COMPUTERS,
BEINGS AND MINDS:
DYNAMIC INTERACTIONS AND
APPLICATIONS
THE
CURRENT DOCUMENT IS AN OLDER VERSION[1] | NEW VERSION
FRAMES | NO
FRAMES
ANIL
MITRA PHD, COPYRIGHT © 2001, REVISED June 2003
|
The origins of this article are in
described in the first section: The Aims and Applications.
The interest was stimulated by the use of computers and the computer model of
mind. Specific applications are in the final section: The Applications So Far. One of the sources of my interest in the content of this article are in the my use of computation in research. The use was originally conceived as passive assistance. The concept expanded to active involvement of a computer. One application is to employs an outline of Evolution and Design which is arrange according to a materialist framework and rearranged in an idealist framework. Comparison of the two outlines using a database program yields information on the significance of the topics. This area of interest may be defined as automation of the knowledge or conceptual process. Thus far, the computation is an assistive tool but is shown to be capable of yielding novel information. A second source of interest lies in my work in mind. Do computers have minds, are they conscious? My view is that modern computers may be assigned mental qualities by convention but do not “know” in the sense of understanding. I believe that modern computers are not conscious. However, I believe knowledge and consciousness may be possible for computers of the future. To make these various cases I review a variety of concepts of computer and computation, of computational theories of mind, and of mind and consciousness. The computational theory is discussed in the section Theory and Concepts while mind and consciousness is discussed in a separate essay, On Mind and Metaphysics. I also outline an experimental approach to the development of knowing, conscious computers. This is discussed in the third and fourth sections Tools and Tasks and Implementation. I believe that idea of the computer – including but not limited to computational theory – is a useful comparison point for the study of mind. I am also interested, for similar reasons, in the more general idea of a computer as a being. Clearly, these two interests interact. Use of a computer in, say, conceptual research shows the capability of specialized intelligence though not, presently, of such hallmarks as understanding, intensionality and consciousness. And, an attempt to understand computers as beings or possessed of a mental character, even unsuccessful or only partially successful, may contribute to artificial intelligence, robotics and the understanding of mind as we currently know it. Summary Can a computer have mind, agency, being?
There is no irrefutable argument against the possibility. Modern theory is
reviewed toward this end and the related use of computers as a co-agent in
human tasks including knowledge. How will computer agency come about? In
addition to theory and experiment, two essential points are: first, computers
will have hardware and software evolution that is not fully driven by their
design... and part of the evolution will be of the device as a whole; and,
second, the evolution will be in contact with human [and/or other beings]
which will result in transfer of and mutual participation in agency. If we
were to meet a device from outer space how would we recognize it as an agent
as having mind? Theoretically the question is interesting but it is necessary
to go beyond the Turing test. Criteria such as adaptation to an environment,
evolutionary levels that are not flat are a beginning. But, at the present
time, intuition and empathy appear to be the best candidates to recognize
agency. |
What
is the Meaning of "Dynamic Interactions of Computers, Beings and
Minds"?
Document
Production and
Maintenance
Document And Knowledge Storage And Retrieval
Research,
Conceptual Synthesis
How to Get a Computer to Think
Recognizing Thinking, Mind, Consciousness
Knowledge Representation... Models of
Representation
Topics
in Artificial Intelligence
Knowledge-based systems and applications
Information and meaning modes:
A set of tools for research and social
application
Peripherals, sensors and motors
Evolution
and life - a concept
Some elements of the computer environment
Standard
software as meaning processors
Miscellaneous Knowledge-ware Aids
6. Appendix: Software Classes and Listing
Applications Development System
Production Level Data Processing
Multimedia - playback, production and
development
Knowledge and Knowledge Systems, Artificial
Intelligence
Design, Decision, Planning and Government
Dynamic Interactions and Applications
to
Uses of Computers in
Research and Synthesis of Concepts and Knowledge
Understanding and Mechanical Reproduction of Mind and Being
Management of Research
A Project for Storage and Access of All Human Knowledge
This document had practical beginnings that are reflected in the Aims, below. In addition to an intrinsic interest, I turned to theory to further my practical use of computers. Since some of my research is in mind and being, my interest in computation is twofold: computers as tools and computers as objects. The developments of machine as an object and as a tool are mutually enhancing. Computer as object is an approach to the study of mind and being; the function of mind and being is an approach to understanding computation. Beyond modeling and simulation, there is an interaction between human being and machine that extends human abilities and enhances the performance of the machine. This interaction is dynamic in a way that is described below. Not all of the performance of machines or computers is designed. Although a machine can be designed, the machines of a hundred years from now may be envisaged but cannot be designed. Man and machine are in mutual evolution and the outcome will be the result of design, opportunity and mutual conditioning.
This document is a design for a program to further the dual and interactive aims of using computers in my research and developing computers as objects. The research use is organizational and in the actual research process. The latter is both mechanical and intelligent. The approach will be to focus on designs, dynamic interaction and co-evolution of human being and machine.
The key terms that need to be explained are computer, and dynamic interaction. It will be useful to consider the concept of Modeling before that of dynamic interaction. The focus here is on the use of computers and therefore the mind, being and the concepts of mind and being are important in order to know whether modeling is faithful. These topics and their interactions are further considered in Mind and Metaphysics.
The following discussion is much improved in Journey in Being
There is a theoretical and a practical aspect to the concept of a computer. The theoretical side is that a computer is a digital information processing and communication system[2]. The practical side is that modern electronic computers store large amounts of information and process information rapidly; this practical capability means that significant theoretical potential can be realized. Computers can simulate mind and robots[3] can simulate being. Computers can simulate robots and being. Thus computer programs can be written to simulate being. That is, living systems can be simulated. Regarding simulation, two questions arise. Can the performance of machines reproduce the performance of human and other beings? And, even if machine input-output is faithful to human input-output, can such a machine have a mind and consciousness in the way that a human or other being does? Some considerations follow.
Computers are (1) designed to perform a theoretical function, which, due to faults, they do with a degree of success. It is the performance of this function that defines a computer. Computers are (2) manifested in objects. What degree of mind, being and consciousness do they have in virtue of (1) and (2)? As objects, are computers any different than a rock that has minimal qualities of mind, consciousness and being when compared to animals? As regards the designed function, which has to do with an assigned semantics - mind, consciousness and being are assigned or derived and highly contingent. Is there a way to overcome the derived quality of the "mind" of a computer? One way may be through co-evolution of (human) animal and machine. In such an evolution, the derived quality of machine-mind would become intrinsic, part of the object-hood of the machine and not merely the designed or assigned function. At that time, with growth in understanding, it may be possible to design and build mind into generic systems. Another way is to start with a consideration of the source or origin of mind in living beings.
Living -and mental- systems are not designed. Rather, they are the expression of deep properties of the elements in a way that designed systems are not. The object-hood of living systems coincides with the function. Mind and consciousness, on the material model, are expressions.
What makes living organisms have mind and consciousness? Note the deep grounding: every cell in the body is a variant of the protozoan cell; the protozoan cell is grounded in inorganic matter; every cell has the entire genetic code...
The statement that systems with minds are not designed is an approximation that holds in the initial stages of physical evolution. Once life comes into being it is part of the environment and is, therefore, self-conditioning; this is not initially intentional or by design. Life itself has no designs in its beginnings. Later, as the mental aspect of life becomes prominent, the environment is conditioned by designs and this, in turn, affects the evolution of life forms. Finally, through mind, life can recognize the effect of its actions on its own evolution and make connections between its actions and outcomes for its own evolution. This is design; the claim is not that life completely designs itself but that its designs may enter into the evolution of its forms in an intentional way. Reflection shows that the evolution of machines and technologies has a similar aspect. Established technologies are not the direct result of plans on a drawing board. At each stage of development there is mixture of happenstance, intentional design and selection.
Another practical aspect has to do with the analog-digital distinction. Roughly, a digital machine is a discrete[4] state machine while the states of an analog machine constitute a continuum. The states of a machine are discrete when there is a finite “gap” between any two states. Even though the actual states of the machine may constitute a continuum, a computer is, by design, effectively a discrete state machine. Since control of a discrete state machine is usually explicitly from one state to the next, the states can be assigned symbolic values and the machine designed or programmed as a symbol processor. Typically, machines whose states effectively constitute a continuum model other systems by a direct correspondence of the physical dynamics. It is not necessary for the discrete / continuous distinction to correspond to a symbolic processor / analog processor distinction. There are potential situations where the physical continuum properties of effectively discrete state machines come into play in a useful way. It may be useful to understand the actual properties in understanding fault behavior. Despite the promise of digital machines it may be useful to include analog or combined analog-digital modeling[5] in the development of computers as objects and tools.
In the meaning used here, a system models another when it reproduces certain definitive characteristics. What are the definitive characteristics of mind? In deciding whether a machine has a mind or is conscious there must be, in addition to practical recognition[6], an appeal to theory - to definitive characteristics. This is one reason for the importance of theory. There is no -generally agreed upon- final characteristic or set of characteristics. See Mind and Metaphysics for some considerations on characteristics of mind and consciousness. Theory and modeling will develop in mutual interaction.
In general, modeling includes but is not identical to simulation. The concept of simulation is the reproduction of input-output performance. According to behaviorism, mind is input-output performance - simulation is modeling. However, if there is mental content, if there is consciousness, if there truly is mind[7] - then simulation of mind is not modeling.
There are two extreme views to the nature of the uses of computers. In the first, a computer is a mere tool[8]. The second view is that computers can model and replace human and other beings. A better approach to the use of computers is to focus on the interaction between computer and human being - between "man and machine". Practically, the combined performance exceeds the individual performances of machines or of human beings. The combined performance is not merely additive or interactive. The mutual interaction has the potential to modify both the machine and the human being. Through design and evolutionary interaction there is a potential to transfer human capabilities and characteristics to computers. This entry of machines into the loop of being is what I call dynamic. In a preliminary stage the machine is a dynamic extension; then the machine is recognized as having a degree of autonomy - as being in dynamic interaction with human being.
Modeling and theory are a part of dynamic interaction. There is a dynamic loop: model - performance - altered model. This a is part of the dynamic interactions.
The outline is as follows:
Aims and Applications
Theory and Concepts
Tasks and Tools
Implementation
Aims and Applications and "Theory" follow the same application driven outline. Tasks and tools include a toolkit for implementation. The plan of implementation is to develop the applications.
The original purpose of this document was a design for the use of computers in my research. This had two aspects. They were document management for my research and management of a research group. The group was needed because of the breadth of my research interest. The objectives of the document evolved in a natural way into the system outlined below in Automation. For the aims of assisting and dynamic interaction in research, modeling of mind and being enters in two ways: as a research topic and as part of the theoretical base for design of assisting / dynamic interaction systems.
As archive - Word processor, text, html
For print - Word processor, publisher
For Internet - html, web editor
Setting up communication[9] through electronic networking.
This also relates to research and storage of document systems.
Personal
Enterprise
Research - see Bibliography on Research Organization and Leadership for details
Group and projects organization, creative process, group communication
Funding and support of research
General administration and management
Kinds of tool - assist, interactive or dynamic, independent
Synthesis
Mind
Intelligence
Consciousness
For concepts, ideas for experiments: Mind and Metaphysics.
Interest in "artificial being" [or agent, life...] is twofold - I stated this above. A robot is an artificial being. It is also interesting to simulate or model both being and robots. This can be done philosophically, mathematically - and through physics, biology and psychology, physically - with another robot or physical model, or through computer programs. Computer programs would simulate or model - be designed and treated as "being objects". Here is a significant question. How will a simulation or model be faithful to "being-in-the-world"? "Being-in-the-world" includes consciousness, intentionality and so on. How will faithfulness be recognized or known? Is there a theory that will permit recognition of faithfulness? Will that theory be the same as the theoretical simulation or modeling? These issues are elaborated below.
Design and fabrication. A special case of this is programming.
Evolution
Transference from known agents of thought and consciousness to machine. This could be by design and overt or could come about as a result of designer investment and interaction.
Once the machine can think or simulate thinking or have consciousness, it can enter these processes as an agent in the case of thinking or consciousness or as a quasi-agent in the case of simulated thinking.
Combinations and synergies of the above.
Perceptual: similarity – comparison,
analogy, empathy
Perceptual: dissimilarity – openness, abstraction… from functions and signs
Conceptual: from description of the perceptual to abstraction, generalization, concept and theory formation
It is argued, with some validity, that recognition of mental phenomena in others is automatic. However, this is not true for all mental phenomena. There is also the issue of recognition in the case of other kinds of organism and in machines.
Theory is driven by: needs for the aims and applications, and by the standard body of theory.
In the disciplines of the cognitive sciences, Cognitivism has a special meaning. It is the thesis that the mind is essentially similar to a digital computer. It is not merely that the mind or brain can be simulated by a computer - that is Weak Artificial Intelligence; and it is not quite that the mind is a computer program - that is Strong Artificial Intelligence. Cognitivism is an approach to understanding mind and, equally, it can provide understanding of computation.
For Cognitivism to have a definite meaning we must have a concept of what is computation and what is mind; and we would like to know how computation is instantiated in a computer and mind in the brain. There are a number of conceptions of a computational theory of mind such as formal symbol manipulation, connectionist cognitive modeling, theory of computation[10], and information processing.
What are the aims of Cognitivism? And what should they be?
To answer these questions Cognitivism should be placed in a broader context. Cognitivism is a very specific thesis about the relation between mind and computation. The broadest context is of being and machine and the most general relation is the evolution in which the dynamic interaction modifies both agent and machine from their initial being and the dynamic interaction is greater than their mere addition. Both theory and practice are important. In a future evolved state, theory will give only a partial understanding and the synthesis of agent and machine will be necessary to sustain development. A glimmering of this is available in the use of computation in mathematical proof where it is beyond human capacity to explicitly check the steps in the deduction.
It is necessary to know sufficient cognitive theory. This includes the topics of Cognitivism, strong and weak AI, related fields and main theses, theory, developments.
It is also necessary to know sufficiently about consciousness, mind and brain. The following is a brief list.
Neurophysiology, mind and consciousness: Edelman's model for neural "production" of mental phenomena is interesting for its logic - it is one of the few attempts that is based in careful consideration of the nature of mental phenomena, coherence and results - Edelman does not claim completeness nor does it do everything claimed. However it is one of the best attempts to date and such attempts should be combined with the computational theory of the mind.
The nature of mind - consciousness, intentionality... and cognitive ideas such as "language of thought"...
Further discussion of mind and brain is in Mind and Metaphysics.
Just as it is necessary to consider the context of cognitivism, it is also necessary to consider the context mind and computation. This is the content of "agent and machine".
Alternative terms are: for agent - being, human being, and intentional being... and for machine - tool, computer, and digital computer...
In this topic also consider: what is the nature of the categories "mind" and "matter"... are they fundamental -and if so what are their natures and relations - or are they high level derived concepts. In the latter case what do we see as fundamental and what are "mind" and "matter" in the fundamental context?
Make sure to also review models of representation and perhaps make "knowledge representation, research, concepts..." a separate section.
Expand "Artificial Intelligence" to AI and Robotics [Artificial Being] and... and add some relevant details.
Changing systems, evolution... the objective is to have a model not just of knowledge representation but of the evolution of knowledge - how knowledge changes. Strict representation is not needed or desired. It is not the first objective to produce an encapsulated system that will be used mechanically and produce a result. Rough representations can be used and are initially desired. There is no initial commitment to a fixed system and method. The software and human interact: the software is designed and built - as simply as possible; it is applied to a knowledge system that has been tailored for application; the results are interpreted. In summary, the process is interactive at a number of levels and human interpretation is important. An example of the way the process works is given next in "Alternative Representations".
Review models of representation, models of evolution of knowledge and research concepts.
Meshing - the idea is to compare alternative representations of the same system of knowledge and learn from the comparison. An example is given in the section on Implementation.
Production systems, neural networks, genetic algorithms and programming, computer vision, search including heuristic search, planning, logic, knowledge representation and reasoning, managing / reasoning under uncertainty, common sense reasoning in logic, Bayes networks, automatic planning and multi-agent communication, robotics and computer vision, machine learning, intelligent architectures - connectionist or associative vs. von Neumann, and natural language understanding and processing, interactivity, narrative, and artificial intelligence.
Declarative knowledge representation methods. Time and action, non-monotonic logics, causality, inheritance and description logics, ontologies, contexts, knowledge acquisition and reformulation, multiple views, abstraction, deduction vs. abduction, knowledge and other mental attitudes.
History: knowledge (declarative) vs. procedure based systems.
Knowledge-based (expert) system technology is the most widely-used application technology to emerge from AI. Topics: basics of knowledge based systems (KBS) and expert systems (ES); technology transfer from research to industry; knowledge engineering, KB programming, knowledge acquisition methodology; evolution of the technology as applied to business and government problems, current and future impact.
Manipulator kinematics and inverse kinematics; manipulator dynamics, motion, and force control; motion planning and robot programming. Robot programming topics include: basics of motor control and sensor characteristics; sensor fusion, model construction, and robust estimation; control regimes (fuzzy control and potential fields); active perception; reactive planning architectures; various topics in sensor-based control, including vision-guided navigation. Some increasingly complex behaviors for mobile robots: simple dead reckoning and reactivity, planning and map building, communication and cooperation.
Issues and techniques of computer vision. Image formation, edge detection and image segmentation, stereo, motion, shape representation, recognition.
The objective: what are the tasks - and what are the tools necessary to perform these tasks? The tasks are the functions or applications. The set of tools, then, is a toolkit necessary to perform the tasks, to build the agents to perform the tasks. How do we get a toolkit? The functions or tasks are those of (human) being. One approach is to consider a robot that is to function like a human. Consider the elements that build up the basic functions. Dual consideration of robot and human has the effects: 1. Focus on the robot draws attention to the elementary components of the toolkit - from a design point of view, and 2. Focus on the human encourages completing the tasks and to possible functional and intrinsic shortcomings of the toolkit. The shortcomings will point to incompleteness of the kit but will not detract from utility.
Provisional hypotheses: the phenomena of the world are causal - effects or data reaching the robot or human bear signs of the world. Upon receipt there is translation of data in sense organs to neural signals, transmission to the brain, synthesis-processing-sorting, transmission back to the periphery and motion. This story omits details and levels of neural and extra-neural processing.
A robot needs sensory modules, transmitters, processors and motion modules.
A human perceives objects, patterns, and whole phenomena. This is perception. The human can recognize various aspects to objects - color, shape and so on. The robot will have various sensory and kinetic modalities but will also synthesize them into percepts. Percepts and their surrogates or symbols are the content of thought. Thought is inherently geometric and algebraic, synthetic and analytic, and iconic and symbolic. If, for the robot will also process in appropriate modalities. For the robot the processing is programmed; how are the geometric and algebraic modalities programmed? Are the modalities intrinsic or simulated?
What kinds of programs? Perception - vision and so on. Thought - iconic and symbolic. Iconic thought modeled on the perceptual programs? Symbolic thought includes language, logic, and mathematics. A low level example of a language processor is a word processor; almost all of the language function is assigned and interpreted. Other low level processors are database programs and mathematical processors including spread sheets. Motion - gross bodily motion, speech, and affect.
In the case of the robot the builder assigns: semantics, meaning, consciousness-subjectivity, intentionality. For a human these are intrinsic. The robot's processing is programmed; the human's is not - even if there is a program. How will a robot have such intrinsic being-in-the-world? In a number of senses the human is a multi-layered bottom-up entity: organic molecules-nucleic entities-cells-...-organs; the aspects of the being-in-the-world do not manifest at high level organization and processing but begin at the level of sense organs; in these ways the human is tied in to the world. It seems that the intrinsic intentionality and so on of the human are related to this tying in. The robot is rather aloof - the processing is centralized, the being is assigned rather than intrinsic. This is not necessarily a problem for a practical robot. But for a robot to have being, there must be some internal structure that makes its being intrinsic. How does that structure do this? This is the problem of the homunculus. How would a robot be built to be more like a human or animal? It is not necessary for useful robot design to be modeled after human design but the question is both conceptually and practically interesting.
Robots and connectionist architectures.
An outline of the listing is as follows. (1) Information and meaning modes, (2) Machine modes of information representation and processing, (3) High level processing and software, (4) A set of tools for research and social application, and (5) Human agent. The inclusion of the human agent has the rationale that a fundamental approach to machine intelligence -life, mind, consciousness, being, agency and so on- is through transference of abilities from human to machine.
There are two basic questions. What are the human modes of information? How can these modes be realized, processed mechanically? The following modes, singly and in combination, imply a range of hardware and software.
Sensory
Symbolic
Pure symbolic
Compound
Perceptual: symbolic - sensory
Semantic: symbolic-meaning
Analog
Digital
Hardware implemented
Programmable
Software implementation
Capture/entry
Translation, conversion
Synthesis
Production
Transformation
Communication
Data, language, logical and mathematical representation and processing / processors.
Iconic depiction and processing.
Listing of useful software classes is in an appendix. The classes listed are those of potential use for the objectives - The Aims and Applications- and the Theory and Concepts. Examples are operating systems, application development systems, artificial intelligence, technical and professional software, and business systems.
The main classes are:
The application is general but includes -as an important special case- administration, management, and performance of research and conceptual synthesis.
Literature Tools and Knowledge Resources Print, Other Media and Electronic Storage // Text System Tools // Text and Electronic Multimedia Production // Library Tools // Tools for Communication of Ideas, Concepts, Knowledge
Interaction and Communication Tools
Dynamics of Knowledge: Origins, Nature, Transformation and Application - with tools
Software and Applications Development Tools
Administration and Resources [support]
Field Applications Implementation Tools
Interactive communication center // Problem - resource center // Human resource: observation, communication, and action.
Information Processing Tools - see Information and meaning modes for details.
Representation, databases, storage, search, transmission / communication, networking
Local / wide area networks; private / public information networks; Internet
Libraries and other repositories [networked]
Dictionaries, encyclopedias
Human knowledge: conceptual schemes; field(s) of concepts; origin, growth and transformation of schemes - modes: iconic and physical [perceptual] to symbolic, atomism and pattern, symbol as icon, recognition and originality in symbolism [this does not even occur without experience and is implicitly experimental].
Idea scratch pads
Tree representation of knowledge and concepts; [R]DBMS[11] representation of trees
Question and answer
Reference systems: informal, primary, secondary, and tertiary sources
AI and other knowledge / research tools
Iconic processing [multimedia]
Symbolic processors; programmable processors and automation
DBMS have built in automation for reorganizing tree-hierarchies. They therefore have the capability -with appropriate input- to reorganize knowledge and conceptual schemes. There is potential for production of knowledge and understanding based in automated and manual meshing of alternate schemes.
Document [word] processing - contents, index, cross-reference and hyperlink; html editor/translator
Production, publishing, presentation
File management and linking
Write once / many
Read-write accuracy and speed
Access: random / sequential
Volatile / permanent
Permanence / reliability... and strategies for desired degrees of permanence and reliability
Safety: [multiple modes of and multiple] backup
Security: encryption, protection
Accessibility: standardization of formats and readers [&markup], search, networking and communication
Speed
Reliability
Single / multiple
VLSI and other technologies
Communication: processor-processor and processor-peripheral
von Neumann / parallel / connectionist
Environment conditions: humidity and wetness, marine and submerged; temperature... polar, desert; atmospheric: caustic, corrosive, dust and particulates, pressure extremes; space; industrial. Acceleration [g] and shock.
Interface: machine, animal, communications, human
Mobile/stationary factors: size and "footprint", weight; mounting and carriage; modularity - plug and play; power source - external / self-contained and local / imported; durability; communications.
The sources of the concept and objectives for the implementation are in the previous sections.
The possible
Machines with minds - intelligent and conscious machines? Cognitivism and the computational theory of mind. Theoretical, experimental, evolutionary approaches. Careful analysis of correspondences between the functions and systems of machines -computers and robots- and those of living entities. Connectionist or associative vs. von Neumann architectures. For some details see Mind and Metaphysics.
Theory and tools
Design and evolution with self-design - and non-design effects
Simulation and computation of design... and of evolution
Simulation, modeling and experiment
Brute force or massive computational
power and
intelligent deployment
- optimum combinations.
Computational functionality and simulated environments.
Software and hardware.
Software vs. combined hardware and software approaches. Final or ultimate validity of distinctions between software and hardware; do the concepts of software and hardware exhaust modes of description for computation?
First use existing / commercial applications; then develop applications around the existing application base; then develop stand alone applications - even custom applications can use standard code and be tailored to use standard applications. An exception is when the learning associated with development is useful.
Develop assistants when sufficient, then interactive and dynamic systems; then emulators and agents.
Intelligent deployment and development of computation at all its levels and in all its capabilities in the tasks for which it is suited - rather than exclusively as an imitator of human intelligence. This is not a statement against projects to replicate human intelligence and being.
This follows the outline of the applications.
For planning, growth of being; dynamic application
Comparison with printing... writing? Just as rooms, books create environments that foster "creative spaces" so do computers. Computers can simulate these other spaces but, more significantly, the nature of the environments that may be made possible by computers -on account of their massive storage, processing and representational capabilities - have potential and are in co-evolution with human designers and users.
Learning the environment
Logical structure to file organization systems
Interactive, graphic interfaces... interactions with intelligent, customizable interfaces and with other individuals and groups through the interface
Ubiquitous presence
Automation
Number codes for concepts
Large screens -- large virtual desktops and documents // Partitioning the screen // Multiple screens and/or windows... and multiple applications and documents // Cut and past between applications and windows // Multiple workspaces
Draft vs. production formats and screen layout
Document navigation systems
Reformatting and changing styles
It is not implied that the meaning is intrinsic rather than assigned any more than for books and a printing press. However the interactive, kinematic environment of computers has the potential to become dynamic and simulate meaning.
RDBMS, word processor, spreadsheet, planner and project management - e.g. numbered outlines are conceptual representations; then transformations of the hierarchy are transformations of concepts.
Storage: e.g. documents, document systems, human knowledge project. Search and retrieval. Searching documents and text. Keyword search; menu / tree search; leafing through electronic documents.
Research, production and publication: print and Network
Update and maintenance: complex document; changes in one part affect other parts
Linking
Generic outline: connection to past, future and literature
General systems: encyclopedia, educational curricula
Specific systems: Being and the Elements of Being, core curricula for science, engineering, and humanities
Text production templates
An encyclopedia as a database; listing all articles; conceptual and alphabetic organization. Dynamic uses, human knowledge project.
Idealism-materialism based on the outline of Evolution and Design. Evolution and Design as a database.
Note Evolution and Design is a conceptual organization of human knowledge based on an evolutionary paradigm.
Being and the Elements of Being [ no frames ] includes a search for alternative and complementary paradigms. Such paradigms are based in being vs. origins, timelessness vs. the temporality of evolution.
Knowledge representation - File directory structure - Bookmarks - Hyperlinks
Representation by and transformations among (a) organization into files and collections (e.g. by an operating system such as Windows 2000 into files and directories or folders), (b) text and other data organized as an hierarchic outline including numbered outlines, (c) organization of information in Bookmark files by Netscape Navigator. Since Netscape is used by Britannica to browse and search the Britannica database this is useful.
Scratchpad
Conceptual experimentation
The classes listed are those of potential use for the objectives - The Aims and Applications - and the Theory and Concepts. Examples are operating systems, application development systems, artificial intelligence, technical and professional software, and business systems. The choice of classes is determined, also, by a number of principles stated above. The first is that of having an [open ended] toolkit. Secondly, regardless of detractors, standard software is important. Cleanliness is not a fundamental objective. The essential objective is the maximization and construction of being. A final principle, not stated above, is that modes of realization are undetermined; therefore the toolkit will, in addition to being logically designed, include a miscellany based on intuition and happenstance.
Networks: management, operating systems, Internet
Communications: E-mail, fax, message center, video/teleconference, telecommute
Development: compilers, languages, visual environments, cross compilers, debugging and testing
Processor control, memory management, file management
User interface - batch / interactive, remote / local, system vs. application level access, GUIs, network interface
Multiple operating systems
Device drivers
Word, text processors, fonts, font utilities - general, scientific, other; numeric, array and spreadsheet; database management; graphic - draw and paint - and photo; CAD; video, sound, music and speech - recognition and synthesis, musical instrument digital interface (MIDI)
Paint and draw, format converters, scientific, presentation, clipart/multimedia
Publishing, desktop publishing, typesetting
CD-ROM ware (includes knowledge-ware)
AI/expert system, AI based design and planning tools
Mathematics and Statistics; Science and Engineering
Interactive classroom simulation, computer based training, text and media development
Law, Medicine and Engineering
Medical, psychiatric and other therapeutics and management - managed care planning
Business and finance, industry and agriculture, service and service industries, and trade
Grants
E.g. information/communication system as extension, and as co-agent or co-being
[1] The accuracy of this document – and the footnotes – regarding robots, digital machines, computation and its theory is capable of improvement. I have let the current document stand as it is since it is superseded by a new version
[2] This concept can be made more precise and fleshed out through concepts such as “algorithm”. Digital -in contrast to analog- processing can be made reliable to any desired degree. Many real processes and problem solutions can be exactly or approximately simulated by a digital processor. Thus the digital nature of computation is also a practical point
[3] A robot could be defined as an information processing, communication, and decision-action system. This could be regarded as a generalized definition of a computer
[4] Usually a finite state machine
[5] A significant theoretical question is whether discrete and continuous mathematics are equivalent. If they are, the distinction between analog and digital machines may be -at least theoretically- unimportant
[6] Through development and participation in a mutual context and the resulting empathy that includes implicit appeal to reasoning of the form “like effects imply like causes”
[7] True behaviorism is outdated. A true behaviorist would argue that mind or consciousness is behavior
[8] This calls into the question the nature of “tools”
[9] Dissemination
[10] Theory of computation is based in the Church-Turing thesis and Turing’s theorem as a result of which a universal Turing machine can compute any algorithm. The transition from machine to mind is in the idea that, since many human mental abilities are algorithmic, the mind may be a universal Turing machine. There is an issue of whether syntax is intrinsic or assigned. There is an issue of whether semantics is realized in computation. In proof theory, within limits, the semantic relations between propositions are completely isomorphic to syntactic relations between sentences. Thus if the syntax is intrinsic so is semantics
[11] DataBase Management Systems are flat or relational