project


A. The business problem
Large organizations don’t work as one body. This is problematic, because of numerous reasons. To name just a few common ones:

  • The agenda, priorities, focus & policies of higher management may not be known or implemented by the lower level units & employees, leading to garbage factories, missed targets & activities not aligned with company policies & agenda
  • Adapting to changing business environment is slow in large organizations, because of the difficulty in changing both processes and value streams, as well as the mindset & knowledge of the people running them
  • Problems and threats, or on the other hand innovative ideas and opportunities are not handled because they’re usually not propagated from the lower level units to the executive level
  • A need for activities in one unit, with not enough resources, can’t use free resources in another unit, as well as existing know-how or goods already achieved in other units

B. An analogy: blood vessels
Blood is the source of life to all organs and cells in an organism’s body. It supplies all cells with the inputs required & returns their outputs. It carries commands sent from the brain to organs, via hormones, as well as the necessary chemicals & food the body tissues require. It also spreads solutions for disease agents across the body.
In order to reach every cell, in all organs of the body, the blood vessels are organized in an hierarchical structure, starting from the heart & lungs, and spreading downstream till every cell, & back to the lungs & heart.
Blood flows in frequent cycles, circulating the means of life continuously across the body. It interfaces with the cells via special membrane controlling the flow of materials in & out of cells.

A business enterprise is a large multi-cell organism, that uses knowledge to transform supplies into goods, in a complex value stream. What ties the multiple humans working in an enterprise into a large super-organism, are the communications between them, that coordinate the processes comprising the value stream to drive the enterprise to survive & grow in a dynamic market environment.
However, we believe that these vital human communications are based on paradigms that were established & formed in the pre-computer-mediated era, & for sure before the new social interactions paradigms of the Web 2.0.
We suggest a simple mechanism, inspired by the architecture of blood vessels, for making the communications inside the company flow from the top management to all employees, and also across the entire organizations, in order to help the enterprise work as one body.
C. Social media capabilities
We propose new social interaction “vessels”, flowing from the CEO, through the organization structure, to every employee, and also aggregating the responses from the employees all the way back to the CEO. The basic component of social interactions is a simple short text (the kind passed in services such as Twitter, normally limited to the size of Short Text Messages), along with simple discussion semantics such as “in-reply-to”, “for”, “re” prefixes. It’s highly important that the input from employees will be in this open-ended form, & not forced into any structured schema form, in order to promote the discovery of insights not known in advance, and the emergence of bottom-up new usages of the system. The text can contain marked tags, that characterizes its content, either given by the user, or automatically marked by the system. The system will query users every day for status messages, that may contain such information as their:

  • priorities & focus
  • risks, undesired effects & problems
  • achievements, opportunities & value drivers
  • work status, load & health
  • requests & questions

Querying can be done in any communication channel used by employees (IM, SMS & Email, &c).
Every day, each employee will also receive a collection of messages from the hierarchy path above it, from the CEO, to its direct supervisors.
Using the tags, messages can be passed between users not in an hierarchical path, just on the basis of similar tags. Tags may also be collected in user’s profiles, so that a user who once wrote a message containing a certain tag, will receive future messages with that tag by other users.
Every manager will receive daily a collection of messages from the hierarchy path beneath it. Aggregation, clustering & classification can be done on the responses, to make the results arriving upwards summarized. Visualization methods can be used for presenting a GUI that enables both topsight view of the aggregated results, and ability to explore area of interest.
Messages may be marked with an importance indicator. The higher the importance a message is ranked, the more exposure it will have across the enterprise.
Users will also be able to vote on other users messages, & increase their rank & exposure.

An important use case is with risk management. A user may enter a message describing a risk it wants to put to discussion, and rank it with high importance. The message will be exposed to many other employees across the enterprise, that are related to the tags in the message. Their responses will form a multiple stake-holders discussion, which is the best known way to prepare & address risks.

When considering the extended enterprise, certain units & employees interact with external people (suppliers, partners, customers &c). The flow of social interaction can flow through them to the external people, & back to the CEO. Similarly, the chain can start from above the CEO, e.g., main share holders, allowing them to both interact with, & learn on the overall, current status of the company.

The frequency cycle of this process should be as high as possible, such as 1-2 days, but can also be once or twice a week.

D. The utility of solving the business problem social media capabilities
Unlike the common communications practice in today’s common enterprises, in which the the frequency of communications between the top executives and the employees of the lower level units is limited to 1-4 times per year, and usually also limited to unidirectional communications, the suggested capabilities can foster bidirectional communications on a daily basis, flowing from top management to all employees, and also between employees across the enterprise. This is very likely to address the common reasons given above why enterprises don’t work as one body:

  • The agenda, priorities, focus & policies of higher management will be known & implemented by the lower level units & employees, leading to the elimination of garbage factories, met targets & aligning all activities with the company policies & agenda
  • The frequent circulation of knowledge on changing business environment, and the way the company adapts to them, can create positive feedback loops, that incrementally change & adapt processes and value streams, as well as the mindset & knowledge of the people running them, to the changes in the business environment. Using today’s practices such adaptations can take years, but may be reduced to only weeks using the suggested capabilities.
  • Problems and threats, or, on the other hand, innovative ideas and opportunities will be properly propagated from the lower level units to the executive level, which will enable their effective handling & value extraction
  • A need for activities in one unit, with not enough resources, will be communicated to other units with free resources, or relevant existing know-how or goods already achieved, which will enable collaboration, higher resource efficiency & considerable time saving.

The main benefit for the end-users will arrive from the much stronger bonding & involvement with the entire organization, that can make employees feel more motivated and appreciated. Other obvious benefits are greater responsiveness from their management, & stronger collaboration with other employees across the enterprise.

E. The information that will be collected and how it will be useful for the enterprise
The communications that will circulate in the social vessels may contain valuable information, of many kinds:

  • Risks & threats that may be handled immediately after they are discovered, instead of after they cause their damage
  • Opportunities, value-drivers and innovative ideas that will arrive to the executives that can understand their value & decide on their implementation
  • Trends that may point out problems, and emerging changes, that can be handled before they are reaching a critical mass or serious effect
  • Insights on external factors outside the company, that can arrive even from low-level employees, and hold important strategic opportunities or threats

Once the collected information reaches a sustainable size, it can be applied to analytics that can provide both macro insights on the status & health of the entire organization, and well as micro insights on bottle-necks and inefficiencies that can be removed to effect bottom-line profits. For example:

  • Analyzing negative sentiment in messages, based on Natural Language Processing, can indicate trends in cultural health problems, in certain area of the company or across the organization
  • Aggregated messages tagged with over-load, at certain units or type of resources, may indicate a bottle-neck that delays other units & processes

F. Ensuring privacy and security of information gathered
While the querying interface of the system to employees are common media channels, such as SMS, IM & Email, the outputs of the system (collection of message from the hierarchy above, and aggregated responses from the hierarchy below) are presented in a Web application, that can be protected by any standard of security, for both authentication protection and authorization. Messages can also be marked with security level, to make them available only to employees with access to this level. Any other organization policy, taking into account organization structure or roles, can be applied to determine authorization to view messages.

I read a few years ago about the DARPA CALO project (Cognitive Agent that Learns & Organizes), or was it the PAL project (Perceptive Agent that Learns)? Anyway, I was quite amazed, because I was thinking back then about similar architecture & technologies. Well, about a month ago, they decided to actually ship the technology, & open its source!!!!

It's called OpenIRIS (http://www.openiris.org/), & it's a "Semantic Desktop", in which you work on your applications (Browser, Mail, Chat, Calendar, Tasks, Documents &c), & behind the scenes everything is analyzed & organized in a beautiful ontology (!!!) that enables you to "Integrate. Relate. Infer. Share.".
DARPA just paid researchers from some 22 universities, to actually go & implement the semantic technologies that have such huge promises, using today's paradigms & technologies.

I've started playing with it a few weeks ago, & today decided to actually use it. Well, I'm holding my hands from evangalizing (except for the post's title), but I'm quite impressed from the result! There are some small problems, & the giant platform is slightly slow, but the basics seem to work – some giant OWL-based ontology is being accumulated behind-the-scenes, & used for integrating the information. (One thing does annoy: I hope they'll switch to FireFox (instead of the old Mozilla), because I can't use a browser without my extensions…). I might even try write a plug-in for FreeMind or some other app I can't live without, & see how it works.

Thanks DARPA, SRI & all other researchers for bringing the future closer!

Update: Oops! There's only a Windows version :( … Seems like I won't be using it much, coz my primary OS is Linux. (hey, please spend the last mile effort for the sake of Linux & MacOS early adopters…)

Reader of this blog, if you haven’t already, please proceed to read Subhash Kak’s article: Artificial and Biological Intelligence

Some remarks:

  • A principle of emergence is self-organizing. Reorganization is a primary process of intelligence.
  • the self-awareness of the humanity animal is somewhere else, encoded in a different language & world model.
  • an ai could work on the science of understanding humans, as they themselves can’t
  • quantum computing theory may explains the brain (remember von Neumann’s quote in Dyson’s article, that logic will have to pseudo-morphose into neuroscience, & not the other way around.)
  • “unification of minds or consciousnesses”
  • (to be continued)

Very cool article: Edge: TURING’S CATHEDRAL by George Dyson

From the perspective of an agents framework’s developer, I have these remarks:

  1. ontologies specify behavior. edit the ontology & the software behavior changes. why?
  2. create a full corporation of software agents, with hundreds of agent types & thousands of agent workers.
  3. the ontology defines the behavior of all agents – their genes, then the ontology also contains the knowledge learnt by the agents – their brain.
  4. the key ingredient for agents corporation is communication: normal communication for regular behavior, & spontaneous communication for mutated adaptive behavior.
  5. Google is the access method to the global knowledge base of unstructured data. Google should be used extensively by each agent, in order to find new knowledge relevant to its behavior.
  6. There is a barrier between machines & humans today: machines can only answer questions that programmers defined well & hard-coded the procedure for answering. most questions people have are not (yet) well-defined & programmers still didn’t define procedures for them. Agentier should be able to communicate directly with people in order to solve “questions whose answers are, in principle, computable, but that, in practice, we are unable to ask in unambiguous language that computers can understand.”
  7. Basically this means that a good agent framework should be human brain compatible: it should solve problems that the human brain normally solves.

Quotes:

  • “An argument in favour of building a machine with initial randomness is that, if it is large enough, it will contain every network that will ever be required.” (Irving J. Good)
  • “It is much easier to find explicit answers than to ask explicit questions. And some will be answers to questions that programmers wil never have to ask.” (G. Dyson)
  • Pay extreme notice & caution not to conclude unfalsifiable conclusions. Everything must be testable & falsifiable.

    Your task is to draw a picture, but also provide the means of testing whether the picture fits reality or not.

    Picture:
    human tissue, made of 6B humans. what makes it a tissue are connections. connections are made thru “chemicals”, manifested as feelings felt by the humans. such connections bond families, friendships, organizations, communities. other connections are done by means of social mechanisms.
    the imagined outcome is a clear zoommable picture, that explains the bonds, the layers of the tissue, & the macro behavior of the tissue: what kind of animal is it, what does it do.
    to get there, I can take the normal biological investigation methodology, or try a more rigid one, using description logic (OWL) & simulations (StarLogo). I can try use Wolfram’s New-Kind-Of-Science methodology, which seems to be so fruitefull.
    Next task: map the chemicals. (not yet the social mechanisms)

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