A new theory called Assembly Theory, proposed by Dr. Leroy Cronin (Glasgow University) and Dr. Sara Walker (Arizona State University), proposes that life can be characterized by counting how many times a basic element is repeated in a given physical object. Among other predictions and characterizations, Assembly Theory suggests that beer is the most advanced living system on Earth, among those molecules studied in their first paper, as reported also recently by Quanta Magazine.
In recent months, however, Assembly Theory has been subject to heavy criticisms led by Dr. Zenil (Cambridge University) and Dr. Steven Bennett (Harvard University) based upon what they argue is an over simplistic view and theory of life promoted by the authors of Assembly Theory the nature of organic chemistry.
In a recent contribution, posted on a preprint server, followed by an extensive explanation on a blog post, Dr. Zenil and his group demonstrated that the result of picking beer as the greatest example of life on Earth despite not being a living organism and on top of any other organism considered may be the result of an ill-defined method that does not match the elegant prose of the theory that has taken most, if not all, its ideas, from the principles of an established theory called algorithmic information. The group has also shown, in a yet to be peer-reviewed paper, that despite the claims of the reach of Assembly Theory such as being able to detect alien life, the assembly index at the core of Assembly Theory can be replaced by almost any simple statistical index to reproduce their results at the same efficacy if not better. These other indexes include the Huffman coding, an algorithm to count optimally copies in data introduced in the 1960s that can be applied directly to the data they considered, mass spectral matrices. This, to Dr. Zenil and others, like Dr. Bennett, is the result of lack of basic knowledge in the fields of complexity and organic chemistry, and a lack of scientific methodology, such as basic control experiments. This is, basic comparisons with already existing theories and measures. To Dr. Zenil and others, it is not surprise that life is highly hierarchically modular, as known since the study of cellular biology and genetics. However, it cannot define life because many other processes are involved, and Assembly Theory, according to their paper, will fail and produce false positives and false negatives. According to the critics, these results undermine the fundamental assumptions and methods of the so-called Assembly Theory.
The authors of Assembly Theory also argue that their algorithm is the first to be applied directly to observed data and be able to deal with it directly. This, to Dr. Zenil, is also highly debatable. In a peer-reviewed paper, that the authors of Assembly Theory did not cite, Dr. Zenil and his group showed that by taking chemical molecules and compounds distance matrices, which can be extracted from direct observations, just as signal are extracted for mass spectral data to be produced as used by Assembly Theory, a clear separation between organic and non-organic compounds was derived and reported five years before the first paper of Assembly Theory. The same indexes used by Dr. Zenil and his group on the same data used by Assembly Theory, were also able to reproduce the same results putting in question the net contribution of Assembly Theory.
Dr. Zenil and his group contend that while hierarchical modularity is indeed a property of living systems, it should not be considered the sole or primary one. They propose that embracing algorithmic insights can lead to a more comprehensive understanding of living systems and their behavior, like they recently did in a peer-reviewed paper. By advocating for a more nuanced but more powerful approach, Dr. Zenil seeks to encourage researchers to adopt a multidimensional view that captures the intricacies and emergent properties of biological, technological, and societal systems.
By challenging the simplistic view presented by Assembly Theory, Dr. Zenil advocates for a more comprehensive understanding of the methods of complexity theory. The authors of Assembly Theory, for example, have been mischaracterizing the field in favor of advancing their theory according to Dr. Zenil. “Their arguments that certain measures are only estimations or are difficult to estimate, means that they think their measures are not estimations but exact calculations of life” according to Dr. Zenil. His emphasis on algorithmic methods and deeper approaches to living systems has paved the way for groundbreaking research in the past in publications that range from Nature Machine Intelligence to the Transactions of the Royal Society based on the premise that life, “as every biologist knows, is full of exemptions and simplistic theories counting for exact copies of a unique feature are set to fail”.
Dr. Hector Zenil is a pioneer in complexity science who has made contributions to the fields of complexity theory, systems biology, and the foundations of artificial intelligence. During his tenures at institutions such as the Department of Chemical Engineering and Biotechnology at Cambridge, the Department of Computer Science at Oxford, and the Unit of Computational Medicine at Karolinska Institute (the institution that awards the Nobel Prize in Physiology or Medicine), he introduced agnostic measures of algorithmic complexity that have made contributions to areas ranging from genetics to systems biology that may even help to detect biosignatures and create a framework to help decipher messages that alien intelligence may broadcast.
Dr. Steven Benner is a pioneer in the fields of paleogenetics, evolutionary bioinformatics, astrobiology and synthetic biology, working at Harvard, the ETH Zurich, and the University of Florida before establishing the Foundation for Applied Molecular Evolution (Alachua) and Firebird Biomolecular Sciences LLC. His synthetic biology has had over $1.3 billion in medical applications and is currently used in coronavirus detection. His laboratory has also resurrected 3-billion-year-old proteins in Jurassic Park experiments and helped define how life may have arisen on Earth and Mars.
References:
Marshall, S.M., Mathis, C., Carrick, E. et al. Identifying molecules as biosignatures with assembly theory and mass spectrometry. Nat Commun 12, 3033 (2021).
Hector Zenil, The 8 Fallacies of Assembly Theory, Medium (two versions, Dec 2022 and May 2023). https://hectorzenil.medium.com/the-8-fallacies-of-assembly-theory-ba54428b0b45
Steve A. Benner, Assembly Theory and Agnostic Life Finding. In The Primordial Scoop (March 2023) https://primordialscoop.org/2023/03/24/assembly-theory-and-agnostic-life-finding/
Hector Zenil, Narsis A. Kiani, Ming-mei Shang, and Jesper Tegnér, Algorithmic Complexity and Reprogrammability of Chemical Structure Networks, Parallel Processing Letters, Vol. 28, No. 01, 1850005 (2018)
Abicumaran Uthamacumaran, Felipe S. Abrahão, Narsis A. Kiani, Hector Zenil, On the Salient Limitations of the Methods of Assembly Theory and their Classification of Molecular Biosignatures, arXiv:2210.00901 [cs.IT] (2022)
Hector Zenil, James A. R. Marshall, and Jesper Tegnér, Approximations of algorithmic and structural complexity validate cognitive-behavioral experimental results, Front. Comput. Neurosci., vol. 16 – 2022 (2023).
Hector Zenil, Alyssa Adams, Felipe S. Abrahão, Optimal Spatial Deconvolution and Message Reconstruction from a Large Generative Model of Models, arXiv:2303.16045 [cs.IT] (2023)
