Any practice for which such expansive claims could be seriously entertained would seem to be one that should be studied widely, in depth and with great alacrity, with the vision that the study of improvisation could present a new animating paradigm for scholarly inquiry in many fields in the humanities, arts, and social sciences. In fact, significant work on improvisation is already taking place in anthropology, sociology, architecture, cognitive science, music cognition and psychology, cultural studies, dance, gender studies, linguistics, literary criticism, music education and music therapy, musicology and ethnomusicology, organizational studies, philosophy, aesthetics, political science, theatre and performance studies--and many other fields. Most recently (2007), an interdisciplinary team of researchers led by literary scholar Ajay Heble and philosopher Eric Lewis will be pursuing a major research initiative in “Improvisation, Community, and Social Practice,” with the support of a multi-year grant from Canada’s Social Sciences and Humanities Research Council (SSHRC). This research team, of which I am part, will certainly pursue new ways of theorizing, informed by contemporary practices of improvisation in the arts that include technology as a central component.¹²

For LAM networkers, improvisation becomes a central component in a conception of “strong” interactivity, as distinct from “weakly interactive” or “reflex” systems in which, for instance, “incoming sound or data is analysed by software and a resultant reaction (e.g., a new sound event) is determined by pre-arranged processes” that “might also utilise stochasticity to effect surprise.” In contrast to systems that manifest “an illusion of integrated performer-machine interaction, feigned by the designer,” the strong interactivity of a live algorithm, as described by Blackwell and Young, is characterized by properties analogous to those found in human performance, e.g., “autonomy, innovation, idiosyncrasy and comprehensibility.”

Strong interactivity depends on instigation and surprise as well as response. Individual decision-making is immediate, necessary and basic; when to play or not, when to modify activity in any number of parameters (loudness, pitch, tone quality), when to imitate or ignore another participant, when to ‘agree’ the performance is concluding. When to make a decision. And why. Without the capacity to innovate, listeners would lose the belief that the LA was truly engaged with the performance instead of merely accompanying it. The iterative, generative, idiosyncratic world of algorithmic organisation must be accessed, but the mechanical and the predictable must be avoided. It is the ability to innovate that distinguishes automation from autonomy.¹³

Young and Blackwell feel that strong interactivity “is exemplified in the human-only practice of ‘free’ improvisation.” In this regard, LAM research consists of “a marrying of algorithmic music, live electronics and free improvisation,” and my own activity as composer since the late 1970s exemplifies this approach. In my most widely performed piece, Voyager, originally programmed by me in 1987 and extensively updated since that time, improvisors are engaged in dialogue with a computer-driven, interactive improvisor. A set of algorithms analyzes aspects of a human improvisor’s performance in real time, using that analysis to guide another set of algorithms that blend complex responses to the musician’s playing with independent musical behavior.