Article
The Sixth Wave Reframed: Technological Convergence and Causal Layered Analysis
Detlef Reis1,2,*
1Institute of Knowledge and Innovation, Southeast Asia (IKI-SEA), Bangkok University, Bangkok, Thailand
2Thinkergy Ltd., Hong Kong SAR, China
Abstract
Long-wave accounts of technological change often explain transformation through dominant technologies, such as digitalization or sustainable innovation. This article argues that such perspectives are incomplete. Drawing on long-wave theory and Causal Layered Analysis (CLA), it proposes that the Sixth Wave is best understood as the convergence of three interdependent technology spaces: digital technologies as enabling intelligence, clean and sustainable technologies as boundary-setting constraints, and human-centered technologies as sources of purpose and legitimacy. Using CLA diagnostically, the article shows how this convergence reshapes systems, worldviews, and cultural narratives, thereby culminating in the Sixth Wave maxim “Less, but Better.” The article contributes to futures studies by positioning long-wave transitions as multi-layered convergence processes rather than single-technology-led sequences.
Keywords
Sixth Wave, Long Waves, Technological Convergence, Causal Layered Analysis, Less but Better
Introduction
Contemporary discourse on the emerging Sixth Wave of technological innovation is marked by a growing sense that a new period of transformation is underway. Advances in artificial intelligence, data-driven systems, and digital platforms are widely interpreted as signaling a new phase of economic and societal change. At the same time, accelerating climate pressures and sustainability imperatives have led many observers to frame the next wave primarily in terms of clean and sustainable technologies. In both academic and policy-oriented accounts, these developments are often presented as wave-defining forces in their own right, whether through digitally driven visions of intelligence and automation (Suleyman, 2023) or through sustainability-centered narratives that position environmental constraint, resilience, and green transformation as central drivers of change (World Economic Forum, 2023).
While such perspectives capture important dimensions of the current transition, they tend to frame the Sixth Wave as being driven by a single dominant technology domain, thereby obscuring its deeper structural dynamics. Long-wave theory suggests that this is a recurring limitation of early interpretations of major technological shifts. Historically, long waves have been shaped not by isolated technologies, but by clusters of interacting innovations embedded within broader institutional, economic, and cultural transformations (Kondratiev, 1935; Schumpeter, 1939). From this perspective, the current transition raises a critical question: if digital technologies associated with the Fifth Wave have reached a stage of maturity, and if sustainability challenges alone cannot fully explain emerging innovation dynamics, what configuration of forces defines the Sixth Wave?
Some contributions have begun to move beyond single-driver explanations by framing the Sixth Wave in terms of dual technology spaces, most notably the interaction between clean technologies and digital enablement. A prominent example is provided by Moody and Nogrady (2010), who emphasize resource constraints and sustainability challenges while acknowledging the enabling role of digital technologies in accelerating clean solutions. While this dual-space framing represents an important step forward, it remains analytically incomplete.
I argue that the Sixth Wave is best understood as a convergence of three interdependent technology spaces: digital technologies, clean and sustainable technologies, and human-centered technologies. Digital technologies—particularly artificial intelligence—now primarily function as enabling intelligence and coordination infrastructure rather than as the defining destination of the wave. Clean and sustainable technologies introduce binding ecological constraints that reshape what is technologically, economically, and politically viable. Human-centered technologies extend beyond abstract concerns such as health, learning, or wellbeing and encompass concrete technological domains, including digital health and personalized medicine, neurotechnology and cognitive enhancement, human–machine collaboration systems, learning and skill augmentation technologies, assistive and inclusive technologies, experience design and human–technology interaction, and emerging frameworks for ethical governance and digital rights. Thereby, these technologies provide orientation by anchoring innovation in human capability, legitimacy, and meaning. It is the interaction of these three spaces, rather than the dominance of any single one, that gives the Sixth Wave its distinctive character.
The central contribution of this article is to show that the Sixth Wave is best explained by convergence across these three technology spaces, and that this convergence operates not only at the level of technological systems but also across deeper cultural layers. To make this multi-layered dynamic visible, the article elegantly integrates long-wave theory with Causal Layered Analysis (CLA) (Inayatullah, 1998). CLA is employed here not as a method for envisioning preferred futures, but as a diagnostic lens that reveals how convergence manifests across surface phenomena, systemic drivers, dominant worldviews, and underlying myths and metaphors.
Through this approach, the article demonstrates how the convergence of digital, clean and sustainable, and human-centered technologies gives rise to a characteristic innovation orientation captured in the maxim “Less, but Better.” The maxim “Less, but Better” was originally articulated as one of the design principles of the German industrial designer Dieter Rams, emphasizing simplicity, durability, and restraint in product design. In this article, the phrase is adapted and reframed to capture the broader structural and cultural orientation emerging in the Sixth Wave of technological innovation. This maxim is interpreted neither as a moral injunction nor as an anti-growth stance, but as an emergent structural outcome of innovation under conditions of intelligence, constraint, and purpose—one that increasingly also functions as a normative orientation shaping how innovation priorities are framed in contexts of growing complexity.
From a futures studies perspective, the article contributes by reframing long-wave transitions as multi-layered convergence phenomena rather than technology-led sequences, and by demonstrating how Causal Layered Analysis can be used diagnostically to interrogate the systemic, cultural, and mythic dimensions of technological epochs, not only to construct scenarios or preferred futures.
The article proceeds as follows. Section 2 situates the Sixth Wave within long-wave theory and examines the maturity of the Fifth Wave, clarifying why digital technologies alone no longer define a new paradigm. Sections 3 and 4 develop the core argument by outlining the three technology spaces of the Sixth Wave and explaining convergence as its defining mechanism. Section 5 deepens this analysis through Causal Layered Analysis, tracing how convergence reshapes innovation logic across multiple layers of meaning. Section 6 synthesizes these insights by explicating the emergence of the maxim “Less, but Better.” Section 7 discusses the implications of this reframing for futures studies, innovation research, and policy discourse, and Section 8 concludes by reframing the Sixth Wave as a convergence-driven transformation.
Long Waves and the Maturity of the Fifth Wave
Long-wave theories of economic and technological change provide a useful lens for understanding the emergence, diffusion, and transformation of major innovation paradigms over time. From Kondratiev’s early identification of long economic cycles to Schumpeter’s analysis of innovation clusters and creative destruction, and later refinements by evolutionary and neo-Schumpeterian scholars, long waves are understood as systemic transformations rather than linear progressions driven by isolated inventions (Kondratiev, 1935; Schumpeter, 1939; Freeman & Louçã, 2001). These transformations encompass not only technologies, but also capital formation, institutional arrangements, organizational models, and cultural expectations.
A recurring insight across long-wave scholarship is that technological revolutions unfold in phases. Early periods of experimentation and installation are typically followed by phases of diffusion, consolidation, and institutional adjustment. As these processes mature, the technologies that once defined a wave increasingly become taken-for-granted infrastructure, enabling subsequent transformations rather than driving them directly (Perez, 2002). This dynamic is critical for understanding the transition from the Fifth to the Sixth Wave.
The Fifth Wave as a Mature Techno-Economic Paradigm
The Fifth Wave is commonly associated with information and communication technologies, digital networks, and the widespread diffusion of computing and the internet. Over several decades, these technologies reshaped production, coordination, and consumption, enabling new business models and global connectivity. During its expansionary phase, digitalization functioned as a dominant techno-economic paradigm, attracting speculative capital and redefining competitive advantage across industries (Perez, 2002; Castells, 1996).
From a long-wave perspective, however, the Fifth Wave has now entered a stage of maturity. Core digital infrastructures—such as broadband connectivity, cloud computing, software platforms, and data architectures—are widely deployed and increasingly treated as baseline conditions rather than sources of strategic differentiation. While digital innovation continues at pace, its character has shifted toward optimization, automation, and incremental extension of existing systems rather than the creation of fundamentally new economic logics.
Recent developments illustrate this transition. The rapid acceleration of digital adoption during the COVID-19 pandemic can be interpreted as an amplification of deployment dynamics rather than the onset of a new long wave. Subsequent consolidation, regulatory scrutiny, and workforce adjustments across major technology firms reflect stabilization patterns consistent with a maturing paradigm (Perez, 2009). In this sense, the Fifth Wave has not ended, but its role has changed.
Digital Technologies as Enabling Infrastructure
Long-wave theory suggests that the maturity of a techno-economic paradigm repositions its core technologies as enabling infrastructure for subsequent waves. Historically, technologies such as steam power, electricity, and mass production systems followed similar trajectories: initially disruptive, later foundational. In the current context, digital technologies—particularly artificial intelligence, data analytics, and software platforms—are increasingly assuming this infrastructural role (Perez, 2010).
This shift has important implications for how the Sixth Wave is conceptualized. Digital technologies now provide the intelligence and coordination capabilities required to manage complex systems, integrate heterogeneous technologies, and enable real-time feedback across sectors. Rather than defining the direction of innovation independently, they increasingly mediate interactions among other domains. As Arthur (2009) has argued, technologies evolve through combinatorial processes, in which existing components are recombined to generate new possibilities—a dynamic significantly amplified by mature digital infrastructures.
Recognizing digital technologies as enablers rather than sole drivers helps avoid two analytical pitfalls: overstating the novelty of ongoing digital acceleration as wave-defining, and underestimating the continued importance of digital capabilities in shaping future innovation trajectories.
From Digital Maturity to a New Wave Configuration
If digital technologies alone no longer suffice to define a new long wave, the question becomes what additional forces are shaping the emerging paradigm. Long-wave scholarship emphasizes that new waves arise not simply from technological novelty, but from the alignment of enabling technologies with new constraints, institutional responses, and value orientations (Schumpeter, 1942; Perez, 2002). In the present context, planetary boundaries, resource limitations, demographic shifts, and evolving social expectations introduce tensions that cannot be resolved through digital optimization alone.
This observation provides the historical rationale for the convergence framework developed in the subsequent sections. The Sixth Wave does not replace the digital foundations of the Fifth, but builds upon them, while incorporating clean and sustainable technologies as boundary-setting forces and human-centered technologies as sources of purpose, capability, and legitimacy. Together, these domains reflect a shift from expansionary orientations toward innovation to more selective, system-aware trajectories.
From this perspective, the maturity of the Fifth Wave is not a sign of stagnation, but a precondition for a new innovation configuration. Digital technologies, having become pervasive and infrastructural, enable the convergence of multiple technology spaces under conditions of increasing complexity. It is this convergence—rather than the dominance of any single technology—that best explains the distinctive dynamics and cultural expressions of the Sixth Wave.
The Three Technology Spaces of the Sixth Wave
Prevailing accounts of the Sixth Wave often emphasize one dominant technology domain—most commonly digitalization, and increasingly clean and sustainable technologies. As discussed in Sections 1 and 2, such framings capture important aspects of the current transition but remain analytically incomplete. Long-wave transformations are not driven by isolated technologies alone, but by interacting configurations of technologies, institutions, and value orientations that together reshape socio-economic systems (Kondratiev, 1935; Schumpeter, 1939; Perez, 2002).
Building on this insight, this article proposes that the Sixth Wave is best understood through the interaction of three interdependent technology spaces: digital technologies, clean and sustainable technologies, and human-centered technologies. Each space performs a distinct systemic function, and none is sufficient on its own to explain the emerging innovation dynamics. It is their combination—and ultimately their convergence—that gives the Sixth Wave its distinctive character.
Digital Technologies: Enabling Intelligence and Orchestration
Digital technologies form the most visible layer of the Sixth Wave and are frequently treated as its primary driver. Advances in artificial intelligence, data analytics, software platforms, and connectivity have dramatically increased the capacity to process complexity, automate tasks, and coordinate activities across systems. However, as argued in Section 2, the role of digital technologies has shifted as the Fifth Wave has reached maturity.
From a long-wave perspective, digital technologies increasingly function as enabling infrastructure rather than as the defining destination of innovation. This pattern is consistent with historical precedents in which the core technologies of one wave—such as steam power or electrification—later became foundational enablers for subsequent transformations (Perez, 2002; Perez, 2010). In the Sixth Wave, digital technologies primarily provide intelligence, speed, and connectivity that allow other domains to scale and interact.
Arthur’s (2009) conception of technology as a combinatorial evolutionary system is particularly relevant here. Mature digital infrastructures expand the scope for recombination by allowing diverse technologies to be integrated, optimized, and coordinated in real time. Thereby, digital technologies act as catalysts and connectors, enabling systemic innovation without determining its direction.
Clean and Sustainable Technologies: Constraint and Corrective
Clean and sustainable technologies introduce a fundamentally different dynamic into the Sixth Wave. Whereas earlier waves were largely shaped by expanding resource frontiers, the current transition unfolds under increasingly explicit planetary constraints. Advances in renewable energy, energy storage, materials science, circular production systems, and environmental monitoring redefine what is economically and technologically viable.
From a systemic perspective, clean technologies function as both constraint and corrective. By internalizing environmental and resource costs that were previously externalized, they reshape innovation trajectories and investment priorities. This logic resonates with Ecological Modernization Theory, which conceptualizes environmental constraints not as external limits to modernization, but as drivers of industrial transformation and refinement (Mol, 1995). Rather than opposing technological progress, ecological constraints force innovation to become more selective, efficient, and system-aware.
Clean and sustainable technologies are also deeply interdependent with other technology spaces. Their effectiveness and scalability increasingly depend on digital intelligence for optimization and coordination, as well as on human-centered considerations such as acceptance, behavior change, and institutional alignment. This interdependence underscores why clean technologies alone cannot define the Sixth Wave, despite their growing prominence in contemporary discourse.
Human-Centered Technologies: Purpose, Capability, and Legitimacy
Human-centered technologies constitute one of the most under-theorized yet increasingly consequential technology spaces of the Sixth Wave. This domain extends beyond abstract concerns such as health, learning, or wellbeing and encompasses a growing set of concrete technological fields aimed at supporting, augmenting, and integrating human capabilities within complex socio-technical systems. These include, among others, digital health and personalized medicine, biotechnology and regenerative medicine, neurotechnology and cognitive enhancement, learning and skill augmentation technologies, assistive and inclusive technologies, human–machine collaboration systems, experience design and human–technology interaction technologies, as well as emerging infrastructures for ethical governance, trust, and digital rights.
While human-centered technologies are often framed as social outcomes or secondary effects of technological change, they increasingly operate as active drivers shaping innovation trajectories, consistent with systems-of-innovation perspectives that emphasize human capability, institutional fit, and user integration as core determinants of innovation dynamics (Edquist, 2005). Advances in biotechnology, genomics, digital diagnostics, brain–computer interfaces, adaptive learning systems, collaborative robotics, and immersive interaction technologies expand what is technically possible in supporting human performance, resilience, and agency (Norman, 2013; Miller & Page, 2007). In this sense, human-centered technologies are not merely reactive responses to societal challenges but are propelled by their own technology-push dynamics, opening new design spaces for innovation.
The importance of aligning technological systems with human and social needs has been recognized since early socio-technical systems theory. Seminal work by Trist and Bamforth (1951) demonstrated that optimizing technical performance in isolation can undermine both human well-being and overall system effectiveness. Their insights remain highly relevant in the context of contemporary digitally enabled systems, where adoption, legitimacy, and sustained performance depend on the quality of human–technology integration rather than technical efficiency alone.
At the same time, strong demand-side forces amplify the prominence of human-centered technologies in the Sixth Wave. Demographic change, rising mental and cognitive overload, declining institutional trust, and mounting pressures on health, education, and care systems create powerful incentives for innovations that enhance human capability, autonomy, and resilience. From a capability perspective, such developments resonate with broader frameworks that emphasize human agency, participation, and well-being as central dimensions of progress (Sen, 1999).
Beyond capability enhancement, human-centered technologies perform a critical legitimacy function within innovation systems. They shape whether technological solutions are trusted, adopted, and sustained, thereby influencing scale, diffusion, and long-term impact (Suchman, 1995; Geels, 2004). From a systems perspective, they act as a purpose anchor, orienting digital enablement and sustainable innovation toward outcomes that are socially meaningful, ethically acceptable, and experientially viable.
Taken together, the three technology spaces outlined above clarify why single-driver or even dual-driver accounts of the Sixth Wave remain insufficient. Digital technologies enable, clean and sustainable technologies constrain and correct, and human-centered technologies orient and legitimize. Individually, each space explains part of the current transformation; collectively, they reveal how the Sixth Wave unfolds through convergence across technological capability, planetary constraint, and human meaning.
Convergence as the Defining Mechanism of the Sixth Wave
The previous section established that the Sixth Wave is shaped by three interdependent technology spaces—digital, clean and sustainable, and human-centered technologies—each performing a distinct systemic role. This section advances the article’s core argument by showing that it is the convergence of these spaces, rather than their parallel development, that constitutes the defining mechanism of the Sixth Wave. Convergence is not treated here as a technological buzzword, but as a structural response to rising systemic complexity and constraint.
Beyond Parallelism: Why Convergence Matters
Technological convergence is not a novel phenomenon. Previous long waves have been characterized by the interaction of multiple technologies, such as the convergence of steel, steam power, and railways in the Second Wave, or computing, telecommunications, and the internet in the Fifth Wave. What distinguishes the Sixth Wave is not convergence per se, but the nature of the domains being integrated and the roles they play.
In earlier waves, convergence primarily occurred within the techno-economic sphere, linking production, energy, and communication technologies to accelerate industrial growth. In the Sixth Wave, convergence spans qualitatively different domains: digital technologies that enable intelligence and coordination, clean and sustainable technologies that impose binding ecological constraints, and human-centered technologies that anchor innovation in purpose, capability, and legitimacy. This cross-domain convergence fundamentally alters how innovation unfolds and how progress is understood.
Convergence under Conditions of Complex Adaptive Systems
The necessity of convergence becomes clearer when Sixth Wave challenges are viewed through the lens of Complex Adaptive Systems (CAS). CAS theory emphasizes that systems composed of multiple interacting agents, technologies, and institutions exhibit non-linear behavior, emergent properties, and sensitivity to initial conditions (Holland, 1992; Holland, 1995). In such systems, outcomes cannot be reliably predicted by analyzing components in isolation.
Many contemporary innovation challenges—particularly in legacy industries such as energy, mobility, healthcare, manufacturing, and urban systems—display these characteristics. They involve heterogeneous actors, layered technologies, regulatory frameworks, and feedback loops that co-evolve over time. Linear optimization strategies and single-technology interventions frequently fail to address underlying systemic tensions, producing unintended consequences or shifting problems elsewhere.
From this perspective, convergence is not a strategic preference but a functional necessity. Digital technologies enable sensing, modeling, and coordination across complex systems. Clean and sustainable technologies introduce boundary conditions that constrain system behavior within ecological limits. Human-centered technologies guide alignment among actors by shaping trust, adoption, and learning. Thereby, these domains enable systems to adapt under constraint rather than collapse under complexity (Arthur, 1999; Miller & Page, 2007).
The convergence perspective advanced here builds on, but also extends, established theories of socio-technical change. Innovation systems approaches have long emphasized the interactive and institutional nature of innovation, highlighting learning, coordination, and co-evolution among actors, technologies, and organizations (Lundvall, 1992; Edquist, 2005). Actor–Network Theory similarly challenged linear and technologically deterministic accounts by foregrounding the entanglement of human and non-human actors in shaping technological outcomes (Latour, 1987). At the same time, debates on technological determinism have demonstrated how persistent assumptions about technology as a primary driver continue to influence interpretations of societal transformation, even when softened by institutional or cultural qualifiers (Bimber, 1994). While these perspectives offer important insights, they are not designed to explain the simultaneous alignment of multiple technology spaces performing distinct systemic roles under shared conditions of constraint and complexity. Nor do diffusion-based accounts, which focus on how innovations spread over time, adequately capture the structural dynamics through which innovation domains themselves become increasingly interdependent (Rogers, 1962).
Convergence and Socio-Technical Transitions
Insights from socio-technical transition theory further illuminate the role of convergence in the Sixth Wave. The Multi-Level Perspective (MLP) conceptualizes transitions as interactions between niche innovations, dominant regimes, and broader landscape pressures (Geels, 2002; Geels, 2004). From this viewpoint, convergence occurs when innovations across multiple domains align sufficiently to destabilize existing regimes and enable new configurations to emerge.
In the Sixth Wave, landscape pressures such as climate change, resource scarcity, demographic shifts, and social expectations intensify the need for coordinated responses. Digital, clean, and human-centered technologies often emerge in different niches and evolve at different speeds. Convergence occurs when these innovations begin to reinforce one another across levels—when digital intelligence accelerates clean solutions, when sustainability constraints reshape digital design choices, and when human-centered considerations influence both technological direction and institutional acceptance.
This alignment is rarely smooth or centrally orchestrated. Instead, it unfolds through experimentation, contestation, and learning across sectors and regions. Understanding convergence as a socio-technical process helps explain why the Sixth Wave is uneven, contested, and path-dependent—yet increasingly coherent at a systemic level.
Functional Differentiation and Alignment
A key contribution of the integrative convergence framework developed in this article is the clarification of functional differentiation among the three technology spaces. Digital technologies primarily enable what is technically possible by providing intelligence, speed, and connectivity. Clean and sustainable technologies define what is physically and ecologically viable by imposing non-negotiable constraints. Human-centered technologies determine what is socially desirable and legitimate by anchoring innovation in human capability, wellbeing, and meaning.
Individually, these functions can pull innovation in different directions. Digital enablement without constraint risks over-acceleration and systemic fragility. Constraint without intelligence risks inefficiency or stagnation. Purpose without capability risks aspiration without impact. Convergence aligns these functions, thereby allowing innovation trajectories to emerge that are adaptive, bounded, and socially grounded.
This alignment is not static. It requires continuous adjustment as technologies, institutions, and expectations evolve. In this sense, convergence in the Sixth Wave is better understood as an ongoing process of coordination and recalibration rather than a fixed end state.
Convergence as a Precondition for a New Innovation Orientation
Viewed through a long-wave lens, convergence in the Sixth Wave represents more than technical integration or policy coordination. It signals a shift in the logic of innovation itself. Earlier waves were largely governed by expansionary principles—speed, scale, and output—supported by relatively abundant resources and limited awareness of systemic limits. The Sixth Wave unfolds under conditions where intelligence, constraint, and human values must be balanced simultaneously.
This balance does not emerge automatically. It is produced through the convergence of enabling, constraining, and orienting forces across complex systems. As digital technologies make selective precision possible, clean technologies enforce responsibility, and human-centered technologies foreground quality and legitimacy, innovation increasingly shifts from doing more of everything toward doing fewer things more deliberately.
As the following section demonstrates, this convergence penetrates beyond technological and institutional systems into deeper cultural layers. Through Causal Layered Analysis, it becomes possible to trace how convergence reshapes worldviews and narratives of progress—culminating in the Sixth Wave maxim “Less, but Better.”
Deepening the Sixth Wave through Causal Layered Analysis
While the preceding sections established convergence as the defining mechanism of the Sixth Wave at the level of technologies and systems, this section deepens the analysis by examining how convergence operates across multiple layers of meaning. To do so, the article employs Causal Layered Analysis (CLA) as a diagnostic and deconstructive lens, rather than as a method for envisioning preferred futures or prescribing normative pathways. Developed within futures studies, CLA distinguishes between observable discourse (litany), systemic structures, dominant worldviews, and underlying myths or metaphors, enabling the systematic interrogation of complex socio-technical transformations (Inayatullah, 1998; Inayatullah, 2004).
In this article, CLA is used to clarify how dominant interpretations of the Sixth Wave operate simultaneously across these layers, and how tensions between them emerge as innovation paradigms shift. The analysis does not seek to resolve such tensions or advance normative scenarios, but to make visible the interaction between surface narratives, structural drivers, and deeper cultural stories. This usage aligns with developments in futures methodology that emphasize CLA as a tool for critical sense-making rather than prescription, particularly in contexts characterized by complexity and uncertainty (Inayatullah & Milojević, 2015).
Litany Level: Signals of Transition
At the litany level, the Sixth Wave is commonly described through observable signals such as rapid advances in artificial intelligence, the diffusion of renewable energy systems, concerns over climate change, rising mental health challenges, and intensifying debates around trust, data use, and technological governance. These phenomena are frequently presented as discrete trends, reported in fragmented ways across media, policy documents, and industry analyses.
CLA highlights that such signals, while salient, offer only a partial view of transformation. As Inayatullah (1998) notes, litany-level descriptions often privilege immediacy and visibility while obscuring deeper drivers. In the context of the Sixth Wave, the simultaneous intensification of digital acceleration, sustainability pressures, and human-centered concerns already suggests that a more integrated shift is underway beneath the surface.
Systemic Level: Enablers, Constraints, and Alignment
At the systemic level, the functional differentiation among the three technology spaces becomes clearer. Digital technologies provide enabling intelligence and coordination capabilities that allow complex systems to be monitored, optimized, and interconnected in real time. Clean and sustainable technologies introduce binding ecological constraints that redefine system boundaries and investment priorities. Human-centered technologies shape system alignment by influencing adoption, legitimacy, and the capacity of actors to engage with increasing complexity.
From this perspective, convergence emerges as a response to systemic pressures that cannot be addressed within a single domain. Innovation challenges increasingly resemble complex adaptive systems, characterized by non-linear interactions, feedback loops, and co-evolving actors. CLA enables these dynamics to be examined without reducing them to technical causality, revealing how structural forces interact with institutional and social dimensions (Inayatullah, 2004).
Worldview Level: From Expansion to Selective Progress
At the worldview level, convergence reshapes dominant assumptions about progress, growth, and innovation. Earlier waves were underpinned by worldviews that emphasized expansion, acceleration, and scale, often equating progress with increased output and consumption. These assumptions were reinforced by relatively abundant resources and limited awareness of systemic limits.
In the Sixth Wave, such worldviews become increasingly difficult to sustain. Ecological constraints, social complexity, and rising coordination costs challenge the notion that more technology and faster innovation necessarily produce better outcomes. CLA reveals an emerging shift toward selective progress, in which innovation is understood as a process of making informed, deliberate choices within bounded systems. Human-centered considerations play a critical role at this level by foregrounding questions of capability, legitimacy, and meaning alongside technical feasibility (Inayatullah & Milojević, 2015).
Myth and Metaphor Level: From Acceleration to Cultivation
At the deepest level of CLA, convergence manifests in changing myths and metaphors that shape how societies imagine the future. Dominant metaphors of previous waves often revolved around acceleration, conquest, and limitless growth. Such narratives aligned with technological revolutions that promised liberation through scale and speed.
In contrast, the Sixth Wave increasingly gives rise to metaphors of cultivation, stewardship, and care. Innovation is imagined less as an endless race and more as the careful tending of complex systems under constraint. Digital intelligence becomes a tool for sensing and coordination, clean technologies define the boundaries of responsible action, and human-centered technologies emphasize flourishing within limits. CLA makes it possible to surface these deeper narrative shifts, which often operate implicitly yet strongly influence collective sense-making (Inayatullah, 2004).
Implications of the CLA Perspective
By tracing convergence across all four CLA layers, this analysis demonstrates that the Sixth Wave is not solely a technological or economic phenomenon. It is also a cultural transformation that reshapes how innovation is understood, justified, and pursued. CLA reveals the coherence between surface-level signals, systemic reconfigurations, evolving worldviews, and emerging narratives, thereby strengthening the explanatory power of the convergence framework.
This multi-layered perspective prepares the ground for the synthesis developed in the following section. As convergence aligns intelligence, constraint, and purpose across systems and cultures, it gives rise to a characteristic innovation orientation. Section 6 articulates this logic through the maxim “Less, but Better,” showing how it emerges as both a structural outcome of convergence and an increasingly explicit orientation guiding innovation choices in the Sixth Wave.
To synthesize the prior analysis, Table 1 provides a comparative overview of the Causal Layered Analysis of long waves in general, the Fifth Wave, and the emerging Sixth Wave. The table does not seek to exhaust the complexity of each wave, but to highlight the distinctive shift in innovation orientation as convergence unfolds across technological, systemic, worldview, and mythic layers.
Table 1: A Causal Layered Analysis of Long Waves, the Fifth Wave, and the Sixth Wave
| Causal layers | Long waves in general | Fifth Wave | Sixth Wave |
|---|---|---|---|
| Litany
Observable trends, headlines, and surface-level phenomena |
|
|
|
| Systemic Causes
Structural drivers, institutional dynamics, and techno-economic forces |
|
|
Key systemic shift: From single-tech acceleration to multi-tech convergence under constraint |
| Worldview / Discourse
Dominant values, assumptions, and ways of framing progress |
|
|
Worldview shift: |
| Myth / Metaphor
Deep narratives, collective archetypes, and civilizational stories |
Core myth: “The Wave”
Deep story: |
Core myth: “Faster. More. Always.”
Deep story: |
Core myth: “Less, but Better.”
Deep story: With intelligence, restraint, and creativity, we can do better — not just more. |
From Convergence to the Maxim “Less, but Better”
The foregoing sections have shown that the Sixth Wave is shaped by the convergence of three interdependent technology spaces: digital technologies as enabling intelligence, clean and sustainable technologies as boundary-setting constraints, and human-centered technologies as sources of purpose, capability, and legitimacy. This section synthesizes these insights by articulating the innovation orientation that emerges from this convergence, captured in the maxim “Less, but Better.”
Figure 1 synthesizes the core argument of this article by visualizing how the Sixth Wave emerges through the convergence of three technology spaces—digital, clean and sustainable, and human-centered—each performing a distinct systemic role.
The maxim is not introduced here as a slogan or normative injunction imposed from outside the system. Rather, it is interpreted as a structural outcome of innovation under conditions of intelligence, constraint, and complexity. At the same time, it increasingly functions as an explicit orientation guiding innovation choices across sectors and contexts. Understanding this dual character is essential for grasping its significance in the Sixth Wave.
From Expansionary to Selective Innovation Orientations
Earlier long waves were largely governed by expansionary orientations toward innovation. Technological progress was closely associated with increased scale, speed, and output, supported by relatively abundant resources and limited awareness of systemic limits. In such contexts, doing more—producing more goods, deploying more technology, accelerating processes—was often equated with progress.
The Sixth Wave unfolds under markedly different conditions. Ecological constraints, social complexity, and rising coordination costs challenge the assumption that expansion alone delivers desirable outcomes. At the same time, mature digital infrastructures dramatically increase the capacity to sense, model, and optimize systems. This combination creates the conditions for a shift from expansionary to selective innovation—an orientation that emphasizes deliberate choice, alignment, and societal direction-setting as techno-economic paradigms mature (Perez, 2010).
“Less, but Better” captures this shift succinctly. It reflects the growing recognition that value creation increasingly depends on precision rather than proliferation, and on quality rather than quantity. This logic does not imply technological retreat or stagnation, but a reorientation of innovation priorities toward what matters most within bounded systems.
The maxim was initially intuited by the author as a guiding metaphor for the Sixth Wave prior to its formal articulation in this article, emerging through reflective and contemplative sense-making rather than deductive analysis. Its subsequent examination through Causal Layered Analysis provided the analytical grounding that revealed its structural, systemic, and cultural validity—an epistemic sequence consistent with futures scholarship that recognizes intuition as a legitimate entry point for insight, later stabilized through methodological inquiry. The epistemic role of intuition in futures inquiry is discussed by Inayatullah (2008), who argues that intuitive insight—often arising in reflective or meditative states—can precede rational analysis and later be interrogated, deepened, and validated through methods such as Causal Layered Analysis. This article follows that sequence by treating intuition as a starting signal rather than a substitute for analysis.
Fig. 1: Convergence of the three technology spaces in the Sixth Wave
Convergence as the Source of the Maxim
The maxim “Less, but Better” cannot be explained by any single technology space in isolation. Digital technologies alone tend to reinforce acceleration and optimization logics. Clean and sustainable technologies alone emphasize constraint and efficiency, but risk being framed as limiting or restrictive. Human-centered technologies alone foreground wellbeing and meaning, but may lack the enabling capacity to scale impact.
It is through convergence that these tendencies are reconciled. Digital intelligence enables fine-grained understanding and coordination of complex systems, making selective intervention possible. Clean and sustainable technologies impose non-negotiable boundaries that narrow the space of viable options, forcing prioritization. Human-centered technologies orient innovation toward outcomes that enhance capability, trust, and legitimacy, shaping judgments about what constitutes “better.”
Together, these forces thereby reduce the feasibility—and desirability—of indiscriminate expansion. Innovation increasingly takes the form of doing fewer things more intentionally, aligning technical possibility with ecological responsibility and human purpose. This orientation has begun to be articulated explicitly in recent syntheses of Sixth Wave dynamics, which frame “Less, but Better” as a guiding logic for innovation under conditions of intelligence, constraint, and complexity (Reis, 2026, forthcoming).
“Less, but Better” as Structural Outcome
From a structural perspective, “Less, but Better” emerges as an outcome of operating within complex adaptive systems under constraint. As discussed in Section 4, such systems exhibit non-linear dynamics and sensitivity to intervention. Excessive complexity, redundancy, or acceleration can undermine system performance, resilience, and legitimacy.
Under these conditions, innovation strategies that prioritize simplicity, robustness, and coherence become structurally advantageous. Digital technologies make it possible to identify leverage points and optimize across systems. Sustainability constraints limit overextension and encourage resource efficiency. Human-centered considerations ensure that solutions remain usable, trusted, and socially embedded.
In this sense, “Less, but Better” reflects a functional adaptation to complexity. It expresses how innovation systems evolve when intelligence, constraint, and purpose are jointly present.
“Less, but Better” as Normative Orientation
At the same time, the maxim increasingly operates as a normative orientation—an explicit aim shaping how innovation is framed and evaluated. Across sectors, there is growing emphasis on designing products, services, and systems that are more durable, more meaningful, and more aligned with human and ecological needs, even if this entails fewer features, reduced throughput, or slower cycles.
This orientation is increasingly visible in policy and innovation discourse that emphasizes wellbeing, mission-oriented innovation, and long-term value creation alongside economic performance (OECD, 2019; OECD, 2021; OECD, 2023). Within such framings, “Less, but Better” functions not as a universal prescription, but as a heuristic that encourages reflection on trade-offs between scale, sustainability, and human experience.
Importantly, this normative dimension does not contradict the structural interpretation. Rather, it reflects how actors internalize systemic conditions and translate them into guiding principles. As with earlier long waves, emergent logics eventually become articulated as intentional strategies and design philosophies.
Implications for Innovation Practice
Interpreted through the lens of convergence, “Less, but Better” reframes innovation practice in several ways. It shifts attention from maximizing outputs to aligning systems, from accelerating deployment to enhancing coherence, and from novelty for its own sake to meaningful value creation. These shifts resonate particularly strongly in legacy industries and public systems, where innovation challenges increasingly resemble complex adaptive systems involving multiple technologies, actors, and institutional constraints.
By articulating “Less, but Better” as both an emergent outcome and a normative orientation, this section bridges structural analysis and practical sense-making. It prepares the ground for the discussion that follows, which examines how this reframing contributes to futures studies, innovation research, and policy discourse without collapsing into prescriptive agendas.
Discussion and Implications
The antecedent analysis reframes the Sixth Wave as a convergence-driven transformation spanning digital, clean and sustainable, and human-centered technology spaces, and demonstrates how this convergence unfolds across multiple cultural layers. This section discusses the implications of this reframing for futures studies, innovation research, and policy discourse, focusing on how the convergence perspective reshapes key analytical assumptions within these domains.
Implications for Futures Studies
For futures studies, the convergence framing underscores the importance of moving beyond sector-specific or technology-centric anticipations of change. Many futures analyses continue to privilege dominant technological drivers—most recently artificial intelligence or sustainability—while treating social, cultural, and human dimensions as secondary effects. The Sixth Wave analysis presented here suggests that such approaches risk missing how transformative dynamics operate across multiple, interacting layers, a concern long emphasized within futures methodology (Inayatullah, 1998; Inayatullah, 2004).
The use of Causal Layered Analysis highlights the value of futures methods capable of integrating surface-level trends with systemic structures, worldviews, and underlying narratives. In the context of the Sixth Wave, CLA makes visible how convergence reshapes not only technological trajectories, but also assumptions about progress, responsibility, and value creation, reinforcing the role of futures studies in engaging with long-wave transformations that cut across technological, institutional, and cultural domains.
Implications for Innovation Research
For innovation research, the convergence framing challenges models that focus predominantly on isolated technological domains, firm-level capabilities, or market dynamics. While these approaches remain valuable, they may be insufficient for capturing innovation dynamics that unfold across complex adaptive systems characterized by non-linear interactions, feedback loops, and co-evolving actors (Holland, 1992; Arthur, 1999).
The Sixth Wave suggests that innovation outcomes increasingly depend on alignment among enabling intelligence, ecological boundaries, and human-centered considerations. This perspective resonates with socio-technical transition research, which emphasizes that transformative change emerges through the interaction of technologies, institutions, and social practices rather than through single-factor optimization (Geels, 2002; Geels, 2004). From this standpoint, convergence thereby becomes a necessary condition for regime-level change under conditions of heightened complexity and constraint.
The maxim “Less, but Better” can thus be interpreted as an emergent orientation reflecting how innovation systems adapt when confronted with systemic limits and coordination challenges.
Implications for Policy Discourse
From a policy perspective, the convergence-driven nature of the Sixth Wave complicates traditional approaches that focus on discrete sectors or technological domains. Policies addressing digital transformation, sustainability, or human capital development are often formulated independently, despite their growing interdependence. Socio-technical transition theory suggests that such fragmentation can hinder systemic adaptation by failing to account for cross-domain interactions and feedback effects (Geels, 2004).
Viewing the Sixth Wave through the lens of convergence does not imply centralized control or uniform policy solutions. Instead, it highlights the importance of recognizing how enabling infrastructures, boundary conditions, and legitimacy concerns interact in shaping innovation trajectories. In this sense, “Less, but Better” functions as an interpretive lens through which emerging policy debates around efficiency, resilience, and societal value can be better understood.
Convergence, Complexity, and Reflexivity
Across futures studies, innovation research, and policy discourse, a shared implication of the Sixth Wave reframing is the growing importance of reflexivity. Convergence across technology spaces intensifies interdependencies and feedback loops, increasing the likelihood of unintended consequences and reducing the effectiveness of linear interventions. As research on complex adaptive systems has long emphasized, adaptive learning and iterative adjustment become critical under such conditions (Holland, 1995).
Some accounts of the current technological epoch emphasize digital platforms as the primary driver of the present wave, highlighting the role of data-driven business models, network effects, and algorithmic coordination (Srnicek, 2017; Suleyman, 2023). While these perspectives capture important aspects of recent innovation dynamics, a predominantly platform-centric framing risks oversimplification. From the perspective advanced here, digital technologies are best understood as enabling elements within a broader convergence of digital, clean and sustainable, and human-centered technologies, whose interaction reshapes both the structural conditions and cultural meanings of innovation.
By situating convergence within a multi-layered analytical framework, the Sixth Wave perspective does not seek to resolve complexity, but to make it more intelligible, reinforcing the need for ongoing sense-making across technological, institutional, and cultural domains as societies navigate long-wave transitions.
Last but not least, while the present analysis clarifies how convergence across digital, clean and sustainable, and human-centered technologies reshapes innovation dynamics and cultural orientations, it does not address governance arrangements in depth. Questions of global coordination, institutional capacity, and inequity—particularly where governance systems lag behind rising technological complexity—remain critical to how Sixth Wave dynamics unfold in practice and warrant dedicated future research. Likewise, although long wave theory suggests that subsequent waves will eventually emerge, the article deliberately refrains from speculating on a potential “seventh wave,” focusing instead on explicating the structure and meaning of the Sixth Wave as it is currently unfolding.
Conclusion — The Sixth Wave Reframed
This article reframed the Sixth Wave of technological innovation by moving beyond single-driver and dual-driver explanations toward a convergence-based understanding. Drawing on long-wave theory and Causal Layered Analysis, it argued that the Sixth Wave is best explained by the convergence of three interdependent technology spaces: digital technologies, clean and sustainable technologies, and human-centered technologies. Rather than treating these domains as parallel or competing drivers, the analysis showed how each performs a distinct systemic function—enabling intelligence, imposing boundary conditions, and providing purpose and legitimacy—and how their interaction reshapes innovation dynamics at multiple levels.
By situating the Sixth Wave within the historical logic of long-wave transitions, the article clarified why digital technologies associated with the Fifth Wave now function primarily as enabling infrastructure rather than as defining drivers. At the same time, it demonstrated how ecological constraints and human-centered considerations introduce orientations that cannot be accounted for within purely techno-economic frameworks. The convergence perspective thus provides a more coherent explanation of contemporary innovation dynamics than approaches focused on isolated technologies or sectors.
The application of Causal Layered Analysis further revealed that this convergence extends beyond technological systems into deeper cultural layers. At the level of worldviews and narratives, assumptions about progress shift from expansion and acceleration toward selectivity, coherence, and responsibility. Within this context, the maxim “Less, but Better” emerges as both a structural outcome of innovation under conditions of intelligence and constraint, and as an increasingly explicit orientation shaping how innovation priorities are framed and evaluated.
By highlighting convergence as a defining mechanism of the Sixth Wave and tracing its implications across systems and cultures, this article contributes to futures studies by clarifying how technological change, societal values, and orientations toward innovation co-evolve under conditions of growing complexity (Perez, 2002).
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