Part I — Foundations of Technology Evaluation

Chapter 1. Understanding Emerging and New Technologies

1.1 Introduction

Technology is one of the principal mechanisms through which human societies transform their physical, economic, institutional and social environments. From agricultural tools and writing systems to industrial machinery, electricity, telecommunications, computers, biotechnology and artificial intelligence, technological development has repeatedly altered the possibilities available to individuals and organizations.

However, technology should not be understood simply as a collection of machines, software applications or scientific discoveries. Technology is also embedded in institutions, markets, organizational processes, human behaviour, infrastructure, cultural expectations and systems of governance. A technology therefore acquires meaning through the context in which it is developed and used.

This distinction is particularly important when considering emerging technologies.

An emerging technology may have enormous technical potential while still having uncertain economic value, unclear social consequences, limited regulatory structures and incomplete evidence concerning long-term effects. Consequently, technological novelty does not automatically establish technological desirability.

The central concern of this chapter is therefore not simply to define emerging technology but to establish why the identification and classification of technologies are important prerequisites for systematic evaluation.

Technology assessment has historically sought to provide decision-makers with information concerning the possible consequences of technological development. Contemporary technology assessment increasingly has to operate under conditions of rapid technological change and uncertainty, while considering societal, economic, environmental and other consequences (Robinson et al., 2023).

The chapter develops six foundational ideas:

technology is a sociotechnical phenomenon;

emerging technology differs from merely new technology;

technological maturity must be distinguished from technological value;

technologies evolve through interconnected ecosystems;

technological convergence increases evaluation complexity; and

responsible technology evaluation begins before large-scale adoption.

1.2 What Is Technology?

Technology may be understood broadly as the application of knowledge, techniques, tools and organizational arrangements to accomplish human purposes.

This definition includes physical artefacts such as machines and medical devices, but also includes software, algorithms, production processes, organizational systems and methods.

A useful conceptual distinction can be made between:

This broader understanding is important because the object being evaluated is often not a single technological artefact.

For example, evaluating an electric vehicle involves more than evaluating the vehicle itself. Evaluation may include charging infrastructure, electricity generation, battery supply chains, software, roads, maintenance, consumer behaviour, regulations and recycling systems.

Similarly, evaluating generative artificial intelligence involves more than evaluating a language model. It may require examination of training data, computing infrastructure, interfaces, human users, organizational policies, cybersecurity, intellectual property, environmental resource use and regulatory arrangements.

Technology therefore exists within systems.

1.3 New Technology and Emerging Technology

The terms “new technology” and “emerging technology” are frequently used interchangeably, but they are not necessarily synonymous.

A new technology may simply be a recently introduced product or process.

An emerging technology generally involves a greater degree of uncertainty concerning its future development, applications, adoption, impacts or societal significance.

For example, a new model of an established laptop may be new without being an emerging technology. By contrast, a new quantum-computing architecture may be emerging because its practical applications, scalability and economic significance remain under development.

Table 1.1 provides a conceptual distinction.

Table 1.1 — New Technology Compared with Emerging Technology

The distinction matters because the evaluation strategy should reflect the maturity of the technology.

1.4 Disruptive Technology

The concept of disruptive technology is often used in popular discussion to describe any technology that produces significant change. Academic use should be more precise.

Christensen (1997) developed the theory of disruptive innovation to describe processes through which new offerings can initially serve less demanding or overlooked market segments and subsequently alter competitive structures.

Not every powerful innovation is therefore disruptive in the technical sense of the theory.

A technology may be:

sustaining rather than disruptive;

incremental rather than radical;

architectural rather than component-based;

evolutionary rather than revolutionary; or

disruptive in one market but not another.

Technology evaluation should therefore avoid automatically equating novelty with disruption.

1.5 General-Purpose Technologies

Some technologies have effects that extend across many industries.

These are often described as general-purpose technologies.

Examples historically include:

steam power;

electricity;

the internal combustion engine;

computing;

the internet.

Artificial intelligence may increasingly exhibit characteristics associated with general-purpose technologies because it can be incorporated into numerous sectors and organizational processes.

General-purpose technologies create special evaluation challenges because their consequences are distributed across multiple domains.

A technology used in education may have implications for:

teaching;

assessment;

academic integrity;

student learning;

employment;

research;

administration;

data governance.

Consequently, the evaluation of general-purpose technologies cannot be confined to one application.

1.6 Converging Technologies

One of the most significant characteristics of contemporary innovation is technological convergence.

Technologies increasingly combine rather than develop independently.

For example:

Artificial intelligence + robotics = intelligent autonomous systems

Artificial intelligence + biotechnology = computational biology and AI-supported drug discovery

IoT + cloud computing + AI = intelligent connected systems

Digital twins + sensors + AI = predictive industrial systems

Quantum computing + cryptography = new approaches to secure information systems

Biotechnology + advanced computing + automation = highly integrated biological production systems

This convergence creates evaluation complexity because risks and benefits may emerge from interactions among technologies rather than from individual technologies.

Technology Convergence Model

Figure 1.1 — Technology Convergence Model

Figure 1.1. Technology Convergence Model — Conceptual Explanation

The Technology Convergence Model illustrates the increasing interdependence of emerging technologies and the resulting need for a broader approach to technology evaluation. Artificial intelligence is positioned as a central enabling technology that interacts with robotics, the Internet of Things (IoT), and biotechnology. Rather than operating as isolated technological domains, these technologies can increasingly be integrated into a convergent system in which capabilities, data, processes, and applications interact across technological boundaries.

The convergent system can generate consequences across multiple domains. The model therefore identifies economic effects, social effects, and environmental effects as interconnected areas for evaluation. These effects may arise from the combined operation of technologies rather than from any single technology in isolation. Consequently, an evaluation framework must consider both the characteristics of individual technologies and the interactions, dependencies, synergies, and unintended consequences that emerge when they are combined.

Governance provides the overarching context for managing these convergent systems. Governance may encompass institutional decision-making, regulatory requirements, accountability, ethical oversight, data governance, risk management, and the allocation of responsibility among technology developers, organizations, users, and other stakeholders.

The evaluation challenge therefore moves from evaluating individual technologies to evaluating technology combinations. This shift requires evaluators to examine not only whether each technology performs effectively on its own, but also how technologies interact, how their combined effects emerge, and whether the resulting system remains economically viable, socially responsible, environmentally sustainable, and appropriately governed.

Core Implication

The unit of technology evaluation increasingly shifts from the individual technology to the convergent technological system.

1.7 Technological Maturity

Technological maturity is a central concept in technology evaluation.

A technology may be scientifically plausible without being technically mature enough for deployment.

Technology Readiness Levels (TRLs) were developed as a structured method for describing technological maturity. NASA currently describes a nine-level scale ranging from basic principles observed and reported at TRL 1 to operationally proven systems at TRL 9.

Table 1.2 — Technology Readiness Levels

TRL is useful because it distinguishes an idea from a demonstrated technology.

However, TRL should not be confused with overall technology readiness.

A technology can have high technical maturity while still having:

low organizational readiness;

uncertain economic viability;

unresolved ethical concerns;

poor social acceptance;

weak regulatory arrangements;

substantial environmental impacts.

Thus:

Technical readiness is necessary for many technology decisions, but technical readiness alone does not establish overall readiness.

NASA itself notes that technology assessment involves understanding both technological maturity and the difficulty of advancing the technology to the required level.

1.8 Technology Maturity Versus Technology Value

One of the most important distinctions in this book is between maturity and value.

Consider two technologies.

Technology A has TRL 9 but provides limited additional value compared with an existing solution.

Technology B has TRL 6 but could potentially transform a major social problem if additional technical and organizational barriers are overcome.

The technologies differ in maturity and potential value.

Therefore:

Technology maturity ≠ technological value.

A comprehensive assessment must ask at least four different questions:

Can it work?

Does it solve the intended problem?

Is it valuable enough to justify implementation?

Can it be deployed responsibly?

These questions form the conceptual foundation of the framework developed later in Chapter 4.

1.9 Technology Ecosystems

Technology should also be understood as part of an ecosystem.

An ecosystem consists of interconnected actors, resources, infrastructures and institutions.

Technology Ecosystem

Figure 1.2 — Technology Ecosystem

Figure 1.2. Technology Ecosystem — Conceptual Explanation

The Technology Ecosystem framework conceptualizes technology as operating within a network of interconnected actors, resources, institutions, and environmental conditions. Rather than treating technology as an isolated artefact, the model places technology at the centre of an ecosystem involving government, users, developers, data, markets, organizations, investors, infrastructure, and the broader environment.

Government provides an important institutional and regulatory context for technology development and use. Users and developers interact directly with technology, while data functions as a critical resource connecting technological activity with organizational processes and decision-making. Markets and investors contribute economic and financial conditions, while organizations provide settings in which technologies are implemented, managed, and integrated into existing systems.

Infrastructure provides the enabling foundation through which technologies can operate and generate outcomes. Infrastructure may include physical facilities, telecommunications networks, electricity, digital connectivity, information systems, healthcare systems, transportation networks, and other supporting capabilities. The environment represents the wider ecological and contextual conditions within which technology is developed, deployed, and experienced.

The model emphasizes that the same technology can produce different outcomes in different ecosystems. A digital-health application may perform effectively in a country with widespread internet access, strong healthcare infrastructure, and interoperable electronic records, but perform poorly in a region where connectivity, electricity, and digital literacy are limited.

Technology evaluation is therefore context dependent. Evaluation should consider not only the intrinsic characteristics and technical performance of a technology, but also the ecosystem in which the technology is introduced. Differences in institutional capacity, infrastructure, user characteristics, market conditions, investment, regulatory arrangements, data availability, and environmental circumstances can influence whether a technology achieves its intended outcomes.

Core Principle

Technology outcomes are ecosystem dependent; therefore, meaningful technology evaluation must assess the technology together with the context in which it is developed, deployed, and used.

1.10 Technology and Society

Technology both influences society and is influenced by society.

Users adapt technologies to their needs.

Organizations redesign work around technologies.

Governments regulate technologies.

Markets create incentives for technological development.

Cultural values influence acceptance.

Ethical expectations influence design.

Consequently, technology is not independent of human institutions.

This is one reason why technological determinism—the assumption that technology independently drives social change—can be misleading.

Technology creates possibilities, but social, economic and institutional conditions influence which possibilities become realities.

1.11 Case Study: Generative Artificial Intelligence in Higher Education

Generative AI provides a useful illustration.

A university may consider adopting generative AI for:

student support;

administrative communication;

tutoring;

feedback;

research assistance;

language support;

curriculum development.

The technical question might concern accuracy and reliability.

The organizational question might concern staff capability.

The economic question might concern subscription and implementation costs.

The human question might concern student learning and academic work.

The ethical question might concern authorship, academic integrity, privacy and transparency.

The social question might concern unequal access.

The governance question might concern institutional policies and accountability.

Therefore, the technology cannot be evaluated adequately through technical demonstrations alone.

1.12 Chapter 1 Evaluation Matrix

Table 1.3 — Preliminary Technology Identification Matrix

1.13 Chapter Research Questions

What characteristics distinguish emerging technologies from established technologies?

How does technological maturity influence technology evaluation?

How does technological convergence affect risk and evaluation complexity?

Why should technology be evaluated as part of a wider sociotechnical ecosystem?

How can organizations distinguish technological maturity from technological value?

1.14 Chapter Summary

Emerging technologies represent more than new technological artefacts. They exist within complex sociotechnical ecosystems involving users, organizations, markets, infrastructure, governments and environments.

This chapter established the distinction between new and emerging technologies, examined technological convergence, introduced general-purpose and disruptive technologies, and discussed technological maturity through Technology Readiness Levels.

The central lesson is that technological capability should not be confused with technological value.

A mature technology can have limited value, while an immature technology may possess substantial future potential. Consequently, technology evaluation requires consideration of multiple dimensions.

Chapter 2 develops the historical and conceptual evolution of technology assessment.

1.15 Discussion Questions

What is the difference between a new technology and an emerging technology?

Is artificial intelligence a general-purpose technology? Explain the evidence and reasoning that would be required.

Why is TRL insufficient as a complete technology-evaluation framework?

How can technological convergence increase uncertainty?

How should technology evaluation account for differences between countries and organizations?