Making Effective Decisions: Machine Learning and the Ecogame in 1970
- URL: http://arxiv.org/abs/2508.07027v1
- Date: Sat, 09 Aug 2025 15:51:26 GMT
- Title: Making Effective Decisions: Machine Learning and the Ecogame in 1970
- Authors: Catherine Mason,
- Abstract summary: This paper considers Ecogame, an innovative art project of 1970, whose creators believed in a positive vision of a technological future.<n>Using simulation and early machine learning techniques over a live network, Ecogame combined the power of visual art with cybernetic concepts of adaptation, feedback, and control to propose that behaviour had implications for the total system.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: This paper considers Ecogame, an innovative art project of 1970, whose creators believed in a positive vision of a technological future; an understanding, posited on cybernetics, of a future that could be participatory via digital means, and therefore more democratised. Using simulation and early machine learning techniques over a live network, Ecogame combined the power of visual art with cybernetic concepts of adaptation, feedback, and control to propose that behaviour had implications for the total system. It provides an historical precedent for contemporary AI-driven art about using AI in a more human-centred way.
Related papers
- Art Notions in the Age of (Mis)anthropic AI [0.0]
I take the cultural effects of generative artificial intelligence (generative AI) as a context for examining a broader perspective of AI's impact on contemporary art notions.<n>I summarize the distinct but often confused aspects of art notions and review the principal lines in which AI influences them.<n>I introduce several viewpoints for a further critique of AI's cultural zeitgeist.
arXiv Detail & Related papers (2026-02-20T13:27:28Z) - The Impact of Artificial Intelligence on Traditional Art Forms: A Disruption or Enhancement [0.0]
We look at the ways that recent technologies like Geneversarative Adrial Networks and Diffusion Models are changing the fields of painting, sculpture, calligraphy, dance, music, and the arts of craft.<n>Using examples and data, we illustrate the ways that AI can democratize creative expression, improve productivity, and preserve cultural heritage.<n>We advocate for the development of ethical guidelines, collaborative approaches, and inclusive technology development.
arXiv Detail & Related papers (2025-09-07T16:37:04Z) - Generative Physical AI in Vision: A Survey [78.07014292304373]
Gene Artificial Intelligence (AI) has rapidly advanced the field of computer vision by enabling machines to create and interpret visual data with unprecedented sophistication.<n>This transformation builds upon a foundation of generative models to produce realistic images, videos, and 3D/4D content.<n>As generative models evolve to increasingly integrate physical realism and dynamic simulation, their potential to function as "world simulators" expands.
arXiv Detail & Related papers (2025-01-19T03:19:47Z) - Goetterfunke: Creativity in Machinae Sapiens. About the Qualitative Shift in Generative AI with a Focus on Text-To-Image [0.0]
In human-AI collaboration, the computer seems to have become more than a tool.<n>This article is about (the possibility of) creativity in computers within the current Machine Learning paradigm.<n>It outlines some of the key concepts behind the technologies and the innovations that have contributed to this qualitative shift.
arXiv Detail & Related papers (2024-10-25T16:04:11Z) - Artificial Intelligence from Idea to Implementation. How Can AI Reshape the Education Landscape? [0.0]
The paper shows how AI technologies have moved from theoretical constructs to practical tools that are reshaping pedagogical approaches and student engagement.
The essay concludes by discussing the prospects of AI in education, emphasizing the need for a balanced approach that considers both technological advancements and societal implications.
arXiv Detail & Related papers (2024-07-14T04:40:16Z) - Artificial General Intelligence (AGI)-Native Wireless Systems: A Journey Beyond 6G [58.440115433585824]
Building future wireless systems that support services like digital twins (DTs) is challenging to achieve through advances to conventional technologies like meta-surfaces.
While artificial intelligence (AI)-native networks promise to overcome some limitations of wireless technologies, developments still rely on AI tools like neural networks.
This paper revisits the concept of AI-native wireless systems, equipping them with the common sense necessary to transform them into artificial general intelligence (AGI)-native systems.
arXiv Detail & Related papers (2024-04-29T04:51:05Z) - AI-Generated Images as Data Source: The Dawn of Synthetic Era [61.879821573066216]
generative AI has unlocked the potential to create synthetic images that closely resemble real-world photographs.
This paper explores the innovative concept of harnessing these AI-generated images as new data sources.
In contrast to real data, AI-generated data exhibit remarkable advantages, including unmatched abundance and scalability.
arXiv Detail & Related papers (2023-10-03T06:55:19Z) - Beyond Reality: The Pivotal Role of Generative AI in the Metaverse [98.1561456565877]
This paper offers a comprehensive exploration of how generative AI technologies are shaping the Metaverse.
We delve into the applications of text generation models like ChatGPT and GPT-3, which are enhancing conversational interfaces with AI-generated characters.
We also examine the potential of 3D model generation technologies like Point-E and Lumirithmic in creating realistic virtual objects.
arXiv Detail & Related papers (2023-07-28T05:44:20Z) - The Future of Artificial Intelligence (AI) and Machine Learning (ML) in
Landscape Design: A Case Study in Coastal Virginia, USA [4.149972584899897]
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.
arXiv Detail & Related papers (2023-05-03T13:13:30Z) - 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) - Artificial Intelligence for the Metaverse: A Survey [66.57225253532748]
We first deliver a preliminary of AI, including machine learning algorithms and deep learning architectures, and its role in the metaverse.
We then convey a comprehensive investigation of AI-based methods concerning six technical aspects that have potentials for the metaverse.
Several AI-aided applications, such as healthcare, manufacturing, smart cities, and gaming, are studied to be deployed in the virtual worlds.
arXiv Detail & Related papers (2022-02-15T03:34:56Z)
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.