Evolutionary Capacity:
Why organisms cannot be like machines

by Eric Drexler on 2009/08/02

I‘ve just posted a paper on evolution and the organization of complex systems at E-drexler.com. The paper discusses things like factories, paint, and conjoined twins to illustrate four crucial differences between machine-like and life-like systems.

As an update, I added a preface that outlines the thesis of the paper and explains why the title (“Biological and Nanomechanical Systems: Contrasts in Evolutionary Capacity”) is somewhat misleading — the topic is far more broad than that, and addresses fundamental questions about the relationship between evolution and how systems are organized.

Here’s the preface:


Biological and Nanomechanical Systems: Contrasts in Evolutionary Capacity

Despite its title, the paper that follows [posted here] is best read, not as discussion of nanomechanical systems, but as an exploration of broad and fundamental questions about the contrasts between biological organisms and machine-like systems of all kinds. It describes and analyzes the consequences of a pattern of profound differences between the products of design and the products of evolution, a pattern that is directly linked to their enormous and fundamental difference in evolvability. The reason for these differences explains why members of vast class of machine-like systems could never evolve, whether or not some of those systems would have potential functional advantages relative to the products of biological evolution.

The basic argument is as follows:

  • Evolvable systems must be able, with some regularity, to tolerate (and occasionally benefit from) significant, incremental uncoordinated structural changes. This is a stringent contraint because, in an evolutionary context, “tolerate” means that they must function — and remain competitive — after each such change.
  • Biological systems must satify this condition, and how they do so has pervasive and sometimes surprising consequences for how they are organized and how they develop.
  • Designed systems need not (and generally do not) satify this condition, and this permits them to change more freely (evolving in a non-biological sense), through design. In a design process, structural changes can be widespread and coordinated, and intermediate designs can be fertile as concepts, even if they do not work well as physical systems.

In reading the paper, please keep in mind the obsolescence (since 1992!) of my initial, 1986 suggestion of using small self-replicating systems as a basis for high-throughput atomically precise manufacturing. There are better ways to do the job, and it is perhaps unsurprising that factory-style systems are superior.

Thinking about machines in the context of self-replication did, however, draw my attention to deeper questions about the organization of biological systems, and why they are have so little resemblance to the products of intelligent designers. This paper is the result, and nanotechnology is almost beside the point.

The conclusions of this paper are relevant to current concepts of advanced nanotechnology chiefly because they explain what otherwise might seem mysterious: that systems entirely unlike living cells can, by several engineering metrics, implement better ways to perform atomically precise fabrication.


Drexler, K. E. (1989). “Biological and nanomechanical systems:
Contrasts in evolutionary complexity”, In C. G. Langton (Ed.),
Artificial Life (pp. 501-519). Redwood City, CA: Addison-Wesley


See the paper here:
  “Biological and Nanomechanical Systems:
    Contrasts in Evolutionary Capacity”


If you have a taste for abstractions at this level, see also:


{ 3 comments… read them below or add one }

Darius Bacon August 3, 2009 at 3:25 pm UTC

It should be interesting to compare this to Gerald Sussman’s more recent essay http://groups.csail.mit.edu/mac/users/gjs/6.945/readings/robust-systems.pdf on building what you call O-style software systems.

I noticed a bunch of OCR errors in my first pass through:

Parts have definite sizes, shapes, amid positions with respect to one another. [presumably should be "and"]
with a flange having a special shape arid a special pattern of bolt holes
It is easy to get. some rough idea of time probabilities involved.
In modern digital systems (which cant incorporate error-correcting codes)
error rates in fact can be made arbitrarily how through redundancy
such as continuity of skit, amid vascularization
time characteristics of O-style systems ["the"]
does not enable all imaginable evolutionary steps, hunt only some
Among time prohibited steps [actually, just search the whole page for "time"]
vertebrate retinas have their neural wiring mm front of their photosensors
the sensible structure, with time wiring behind. Why hasn’t. evolution flipped time vertebrate retina?
by introducing a new piece in the structure, Finally, ideas are typically adaptive, taking a form that depends on their relationships to other ideas, Design concepts
Inn considering the evolution of the protein machinery of modern cells, bacterial numbers and generation times are relevant,, since bacteria dominated the bio sphere for of years and eukaryotes are relatively recent.
it seems that the hatter would be a distinct and challenging goal
nanoreplicators will hue designed
the hatter will be shaped
not designed,, they are not necessarily structured in a way that lends itself to understanding Processes
from scratch, Because
it will he natural
evolved to evolve, Nanoengineering
artificial life will riot automatically be furthered
Eric Drexler August 8, 2009 at 3:32 pm UTC

@ Darius Bacon — That looks like an interesting paper. Back in my MIT days, Gerald Sussman was on my doctoral committee, so maybe I’d better read it, too.

(Re. the OCR errors, thanks for the help. I think these have been fixed.)

Gus K. August 14, 2009 at 7:49 pm UTC

Dr. Drexler:

Your paper reminded me of unrelated work by Elizer Yudkowsky and the Singularity Institute who argue, in essence, that engineered intelligent systems can self evolve into out of control systems of high intelligence.

While this is not directly related to your recent paper. I was wondering if you could briefly comment on their work.

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