Uncer
Directional Matrix: from Canonical to More-than-human Design
| Strand | Core move | What counts as uncertainty | Main contribution for more-than-human design |
|---|---|---|---|
| Canonical typologies | Build diagnostic maps of uncertainty by location, level, and nature [1], [3] | Missing data, model uncertainty, scenario uncertainty, ignorance, epistemic vs ontological uncertainty [1], [5] | Gives a disciplined way to ask whether a design problem needs better knowledge, broader scenarios, or adaptation to irreducible indeterminacy |
| Governance and post-normal science | Shift from prediction alone to action in contested, high-stakes settings [2], [6] | Uncertainty in systems, institutions, strategies, and public frames [2] | Shows that design under uncertainty must include participation, precaution, flexibility, and learning rather than only optimization [2], [6] |
| Relational and ignorance-centered approaches | Treat uncertainty as a relation between knowers, objects, and institutions [7], [8] | Knowing too little, knowing too differently, and not knowing because ignorance is organized or strategic [7], [8] | Warns that design can misdiagnose conflict as a data gap when the real issue is plural framing or produced non-knowledge |
| Traditional and Indigenous knowledge literatures | Treat knowledge as practical, historical, ethical, and cosmological at once [9], [26], [27] | Uncertainty emerges when only the factual layer is extracted and the wider system of values, practices, and cosmology is stripped away [9], [27] | Pushes design toward partnership with whole knowledge systems rather than selective uptake of local observations |
| Pluriversal and ontological work | Treat disagreements as conflicts about what exists, not just how one world is interpreted [10], [11], [12], [28], [29] | Uncertainty arises at the meeting point of partially connected worlds and incompatible ontologies [11], [12] | Recasts design as diplomatic coordination across worlds rather than consensus-building inside one ontology |
| Multispecies and other-than-human agency | Move animals, plants, microbes, rivers, materials, and ecological processes from background to participant [13], [14], [17], [30], [31] | Uncertainty includes not knowing how nonhuman agencies perceive, respond, interrupt, or co-produce outcomes [13], [14], [17] | Opens the possibility that design is led not only by human needs but by nonhuman signals, rhythms, constraints, and interventions |
| More-than-human design methods | Translate these arguments into participatory and design frameworks [22], [23], [24], [25], [32], [33], [34] | Uncertainty includes not knowing how to represent, sense, or share agency with nonhuman participants without reducing them to proxies [22], [23] | Supplies practical methods for attunement, mediation, representation, autonomy, and commoning across species |
Canonical Approaches
The uncertainty distinguished in terms of location, level, and nature [1]. This architecture is common even when labels vary [3].
The cases where probabilities can be useful are distinct from cases where the outcome space or causal model is itself unstable [4], [5]. This matters because some situations call for better estimation, while others call for precaution, scenario thinking, or institutional buffering against surprise [6].
Governance work shows that uncertainty can be substantive, strategic, or institutional, and that each can be epistemic, ontological, or ambiguous [2]. That is relevant for design because it shows that more data cannot solve some problems or conflicts.
Anthropocentrism
The mainstream matrix remains human-centred. Even when it accepts ambiguity or ignorance, it often assumes that the goal is to help human decision-makers manage an external world.
Relational accounts argue that uncertainty is not only in systems but in the relations between system and multiple knowers who frame it differently [7]. Some unknowns are not accidental gaps but are socially maintained, institutionally filtered, or strategically useful absences [8]. Thus decision or design failures or harms often begins upstream, when problem framing erases some actors, knowledges, or consequences before deliberation starts.
Once uncertainty includes ignorance and indeterminacy of open, socially mediated, and partly unknowable fields, the application of settled knowledge to passive matter or living recipients cannot justify designs [6].
Roles of pluriversal knowledge
Traditional ecological knowledge can include observations, but management systems, past and current uses of land, ethics, identity, and cosmology [26] [27].
That matters for uncertainty because many institutional settings admit only the first layer. If this happens a design process may look inclusive while still erasing the conditions that make the knowledge meaningful. In practice, the overlaps in epistemic practices between differing approaches are common (cf. redundancy) [9].
The practical implication is that plural knowing should not be handled as a reservoir of supplemental facts for a prior design frame (such as the approval of intensive animal husbandry, carnivore diets, dominant economic relationships). Instead, plural epistemologies can serve as sources of problem definitions, criteria of success, and modes of relation.
This is useful but still presumes human decision-makers working with multiple forms of knowledge.
From plural knowledge to multiple worlds
Ontological and cosmopolitical work argues that the disagreement extends beyond misaligned beliefs about one world but also about what beings are present and what relations count as real [10], [11], [12]. This can take form of mountains as participants in collective life in Andean worldviews but also as debates in science or policy about reality or symptomatic of entities such as individuality, selection, evolution, innovation, etc.
Ontological accountability then means that inclusivity depends on questioning the assumptions built into the categories, practices, and institutions through which policy defines reality [29]. The result is a shift from consensus around one ontology to negotiated coexistence across worlds [12], [28].
Nonhuman beings as knowers and parts of knowledge systems
Animals can be knowers through know-how, social learning, and membership in epistemic communities rather than through human-like propositional speech [15]. E.g., destroying migration routes or killing older knowledgeable animals is damage to the transmission of animal knowledge [15].
Plants and fungi or bryophytes are a relevant challenge.
So are microbes.
Uncertainty deepens when the relevant lifeforms are invisible, distributed, rapidly changing, and entangled with human bodies and infrastructures as microbes [17], [18], [19].
Cf. microbes as sociopolitical entities. Access to healthy microbiomes depends on housing, food, pollution, labor, and other unequal conditions, which means microbial life becomes part of environmental and social justice rather than a separate scientific layer [17]. Metagenomics can generate a feeling for the microbiome, using sequencing, sensory attention, and household experiments to unsettle germ-war metaphors and create more hesitant, ecological relations with microbial life [18]. Fermentation studies show microbes as collaborators in place-based cultural practices, where humans cultivate microbial refugia and live within feedback loops of care, food, and environmental management [19].
Communities, systems and places is another one.
The river literature makes a related move in a more governance-oriented register. River co-learning arenas treat rivers as participants, subjects, and warning presences whose dynamics and relations shape what counts as relevant knowledge [31].
Eel Example
Eel movement reveals forms of sensing, preference, and vulnerability that can shape infrastructure design [20], [21].
E.g., European eels can respond to flow acceleration and other hydrodynamic conditions [20]. Under abrupt acceleration, they often reject a passage and turn back upstream. Under lower acceleration, they explore laterally and search more productively [20]. This suggests knowledge-bearing behaviour that indicates how a river passage is being read by the animal.
Similar consideration apply to variation within eel populations, exhaustion thresholds, slope, discharge, and the continuity of passable paths [21]. Design therefore has to represent eel needs as distributed, relational, and variable [21].
This makes eels a useful case for more-than-human design. They show that nonhuman guidance can be specific and technical rather than symbolic. They also expose the limits of reduced representation. If eel needs are translated only into coarse human abstractions, designs will fail by ignoring eels' acute sensing.
How can nonhuman beings lead design?
| Mode of nonhuman leadership | What it means | Consequence for design |
|---|---|---|
| Nonhumans as epistemic guides | Animal know-how, plant attentiveness, river warnings, microbial shifts, and seasonal rhythms can indicate conditions that formal monitoring misses or notices too late [15], [16], [17], [31] | Design should begin from situated ecological signals and long-duration field attention, not only from abstract metrics |
| Nonhumans as ontological anchors | Rivers, mountains, forests, and other beings may be treated as living participants whose status changes what the design problem is [10], [11], [12], [29] | Design criteria must include the maintenance of relations, obligations, and life-supporting reciprocity, not just efficient resource use |
| Nonhumans as co-designers | Animals, plants, microbes, and technical mediators can shape siting, habitat, temporal sequencing, and acceptable forms of intervention [24], [25], [33] | Design should create channels through which nonhuman preferences and capacities materially alter proposals |
| Nonhumans as intervening agents | Droughts, pathogens, fires, and other ecological processes can redirect research, governance, and collaboration in ways human planning did not foresee [13], [30] | Design should be adaptive and interruptible, leaving room for ecological feedback to redirect action |
Methods of Inclusion
| Method family | How it works | What it helps with | Main caution |
|---|---|---|---|
| Ontological auditing | Question the assumptions built into key terms, policies, and categories [29] | Reveals who or what a design process cannot presently see | Can become procedural if not linked to real redistribution of authority |
| Attunement and arts of noticing | Use situated observation, sensing, walking, and narrative methods to learn habitats, rhythms, and signs [16], [33] | Helps register nonhuman temporalities and needs before formal abstraction | Risks romantic projection if not grounded in ecological and social specificity |
| Counter-mapping and co-learning | Build maps, stories, and arenas where local and more-than-human relations can challenge official models [31], [33] | Surfaces hidden barriers, asymmetries, and alternate problem definitions | Can still recentre humans if nonhuman participation remains only symbolic |
| Personas and proxy coalitions | Build structured archetypes for species and validate them through coalitions of scientists, local actors, and advocates [22] | Makes nonhuman stakeholders discussable within design processes that otherwise exclude them | Personas can flatten difference, hide uncertainty, or smuggle in designer bias |
| Bioinclusive participation frameworks | Combine human proxies, direct participation, and expanded notions of stakeholder and designer [23], [24] | Gives a stronger normative basis for nonhuman inclusion and power-sharing | Communication remains asymmetric and often mediated by humans |
| Technical mediation | Use sensors, digital twins, monitoring systems, computational models, or hydraulic experiments to translate nonhuman signals into decisions [20], [21], [25], [34] | Makes long-duration or hard-to-sense processes actionable in design | Can intensify extraction or algorithmic control if framed only by human priorities [34] |
| Participation beyond invitation | Treat design as already entangled with more-than-human participants and reorganize processes accordingly [32] | Moves from consultation toward ongoing answerability | Requires slower, less managerial forms of practice |
Taken together, these methods imply that nonhuman representation is never solved once and for all. The real question is not whether humans can perfectly represent nonhumans. It is whether a method remains corrigible by nonhuman response, ecological feedback, and the situated knowledges of those already living closely with these beings.
Implications for future designing with and for all lifeforms
- Diagnose the kind of uncertainty before choosing a method. Some problems need measurement; others need scenarios, precaution, negotiation across frames, or acceptance of irreducible indeterminacy [1], [2], [5].
- Treat ambiguity as a design condition, not a communication bug. When actors know too differently, more information may intensify conflict rather than resolve it [2], [7].
- Refuse extraction of knowledge from its world. Practical observations matter, but values, ethics, identity, and cosmology are also design-relevant [9], [26], [27].
- Treat some nonhumans as knowers, not only as affected entities. Animal know-how, plant attentiveness, river warnings, and microbial shifts can all be relevant forms of guidance for design, though not all imply the same kind of knowing [15], [16], [17], [31].
- Use being-specific evidence where it matters. Eel passage shows that more-than-human design often depends on fine-grained behavioral and hydraulic knowledge rather than generic care language [20], [21].
- Design for hesitation and reversibility. Precaution becomes strongest when causal models are weak, outcome spaces are open, or ignorance is likely [5], [6], [28].
- Build diplomatic rather than universalizing processes. In pluriversal settings, the aim is not one master ontology but working relations across partially connected worlds [11], [12], [28].
- Let nonhuman agencies redirect the process. More-than-human design is not only advocacy on behalf of lifeforms; it is the creation of procedures that can register and respond when lifeforms and ecological processes push back [13], [14], [24].
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