Indeterminacies: the Potential and Paradox of Noise
Edy Fung, March 2023, Stockholm
My interest in noise originates from the perspective of machine listening and electroacoustic practices against the backdrop of the Anthropocene. The trajectory of my work is to adopt a more-than-human approach towards noise which could potentially reevaluate what was considered a meaningful or useless sound beyond the anthropocentric perspective, as a departure to reimagine new ways to address issues with information.
My concern with noise has grown and evolved with the desire to challenge and rethink the digital norms that are shaping us, specifically binary signals and deterministic engines. We live in conventions that are inherited straight after the boom of microprocessor manufacturing. Our dependence on Turing machines surged forward to drive the current predictive analytics in forecasts and machine learning technology. The cybernetic movement was overly dispersed in different fields by the end of the 1960s and became oblivious. Before we could reconnect with the knowledge of cybernetics and integrate it into current computer sciences, we are forcing ways to develop artificial neural networks with a lack of coherence. Thus I would like to ground my research on what was being left off from cybernetics in the belief that the field provides a lens for developing some alternatives to current digital realities. Generally, computers do not like noise; they need certainty to perform their function. I aim to speculate how noise allows the creative space in that we as artists and musicians are the ones who use the tools and instruments, not to be used by them.
Literally, as well as symbolically, the notion of noise is embedded everywhere in our modern life. Although most commonly applied to the sonic environment, noise itself can be manifested in anything consisting of waves, that is, in both the mechanical and electromagnetic spectrum. Thus noise has actual material and immaterial implications. Acoustic noise is only one of the conversions. Noise is any spectral phenomenon about random fluctuations over time. Noise causes a measurement to vary over time. Noise causes patterns to be unrecognised and in itself is unpredictable, therefore is one way of understanding the indeterminate and acausal nature of the world. The notion of noise has gained a lot of prominence, not only in sound or engineering physics, having a significant role in information theory, data science, and sociopolitical contexts.
In the history of music, Noise mainly refers to a specific type of genre which stemmed from the avant-garde; and more recently in history Noise Rock and Noise Punk. We associate noise as provocative, subversive and anarchist. The performance aspect of noise triggers political transformations within a society of silence (Attali), due to the powerful and immediate impact on the physical environment. Since the Futurist movement noise has been conceptualised to signal the arrival of a new era along with the advancement of technological revolutions. From Schaeffer’s “Five Studies of Noises” to Merzbow’s noise synthesis spanning over the transition from analogue to laptop noise, this urge of ‘boundary-pushing’ still remains true and is gaining momentum today.
Speaking of drawing sociopolitical references, in Mattin’s artistic experiments in “Social Dissonance”, noise suggests frequencies in sound as well as crowds in a society. He orchestrates participants to challenge the forms of scoring in the context of social order and plays with improvisation in connection to liberation and sometimes chaos within the collective structure. Noise is analogous to cultural expression against a backdrop of existing ways of organisation and social contract. For this context, Toth adds that noise is the refusal of representation or identity; but he takes it beyond and contemplates the speed of sonic dissemination in global communication channels, positing the question of how digital noise performance could “mesh with information-based businesses, spurred by developing cyber-technology, military research, or computer-driven control operations”.
Yet the issue with noise itself is more complex. Steyerl even pushes the question of who gets to distinguish what a signal is and what a noise is, in the spectrum of sound. She points out the subjectivity and morality in the process of separating signals and noises with an example from Jacques Rancière about ancient Greece, that “sounds produced by affluent male locals were defined as speech, whereas women, children, slaves, and foreigners were assumed to produce garbled noise”. Perhaps this also echoes the problem of noise reduction being a method to help measure data in an unbiased way. In some cases, noise also exhibits a paradoxical character: the more noise reduction to clear bias, the more biases it can induce (Kahneman, Sibony & Sunstein).
While noise is undesired, dirty data and therefore omitted in pattern recognition, its hindrance character serves a function in terms of encryption. Noise is intentionally introduced to enhance security. The classification of noise as information is as valid as that of signals; noise is not necessarily the negation of information. Clearly, there is still an extensive realm that is unexplored in the subject of noise. Cecile Malaspina argues for a reassessment of the epistemology of noise, that human beings are too arrogant to be certain about what we can know (and what we can’t) when noise could have offered another dimension for accessing information. She believes this results in a fundamental error in the conceptualisation of noise in Shannon and Weaver’s work, upon which almost the entire computer science is founded.
Apart from Malaspina and Steyerl’s critical writing, most of the philosophical discourses on noise have not dwelt on the more tangible applications of noise in information and communication technology. Nearly 99.9% of the electronic devices that we engage in nowadays contain digital technology, in which electronic noise plays a part in the transmission of signals, such as the Johnson–Nyquist noise. There are a lot of research possibilities between analogue and digital transitions and the potential of analogue circuits has not been explored to the fullest. In Malaspina’s terms, digital technology would be perceived as a way of operating by deliberately missing information. Digital circuits abstract electricity into discrete voltages to be signals of logic values 0 and 1 and forbid any values in between. Noise margins are introduced to condition a threshold for voltages to be accepted as absolute 0 or 1 signals. Analogue predecessors work with full voltage intervals, and in other words, take into account the full range of electric information. In sound, analogue synthesisers demonstrate this in the process of “sonifying” electricity; no voltages are discriminated against in analogue circuits and analogue signals. Furthermore, VCO for instance allows room for happy accidents such as phase noise, namely the random fluctuations of waveforms. As cited by Taylor, Brian Eno appears to valorise the unpredictability of analogue production: the sounds “between the knobs” challenge the flawless efficiency and ‘discipline’ of digital technology.