Why does artificial intelligence take it for granted to be confined to mimicking human intelligence, instead of something else, like plant intelligence? And, how can we reflect plant intelligence and plant epistemology back into algorithmic questioning?

Intro

On 14 January 2025, I had a precious enlightening conversation. Ian took some valuable time to give me specific feedback on my KIPP Summative Assessment 1. My KIPP Summative Assessment 1 actually consists of two proposals: one is my dream project, and the other is a new research project that distils the core concepts catching my attention from all the courses I took in Semester 1into a new research topic, considering the limitations of a one-year master’s programme. (Please see the link to the blog post detailed my KIPP 1000 Word Preliminary Project Proposal: https://blogs.ed.ac.uk/s2766608_data-inequality-and-society-kipp–futures-project-2024-25/2025/07/21/🦋-kipp-1000-word-preliminary-project-proposal-submitted-in-december-2024/)

During our conversation, I primarily expressed my concerns regarding the manageability of the dream project—particularly its scale and the constraints of time—as well as the uncertainty surrounding the final direction I should take. I was relieved when Ian gave the green light to both research proposals. Since Ian confirmed that both were feasible, and following further discussions with Dr Rashné Limki, the instructor of Coloniality of Data, about the viability of the first proposal within the scope of a master’s thesis, we were able to jointly identify solutions to address the challenges and render it workable for the programme (this will be detailed in a subsequent blog post).

As a result, I have decided to stay true to my passion and choose Proposal 1—this long-brewing dream project—rather than opting for a slightly compromised alternative. Therefore, this blog post will primarily focus on reflecting upon Ian’s feedback regarding my dream project on endosymbiosis-inspired algorithms called Competitive Algorithms, Cooperative Alternatives: Rethinking Space Telescope Scheduling Through Symbiogenetic Principles.

Brief Overview of the Proposal
This master’s dissertation aims to intervene in the epistemological and ontological architectures of algorithmic intelligence. Drawing on current scientific debates in biology and botany (e.g. non-competitive evolutionary models in nature)( Margulis & Sagan, 2002；Schlanger, 2024；Kimmerer, 2013), this research seeks to apply the essence of these debates to the field of AI design and to develop an initial theoretical framework for endosymbiosis-inspired algorithms. The goal at this stage is not to implement a fully functional algorithm, but to reconceptualise the philosophical premises underpinning dominant algorithmic models—particularly assumptions of evolutionary competition, separability, and optimisation. Through a speculative and interdisciplinary methodology (for example, “utopia as method” as proposed by Ruth Levitas)(Levitas, 2013), this project lays the groundwork for future explorations into feminist algorithmic design rooted in cooperation, mutual transformation, and multispecies intelligence.

Ian’s Core Feedback
Ian emphasised that the core idea of my proposal—to replace competitive algorithmic logic with symbiosis and cooperation—intersects meaningfully with a major paradigm shift currently taking place within scientific debates in botany and ecology. The more we come to understand plant intelligence and capability, the more the traditional human framing of nature as inherently competitive is called into question.

Ian recommended The Light Eaters （Schlanger, 2024）, a book which, despite its occasional cherry-picking of evidence, contains compelling examples—such as how sunflowers move their leaves to ensure their companions also receive sunlight, and how plants grow and function collectively. These instances highlight the plural possibilities beyond competition in the plant (and natural) world: cooperation, mimicry, and more. They challenge the long-standing notion that “nature = competition.”

He affirmed that my proposal “touches on something that is on the crest of kind of coming out of a lot of scientific debates,” and that its key contribution may lie in applying these scientific arguments to the broader domain of AI. In short, he recognised the promise of the project, suggesting that with careful development it could become a strong foundation for future doctoral research.

This offered me a sense of reaffirmation: that my proposal is not simply an abstract speculation of my own imagination, but that its challenge to Darwinian thinking resonates with domains where cutting-edge scientists are already engaging in serious debate.

Staying true to my feminist STS (Science and Technology Studies) standpoint, particularly that of situated knowledgesas inspired by Donna Haraway (1998), I do not believe in a ‘great divide’ between science and society. On the contrary, I see the production of scientific knowledge as always embedded in specific socio-cultural contexts. The two are mutually permeable and co-constitutive. My task, then, is to bring the conversations within plant studies, and more broadly, the scientific community, into dialogue with a new intersectional terrain: one where philosophy, technology, and the life sciences meet.

Ian made me feel a rare sense of intellectual affinity. Throughout this year of study, I’ve been immersed in powerful critical literature on algorithmic systems. Yet I often found that something was missing: a sense of future possibility.

Before entering this programme, I was undeniably influenced by technofeminism and cyborg feminism, and inclined towards a form of techno-optimism. Now, after a year of critical engagement, my position on the spectrum has shifted closer to the centre. Scholars have pointed out how technofeminism and cyborg feminism encouraged women and marginalised groups to invest hope and emotion into technologies—as if they might deliver us to a more liberated, utopian future. But decades have passed, and these hopes remain largely unanswered. Technologies have neither empowered the vulnerable nor responded to the emotional investments placed in them. Caroline Bassett’s （Bassett, 2023） essay The Cruel Optimism of Technological Dreams, published in Feminist AI, delivers a poignant critique of this dynamic.

That said, I remain far from technophobic. I’m inspired by philosopher of technology Gilbert Simondon’s （Simondon, 1958/2017） eloquent critique of cultural alienation from machines:

“The machine is something which fights against the death of the universe; it slows down, as life does, the degradation of energy, and becomes a stabiliser of the world.”

In the past, the power to wield this entropy-resisting potential of machines was concentrated in the hands of a privileged few—often white male developers. I still believe that part of our responsibility is to reclaim this potential, so that other groups, too, may harness the machine’s power to resist decay, sustain vitality, and offer stability to their worlds.

In other words, my position on algorithmic justice is not purely critical—I also wish to contribute creatively, to open up spaces of hope. This is what I hope to offer the field of critical algorithm and data studies: a breath of fresh air. My aspiration is to see whether ongoing scientific and ecological conversations—on plant intelligence and cooperative evolutionary ecology—can revitalise and reimagine the ethics and design of AI algorithms, forging new pathways for the future.

Reflections After the Conversation with Ian
1. Given the utopian orientation of this research—its constructive desire to open toward future possibilities—the project will adopt utopia as method, a framework introduced in the Utopia and the Future course. Proposed by Ruth Levitas, this methodology consists of three elements or “modes”: excavation (archaeology), critique (ontology), and construction(architecture). It will serve as the central methodological scaffold for the dissertation, functioning as an umbrella under which other research methods can be situated.

2. While my original proposal focused on microbes as a model for symbiotic evolution, Ian extended the horizon to include the plant world, which enriched my examples significantly. I plan to readThe Light Eaters, the book Ian recommended, during the dissertation writing stage. His emphasis on plant intelligence helped sharpen the rationale for my final project, which now centres around the following questions:

Why does artificial intelligence take it for granted to be confined to mimicking human intelligence, instead of something else—like plant intelligence? And how can we reflect plant intelligence and plant epistemology back into algorithmic questioning?

The Coloniality of Data course encouraged us not merely to speculate, but to treat these speculative alternatives as forms of serious science. This resonates with Donna Haraway’s concept of speculative science, which she understands not as futuristic fantasy, but as a practice of worlding (Haraway, 2016). Drawing on this ethos, I believe my final project must ask:
What might artificial intelligence inspired by plant or microbial intelligence—or other nonhuman forms of knowing—look like?
(Of course, at that point the prefix artificial itself becomes questionable. “Machine intelligence” might be a relatively proper and neutral diction. But what I refer to here is a distributed machinic actant—currently framed as external to the human—that feeds information, knowledge, and intelligence back to us.)

AI Insights from Plant Intelligence: In Dialogue with Robin Kimmerer
If we are to take plant intelligence seriously, then alongside Ian’s suggested reading, I would also like to bring into this conversation a resource from the Coloniality of Data course—a podcast episode featuring Robin Kimmerer titled The Intelligence of Plants.

Kimmerer (2015; 2016), a botanist and professor from the Citizen Potawatomi Nation, embodies what she refers to as two-eyed seeing. She has long worked—both inside and outside the academy—to integrate these two epistemic perspectives: one rooted in the traditional knowledge passed down to her by the human elders of her Indigenous community and the plant elders of the forest; the other shaped by her rigorous scientific training within Western research institutions. As she puts it,

“Science polishes the gift of seeing; Indigenous traditions work with gifts of listening and language.”

When studying botany at university, she discovered that these two ways of knowing “plants” were radically different. Science positioned the human researcher as the epistemic subject and reduced the plant to a lifeless object, devoid of agency, awareness, or intelligence—denying its gifts and capacities. Kimmerer was trained to classify plants mechanically and rigidly by their morphology and external characteristics, to assign them Latin names and slot them into the hierarchical categories of Linnaean taxonomy.

In fact, the act of naming in science has always been closely tied to coloniality. It draws from the Christian tradition of naming as a means of creation—“the Word made flesh”—and also from the colonial history of the Age of Discovery, when explorers collected, categorised, and named people, places, and things in the lands they colonised. Natural history as a scientific project flourished under these conditions and naming practices, deeply entangled with colonial violence.

Yet, Kimmerer’s Indigenous perspective led her to question whether the scientific gaze truly captured the value of plants? Or whether it actually devalued them. Yes, science’s magnifying lenses and microscopes allow us to examine plants with precision and assign them into neat categories. But from the standpoint of Kimmerer and the epistemologies she inhabits, these are merely the most superficial, material aspects of plant life.

She recalls how, in her first year studying botany, she told her professor that she wanted to understand why purple and yellow flowers so often appeared in pairs. “Why is their combination so beautiful?” she asked. Her question was dismissed for the reason not as being scientific, but as an aesthetic inquiry suited to art school. Science, after all, does not deal with beauty. It does not concern itself with colour combinations, nor with the relational aesthetics of flower pairings. Its attention remains fixeated on pure materiality, overlooking spirit, beauty, and connection as legitimate ways of knowing.

But plants are not merely passive materialities to be observed. They can also be known through emotional and spiritual relations. If we find ourselves uncomfortable or sceptical of the idea that emotion and spirituality can constitute knowledge, then that discomfort is itself precious. It marks the edge of our own epistemic horizon—the point at which a shift in perspective becomes possible.

This is why Kimmerer insists that Indigenous knowledge is not just about seeing, but about listening—refining the capacity to hear the stories that the world is constantly telling. It is a way of knowing that activates all the senses, including the heart and spirit.

More importantly, Indigenous traditions acknowledge the spirit of all beings—or to use less mystical language, their agency, capacities, and gifts. This orientation makes it possible to perceive the world through relations. Only when we acknowledge that all beings possess some form of intelligence and agency can we begin to understand the rich, reciprocal complexity of their interconnections.

Interestingly, Kimmerer’s intuitive question about purple and yellow flowers has since been partially supported by biological explanations: the two colours sit opposite one another on the colour wheel, creating a striking complementary contrast that attracts pollinators. Their vivid pairing enhances mutual visibility and facilitates shared survival. In short, their aesthetic beauty also contributes to ecological advantage. Their co-existence is symbiotic and mutually beneficial.

Clearly, when science is willing to open its self-imposed boundaries, it can access fuller, richer understandings of the world. Questions of beauty, of sensory perception, and of emotion should not belong to artists alone. They ought to be shared by scientists too.

As Donna Haraway and Bruno Latour have both argued, the so-called great divide between nature and culture is deeply suspect (Latour, 1993; Haraway, 1988). It does not naturally exist in the world, but is rather enacted through specific scientific and epistemic practices. Karen Barad (2007) terms this an agential cut—like a surgical incision, it violently separates sense from reason, aesthetics from knowledge, and nature from culture, as if they were fundamentally distinct domains. Yet this cut obscures the lively, generative entanglements that have always already existed between them.

Scientific Evidence of Plant Intelligence and Cooperative Evolution
Kimmerer points out that, in fact, plants—and animals too—are repeatedly being revealed in contemporary scientific research as far more intelligent than we have long assumed. They not only possess astonishing abilities, but crucially, these are abilities that humans lack. Yet through the flattening lens of scientific reductionism, humans have consistently denied the existence of such capacities—a profound loss. For we could have learned from plants, animals, and other-than-human beings entirely different forms of intelligence and capacity, ones that might have helped us thrive in the precarious conditions of the Anthropocene.

For instance: plants are capable of photosynthesis—a generative power unavailable to humans. They can transform inorganic elements into nourishment, giving back to the world by sustaining animals, humans, trees, and soil alike. Rocks accept the presence of mosses in their crevices, while mosses slowly weather the rocks back into soil. In this dialogue of relation, moss and stone offer themselves to one another, collaboratively enriching the ecosystem through limited resources.

Kimmerer’s position aligns closely with that of The Light Eaters, previously mentioned, as well as with Lynn Margulis, the scientist who inspired my proposal through her theory of endosymbiotic evolution:

1. All three challenge the idea that competition is the sole engine of biological evolution and species success. And, they do so through grounded scientific evidence. Margulis’s reasoning is already detailed in my proposal, but for Kimmerer, the example of moss is equally telling: small in size, growing from cracks and fissures, acquiring resources through inefficient survival strategies—mosses would seem to rank low on any measure of evolutionary “fitness.” And yet, they have persisted on Earth for over 350 million years—far longer than the mighty dinosaurs (160 million years), or the so-called intelligent Homo sapiens (just 200,000 years). What, exactly, have mossescompeted for—and won? Clearly, it is not about competition. But it is equally clear that they have done something right. Their relational coexistence with stone, logs, and other beings must be recognised as an evolutionarily significant fact.
2. Kimmerer and Margulis both argue, based on empirical evidence, that nonhuman intelligence is on the edge of a scientific paradigm shift.Fewer and fewer scientists cling to the belief that humans are the sole gatekeepers and holders of intelligence. Increasingly, scientific observation and empirical studies are acknowledging that plants possess capacities for learning, memory, and adaptation, even if these abilities operate in forms that differ from human cognition.

This also resonates with what Ian noted in his feedback: that debates around who or what can be considered an “intelligent being” are now actively unfolding in the scientific world. It is, as he put it, a moment of crest—a peak—within the larger wave of transformation in science.

Reflections and Challenges to AI That Mimics Human Intelligence
My research, too, is a vivid response to these ongoing debates. If artificial intelligence is already prompting the wider public to reconsider who or what can be deemed intelligent, then might we also begin to recognise—more broadly and generously—the intelligence of the plants, animals, and microbes who have, for unfathomably long periods of time, nourished and sustained human life through their own unique wisdom and capacities?

While humans continue to ask whether machines can pass the Turing Test—which implies alignment with the traits of human intelligence—should we not also question the underlying premise: that human intelligence serves as the template, or, to borrow from Greek philosophy, the ideal form of intelligence itself? But is that necessarily true?

Can we not instead imagine another kind of machine intelligence—one whose models of learning are not only human, but more than human? What might such intelligence look like? Could algorithms move beyond dominance and decision-making, and instead learn through interspecies dialogue? Might such a machine intelligence be more reciprocal, leading us toward an alternative future of AI?

This is especially urgent at a time when cyborg feminism and technofeminism—in some sense—have been betrayed by the trajectory of contemporary artificial intelligence. A Cyborg Manifesto, published in 1985, inspired generations of marginalised communities to invest their time, energy, and most importantly, their hope in the promise of digital technologies. But forty years on, has that promise been fulfilled? Or have they, instead, been wounded by cruel optimism?

Decolonising Knowledge and Restoring Indigenous Traditional Ways of Knowing
As contemporary science gradually catches up with the worldview embedded in Indigenous knowledge traditions, this process is expanding our understanding of the life-knowledges of nonhuman species such as plants, animals, and microbes, and human imagination and epistemology must evolve accordingly. If, as Haraway has argued through the concept of situated knowledges, knowledge is always shaped by its context, then can our imagination of machine intelligence also move beyond that of the white, male-dominated visions from the 1956 Dartmouth Summer Research Project on Artificial Intelligence? Might the criteria for machine intelligence shift away from the imitation game proposed by Alan Turing in 1950, which defined intelligence in terms of mimicking the traits of human intelligence?

It is important to recognise that while my final project may appear to present a novel, anti-competitive narrative in evolutionary science—applying it as inspiration for AI design—this perceived novelty is actually a consequence of historical erasure and epistemic delay. It only feels new because contemporary science is belatedly catching up with the long-held worldviews sustained within Indigenous cosmologies, such as those voiced by Kimmerer. Her insights remind us that cooperation has never been a new idea. It has simply been unrecognised for a long time. This is not a modern phenomenon—it is an ancient form of wisdom, temporarily eclipsed by the coloniality of modernity’s knowledge systems. Indigenous knowledge traditions never required this so-called “revolution,” because they never forgot that plants, rocks, and water are sentient, emotional, and remembering beings.

Kimmerer’s two-eyed seeing—her dual gaze that draws from both scientific knowledge and Indigenous ecological knowledge, from nature and culture—reminds me that my research proposal should not be seen merely as a speculative design exercise or a form of biomimicry. It is, more deeply, an epistemological act of repair. It aims to recalibrate perception and cognition, to reclaim plural ways of seeing. Whether by becoming a “compound-eyed human” (as in Wu Ming-Yi’s formulation), or through Haraway’s “tentacular sensing”—a more-than-visual mode of knowing that gropes, tangles, and makes kin with the world, the goal is to remember what technoscience has forgotten.

My task is to imagine and prototype an alternative world. And intelligence is the battlefield.

Unanswered Questions for Myself
What kind of machine ethics might emerge from an AI inspired by nonhuman intelligence and symbiotic modes of existence exhibited by more-than-human beings?

Given that such a speculative alternative—or what utopia as method would call its architectural dimension—has no realised counterpart in the current world that could be ethically assessed, I am inclined to speculate on its possible ethical contours by turning to Through Vegetal Being (Irigaray & Marder, 2016), a co-authored work by Luce Irigaray and Michael Marder. They argue that vegetality is not a lack of animality, rationality, or subjectivity but rather an alternative mode of existence. It represents a way of co-existing that is non-intrusive, non-controlling. Both thinkers propose that we should exist through vegetal being—to think in the manner of plants, or to let plant-being transform our understandings of existence and ethics.

Irigaray, drawing on her longstanding psychoanalytic feminist position, further suggests that the feminine qualities of vegetality—its nourishing, yielding, and open nature—offer a latent ethical and metaphysical resistance to the masculine rational subject. As Kimmerer beautifully puts it in Braiding Sweetgrass: “We are all bound by a covenant of reciprocity. Plant breath for animal breath, winter and summer, predator and prey, grass and fire, night and day, living and dying.” These vegetal qualities, rooted in reciprocity and relationality, stand in sharp contrast to the rational subject emblematic of Western philosophical tradition—a subject that, not coincidentally, mirrors the predominant figure of those currently developing AI systems inspired by competitive evolutionary logics: the very systems my research seeks to challenge.

If Ian brings plants like sunflowers into scientific discourse, and if Kimmerer invites us to see them as ki—living, conscious, intelligent, agential kin—then Irigaray calls us to become them (not literally, but ethically and ontologically).

Before we consider engineering plant intelligence into algorithms—an undertaking that would likely be of incomprehensible scale—we might first begin by asking how vegetal thinking, its modes of co-existence and ethics, might be translated into technical design. To design endosymbiotic algorithms, perhaps we must first learn to breathe like a leaf, to pair with heterogeneous petals, to rotate like a sunflower, and to dwell in dependence on others as mosses do.

 Reference

Bassett, C. (2023). The cruel optimism of technological dreams. Feminist AI: Critical perspectives on algorithms, data, and intelligent machines (pp. 137–154). Oxford University Press. Academic Oxford

Barad, K. (2007). Meeting the universe halfway: Quantum physics and the entanglement of matter and meaning. Duke University Press.

Haraway, D. J. (1988). Situated knowledges: The science question in feminism and the privilege of partial perspective. Feminist Studies, 14(3), 575–599.

Haraway, D. J. (2016). Staying with the trouble: Making kin in the Chthulucene. Duke University Press.

Irigaray, L., & Marder, M. (2016). Through vegetal being: Two philosophical perspectives. Columbia University Press. PhilPapers

Kimmerer, R. W. (2015). Braiding sweetgrass: Indigenous wisdom, scientific knowledge, and the teachings of plants. Milkweed Editions. Wikipedia

Kimmerer, R. W. (2016, February 25). The intelligence of plants [Audio podcast episode]. In On Being with Krista Tippett. On Being Studios. https://onbeing.org/programs/robin-wall-kimmerer-the-intelligence-of-plants-2022/

Latour, B. (1993). We have never been modern (C. Porter, Trans.). Harvard University Press. (Original work published 1991)

Levitas, R. (2011). The concept of utopia. Peter Lang.

Levitas, R. (2013). Utopia as method: The imaginary reconstitution of society. Palgrave Macmillan. SpringerLink

Margulis, L., & Sagan, D. (1986). Microcosmos: Four billion years of microbial evolution. University of California Press.

Schlanger, Z. (2024). The light eaters: How the unseen world of plant intelligence offers a new understanding of life on Earth. Harper. Amazon

Simondon, G. (2017). On the mode of existence of technical objects (C. Malaspina & J. Rogove, Trans.). University of Minnesota Press. (Original work published 1958) socialecologies.wordpress.com

🦋 Structured Blog Post 8 | Sunflowers, Rudbeckias, Asters, and Mosses – Remembering What Was Forgotten: Reflections on Plant Intelligence, and How to Reflect Plant Epistemologies Back into Algorithmic Questioning / Meng-Chieh Tsai | Cauldron of Dream Project Brewing by is licensed under a