Vallverdú, Jordi (2023) What if plants compute?. Animal Sentience 33(17)
DOI: 10.51291/2377-7478.1793
Date of submission: 2023-04-19
Date of acceptance: 2023-04-29




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                       Animal Sentience 2023.471: Vallverdú on Segundo-Ortín & Calvo on Plant Sentience



                                 What if plants compute?
                      Commentary on Segundo-Ortín & Calvo on Plant Sentience

                                    Jordi Vallverdú
                Philosophy Department, Universitat Autònoma de Barcelona

       Abstract: The unexpended cognitive capacities of plants suggest the possibility of combining
       them with advances in computation. It is important to explore such a new field of research
       despite the incompleteness of the empirical support for it.



                      Jordi Vallverdú, ICREA Academia researcher at UAB, is an
                      expert on cognition and epistemology, oriented to
                      computational fields. His interests include emotional
                      modelling, ethics, and art. Currently, he is working on causal
                      analysis in Deep Learning systems. Website



The new discoveries about the cognitive capacities of plants need to be connected with
contemporary advances in the power of computation (Baluška & Levin, 2016). Do plants
themselves compute? Or can they provide mechanisms for computing? Adamatzky et al.
(2017) have shown that plants can provide a reliable way to design computational systems. It
might be possible to combine them with computation following engineering principles
because of their intrinsic mechanistic properties. Adamatzky (2019) suggests that using action
potentials as multi-functional signals in plants, through their vascular network, specifically
those of their leaves, can be implemented as a complete set of Boolean functions by selecting
locations for stimulating and recording electrodes.

Unconventional computing establishes bridges on both sides: (1) applying engineering
mechanisms to raw biological materials and (2) reverse-engineering how such biological
systems are built to process complex information. Very basic and classic examples of
bioinspiration for computational purposes are neural networks, genetic algorithms,
neurochips, neuromorphic computing, and swarm intelligence, among a lost list. On the other
side, the recent creation of xenobots based on Deep learning analysis of biological data
(Kriegman, et al, 2020), reservoir computing with plants (Pieters, 2022), and mycelium
computing using mushrooms all show that it is possible to implement not only computation
but basic logic and belectronic circuits with mycelium (Adamatzky, 2018; Adamatzky et al.
2020).

I can still recall the surprise and dismissal occasioned by Paco Calvo’s first ideas about plant
cognition. After further reading in several fields, my interests converged on minimal cognition
and plant cognition. Now there is the study of artificial cognition and the use of biologically
inspired design in new computational systems such as those created in the past decade in the
UWE Bristol Unconventional Computing Laboratory. The phylogenetic perspective of
cognitive complexity has revealed mechanisms in minimal cognitive systems such as slime
moulds (Vallverdú, 2018), that could be applied to other cognitive systems, such as the human
one, or to designing for scientific purposes, as in network design (Tero et al, 2010). Minimal



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                       Animal Sentience 2023.471: Vallverdú on Segundo-Ortín & Calvo on Plant Sentience


cognition may provide a key to understanding complex cognitive systems, natural, mixed, or
artificial.

References

Adamatzky, A. (2018). Towards fungal computer. Interface focus, 8(6), 20180029.
Adamatzky, A. (2019). Plant leaf computing. Biosystems, 182, 59-64.
Adamatzky, A., Tegelaar, M., Wosten, H. A., Powell, A. L., Beasley, A. E., & Mayne, R. (2020).
     On boolean gates in fungal colony. Biosystems, 193, 104138.
Adamatzky, A., Harding, S., Erokhin, V., Mayne, R., Gizzie, N., Baluška, F., Mancuso, S., &
     Sirakoulis, G. C. (2017). Computers from plants we never made: Speculations. In
     Inspired by Nature: Essays Presented to Julian F. Miller on the Occasion of his 60th
     Birthday (pp. 357-387). Cham: Springer International Publishing.
Baluška, F., & Levin, M. (2016). On having no head: cognition throughout biological systems.
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Kriegman, S., Blackiston, D., Levin, M., & Bongard, J. (2020). A scalable pipeline for designing
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Pieters, O. (2022). Reservoir Computing with Plants (Doctoral dissertation, Ghent
        University).
Segundo-Ortin, Miguel & Calvo, Paco (2023) Plant sentience? Between romanticism and
      denial. Science. Animal Sentience, 33(1).
Tero, A., Takagi, S., Saigusa, T., Ito, K., Bebber, D. P., Fricker, M. D., & Nakagaki, T. (2010).
       Rules for biologically inspired adaptive network design. Science, 327(5964), 439-442.
Vallverdú, J., Castro, O., Mayne, R., Talanov, M., Levin, M., Baluška, F., Yukio Gunji, P.,
       Audrey Dussutour, Zenil, H. & Adamatzky, A. (2018). Slime mould: the fundamental
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