Author: Dr. Valerio PERNA
Affiliation: POLIS University – INNOVATION_Factory, Albania
Abstract
In recent years, the concept of intelligence has become a popular term that accompanies various actions, practices, processes, and products. This prominent presence in contemporary discussions stems from two significant factors. Firstly, there has been a fundamental shift in our understand- ing of intelligence. It is no longer seen solely as a quality exclusive to humans but rather as a collec- tion of emerging properties and conditions that can exist in both human and non-human entities. Secondly, intelligence is now viewed as a multi-layered relationship between a ‘brain’ (whether human or non-human), a body, and the environment(s) in which that body exists.
Presently, intelligence encompasses all aspects of design, introducing a new form of design intel- ligence that differs greatly from the human-centered approaches of the past. Similarly, creativity is no longer solely attributed to the human brain. Its definition has expanded to include the op- erational value of novel abstractions and pattern associations generated through machine-driven thinking processes.
Architects are now exploring various “intelligent” tools such as different AI languages, generative adversarial networks and text-to-image tools to understand how non-human intelligence can be applied to address contemporary issues in cities and urban centers, and considering also the ex- pected benefits and the possible risks originating from their use.
The paper aims to investigate the emergence of a post-digital sensibility in architecture and seeks to delve– through theoretical and practical apporaches - the notion of creativity and intelligence in a post-human design ecology while demystifying the so-called ‘risks’ associated with the utili- zation of Neural Network processes in design. Furthermore, it aims to assess the extent to which these processes can inform architectural design for today’s challenges.
Reference:
Anderson, P., & Speed, C. (2008). The New Ecology of Things (NET): Social, spatial, and tempo- ral dimensions of ubiquitous things. International Journal of Human-Computer Studies, 66(10), 929-940.
Bishop, C. M. (2006). Pattern recognition and machine learning. Springer.
Goodfellow, I., Bengio, Y., Courville, A., & Bengio, Y. (2016). Deep learning (Vol. 1). MIT press Cambridge.
Boden, M. (2016). AI: Its Nature and Future (p. 1). Oxford University Press.
Buchanan, B. G., & Smith, R. G. (1988). Fundamentals of expert systems. Annual review of com- puter science, 3(1), 23-58.
del Campo, M. (2018). Autonomous tectonics: the work of SPAN, between autonomous behaviour and cultural agency (Doctoral dissertation, RMIT University).
del Campo, M., & Leach, N. (Eds.). (2022). Machine Hallucinations: Architecture and Artificial Intelligence. Hoboken: John Wiley & Sons.
Cascone, K. (2017). The aesthetics of failure:“Post-digital” tendencies in contemporary computer music. In Electronica, Dance and Club Music (pp. 97-103). London: Routledge.
Lévy, P. (2006). Collective Intelligence, A Civilisation: Towards a Method of Positive Interpreta- tion. International Journal of Politics, Culture, and Society, 18(3/4), The New Sociological Imagi- nation (Spring - Summer, 2005), 189-198.
Oxman, R. (1999). Digital architecture as a challenge for design pedagogy: Theory, knowledge, models and medium. Design Studies, 20(2), 99-120.
Saggio, A. (2007). Introduzione alla rivoluzione informatica in architettura. Roma: Carocci.
Vogiatzaki, M. (2016) Intelligence. archiDOCT, 6(1), 6-13
Yoo, T., et al. (2021). Architectural design meets artificial intelligence: An updated systematic re- view. Automation in Construction, 125, 91-104