Sources and References

Primary texts — C.P. Snow, The Two Cultures and the Scientific Revolution (1959); Jacques Ellul, The Technological Society (1964); Langdon Winner, Autonomous Technology (1977) and “Do Artifacts Have Politics?” (1980); Wiebe Bijker, Thomas Hughes, and Trevor Pinch (eds.), The Social Construction of Technological Systems (1987); Thomas Hughes, Networks of Power (1983); Bruno Latour, Reassembling the Social (2005); Michel Callon, “Some Elements of a Sociology of Translation” (1986); Thomas Kuhn, The Structure of Scientific Revolutions (1962); Harry Braverman, Labor and Monopoly Capital (1974); Batya Friedman, Peter Kahn, and Alan Borning, “Value Sensitive Design and Information Systems” (2006); Leo Marx, “Technology: The Emergence of a Hazardous Concept” (2010).

Supplementary texts — Merritt Roe Smith and Leo Marx (eds.), Does Technology Drive History? The Dilemma of Technological Determinism (MIT Press, 1994); Donald MacKenzie and Judy Wajcman (eds.), The Social Shaping of Technology (Open University Press, 1999); Andrew Feenberg, Questioning Technology (Routledge, 1999); David Nye, Technology Matters: Questions to Live With (MIT Press, 2006); Sheila Jasanoff (ed.), States of Knowledge: The Co-Production of Science and Social Order (Routledge, 2004); Martin Heidegger, “The Question Concerning Technology” (1954); Carl Mitcham, Thinking Through Technology (University of Chicago Press, 1994).

Online resources — MIT OpenCourseWare, STS.005 “Disease and Society in America”; Stanford Encyclopedia of Philosophy entries on philosophy of technology; IEEE Technology and Society Magazine archives.

Chapter 1: Foundations — Technology, Culture, and Prediction

1.1 The Two Cultures

Snow’s Thesis

In 1959, the British physicist and novelist C.P. Snow delivered a lecture at Cambridge titled The Two Cultures and the Scientific Revolution, which would become one of the most cited interventions in twentieth-century intellectual life. Snow argued that Western intellectual culture had fractured into two mutually incomprehensible camps: the literary intellectuals on one side and the natural scientists on the other. Between these two groups, Snow observed, lay a “gulf of mutual incomprehension — sometimes (particularly among the young) hostility and dislike, but most of all lack of understanding.”

Snow’s argument was grounded in his unusual biography. He had trained as a physical chemist at Cambridge while simultaneously pursuing a successful career as a novelist. He moved comfortably in both worlds and was struck by how little communication passed between them. Literary intellectuals, he noted, would casually dismiss scientists as culturally illiterate, while scientists would regard humanists as hopelessly ignorant of the basic workings of the natural world. Snow’s famous test case was the second law of thermodynamics: he claimed that asking a literary intellectual to explain this law was roughly equivalent to asking a scientist whether they had read Shakespeare — yet while the latter question would provoke embarrassment, the former would be met with indifference or even pride in one’s ignorance.

Relevance to Engineering Education

Snow’s thesis has particular resonance for engineering students. Engineering occupies an interesting position in the two-cultures divide: it is firmly rooted in scientific and mathematical knowledge, yet its practice is fundamentally concerned with human problems — designing artifacts, systems, and processes that serve social purposes. Engineers must grapple with questions of aesthetics, ethics, economics, and politics that are traditionally the province of the humanities and social sciences. A course in Science, Technology, and Society (STS) exists precisely at this intersection, inviting students trained in technical disciplines to think critically about the social dimensions of their future work.

Snow’s lecture also carried a political argument that is sometimes overlooked. He believed that the divide between the two cultures was hampering the West’s ability to address the central problem of the age: global inequality. Scientists and engineers, he argued, understood that industrialization and technological development could raise living standards worldwide. Literary intellectuals, by contrast, were more likely to view industrialization with suspicion, mourning the loss of traditional ways of life. Snow saw this as a dangerous form of nostalgia that consigned billions to poverty.

Criticisms and Legacy

Snow’s thesis attracted vigorous criticism. The literary critic F.R. Leavis published a scathing response in 1962, attacking Snow’s intellectual credentials and arguing that literature provided a depth of moral understanding that science could not replicate. More substantive criticisms noted that Snow’s binary was too simple: the intellectual landscape included many cultures, not just two. Social scientists, for instance, fit neatly into neither camp. Others pointed out that Snow romanticized science, treating it as a monolithic culture of progress while ignoring the ways scientific knowledge could be used for destruction.

Despite these criticisms, the two-cultures framework remains a useful starting point for thinking about the relationship between technical and humanistic knowledge. It reminds us that understanding technology requires more than technical competence — it demands attention to context, values, and human consequences.

1.2 What Is Technology?

The Problem of Definition

The word “technology” is so ubiquitous in modern usage that it may seem unnecessary to define it. Yet the concept is surprisingly slippery, and different definitions lead to very different conclusions about the relationship between technology and society. The historian Leo Marx has argued that “technology” as we understand it is a relatively recent concept, emerging in its modern sense only in the early twentieth century. Before that, people spoke of the useful arts, mechanical arts, or invention — terms that carried different connotations and embedded different assumptions about the relationship between human skill and material artifacts.

At its broadest, technology can be defined as the application of knowledge to practical purposes. But this definition is so expansive as to be nearly useless: it would encompass everything from cooking to constitutional law. More useful are the three philosophical perspectives that have shaped scholarly debate about the nature of technology.

The Instrumentalist View

The instrumentalist view treats technology as a collection of neutral tools. On this account, technologies are simply means to ends, and they carry no inherent values or political implications. A hammer can be used to build a house or to commit a murder; the technology itself is indifferent. This is the most common everyday understanding of technology, and it is often expressed in the slogan “guns don’t kill people, people kill people.”

The appeal of instrumentalism is its simplicity and its alignment with common sense. It also carries an optimistic implication: if technologies are neutral tools, then the problems associated with technology are really problems of human choice, and they can be solved through better education, regulation, or moral development without abandoning the technologies themselves.

However, instrumentalism has been widely criticized by scholars in STS. Critics argue that it ignores the ways technologies shape the choices available to their users. A highway system, for example, is not a neutral tool: it privileges automobile travel over public transit, encourages suburban sprawl, and restructures the spatial organization of cities in ways that are difficult to reverse. The mere existence of a technology changes the social landscape in which decisions are made.

The Substantivist View

The substantivist view, associated with thinkers like Jacques Ellul and Martin Heidegger, holds that technology is not neutral but carries its own values and logic. For Ellul, modern technology — which he called la technique — is an autonomous force that reshapes society according to the imperative of efficiency. Technique, in Ellul’s sense, is not limited to machines; it encompasses all standardized methods for achieving predetermined results, including bureaucratic organization, scientific management, and even psychological manipulation. The crucial point is that technique follows its own internal logic: once a more efficient method is discovered, it will inevitably be adopted, regardless of human preferences or values.

Heidegger’s critique operates at an even more fundamental level. In his 1954 essay “The Question Concerning Technology,” Heidegger argued that modern technology represents a distinctive way of revealing the world — what he called Enframing (Gestell). Under Enframing, the natural world is revealed as a “standing reserve” (Bestand) of resources to be optimized and exploited. A river, for example, ceases to be experienced as a natural phenomenon and becomes instead a potential source of hydroelectric power. This technological mode of revealing is not simply one perspective among many; it tends to become totalizing, crowding out other ways of experiencing and understanding the world.

The substantivist view carries troubling implications. If technology is not a neutral tool but an autonomous force with its own logic, then it may be impossible to direct technology toward humane ends without fundamentally transforming the technological system itself. This has led some substantivists toward a kind of technological pessimism or even neo-Luddism.

The Contextual View

The contextual view of technology seeks a middle ground between instrumentalism and substantivism. On this account, technologies are neither neutral tools nor autonomous forces but are shaped by and embedded in specific social, cultural, economic, and political contexts. The meaning and effects of a technology depend on how it is designed, deployed, and used within these contexts.

This view draws on the insight that technologies are human creations, designed by people with particular interests, assumptions, and values, and used by people in specific social settings. A technology that appears autonomous or deterministic may, on closer examination, turn out to reflect the interests of particular social groups. The contextual view thus opens the door to a more nuanced analysis of technology — one that attends to the specific circumstances in which technologies are developed and used, rather than making sweeping claims about Technology with a capital T.

The contextual approach is the dominant perspective in contemporary STS scholarship. It underlies theoretical frameworks such as the Social Construction of Technology (SCOT) and Actor-Network Theory (ANT), which we will examine in later chapters.

Technology as Practice

An increasingly influential perspective in STS treats technology not as a collection of artifacts but as a form of human activity or practice. On this view, technology is not the smartphone in your hand but the entire complex of knowledge, skills, organizations, and social relationships that produce, maintain, and give meaning to such devices. This perspective has several advantages. It reminds us that technologies do not exist in isolation but are embedded in networks of human activity. It highlights the role of human agency — the choices, skills, and values of the people who design, build, operate, and use technologies. And it directs attention to the often-invisible labor that sustains technological systems: the maintenance workers, repair technicians, and infrastructure operators without whom modern technology would quickly cease to function.

1.3 Predicting Technology

The Allure and Peril of Technological Prediction

Humans have always tried to anticipate the future, and technology has been a perennial focus of such predictions. From H.G. Wells’s science fiction to the exhibits at World’s Fairs, from corporate futurism to Silicon Valley hype cycles, predictions about coming technologies have shaped public expectations, investment decisions, and policy choices. Yet the track record of technological prediction is remarkably poor.

Famous Failures

The history of technological prediction is littered with spectacular failures. In 1876, a Western Union internal memo reportedly dismissed the telephone as having “too many shortcomings to be seriously considered as a means of communication.” In 1943, Thomas Watson, the president of IBM, allegedly declared that there was a world market for “maybe five computers.” In 1995, the astronomer Clifford Stoll published a Newsweek column arguing that the internet would never replace newspapers, that online databases would never substitute for daily papers, and that e-commerce was fundamentally impossible because no online store could replicate the experience of a knowledgeable salesperson.

These failures are not mere curiosities; they reveal systematic biases in how we think about technological change. Several patterns recur:

Linear extrapolation: Forecasters tend to project current trends into the future in a straight line, failing to anticipate disruptions, saturation effects, or paradigm shifts. The assumption that current growth rates will continue indefinitely leads to both excessive optimism (predictions of flying cars and moon colonies by 2000) and excessive pessimism (predictions that cities would be buried in horse manure before the automobile arrived).

Technological myopia: Experts tend to overestimate the importance of the technologies they know best and underestimate the potential of unfamiliar ones. Established industries are particularly prone to this bias, as incumbents have strong incentives to believe that existing technologies will continue to dominate.

Social blindness: Perhaps the most pervasive bias is the tendency to predict technological change while holding social arrangements constant. Predictions about “the home of the future” or “the office of the future” typically imagine new gadgets inserted into existing social structures, failing to anticipate the ways technology and society co-evolve. Early predictions about television, for example, imagined it as a tool for education and cultural enrichment — few foresaw its transformation into a commercial entertainment medium shaped by the economics of advertising.

Futurism and Its Limits

The twentieth century saw the emergence of futurism as a professional discipline, with organizations like the RAND Corporation developing formal methods for technological forecasting, including the Delphi method (structured expert consultation) and scenario planning (developing multiple plausible narratives about the future). These methods represented genuine improvements over casual prediction, but they remained limited by the fundamental unpredictability of technological innovation.

The philosopher Karl Popper offered a particularly incisive critique of prediction in human affairs. Popper argued that we cannot predict the future growth of knowledge — because if we could, we would already possess that knowledge. Since technological change depends on new knowledge, it follows that the course of technological development cannot be predicted by any scientific method.

This does not mean that all thinking about the future is useless. Scenario planning, in particular, can be valuable not as a predictive tool but as a way of expanding our imagination about possible futures and preparing for contingencies. The point is not to predict the future correctly but to be prepared for a range of possibilities and to recognize that our assumptions about technological trajectories are often wrong.

Lessons for STS

The failures of technological prediction carry important lessons for the study of technology and society. They remind us that technological development is not a predetermined process following a fixed trajectory, but a contingent and path-dependent process shaped by social, economic, political, and cultural factors. They warn us against technological determinism — the belief that technology follows its own inevitable logic — and invite us to consider the many branching paths that technological development might take.

1.4 Workshop: Analyzing Artifacts

The first workshop in STV 100 asks students to engage in hands-on analysis of technological artifacts. This exercise draws on a tradition in STS scholarship that treats artifacts as material embodiments of social relationships, cultural values, and political choices.

When analyzing a technological artifact, several dimensions deserve attention. First, consider the artifact’s material properties: what is it made of, how is it constructed, and what are its physical capabilities and limitations? Second, examine its design choices: what alternatives existed, and why were particular design decisions made? Third, investigate the artifact’s social context: who designed it, who manufactured it, who uses it, and how does it fit into broader social, economic, and political systems? Fourth, consider the artifact’s values: what assumptions about users, uses, and the good life are built into its design? Finally, reflect on the artifact’s unintended consequences: how has it been used in ways its designers did not anticipate, and what side effects has it produced?

This mode of analysis — treating artifacts not as given and inevitable but as the products of human choices embedded in social contexts — is a foundational skill in STS and a theme that runs throughout this course.

Chapter 2: Theories of Technological Change

2.1 Technological Determinism

Defining Technological Determinism

Technological determinism is the belief that technology is the primary driver of social change — that the invention and adoption of new technologies determines the structure of society, the nature of social relationships, and the course of history. In its strongest form, technological determinism holds that technological development follows an autonomous logic, proceeding along a fixed trajectory that human beings can neither direct nor resist. Society must adapt to technology, not the other way around.

Technological determinism is deeply embedded in popular culture and everyday discourse. Phrases like “the computer revolution,” “the industrial age,” or “the information society” all reflect a deterministic framing in which a technology defines an entire era. News coverage of technology consistently treats innovation as an unstoppable force to which individuals, organizations, and governments must adapt or perish.

Hard Determinism

Hard technological determinism makes two central claims. First, that technological development proceeds autonomously, following an internal logic that is independent of social, cultural, or political influences. Second, that technology determines social organization — that a given technology produces a specific set of social consequences that are inherent in the technology itself.

The most influential exponent of hard determinism was the French sociologist Jacques Ellul. In The Technological Society (1964), Ellul argued that technique — his term for the systematic, rational pursuit of efficiency in all domains of human life — had become an autonomous force beyond human control. Ellul’s technique is not limited to machines or even to industry; it encompasses scientific management, bureaucratic rationality, psychological manipulation, and every other domain where standardized methods are applied to achieve predetermined results. The key characteristics of Ellul’s technique include:

• Automatism: When multiple technical methods are available, the most efficient one is automatically selected without regard for moral, aesthetic, or political considerations.
• Self-augmentation: Technique grows according to its own internal logic, with each advance creating the conditions for further advances.
• Monism: Technique forms an indivisible whole; it cannot be separated into “good” and “bad” technologies because all technical systems are interconnected.
• Universalism: Technique spreads to all cultures and all domains of human life, homogenizing previously diverse societies.

Ellul’s vision is deeply pessimistic. If technique is truly autonomous, then human freedom is an illusion: we believe we are choosing our technologies, but in reality technology is choosing us.

Soft Determinism

Soft technological determinism represents a more moderate position. It acknowledges that technology is a powerful force shaping society but denies that it is the sole or even the primary determinant of social change. Soft determinists argue that technology constrains and enables social possibilities without fully determining outcomes. A given technology may make certain social arrangements more likely, but the specific form those arrangements take depends on social, cultural, and political factors.

The historian Robert Heilbroner articulated a soft determinist position in his 1967 essay “Do Machines Make History?” Heilbroner argued that the level of technology in a society does constrain its social organization — a society with windmills will have a different social structure than one with steam engines — but that the specific institutions, power relations, and cultural forms are not determined by technology alone.

Soft determinism is more tenable than hard determinism, but it still faces significant challenges. Critics point out that even the claim that technology constrains social possibilities often rests on an unexamined assumption that technologies have fixed, inherent properties. In practice, the same technology can be used in very different ways in different social contexts. The automobile, for example, has produced very different transportation systems in the United States, Europe, and Japan, suggesting that social choices — about urban planning, public investment, cultural values — play at least as large a role as the technology itself.

Autonomous Technology

The concept of autonomous technology, developed most fully by the political theorist Langdon Winner in his 1977 book of the same name, occupies a space between hard and soft determinism. Winner argues that modern technological systems have become so large, complex, and interconnected that they effectively operate beyond meaningful human control. This is not because technology has a will of its own, but because the systems we have built are so complex that no one fully understands them, and the institutional structures surrounding them make fundamental change extremely difficult.

Winner identifies several mechanisms through which technology becomes effectively autonomous:

• Technological drift: Large technological systems develop in unplanned and unintended directions as the cumulative result of many small decisions, none of which was intended to produce the overall outcome.
• Reverse adaptation: Instead of adapting technology to human purposes, humans adapt their purposes to the requirements of technology. Organizations restructure themselves to accommodate new systems; individuals reshape their lives around technological demands.
• Technological imperative: The perception that if something can be done technically, it must be done — that failing to adopt an available technology is irrational or irresponsible.

Winner’s concept of autonomous technology is more nuanced than Ellul’s. It does not claim that technology is literally autonomous but rather that the social, economic, and political structures surrounding technology make it behave as if it were. This is an important distinction because it implies that the problem is not inherent in technology itself but in the way we organize our relationship with technology — and therefore, in principle, the problem can be addressed through political action.

2.2 Alternative Understandings of Technology

Social Construction of Technology (SCOT)

The most influential alternative to technological determinism emerged in the 1980s with the development of the Social Construction of Technology (SCOT) framework by Trevor Pinch and Wiebe Bijker. SCOT inverts the deterministic relationship: instead of technology determining society, SCOT argues that society shapes technology. The central insight is that technologies are not the inevitable products of scientific progress but are shaped by the interests, values, and negotiations of various social groups.

SCOT introduces several key concepts:

Relevant social groups: These are the groups of people who share a particular interpretation of a technology. Different groups may understand the same artifact in very different ways. Bijker’s classic example is the early bicycle. In the 1880s, there was no single “bicycle” — there were many competing designs, including the penny-farthing (with its enormous front wheel) and the safety bicycle (with two equal-sized wheels and a chain drive). For young men who saw cycling as a sporting adventure, the penny-farthing’s speed and danger were features, not bugs. For women, elderly riders, and those who wanted practical transportation, the safety bicycle’s stability was the critical attribute. These different groups constituted different relevant social groups with different interpretations of what a bicycle should be.

Interpretive flexibility: This concept holds that technologies are open to multiple interpretations. There is no single, objectively correct understanding of what a technology is or what it is for. The meaning of a technology is not inherent in its physical properties but is constructed through the interpretations of relevant social groups. This is a radical claim: it implies that the “success” or “failure” of a technology is not determined by its technical merits but by social processes of negotiation and interpretation.

Closure and stabilization: Over time, the interpretive flexibility of a technology diminishes as social groups reach a consensus about its meaning and form. This process of closure can occur through several mechanisms. Rhetorical closure occurs when social groups are persuaded that a problem has been solved, even if it has not been solved in the way they originally wanted. Closure by redefinition occurs when the problem itself is redefined so that a given technology appears to solve it. Once closure is achieved, the technology becomes stabilized — its meaning and form are taken for granted, and the social negotiations that produced it become invisible.

Technological frame: Bijker later introduced the concept of the technological frame to describe the shared cognitive framework that guides a social group’s interaction with a technology. A technological frame includes theories, testing procedures, design methods, relevant problems and solutions, and exemplary artifacts. It structures both the way problems are defined and the range of solutions that are considered.

SCOT has been enormously influential in STS, but it has also attracted significant criticism. Some critics argue that SCOT focuses too narrowly on the design phase of technological development and neglects the ways technologies shape society once they are deployed. Others charge that SCOT’s emphasis on social groups overlooks the role of non-human actors — materials, physical laws, and the technologies themselves — in shaping technological development. Still others criticize SCOT for its relativism: if all interpretations of a technology are equally valid, how can we evaluate competing claims about technological risks or benefits?

Actor-Network Theory (ANT)

Actor-Network Theory (ANT), developed primarily by Bruno Latour, Michel Callon, and John Law, offers a more radical alternative to technological determinism. ANT rejects the fundamental distinction between the social and the technical, arguing that both human and non-human entities — or actants — participate in networks of relationships that produce what we experience as “society” and “technology.”

Callon’s classic study of scallop farming in St. Brieuc Bay illustrates ANT’s approach. In the early 1980s, three marine biologists attempted to develop a conservation strategy for scallops in the bay. Callon’s analysis treats the scallops, the fishermen, the scientists, and their scientific colleagues as actants in a network, analyzing the process of translation through which the scientists attempted to establish themselves as spokespersons for all the other actants. The process of translation involves four stages:

1. Problematization: The scientists define a problem and propose themselves as an obligatory passage point — an actor through whom all others must pass to achieve their goals.
2. Interessement: The scientists attempt to stabilize the identities and interests of other actants, drawing them into the network.
3. Enrollment: The actants accept the roles assigned to them, and the network begins to function.
4. Mobilization: The scientists speak on behalf of the entire network, representing the interests of scallops, fishermen, and colleagues.

The radical feature of Callon’s analysis is that scallops are treated as actants on equal footing with human beings. The scallops can “resist” the scientists’ plans by refusing to attach to the collectors designed for them; the fishermen can “betray” the network by violating the conservation agreement. ANT’s principle of generalized symmetry requires that the same analytical vocabulary be used to describe human and non-human actants, refusing to privilege human agency over non-human agency.

Latour extended ANT into a comprehensive social theory, arguing that what we call “society” is not a pre-existing structure but is constantly produced and reproduced through the associations between human and non-human actants. Technologies, on this view, are not tools used by society but are constitutive elements of the social world. The distinction between “the social” and “the technical” is itself an artifact of our analytical categories, not a feature of reality.

ANT has been extraordinarily influential, but it has also been controversial. Critics object to the symmetrical treatment of humans and non-humans, arguing that it obscures the distinctive qualities of human agency — intentionality, moral responsibility, and the capacity for reflection. Others charge that ANT’s emphasis on networks and translation neglects large-scale social structures such as class, gender, and race. Still others find ANT’s theoretical vocabulary obscure and its empirical analyses impossibly detailed.

Co-Production

The concept of co-production, developed by Sheila Jasanoff, offers yet another framework for understanding the relationship between technology and society. Co-production holds that the natural and social orders are produced together — that our knowledge of the world and our social arrangements are mutually constitutive. Scientific and technological developments do not simply reflect a pre-existing natural reality; they also create new social identities, institutions, and discourses. Conversely, social arrangements shape what counts as valid knowledge and what kinds of technologies are developed.

Jasanoff identifies four key instruments of co-production:

• Making identities: New technologies create new social identities (the “user,” the “patient,” the “driver”) with associated rights, responsibilities, and expectations.
• Making institutions: Technologies and the knowledge that accompanies them give rise to new institutions — regulatory agencies, professional associations, standards bodies — that in turn shape further technological development.
• Making discourses: Technologies generate new vocabularies, narratives, and frameworks for understanding the world.
• Making representations: Technologies produce new ways of representing the world — maps, models, databases, visualizations — that shape perception and action.

Co-production provides a valuable corrective to both technological determinism and social constructivism. It insists that neither technology nor society is the independent variable: they are produced together in an ongoing, dynamic process.

2.3 Momentum and Revolutions

Hughes’s Technological Momentum

The historian of technology Thomas P. Hughes developed the concept of technological momentum as a way of mediating between technological determinism and social constructivism. Hughes argued that large technological systems — such as electrical power grids, telephone networks, or transportation systems — pass through distinct phases of development, and the relationship between technology and society shifts at each phase.

In the early stages of a technological system’s development, social factors predominate. Inventors, entrepreneurs, and engineers make choices that are shaped by economic conditions, cultural values, institutional contexts, and political pressures. The technology is, in SCOT’s terms, interpretively flexible — its design and meaning are still open to negotiation. Hughes’s detailed study of the electrical power industry, Networks of Power (1983), shows how different inventors — Thomas Edison in the United States, Werner von Siemens in Germany — developed different technical systems reflecting different economic and institutional contexts.

As a technological system matures, however, it acquires momentum. Vast investments of capital, the development of specialized skills and organizations, the establishment of regulatory frameworks, and the physical infrastructure itself all create powerful incentives to continue along the existing trajectory. The system becomes increasingly resistant to fundamental change — not because the technology is autonomous, but because the social, economic, and institutional structures that have grown up around it make change difficult and costly.

Hughes’s concept is more subtle than simple determinism. He does not claim that mature technological systems are completely resistant to change, only that they possess a kind of inertia that makes dramatic shifts unlikely. Moreover, the momentum of a technological system can be disrupted by external events — wars, economic crises, radical new inventions — that destabilize the social structures supporting the existing system.

The concept of technological momentum helps explain several important phenomena. It explains why established technologies often persist long after technically superior alternatives are available — a phenomenon known as lock-in or path dependence. The QWERTY keyboard layout, for example, was designed in the 1870s to prevent jamming in mechanical typewriters — a problem that has not existed for decades — yet it persists because the infrastructure of training, muscle memory, and manufactured keyboards creates powerful momentum. More consequentially, fossil fuel energy systems persist not because they are technically superior to alternatives but because the enormous physical, economic, and institutional infrastructure built around them creates powerful resistance to change.

Kuhn’s Paradigm Shifts

Although Thomas Kuhn’s The Structure of Scientific Revolutions (1962) is primarily a work in the philosophy of science, its concepts have been widely applied to technological change. Kuhn argued that science does not progress through the steady accumulation of knowledge but through alternating periods of normal science and revolutionary science.

During periods of normal science, researchers work within a shared paradigm — a set of theories, methods, exemplary problem-solutions, and standards that define legitimate scientific practice. Normal science is essentially a puzzle-solving activity: researchers apply the paradigm to new problems, extending its reach and precision. Anomalies — observations that do not fit the paradigm — are typically explained away or set aside as problems for future research.

Over time, however, anomalies may accumulate to the point where they can no longer be ignored. The paradigm enters a period of crisis, during which confidence in the existing framework erodes and researchers begin to explore alternatives. Eventually, a new paradigm emerges that resolves the accumulated anomalies and opens new avenues of research. The transition from the old paradigm to the new is a paradigm shift or scientific revolution.

Kuhn’s framework has been applied to technological change by analogy. A dominant technology (or technological system) can be seen as constituting a paradigm that defines the problems worth solving, the methods worth using, and the standards of success. The concept of a technological paradigm was developed by the economist Giovanni Dosi, who argued that technologies develop along trajectories defined by the prevailing paradigm. Incremental improvements proceed along the trajectory until the paradigm reaches its limits, at which point a new technological paradigm may emerge.

The analogy between scientific and technological paradigms should not be pushed too far. Technological change involves economic competition, political regulation, and consumer choice in ways that scientific change does not. Nevertheless, the Kuhnian framework provides useful vocabulary for describing the dynamics of technological change: the periods of incremental improvement within an established framework, the accumulation of problems and limitations, and the occasional revolutionary transitions to fundamentally new approaches.

The relationship between Hughes’s momentum and Kuhn’s paradigm shifts is instructive. Technological momentum can be seen as the force that sustains a technological paradigm, maintaining the existing trajectory against incremental pressures for change. A paradigm shift, by contrast, represents a disruption so fundamental that even the momentum of the existing system cannot resist it. Understanding both concepts helps explain why technological change is sometimes gradual and sometimes sudden, and why established systems can persist for so long before being rapidly displaced.

Chapter 3: Technology in Society

3.1 Technology and Work

The Transformation of Labor

The relationship between technology and work is one of the oldest and most consequential themes in the study of technology and society. From the Luddite uprisings of the early nineteenth century to contemporary debates about artificial intelligence and automation, questions about how technology transforms work have been central to public discourse and political conflict.

The Industrial Revolution fundamentally reorganized the nature of work. The shift from artisanal production in workshops to mechanized production in factories involved not just new machines but new forms of social organization: the factory system, wage labor, standardized working hours, and the detailed division of labor. These changes were not simply imposed by technology; they were shaped by economic interests, class conflict, and political choices. Nevertheless, the new technologies — the spinning jenny, the power loom, the steam engine — made the new forms of organization possible and, in many cases, economically advantageous.

Scientific Management and Deskilling

In the early twentieth century, Frederick Winslow Taylor developed the principles of scientific management (also known as Taylorism), which sought to apply scientific methods to the organization of work. Taylor’s core idea was to separate the planning and execution of work: managers would use time-and-motion studies to determine the most efficient way of performing each task, and workers would execute these predetermined procedures as precisely as possible. The worker’s knowledge, judgment, and skill were to be replaced by the manager’s scientific analysis.

The sociologist Harry Braverman offered the most influential critique of this process in his 1974 book Labor and Monopoly Capital: The Degradation of Work in the Twentieth Century. Braverman argued that the history of capitalist production is characterized by a systematic process of deskilling — the progressive elimination of skill, knowledge, and autonomy from the work process. This process serves the interests of capital in two ways: it reduces the cost of labor (unskilled workers can be paid less than skilled ones) and it increases managerial control over the production process (workers who follow predetermined procedures are easier to supervise and replace).

Braverman identified three key mechanisms of deskilling:

1. Separation of conception and execution: The knowledge and planning that were once integral to skilled craft work are removed from the shop floor and concentrated in management.
2. Fragmentation of tasks: Complex jobs are broken down into simple, repetitive operations that can be performed by unskilled workers.
3. Use of machinery to replace human skill: Machines are designed not simply to increase productivity but to embody the knowledge previously held by skilled workers, thereby making those workers dispensable.

Braverman’s analysis was enormously influential but also widely criticized. Critics pointed out that deskilling is not the only tendency in the evolution of work: new technologies also create new skills and new forms of expertise. The computer revolution, for example, has eliminated many routine clerical and manufacturing jobs but has also created entirely new occupations — software engineers, data analysts, user experience designers — that did not previously exist. Moreover, Braverman’s focus on manufacturing neglected the growing service sector, where the dynamics of skill and autonomy are quite different.

Automation and the Future of Work

Contemporary debates about automation echo many of the themes Braverman identified, but in a new technological context. The development of robotics, artificial intelligence, and machine learning has raised the possibility that machines will be able to perform not just routine manual tasks but also cognitive tasks that were once thought to be uniquely human: driving vehicles, diagnosing diseases, writing legal documents, even composing music.

Economists disagree about the likely consequences. Technological optimists argue that automation will follow the pattern of previous technological revolutions: old jobs will be destroyed, but new and better ones will be created in their place. The task for policy is to manage the transition — through education, retraining, and social safety nets — rather than to resist the technology. Technological pessimists worry that this time is different: artificial intelligence may be capable of performing such a wide range of tasks that there will simply not be enough new jobs to replace the old ones. This could produce mass unemployment, extreme inequality, and social instability.

A more nuanced view, associated with scholars like David Autor, distinguishes between routine and non-routine tasks. Technologies tend to automate routine tasks — both physical (assembly line work) and cognitive (data entry, bookkeeping). Non-routine tasks — both physical (janitorial work, home care) and cognitive (management, creative work, complex problem-solving) — are more resistant to automation, at least with current technologies. The result is a polarization of the labor market: demand grows for high-skill, high-wage cognitive workers and for low-skill, low-wage service workers, while middle-skill, middle-wage jobs — the backbone of the industrial middle class — are hollowed out.

These debates remind us that the effects of technology on work are not determined by the technology alone. They depend on economic structures, labor market institutions, educational systems, government policies, and the balance of power between employers and workers. Technology creates possibilities; social and political choices determine which possibilities are realized.

3.2 Technology and Values

Values in Design

One of the most important insights of STS scholarship is that technologies are not value-neutral. The choices made during the design process — about materials, interfaces, features, default settings, and architectures — embed values in technological artifacts. These values may be intentional or unintentional, visible or invisible, but they shape the experience and behavior of users in ways that have moral and political significance.

Langdon Winner’s 1980 essay “Do Artifacts Have Politics?” is the foundational text in this area. Winner argues that technological artifacts can embody political values in two distinct ways:

Inherently political technologies: Some technologies are inherently political in the sense that they are strongly compatible with certain forms of political organization and incompatible with others. Winner’s most discussed example is nuclear power, which he argues requires centralized, hierarchical, and secretive forms of organization — the physical properties of nuclear materials (their lethality, the risk of proliferation) demand elaborate security measures that are inherently at odds with democratic openness and decentralization. Solar energy, by contrast, is more compatible with decentralized, democratic forms of organization. This does not mean that nuclear power makes authoritarianism inevitable, but it does mean that the choice between energy technologies is also a choice about political organization.

Technologies as forms of order: Winner also argues that specific design decisions can embody the intentions of their designers in ways that have lasting political consequences. His most famous (and most contested) example is the low overpasses on Long Island parkways, which he attributed to the urban planner Robert Moses. According to Winner, Moses deliberately designed the overpasses to be too low for buses to pass under, thereby preventing poor and minority New Yorkers (who relied on public transit) from reaching the public beaches of Long Island. Whether or not the historical details of the Moses case are accurate, the general principle is sound: design decisions can have distributional consequences, benefiting some groups while disadvantaging others.

Value Sensitive Design (VSD)

Value Sensitive Design (VSD), developed by Batya Friedman and her colleagues at the University of Washington, offers a systematic approach to integrating human values into the design process. VSD is based on the premise that good design is not just a matter of technical functionality and economic efficiency but must also account for the human values at stake.

VSD employs a tripartite methodology:

1. Conceptual investigations: Identifying the stakeholders affected by the technology, articulating the values at stake, and analyzing potential conflicts between values. Stakeholders include not only direct users but also indirect stakeholders — people who are affected by the technology without using it directly — and future generations.

2. Empirical investigations: Using social science methods (interviews, surveys, observations, experiments) to understand how stakeholders actually experience the technology and how it affects the values identified in the conceptual investigation. This step ensures that the design process is grounded in the actual experiences and perspectives of affected parties, rather than relying solely on the designer’s assumptions.

3. Technical investigations: Examining how the technical properties of the system support or hinder the values identified in the previous investigations, and exploring alternative designs that better support those values.

VSD has been applied to a wide range of technologies, including information systems, urban infrastructure, and medical devices. The values most commonly addressed in VSD research include:

VSD is not without its critics. Some argue that the framework does not provide clear guidance for resolving conflicts between values — when privacy and security pull in opposite directions, for example, VSD does not tell the designer which value should prevail. Others worry that VSD can become a box-checking exercise that gives the appearance of ethical design without fundamentally challenging existing power structures. Nevertheless, VSD represents an important step toward making the values embedded in technology explicit and subject to democratic deliberation.

Ethics of Technology

The broader field of the ethics of technology examines the moral dimensions of technological development, deployment, and use. Several ethical frameworks are relevant:

Consequentialism evaluates technologies by their outcomes: a technology is good if it produces more benefit than harm, taking into account all affected parties. This approach underlies cost-benefit analysis and risk assessment, but it faces challenges in predicting outcomes, measuring incommensurable values (how do you weigh privacy against convenience?), and accounting for the distribution of benefits and harms.

Deontological ethics evaluates technologies by whether they respect fundamental moral principles — such as respect for autonomy, fairness, and human dignity — regardless of their consequences. This approach may condemn a technology that produces aggregate benefits if it violates the rights of particular individuals or groups.

Virtue ethics asks what kind of character traits technologies promote or undermine. Does social media cultivate or erode empathy, patience, and self-control? Does automation encourage or discourage diligence and craftsmanship?

Each framework captures important moral intuitions, and a comprehensive ethics of technology likely needs to draw on all three.

3.3 Sleepwalking into Technological Change

Winner’s Warning

The metaphor of sleepwalking into technological change captures a central concern of STS scholarship: the worry that societies adopt transformative technologies without adequate deliberation about their consequences. Langdon Winner has been the most eloquent voice articulating this concern. In his work, Winner argues that democratic societies have largely failed to subject technology to meaningful political deliberation. New technologies are introduced through market mechanisms and entrepreneurial initiative, with little public input into fundamental questions about whether and how they should be deployed.

Winner identifies several reasons for this democratic deficit:

Technological somnambulism: Most people most of the time do not think critically about the technologies they use. They accept technological change as natural and inevitable, adopting new technologies as they become available without reflecting on their broader implications. This is not a moral failing but a natural consequence of the pace and pervasiveness of technological change: there is simply too much of it for any individual to evaluate critically.

The politics of expertise: Decisions about technology are often framed as technical questions that should be left to experts — engineers, scientists, and corporate managers. This framing excludes ordinary citizens from decisions that profoundly affect their lives and concentrates power in the hands of those with technical knowledge.

Economic imperatives: In a market economy, the primary criterion for adopting a technology is whether it is profitable. Questions about social desirability, environmental sustainability, or democratic governance are treated as secondary considerations to be addressed, if at all, through regulation after the fact.

Unintended Consequences

The concept of unintended consequences is closely related to the sleepwalking metaphor. Technologies routinely produce effects that their designers did not anticipate and that may be unwelcome. The sociologist Robert Merton identified unintended consequences as a pervasive feature of purposive social action, and technology provides some of the most dramatic examples.

The automobile, perhaps more than any other technology, illustrates the phenomenon of unintended consequences. When automobiles were first introduced, they were celebrated as a solution to the pollution, congestion, and public health hazards associated with horse-drawn transportation (yes, horse manure was a major public health concern in nineteenth-century cities). Few anticipated that the automobile would produce its own forms of pollution, congestion, and public health hazards — or that it would fundamentally restructure the spatial organization of cities, contribute to suburban sprawl, erode public transit systems, and become the leading cause of accidental death for young people.

More recently, social media platforms were introduced with optimistic rhetoric about connecting people, democratizing information, and empowering individuals. The unintended consequences — the spread of misinformation, the amplification of political polarization, the erosion of privacy, the rise of cyberbullying, and the effects on mental health — were largely unforeseen by the platforms’ designers and are still not fully understood.

Unintended consequences arise for several reasons. The complexity of social systems means that interventions in one domain invariably produce effects in others. The feedback loops between technology and society mean that the introduction of a new technology changes the social context in which it operates, often in unpredictable ways. And the long time horizons over which consequences unfold mean that effects may not become visible until long after the critical design decisions have been made.

Toward Democratic Governance of Technology

Winner and other STS scholars argue that addressing the problem of sleepwalking requires fundamentally rethinking the governance of technology. Several proposals have been advanced:

Technology assessment: Systematic evaluation of the likely social, economic, environmental, and ethical consequences of new technologies before they are widely deployed. The U.S. Congress established an Office of Technology Assessment (OTA) in 1972 to provide such evaluations, but it was defunded in 1995. Several European countries maintain more robust technology assessment institutions.

Participatory design: Involving affected communities in the design process, so that the values and concerns of diverse stakeholders are reflected in technological artifacts. This approach draws on the Scandinavian tradition of workplace democracy and has been influential in information systems design.

The precautionary principle: When a technology poses potential threats to human health or the environment, precautionary measures should be taken even if the causal relationships are not fully established scientifically. This principle, widely invoked in European environmental regulation, reverses the default assumption that technologies are innocent until proven guilty.

Responsible innovation: A framework that integrates anticipation, reflection, inclusion, and responsiveness into the innovation process. Responsible innovation asks not just “can we do this?” but “should we do this?” and “who should decide?”

3.4 Progress and Its Discontents

The Myth of Progress

The idea that technological innovation represents progress — that new technologies are inherently better than old ones, and that the trajectory of technological development leads to an ever-improving world — is one of the most powerful and pervasive assumptions in modern culture. It is so deeply embedded in our thinking that it often goes unexamined, functioning as what the historian Leo Marx calls a “hazardous concept.”

The modern idea of progress has deep roots. The Enlightenment philosophers of the eighteenth century articulated a vision of history as the progressive triumph of reason over superstition, and they saw scientific and technological advance as both evidence and engine of this progress. The Industrial Revolution seemed to confirm this vision: the material conditions of life in industrialized societies improved dramatically over the course of the nineteenth and twentieth centuries, as measured by life expectancy, literacy, per capita income, and access to consumer goods.

Yet the equation of technological change with progress conceals important complexities:

Progress for whom? The benefits of technological change have never been equally distributed. The Industrial Revolution produced enormous wealth, but it also produced urban poverty, child labor, and environmental degradation. The Green Revolution increased agricultural productivity but also displaced small farmers and increased dependence on chemical inputs. Digital technologies have created new forms of wealth and convenience but have also exacerbated economic inequality and created new forms of surveillance and control. Any assessment of “progress” must ask who benefits and who bears the costs.

Progress at what cost? Technological advances often involve trade-offs that are not captured by simple measures of material improvement. The automobile increased mobility but decreased air quality and community cohesion. Social media expanded communication but may have diminished the quality of public discourse. Nuclear energy provides abundant power but creates waste that remains dangerous for millennia. A full accounting of progress must consider not just what is gained but what is lost.

Progress toward what? The concept of progress implies a destination — a better world toward which we are moving. But there is no consensus about what constitutes a better world. For some, progress means material abundance and individual freedom. For others, it means social equality and community solidarity. For still others, it means ecological sustainability and harmony with nature. These visions are not necessarily compatible, and the technologies that advance one may undermine another.

Techno-Utopianism

Techno-utopianism represents the most optimistic version of the progress narrative. Techno-utopians believe that technology can solve virtually all human problems — poverty, disease, environmental degradation, even death itself. In the early twentieth century, techno-utopianism was expressed in visions of electrified cities, automated factories, and leisure societies. In the late twentieth and early twenty-first centuries, it has been associated with digital technology, particularly the internet, which has been credited with the potential to democratize knowledge, empower individuals, and create a global community.

Silicon Valley has been the epicenter of contemporary techno-utopianism. The ideology of “disruption” — the idea that new technologies should upend established industries and institutions — reflects a faith that technological innovation is inherently beneficial and that resistance to it is retrograde. This ideology has produced genuine innovations, but it has also produced companies and products that prioritize growth and profit over the welfare of users and communities.

Techno-Skepticism and Techno-Pessimism

At the opposite end of the spectrum, techno-skeptics and techno-pessimists question the assumption that technological change is inherently beneficial. Techno-skeptics do not reject technology outright but insist on critical evaluation of its costs and benefits, and they are suspicious of claims that this time, unlike all previous times, a new technology will deliver on its utopian promises without significant downsides.

Techno-pessimists go further, arguing that modern technology is, on balance, harmful to human flourishing. This position has a long intellectual history, from Jean-Jacques Rousseau’s eighteenth-century critique of civilization to the twentieth-century Frankfurt School’s analysis of the “culture industry.” Contemporary techno-pessimists point to environmental destruction, the erosion of privacy, the degradation of work, the atomization of communities, and the existential risks posed by nuclear weapons, climate change, and artificial intelligence.

Neither pure utopianism nor pure pessimism provides an adequate framework for thinking about technology and society. The utopian vision ignores the real harms that technologies produce and the unequal distribution of their benefits. The pessimistic vision ignores the genuine improvements in human welfare that technology has made possible and the human agency that shapes technological development.

A More Nuanced View

STS scholarship offers a more nuanced alternative to both utopianism and pessimism. By treating technology as a social phenomenon — shaped by human choices, embedded in social contexts, and open to political deliberation — STS provides tools for critical evaluation of specific technologies without making sweeping judgments about Technology as such.

Several principles emerge from the STS perspective:

1. There is no such thing as Technology in the abstract — there are only specific technologies, developed in specific contexts, with specific consequences for specific people.

2. Technologies carry values, whether intended or not, and these values should be made explicit and subject to critical examination.

3. The effects of technology are not predetermined — they depend on social, economic, political, and cultural factors that are open to human choice and political action.

4. Democratic governance of technology is both possible and necessary — citizens should have a meaningful voice in decisions about which technologies are developed and how they are deployed.

5. Assessment of technology must be ongoing — the consequences of technological change unfold over time and across social contexts, and our evaluations must be revised as new evidence emerges.

These principles do not provide easy answers to the difficult questions raised by technological change. They do, however, provide a framework for asking better questions — and asking better questions is the first step toward making better choices about the technologies that shape our lives.

Chapter 4: Synthesis and Reflection

Connecting the Frameworks

The theoretical perspectives examined in this course — technological determinism, SCOT, ANT, co-production, technological momentum, and paradigm theory — are not mutually exclusive alternatives but complementary lenses that illuminate different aspects of the technology-society relationship.

Technological determinism reminds us that technology is a powerful force and that its effects cannot be reduced to human intentions. The material properties of technologies — their affordances and constraints — matter, and they shape the range of social possibilities. While hard determinism is untenable, the softer insight that technology is not infinitely malleable remains important.

SCOT reminds us that technologies are human creations, shaped by the interests and interpretations of social groups. The design of technology is not determined by technical logic alone but is the outcome of social negotiations. This perspective is particularly valuable during the design phase of technological development, when choices are still open and alternative paths are still possible.

ANT reminds us that the boundary between the social and the technical is not fixed but is constantly being produced and reproduced through the associations between human and non-human actants. This perspective is particularly valuable for analyzing the complex networks that sustain modern technological systems.

Co-production reminds us that technology and society are not independent variables but are mutually constitutive. Scientific knowledge, technological artifacts, and social orders are produced together, and changes in one domain reverberate through the others.

Technological momentum explains why technological systems, once established, tend to persist along their existing trajectories. The concept bridges determinism and constructivism by showing how the balance between social shaping and technological constraint shifts as systems mature.

Paradigm theory provides vocabulary for describing both the incremental development of technologies within an established framework and the revolutionary transitions that occasionally disrupt established trajectories.

Together, these frameworks equip us to analyze the relationship between technology and society with nuance and sophistication — avoiding both the naivety of uncritical enthusiasm and the paralysis of undifferentiated pessimism.

Reflection: Identifying Your Own Technological Values

A central learning outcome of STV 100 is the ability to assess and reflect on your own technological perspectives and values. As engineering students, you are being trained to create the technologies that will shape the future. The choices you make — about what to design, how to design it, and for whom — will carry values and consequences that extend far beyond the technical domain.

Consider the following questions:

• Do you tend toward instrumentalism (technology is a neutral tool) or substantivism (technology carries its own values)? How does your answer affect the way you think about your responsibilities as a designer?
• Which relevant social groups do you tend to identify with when thinking about a technology? Whose perspectives might you be overlooking?
• When you think about the future of technology, do you tend toward optimism or pessimism? What evidence supports your view, and what evidence challenges it?
• How do you think decisions about new technologies should be made? By engineers? By markets? By democratic processes? By some combination?
• What values do you most want to see reflected in the technologies you will help create?

These are not questions with definitive answers, but engaging with them seriously is essential preparation for a career in which your technical choices will inevitably have social consequences. The goal of STV 100 is not to provide answers but to ensure that you are equipped to ask the right questions — and to recognize that these questions are not peripheral to engineering but are at its very heart.