There are some people who seem to always be happy, regardless of how meager their situations appear to the outside observer. There are also people who cannot seem to sustain happiness, no matter how great their lives are perceived to be by others. This dichotomy exists because the inclination towards happiness manifests in different degrees in different people, with little correlation to their circumstances. While some people are born with a consistent tendency to be happy, I maintain that those who feel that their propensity for happiness is insufficient can increase it considerably over the course of their lives.
Before I describe how this is done, let me first explain what I mean by happiness. We all believe we know what happiness is since most of us have had bouts of it, regardless of our relative inability to sustain it. But if you ask most people what it means to be happy, you typically get a list of effects and synonyms but rarely a good characterization of the underlying cause.
I regard happiness as the appreciation of the absence of need. In this context need is our separation from completeness. At first glance this would seem to indicate that only those who have achieved completeness (the topic of another essay), can be truly happy. But from a deeper perspective it means that happiness is more readily available to those who have greater awareness of their proximity to completeness (or, as is often the case with simpler folk, less awareness of their separation from completeness).
Bear in mind that happiness is not our ultimate objective. In general, sustained happiness is simply an indicator that we are near our true objective of completeness. The closer we are to completeness, the fewer needs we have to focus on and so the more likely we are to be happy. Mind you, those who lack a sufficient propensity for happiness will usually just place a greater emphasis on their remaining needs.
Viewed this way it looks like it is theoretically possible to be too happy. For those of us who still see ourselves as far from complete, our needs are our primary incentive to grow. As such, if we still have needs but our happiness has us directing our attention away from them, this incentive to grow would no longer be effective, thus potentially retarding our growth.
We are protected from this eventuality by our other important incentive to grow. Where need is our negative incentive to grow, our positive incentive to grow is love. Again most of us believe we know what love is since we are of the impression that we have experienced it either directly or indirectly at some point in our lives. But when asked to define love we typically put forth a litany of symptoms, not an explanation of the condition.
Love is the empathically induced completeness that we feel through our awareness of our proximity to completeness. In other words, love is the feeling we get from our realization that we are a part of something truly wonderful. The existence of this positive incentive to grow allows those who are both needful and happy to be inclined to grow through their love, which will draw them towards the ultimate source of the completeness they feel.
Love is the basis of our propensity to be happy. This means that those who feel they lack the inclination to be happy simply do not have enough love in their lives. Such people are insufficiently aware of their proximity to completeness.
To resolve this situation you should first cultivate an awareness of the existence of a state of completeness that transcends all need and is the source of all love in the world. Whether you call this state God, Unity or the peace of perfect equilibrium, the existence of such a state is easy to recognize if you are open to it.
Once you accept the existence of this complete state, you can increase your propensity to be happy by nurturing an awareness of your proximity to it. I maintain that each conscious being is separated from this state of completeness by a single thought. The specific nature of this thought is different for each individual. The trick is figuring out what that thought is for you. But in the interim, you can be happier simply knowing how close we all are to the resultant state of completeness.
Tuesday, December 16, 2008
Wednesday, December 10, 2008
Experience Systems
The next generation of data systems on the horizon are Experience Systems. These are systems that sequence content exposures (i.e. events) to form coordinated user experiences. A user experience is a collection of events that are arranged in a particular order to have a specific impact on the user. The distinguishing components of the Experience System architecture are its Profile Manager, Experience Generator and Event Store.
The user interface of an Experience System encompasses a Query Generator, Preference Manager and Profile Manager. The Profile Manager gathers much more expansive data on the end user than the Preference Manager. These data elements comprise a detailed psychological profile of the user. Such profiles can be generated by prolonged exposure to a psychological assessment system that on the surface would look like a video game played in a very sophisticated virtual world.
This assessment system presents the user with an appropriate narrative under which resides a sophisticated decision tree. The user traverses this tree in the course of “playing the game”. The user’s decisions in the face of a specific sequence of scenarios place her at a particular location on the underlying N-dimensional assessment grid. It is the user’s historical path and current location in this grid that characterizes her profile. The longer the user interacts with the system, the more precisely her profile can be defined.
The shape of the space in which the assessment grid resides reflects the capabilities, inclinations and susceptibilities of a user at a given location. The user’s current psychological location, the shape of the space around her (i.e., her psychological inertia) and the spatial and temporal shape of her historical path through the assessment grid (i.e., her psychological momentum) combined with any user-defined goal states, determine the narrative being presented. The assessment system is dynamic in that it updates itself in response to the results achieved by its user community.
Experience System queries are requests by the user to reach specified goal states. The Experience Generator accepts these requests and the associated user profile data from the Profile Manager and searches the Event Store for appropriate events that can facilitate the transition. These events can be based on exposure to electronic media such as videos, pictures, audio lectures, music and text. They can also include excursions into the offline world to lecture halls, theaters, museums, exercise facilities, stores, parks, beaches, work places and any other available sites. The Experience Generator sequences the selected events into different experiences and coordinates user access to them via the user interface. These experiences are designed to advance the user towards her goal state. They are generally presented in order of the greatest probability of success.
The Event Store is a Content Store that extends into the offline world. Events in the store are rated and cataloged by their potential impact on a given range of user capabilities, inclinations and susceptibilities based on provider assessments (heuristics), empirical data and theoretical extrapolations. Experience Systems manage events that are combined to form Minkowski data spaces that characterize both where and when events occur.
When you consider that we have only recently begun to produce Knowledge Systems, the advent of fully functioning Experience Systems is still some time off in our future. But much of the technology that would be required to produce such systems is already available to us. An assessment system with the requisite sophistication has yet to be developed but many its components already exist separately (there may even be a few of prototypes out there). It is only a matter of time before someone puts them together and triggers a major paradigm shift.
Experience Systems could easily represent the next generation of entertainment, education and life management technologies. As we continue to exploit the deeper potential of data systems, it is becoming increasingly evident that in lieu of a major scientific breakthrough (e.g., cold fusion, instantaneous teleportation, matter transmutation, etc.), this technology domain will be an increasingly important driver of human activity for the foreseeable future.
The user interface of an Experience System encompasses a Query Generator, Preference Manager and Profile Manager. The Profile Manager gathers much more expansive data on the end user than the Preference Manager. These data elements comprise a detailed psychological profile of the user. Such profiles can be generated by prolonged exposure to a psychological assessment system that on the surface would look like a video game played in a very sophisticated virtual world.
This assessment system presents the user with an appropriate narrative under which resides a sophisticated decision tree. The user traverses this tree in the course of “playing the game”. The user’s decisions in the face of a specific sequence of scenarios place her at a particular location on the underlying N-dimensional assessment grid. It is the user’s historical path and current location in this grid that characterizes her profile. The longer the user interacts with the system, the more precisely her profile can be defined.
The shape of the space in which the assessment grid resides reflects the capabilities, inclinations and susceptibilities of a user at a given location. The user’s current psychological location, the shape of the space around her (i.e., her psychological inertia) and the spatial and temporal shape of her historical path through the assessment grid (i.e., her psychological momentum) combined with any user-defined goal states, determine the narrative being presented. The assessment system is dynamic in that it updates itself in response to the results achieved by its user community.
Experience System queries are requests by the user to reach specified goal states. The Experience Generator accepts these requests and the associated user profile data from the Profile Manager and searches the Event Store for appropriate events that can facilitate the transition. These events can be based on exposure to electronic media such as videos, pictures, audio lectures, music and text. They can also include excursions into the offline world to lecture halls, theaters, museums, exercise facilities, stores, parks, beaches, work places and any other available sites. The Experience Generator sequences the selected events into different experiences and coordinates user access to them via the user interface. These experiences are designed to advance the user towards her goal state. They are generally presented in order of the greatest probability of success.
The Event Store is a Content Store that extends into the offline world. Events in the store are rated and cataloged by their potential impact on a given range of user capabilities, inclinations and susceptibilities based on provider assessments (heuristics), empirical data and theoretical extrapolations. Experience Systems manage events that are combined to form Minkowski data spaces that characterize both where and when events occur.
When you consider that we have only recently begun to produce Knowledge Systems, the advent of fully functioning Experience Systems is still some time off in our future. But much of the technology that would be required to produce such systems is already available to us. An assessment system with the requisite sophistication has yet to be developed but many its components already exist separately (there may even be a few of prototypes out there). It is only a matter of time before someone puts them together and triggers a major paradigm shift.
Experience Systems could easily represent the next generation of entertainment, education and life management technologies. As we continue to exploit the deeper potential of data systems, it is becoming increasingly evident that in lieu of a major scientific breakthrough (e.g., cold fusion, instantaneous teleportation, matter transmutation, etc.), this technology domain will be an increasingly important driver of human activity for the foreseeable future.
Tuesday, December 9, 2008
The Evolution of Data Systems
Underlying all of today’s computer applications are Information Systems. Note that information characterizes the separations between entities. Information Systems are based on collections of entities whose types and attributes distinguish them from each other.
Information Systems are generally comprised of some form of a Query Generator, a System Integrator and a Data Store. The Query Generator is essentially the user interface that accepts requests for information and displays the result set. The System Integrator is the subsystem that knows what data elements are where and how to access them. The Data Store encompasses the location of every piece of data in the system that the end user could want to see.
Information Systems require no knowledge of the user beyond the content of the request being made and her authorization level. As such the layout and actions of its components are largely unaffected by the individual uniqueness of the user. In general, Information Systems manage data elements in a Euclidean (flat) data space. This means that, the logical distance between data elements in an Information System is generally the same for all users.
Of late, an increasing number of Knowledge Systems have begun to emerge. Note that knowledge characterizes the connections between entities. The connections between data elements in Knowledge Systems are their metadata, which is essentially data about the data. The distinguishing components of the Knowledge System architecture are its Preference Manager, Search Engine and Content Store.
The user interface of a Knowledge System is comprised of a Query Generator and a Preference Manager. The Preference Manager accepts user preference data in the form of demographic data and transaction history. Preference data are utilized by the user interface to customize its layout. The Search Engine uses preference data to shape the Content Store in terms of relevance to a given user.
The Content Store contains both fundamental data elements and the metadata that connect them on a more abstract level. The metadata of the Content Store are what distinguish it from a Data Store. Knowledge Systems manage relevance metrics that are used to generate non-Euclidean (curved) data spaces. This means that the logical distance between data elements in a Knowledge System can be the different for different users.
Information Systems are currently being engulfed into the history of data systems by the newly emergent Knowledge Systems, which represent the present. But the initial glimmers of the future of data systems are already becoming apparent. This future is the phenomenon known as the Experience System, which builds on the advances produced by the development of Knowledge Systems. The nature of Experience Systems will be the subject of the next essay.
Information Systems are generally comprised of some form of a Query Generator, a System Integrator and a Data Store. The Query Generator is essentially the user interface that accepts requests for information and displays the result set. The System Integrator is the subsystem that knows what data elements are where and how to access them. The Data Store encompasses the location of every piece of data in the system that the end user could want to see.
Information Systems require no knowledge of the user beyond the content of the request being made and her authorization level. As such the layout and actions of its components are largely unaffected by the individual uniqueness of the user. In general, Information Systems manage data elements in a Euclidean (flat) data space. This means that, the logical distance between data elements in an Information System is generally the same for all users.
Of late, an increasing number of Knowledge Systems have begun to emerge. Note that knowledge characterizes the connections between entities. The connections between data elements in Knowledge Systems are their metadata, which is essentially data about the data. The distinguishing components of the Knowledge System architecture are its Preference Manager, Search Engine and Content Store.
The user interface of a Knowledge System is comprised of a Query Generator and a Preference Manager. The Preference Manager accepts user preference data in the form of demographic data and transaction history. Preference data are utilized by the user interface to customize its layout. The Search Engine uses preference data to shape the Content Store in terms of relevance to a given user.
The Content Store contains both fundamental data elements and the metadata that connect them on a more abstract level. The metadata of the Content Store are what distinguish it from a Data Store. Knowledge Systems manage relevance metrics that are used to generate non-Euclidean (curved) data spaces. This means that the logical distance between data elements in a Knowledge System can be the different for different users.
Information Systems are currently being engulfed into the history of data systems by the newly emergent Knowledge Systems, which represent the present. But the initial glimmers of the future of data systems are already becoming apparent. This future is the phenomenon known as the Experience System, which builds on the advances produced by the development of Knowledge Systems. The nature of Experience Systems will be the subject of the next essay.
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