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 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.