General Theory of Living Systems

Full Title or Meme

In order to understand or design any successful, continuing digital ecosystem, there must first be a general theory of living systems that we can use a template to build such a theory.

Context

In 1978 James Grier Miller attempted a General Theory of Living systems which proposed rigid taxonomies of levels of complexity and common processes contained in each level. As with all taxonomies of living systems, this one necessarily has very fuzzing boundaries which help a new learner, but which become an undue burden if carried to extremely fine detail. Miller understood all of this and selected a number of levels that best fit his data. None-the-less, this page will continue in Miller's path and try the same taxonomic approach, but first a short description of alternate methods. Whereas Miller thought that living systems were a subset of all systems, this page takes the view that all complex, successful, enduring systems are subject to the laws of evolution (specifically survival of the fittest) and hence should be considered to be living systems.

In 1979 Douglas Hofstadter started making the case that natural thinking involved "chunking" small ideas together to make a smaller number of classes of objects that hide the details in ways that were currently in process in "object oriented programming. He continued this line of development into the use of fluid analogies in our own thought as a model for how computer networks should work. Analogies (which we make constantly, relentlessly and mostly unconsciously) are what allow categorization to happen. "Our minds are constructed with an unlimited quality for 'chunking' primordial concepts, which then become larger concepts." As an example the word "hub," as in "Denver is the hub for United Airlines," brings to mind a large linked network of concepts that are "chunked" together to make up the commonly used term. Other examples range from basics like "wheel" and "node" to higher-order concepts like "spoke" and "network." Higher-order concepts are assembled from lower-order concepts. He believes there no fundamental difference in thinking with basic concepts and very large concepts because we don't "see" inside them. We build concepts by putting several concepts together and putting a membrane around them and giving that a name. Kind of miraculously these [interior] concepts disappear into the named high-order concept.

While high-level languages and object-oriented programming (OOP) were present in the early days of computing (e.g. MAD and Smalltalk), they did not capture a significant mind-share of working programmers until the release of Java in 1996. With OOP languages, encapsulation or information hiding became a recognized feature of computer system architectures. While this sound like "chunking", one of its purposes was to hide details. Whereas living systems create abstract chunks, information hiding created pieces that were sealed and did not expose details of the implementation. So information hiding does not allow for level crossing and does not share the capability in open systems for higher level systems to directly interface with lower level systems. Since this is a general theory, we cannot assume that information hiding is necessary or appropriate, although privacy advocates might disagree.

In 2007 Cleland and Chyba wrote a chapter in Planets and Life: "In the absence of such a theory, we are in a position analogous to that of a 16th-century investigator trying to define 'water' in the absence of molecular theory." ... "Without access to living things having a different historical origin, it is difficult and perhaps ultimately impossible to formulate an adequately general theory of the nature of living systems"

Bayesian Identity Proofing provides the means for a collection of authentication and verification steps to be validated.

Problems

Human cognitive process are limited and not nearly as logical as some believe.

Cognitive Overload

Human short term memory is extremely limited.

Users come to a web site to get work done, and what are they faced with:

• Authentication
• Registration
• Choices for privacy, etc. etc
• Stress of normal problems of life

Cognitive Dissonance

Human learning is based on causal relationships, primarily so that humans can know what to expect of any given situation. When something does not happen as their experience would indicate, they may find that they are at a loss as to how to react to the current situation resulting in confusion, or loss of context.

Level Dependencies

Each level of complexity depends upon the support of all levels, but specifically on the levels below it.

Just as civilization depends on the good will of the large majority of its citizens, so too a personal computer depends on the existence of some ecosystem where it can successfully be deployed.

Yet even the least complex life form, the virus or the management chip buried deep in some data center, can be the portal for and infection that will have consequences at the highest level.

Successful ecosystems

For an open ecosystem to be successful it must be resilient to change in every one of its components at every level. Since the ecosystem must dynamically evolve as new version of old components are constantly added and the results of many of those changes are unpredictable.

It is not possible to design an ecosystem in advance, just to design components with the best knowledge available at the time and introduce the new component, gradually if there is expected to be a great impact. For ecosystem changes, design thinking involves picking a way that the ecosystem should change and the designing a component that will help it move in that direction. Any design that depends on a completely new ecosystem is not likely to develop as expected.

Solutions

Taxonomy of Levels of connected Systems

Level	Name	Typical use	User Experience
1	Chip	Management of Computer	Only by Administrators
2	Board Computer	Internet of Things	Room temperature or video surveillance
3	Single Processor Computer	Accessing Web Sites	Simple Queries of web
4	Multiple Processor Computer	Local processing & virtualization	Mobile or Desktop device that maintains user info
5	Data Center	Collection of computers in a single location	Only by Administrators
6	Cloud (single owner)	Social Network	Interaction of user searches and tracking
7	Internetwork of Clouds	Maintenance of Names	User cannot access desired resourced for security reasons

Miller's "Processes" that work at all levels

Miller had 19 processes, the timer was added later. The boxes highlighted color are the ones that deal with energy or manner, not the primary focus of this presentation. Two special cases are the reproducer, which might include cloning, but is not further discussed here; and the boundary which is important for identity and information hiding.

Nu	Name	Function	Importance
1	ingestor	input food, parts, energy	Energy Matter, important to computers
2	distributor	move food, parts, energy	Energy Matter, important to computers
3	converter	Change from one form to another	Energy Matter, might be important to computers
4	producer	Establish relationships	Energy Matter, important to interconnections
5	storage	Could include a variety of back-up	Energy Matter, important for reliability
6	extruder	Social Network	Energy Matter, waste heat is an issue
7	motor	Maintenance of Names	Energy Matter, important for robots
8	supporter	How everything fits together	Energy Matter, important for maintenace
9	reproducer	Create new copies of self	Energy Matter and information, future concern
10	boundary	Maintains integrity	Energy Matter and information, allows identity
11	input transducer	detect changes or commands	all recorded external events
12	internal transducer	Internally created events	Tracks changes due to internal operations
13	channel and net	Looks externally in all directions	Ethernet, High speed local nets
14	timer (added later)	Internally generated events	Could be considered a part of internal transducer
15	decoder	Converts data to meaning	For processing at a more abstract level
16	associator	Learning	Intelligence, Artificial or otherwise
17	memory	static storage and remembering	Allows active searching
18	decider	Executive decision maker	Flexibility, reliability, adaptability
19	encoder	Converts internal data for reuse	Either for storage or for transmission
20	output transducer	Sends messages outbound	speech