He says he conceived of SimCity not as a game but rather as a "toy"
because at least in its standard use there is no preset goal or contest. The
player decides what kind of city to build--whether to emphasize its size,
wealth, beauty, or harmony with the environment. In 1987, unable to find a
software publisher who thought there was a market for such a toy, Wright
joined with a businessman, Jeff Braun, to start Maxis and develop SimCity.
The company now has more than 20 titles on the market and has spun off a
separate firm to create business and public policy applications.
Inside SimCity
The seductive power of computer simulation games lies partly in their
extraordinary variety and intricacy. Generating complex variation is one
thing that computers do especially well. But interest in such games was
limited as long as the "user interface" was text. Adding stereo sound and
three-dimensional graphics enables people to handle greater complexity at a
faster pace. This is what makes multimedia simulation such a powerful
communication medium. SimCity shows why.
Like several other programs in the Sim series, SimCity offers a choice
between two types of play: building a system from scratch or solving the
problems in a specific scenario. (All references here are to SimCity 2000,
the more elaborate, three-dimensional version of the game released in 1993.)
The player who builds a city de novo receives a starting fund and a randomly
generated, five-square-mile terrain whose features can be chosen and
modified at no cost prior to the start of play. For example, the player can
decide whether to locate the city on a coast or river and how much area will
be covered by water, hills, and forests. The terrain will be different every
time. Once play begins, the development of the city is open-ended, with no
fixed objectives or time limits, except as the player defines them. In
contrast, in the second type of play, the player loads a scenario with a
given map and limited time to accomplish a specific task, such as
revitalizing Flint, rebuilding Charleston, South Carolina after a hurricane,
or turning "Dullsville, U.S.A.," into an exciting community.
As mayor of SimCity, the player has extraordinary powers; there is no city
council, state government, or public employee union to worry about. (Weep,
Rudolph Giuliani, weep.) The mayor can set local tax rates and locate and
build various community facilities and services, such as power plants, water
systems, roads, highways, rails, airports, police and fire stations,
schools, and hospitals. The mayor can also control annual spending on city
services, adopt ordinances on matters ranging from pollution control to the
promotion of tourism, and zone areas for industrial, commercial, or
residential use.
SimCity operates on a "field of dreams" principle. If as mayor the player
creates the right environment, the Sims--the imaginary inhabitants of the
city--will come and build factories, shops, and homes. When they do,
buildings and factories pop up on the land and change as the city develops.
But if things turn sour--if unemployment rises or high crime rates in a
neighborhood drive people away--the icons on the screen change or go dark to
indicate population losses or building abandonment. All this takes place in
vaguely historical time (the player can set the starting data at 1900, 1950,
2000, or 2050), which primarily affects the available technology and rate of
energy consumption.
To help make decisions about zoning, taxes, expenditures, bond issues, and
other policies, the program provides a wealth of constantly changing data in
maps and graphs showing the city's population growth and density, demand for
residential, commercial, and industrial land, unemployment, power and water
supply, crime, traffic congestion, pollution, and various other aspects of
the city's development. The same sources report changes in interest rates
and the growth of the national economy and neighboring cities. Newspapers
periodically deliver reports of local sentiment, including the latest public
opinion polls and inane, jumbled stories about local and made-up
international events. A hallmark of the Sim games is a light touch. (My
favorite example: In SimAnt, which translates the sociobiology of ant
behavior into game form, one ant curses a group from another colony, "Your
queen mates with termites.")
The key to SimCity is the interaction of private land values with the public
budget. As the player constructs a city, the value of property zoned for
development is continually changing. These changing values are critical, for
they affect property tax receipts and determine--as my six-year-old quickly
discovered--whether the cash flow in the city budget is positive or negative
and therefore whether the player has to raise taxes, cut spending on city
services, and skimp on public investments.
Will Wright aptly refers to the basic conceptual framework of SimCity as a
"capitalistic land value ecology" and argues that it fits the development of
American cities in the twentieth century but would not account for the
development, for example, of St. Petersburg. In fact, SimCity is somewhat
more constraining; the game seems to require a particular type of American
city built on an industrial base.
The model in SimCity, as Wright describes it, consists of a series of
"concentric rings." At the core is a so-called "basic/nonbasic" or
"export/import" model, borrowed from the traditional urban development
literature, that describes the evolving relationship of the industrial,
commercial, and residential sectors. SimCity assumes that while 70 percent
of industrial production is exported outside of a city, 70 percent of
commercial production is consumed internally. Thus in the early stages of a
city's development, while its internal market is small, the industrial
sector must predominate. As the city and its internal market grow, commerce
begins to expand, ultimately overtaking industry as the main source of
employment. The demand for residential space depends on the growth of other
sectors. If jobs outnumber potential participants in the labor force, people
will move to the city and demand for residential development will increase.
If the local economy is doing badly and there are fewer jobs than workers,
unemployment will rise and people will leave the city.
According to Wright, SimCity uses a "bid rent" model to determine land
valuations. Property carries different values depending on its use; for
example, proximity to the urban center is valued most for commercial and
residential purposes and least for industry. The actual numbers used in
SimCity for land values, city investments, and other items bear no relation
to the real world. However, the overall valuation of SimCity and thus its
tax base will depend on how the player distributes and locates different
zones and allocates resources among roads, schools, and other public
services.
Wright says SimCity is built "from the inside out." In the outer rings are
models for traffic, energy, water, and other systems, which react back upon
and modify the land-use model at the core. The hardest problem, according to
Wright, is not what to put in but what to leave out. He is disarming about
the game's limits. Inevitably, SimCity is a "caricature" of reality. The
models deliberately exaggerate effects to provide feedback to the player; in
real life, the effects of many decisions would be imperceptible. The purpose
of SimCity is not accuracy or prediction but communication. "Unless it's
entertaining, the educational value is irrelevant." Asked how he handles
controversial choices, like the effects of tax rates on development, Wright
dodges the question and says, "We go for game play"--whatever is most fun.
Still, when players make decisions in SimCity, the game generates effects on
employment, crime, population growth, tax revenues. I would be more worried
about too easy an acceptance of the validity of those effects if SimCity
worked with real data. Games of that kind may well be on the market not long
from now, enabling players to download real maps and data into a game with a
visual interface like SimCity. But, as now designed, SimCity is clearly a
fictional world and the effects seem only as real as points scored in a
video game. This is even true of the Flint scenario because of the patently
fictional quality of all the numbers used in the game.
SimCity's players learn not from any particular aspect of the model but from
the process of being forced to make choices and face the consequences. Most
immediately, they confront choices of spatial design in distributing land
among potential uses and locating community resources like schools and
NIMBY's like power plants. These choices have a temporal as well as spatial
dimension. Players who overinvest too early in costly capital projects like
an airport or stadium will quickly find themselves in fiscal trouble.
The important payoff comes from struggling to master complexity. Wright
observes, "Playing the game is the process of discovering how the model
works." Of course, few players will be able to give any formal expression to
the model. But much of it is implicit in the manual that comes with the
game, and many players will be able to figure out critical relationships
from the signals that the game provides. To keep up with a city's changing
size and demands, the game requires constant monitoring of the city's power,
water, transportation, budget, and other systems.
If there is a "hidden curriculum" in SimCity and other Sim games, it lies
here. Shoshana Zuboff's 1988 book In the Age of the Smart Machine describes
the confusion and alienation of workers in factories and offices as
computers were first introduced over the previous decade. Physical contact
with the production process had been an important source of practical
knowledge; for example, workers at pulp mills that Zuboff studied had been
able to tell whether anything was wrong merely from the color and odor of
the pulp. Now the workers were asked to make decisions based on information
flashing on a computer screen. This shift deemphasized sensory knowledge and
put a premium on more abstract, "intellective" capacities. This is exactly
what SimCity teaches: the management of complex systems based on
"intelligent scanning" of streams of constantly changing information.
As SimCity has evolved, it has incorporated increasing levels of complexity.
For example, in the original SimCity, the fiscal options were limited. There
was one tax rate that players could raise or lower, no possibility of
floating bonds, and just three types of operating
expenditure--transportation, police, and fire protection. In SimCity 2000,
the player can vary property tax rates by class (residential, commercial,
industrial); offer tax incentives to specific industries; impose a sales or
income tax; borrow funds; refinance bonds; budget a wider variety of
programs now including education, health, and welfare; and vary expenditures
within each budget category (for example, primary and secondary schools
versus higher education) and even by neighborhood.
This degree of complexity may seem astonishing in a game for children. But
when children play SuperMario World and other popular adventure games, they
must learn the most intricate facts about the many imaginary places they
navigate. These worlds are typically filled with strange creatures, hidden
passageways, and special treasures. Going from one level of the game to the
next demands an extraordinary mastery of detail. Compared with these
demands, managing SimCity is surprisingly straightforward.
SimCity makes complexity manageable partly by enabling players to ignore
much of it when they are first learning the game. For example, players can
turn on "auto-budget" and let the program follow its default options until
they are ready to take up fiscal alternatives. When they do, they will find
that SimCity allows the mayor to get advice from various city council
members--or are they consultants?--who appear at the click of a mouse. Their
recommendations may not, however, always be consistent. As I was playing,
one adviser urged me to raise taxes to cut the city's deficit, while another
said I should cut taxes to stimulate growth. This difference seemed to me a
truly real-world touch.
Wright says that the next stage in SimCity's development may enable the
player to dive into a city to run a business inside it. He also wants to
give players the ability to modify the model's assumptions. "We want the
user to be able to define more and more of the model." Ultimately, he says,
the game could allow players to build the models themselves. Whether many
people would use this opportunity is unclear. But the option would permit
mastery of a simulation in the more fundamental sense of being able to
manipulate the assumptions and relationships behind it. In its current
version, the model is an unreachable black box. A new Sim game, SimHealth,
does allow players to modify assumptions and define the governing values.
But in practice, SimHealth shows some of the limitations of the genre.
A Simulation Muddle
The premise of SimHealth is that you have been elected to Congress in 1992
and seek to get reelected by choosing policies for health care. The game and
the voters then rate your performance not against an independent standard
but rather against your own--the values you have selected at the outset.
This is an attractive concept. However, the framework for "clarifying"
values adopted by SimHealth is based on hackneyed and misleading premises.
SimHealth asks players to define their values in terms of two
dualities--liberty and equality, and community and efficiency--on the
premise that more of one value in a pair necessarily means less of the
other.
But is this the case? Historically, many societies that have denied basic
liberties have also had extreme inequalities. When we talk about rights, we
generally mean equal rights; thus the two concepts overlap, often
reinforcing one another. For example, does the right to assemble peaceably
for redress of grievances express the value of liberty or equality? What
about equal educational opportunity? Compared to the U.S. system today, is
Canadian-style national health insurance an expression of equality (since
everyone is covered) or of liberty (since all are guaranteed individual
choice of physician and no one suffers from job lock)?
To assume a zero-sum relation between liberty and equality, and community
and efficiency, obscures a central challenge of policy--how to achieve
progress on more than one value at a time. For example, few would disagree
that by eliminating administrative sources of inefficiency, we are better
able to carry out aims benefiting the community as a whole. But in
SimHealth, efficiency and community are counterposed. Perhaps even more
fundamental, SimHealth's framework fails to appreciate that the main
political differences in health policy, as in other areas of American
politics, concern conflicting interpretations of widely shared values. Those
who take different positions do not necessarily differ in the value they
place, for example, on liberty; they often disagree about what liberty means
in relation to health care (freedom to change jobs without fear of losing
coverage, freedom to pick a health plan, freedom to pick a doctor, freedom
to consult alternative healers, and so on).
SimHealth's philosophical muddle is inadvertently apparent from the
arbitrary connections it asserts between values and particular statements
that are supposed to embody them. The value of community supposedly calls
for "restructur[ing] health insurance to provide the highest quality care."
But it is obscure to me why "community" should mean an emphasis on quality
of care rather than, say, careful stewardship of resources, priority for
public health measures, or universal coverage.
SimHealth does no better a job of explaining health care policies and
proposals. Indeed, the game is littered with crude simplifications and
outright errors of fact. It mixes up the concepts of managed care and
managed competition, confuses an individual's share of premiums with the
coinsurance rate (the individuals' share of payments for covered services),
and misstates the basic arrangements proposed in the Clinton and other
proposed health plans in Congress. The effects of particular policies on
public opinion seemed entirely arbitrary and capricious. I did not detect
any particular political bias. But SimHealth contains so much misinformation
that no one could possibly understand competing proposals and policies, much
less evaluate them, on the basis of the program. And although SimHealth
enables users to modify some assumptions, the model is never clearly
explained and the basic architecture is beyond reach.
The oversimplified values framework and misinformation in SimHealth could be
fixed, but the bigger problem is false pretensions. Unlike the plainly
fictional SimCity, SimHealth claims to simulate the effects of different
real-world proposals, which it cannot do. I suspect that if SimCity
purported to help evaluate policies toward the homeless, it would seem
equally inadequate.
SimHealth is a case of overshoot. The Sim games generally achieve their
impact by engaging players in concrete tasks. SimHealth, however, seeks to
engage players in formulating policy, which is entirely different. A child
can start playing SimCity without any conceptual understanding of urban
development. But to choose among various policy options in SimHealth, the
player needs to understand their relation to one another. The conceptual
threshold is too high, and it is not clear that a game can overcome it. On
the other hand, for those who are familiar with the elements of health
policy, playing SimHealth quickly becomes repetitive; it lacks the complex
variation and intricacy of SimCity and other Sim games. Once the novelty of
making health policy into a game has worn off, I doubt SimHealth will hold
much interest. It certainly has no value in assessing health care reform.
Simulation in Reality
The critical problem raised by simulation is the black-box nature of the
models. In the "real world" of policy simulation, the models are subject to
criticism and debate, at least among professionals. Opposing sides in policy
disputes often come armed with their own simulations, ready to fight numbers
with numbers. However outrageously biased some of these may be, there is
nothing remarkable or offensive about the practice--it is simply one aspect
of today's pursuit of politics by other means.
The troubling questions, in my view, concern the use of simulation as an
element of statecraft. In principle, models used for official purposes are
more open to scrutiny than are those in the private sector, and that is
enormously important. Within and across the branches of the federal
government, the validity of the models and assumptions is subject to intense
scrutiny, and a strong sense of professionalism limits political
manipulation. However, to most participants in policy debates as well as the
public at large, the models are opaque. Only a few can penetrate the black
box and understand what is inside. This has two opposite effects. At a
conscious level, many people are distrustful of official projections, like
much else about government. In practice, however, the numbers take on
immense importance. As a result, those who have technical authority over the
black boxes acquire an extraordinary degree of influence in the political
process. And technical authority matters because the outcome of simulations
often depends on what is assumed in the first place.
There is no obvious remedy to the black-box problem, and it affects
conservatives as much as liberals. Conservatives who are wary of planning
still depend on large-scale models for budgetary projections. Indeed, the
most recent version of the balanced- budget amendment would require Congress
to balance not actual outlays and receipts but projections of future
streams. Since those projections would be produced through computer
simulations, the amendment would give unprecedented authority to whoever
served as official simulator--a role that sounds like the modern equivalent
of court magician, and perhaps is.
The official simulator today, CBO director Robert Reischauer, may now be as
powerful a figure as any member of Congress. The CBO has no veto over
legislation, but it has a power that is nearly as great--the power to
"score" legislation to determine compliance with budget rules and future
effects on the deficit. When someone in Washington today claims savings for
a proposed change in national policy, people ask not whether the savings are
real but rather, "Are they scoreable?" This aspect of national policy has
all the features of a game with arcane rules and assumptions. (One of the
staff economists at the Council of Economic Advisers joked last year that
after leaving he would write a kiss-and-tell book called How to Score in
Washington.)
From the formative stages of policymaking, the effects are substantial. For
the past several years, the CBO has cast a broad shadow over the debate
about health care reform. Among the cognoscenti, cost-containment proposals
have been classified in two ways--"scoreable" and "unscoreable"--depending
on whether the CBO was likely to smile or frown. The prospect that the CBO
would frown on a policy and deem it "unscoreable" has been a grave,
sometimes fatal strike against it.
When the CBO finally made its report on the Clinton health plan, it was
front-page news, and again the black-box problem was apparent. Now it was
time to hear the score, though few understood what went into it. The
president's critics heralded Reischauer for saying that premiums paid to
health alliances should be counted in federal receipts (albeit as an
"off-budget" item) and that the plan would raise the federal deficit by $70
billion in the years prior to 2004 before reducing it. It almost did not
matter that the CBO estimated a near-term increase in the federal deficit in
part because it projected larger savings to state and local government
(indeed, recapturing those savings for the Treasury would make the plan
virtually budget-neutral). Nor did conservatives who were praising
Reischauer seem to appreciate the implications of CBO's general view of cost
containment. While casting a skeptical eye on the market-oriented measures
generally favored by conservatives, CBO has endorsed the effectiveness of
regulatory measures that conservatives dislike. CBO accepted the Clinton
premium caps as 100 percent effective. It has favorably assessed the impact
of single-payer plans, particularly on administrative costs. This is by no
means to say that CBO's judgments will be decisive, only that they have come
to hold unprecedented influence.
CBO has emerged as a power center as the influence of Congress has grown
relative to the executive branch over the past two decades. But CBO has also
become a force in its own right, apart from the Congress, because of the
predominance and persistence of budgetary issues in national politics and
the search by the Congress to find ways to bind itself, like Ulysses to the
mast, to resist strong impulses within. The official simulator is now called
upon to provide not just clairvoyance but collective self-discipline. The
discipline will hold only if the simulations do--only if there is one
authoritative mechanism for defining the future in the present. The power of
CBO has become an institutional necessity.
In the wider world, there is no comparable imperative to find a single
mechanism for simulating alternative policies and theories. If there must be
black boxes, at least we should have many of them to discourage faith in any
one. Even better, we need to open up the boxes by making the models more
transparent.
Transparency ought to become both the objective of simulation designers and
a critical basis for judging their success. Richard Duke--the pioneer who
first introduced computers into urban simulation games in the 1960s--is now
deeply skeptical about models embedded in computers that oblige the user
simply to accept an outcome as valid. Currently a professor at the
University of Michigan and president of the International Simulation and
Gaming Association, Duke says, "If a simulation hides the model, it's of
little interest to me. If a simulation exposes the model, I'm much more
interested." His own work now emphasizes role-playing policy simulation
exercises that allow different players to engage each other, not just a
black-box model. Besides allowing participants to practice skills in
negotiation and group problem solving, the role-playing approach is much
less deterministic: it introduces an unpredictable element of human choice
into simulation games.
Computer simulation games with many simultaneous players linked through the
Internet may also introduce more unpredictability. Moreover, as computer
games become more elaborate and widely used, their sheer multiplication and
increasing plasticity may promote a healthy skepticism about their
predictive power. Playing with simulation is one way to see its limits as
well as its possibilities.
For better or worse, simulation is no mere fad. Indeed, to think of
simulation games as mere entertainment or even as teaching tools is to
underestimate them. They represent a major addition to the intellectual
repertoire that will increasingly shape how we communicate ideas and think
through problems. The advent of this new medium has escaped the attention of
cultural critics because it has come in the form of children's games. But
the computer simulation game is an art form; when combined with
three-dimensional graphics and sound, it is an extraordinarily powerful one.
We shall be working and thinking in SimCity for a long time.
The American Prospect / Send us a message at prospect@epn.org
© 1995 New Prospect, Inc.