Algorithms for Conceptual Navigation


Session Title:

  • Algorithms and the Artist (Visualization: The Next Generation)

Presentation Title:

  • Algorithms for Conceptual Navigation



  • Panel Statement

    Panel: Algorithms and the Artist

    I have always thought of computers as dynamic tools for introspection, exploration and discovery. Computer programming is instrumental in the externalization of ideas and algorithms are formal descriptions of what one hypothesis constitute the production of creative statements. The computer is a playground to speculate on the generative potential of ideas. As a matter of fact, the physical, tangible management of purely conceptual constructs becomes possible. However, the paradox is that while algorithmic specification allows the artist to touch the essence of his ideas it also creates a distance since all specification is indirect and seems to exclude spontaneous action.                                                                        The idea is to view computers as partners in the process of creative decision-making. By way of algorithms we can explore various man-machine relations in this partnership: from studying total autonomy in computer programs to systems designed for explicit interaction. The development of personal algorithms is the key to exploration and the gradual specification of objectives from incomplete knowledge, in sharp contrast to view the computer as slave, as a medium for deterministic visualization. I have characterized the interactive method where man and machine collaborate in a common effort and with common objectives as conceptual navigation; the artist-programmer gets feedback, his expectations are confirmed or contradicted by the program’s behavior.  Eventually, unexpected results may signal new and promising routes exposing unknown territories. Thus, man and machine contribute both to the creation of a computational climate that favors invention and to the development of a critical attitude towards the often complex relationships between programmed intention and actual result. Writing algorithms has also forced me to evaluate experience vs. speculation. If one relies on models that have proven to be successful in the past, one confirms what is already known. Algorithms that use rules reflecting this knowledge produce predictable results. Otherwise, designing processes with the greatest possible freedom in pure speculation is like working outside of any known context making evaluation very hard indeed. The creation of new contexts for growing algorithmic activity mixing memories of the past and an open imagination is, I think, perhaps the most interesting challenge to algorithmic art.