The Future of Artificial Intelligence (AI) and Machine Learning (ML) in
Landscape Design: A Case Study in Coastal Virginia, USA
- URL: http://arxiv.org/abs/2305.02327v1
- Date: Wed, 3 May 2023 13:13:30 GMT
- Title: The Future of Artificial Intelligence (AI) and Machine Learning (ML) in
Landscape Design: A Case Study in Coastal Virginia, USA
- Authors: Zihao Zhang and Ben Bowes
- Abstract summary: This paper presents a case that uses machine learning techniques to predict variables in a coastal environment.
Drawing ideas from posthumanism, this paper argues that, to truly understand the cybernetic environment, we have to take on posthumanist ethics and overcome human exceptionalism.
- Score: 4.149972584899897
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: There have been theory-based endeavours that directly engage with AI and ML
in the landscape discipline. By presenting a case that uses machine learning
techniques to predict variables in a coastal environment, this paper provides
empirical evidence of the forthcoming cybernetic environment, in which
designers are conceptualized not as authors but as choreographers, catalyst
agents, and conductors among many other intelligent agents. Drawing ideas from
posthumanism, this paper argues that, to truly understand the cybernetic
environment, we have to take on posthumanist ethics and overcome human
exceptionalism.
Related papers
- Generative Artificial Intelligence: A Systematic Review and Applications [7.729155237285151]
This paper documents the systematic review and analysis of recent advancements and techniques in Generative AI.
The major impact that generative AI has made to date, has been in language generation with the development of large language models.
The paper ends with a discussion of Responsible AI principles, and the necessary ethical considerations for the sustainability and growth of these generative models.
arXiv Detail & Related papers (2024-05-17T18:03:59Z) - Heuristic Reasoning in AI: Instrumental Use and Mimetic Absorption [0.2209921757303168]
We propose a novel program of reasoning for artificial intelligence (AI)
We show that AIs manifest an adaptive balancing of precision and efficiency, consistent with principles of resource-rational human cognition.
Our findings reveal a nuanced picture of AI cognition, where trade-offs between resources and objectives lead to the emulation of biological systems.
arXiv Detail & Related papers (2024-03-14T13:53:05Z) - A call for embodied AI [1.7544885995294304]
We propose Embodied AI as the next fundamental step in the pursuit of Artificial General Intelligence.
By broadening the scope of Embodied AI, we introduce a theoretical framework based on cognitive architectures.
This framework is aligned with Friston's active inference principle, offering a comprehensive approach to EAI development.
arXiv Detail & Related papers (2024-02-06T09:11:20Z) - On the Emergence of Symmetrical Reality [51.21203247240322]
We introduce the symmetrical reality framework, which offers a unified representation encompassing various forms of physical-virtual amalgamations.
We propose an instance of an AI-driven active assistance service that illustrates the potential applications of symmetrical reality.
arXiv Detail & Related papers (2024-01-26T16:09:39Z) - Machine Psychology [54.287802134327485]
We argue that a fruitful direction for research is engaging large language models in behavioral experiments inspired by psychology.
We highlight theoretical perspectives, experimental paradigms, and computational analysis techniques that this approach brings to the table.
It paves the way for a "machine psychology" for generative artificial intelligence (AI) that goes beyond performance benchmarks.
arXiv Detail & Related papers (2023-03-24T13:24:41Z) - The Entoptic Field Camera as Metaphor-Driven Research-through-Design
with AI Technologies [28.81674106342742]
We describe a Research-through-Design project which explores the shift in means and modes of image production via the creation and use of the Entoptic Field Camera.
We use the term entoptic as a metaphor to investigate how the material interplay of data and models in AI technologies shapes human experiences of reality.
arXiv Detail & Related papers (2023-01-23T17:03:54Z) - World Models and Predictive Coding for Cognitive and Developmental
Robotics: Frontiers and Challenges [51.92834011423463]
We focus on the two concepts of world models and predictive coding.
In neuroscience, predictive coding proposes that the brain continuously predicts its inputs and adapts to model its own dynamics and control behavior in its environment.
arXiv Detail & Related papers (2023-01-14T06:38:14Z) - Selected Trends in Artificial Intelligence for Space Applications [69.3474006357492]
This chapter focuses on differentiable intelligence and on-board machine learning.
We discuss a few selected projects originating from the European Space Agency's (ESA) Advanced Concepts Team (ACT)
arXiv Detail & Related papers (2022-12-10T07:49:50Z) - Pathway to Future Symbiotic Creativity [76.20798455931603]
We propose a classification of the creative system with a hierarchy of 5 classes, showing the pathway of creativity evolving from a mimic-human artist to a Machine artist in its own right.
In art creation, it is necessary for machines to understand humans' mental states, including desires, appreciation, and emotions, humans also need to understand machines' creative capabilities and limitations.
We propose a novel framework for building future Machine artists, which comes with the philosophy that a human-compatible AI system should be based on the "human-in-the-loop" principle.
arXiv Detail & Related papers (2022-08-18T15:12:02Z) - An interdisciplinary conceptual study of Artificial Intelligence (AI)
for helping benefit-risk assessment practices: Towards a comprehensive
qualification matrix of AI programs and devices (pre-print 2020) [55.41644538483948]
This paper proposes a comprehensive analysis of existing concepts coming from different disciplines tackling the notion of intelligence.
The aim is to identify shared notions or discrepancies to consider for qualifying AI systems.
arXiv Detail & Related papers (2021-05-07T12:01:31Z) - Intelligent behavior depends on the ecological niche: Scaling up AI to
human-like intelligence in socio-cultural environments [17.238068736229017]
This paper outlines a perspective on the future of AI, discussing directions for machines models of human-like intelligence.
We emphasize the role of ecological niches in sculpting intelligent behavior, and in particular that human intelligence was fundamentally shaped to adapt to a constantly changing socio-cultural environment.
arXiv Detail & Related papers (2021-03-11T16:24:00Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.