巴特比机器:探索计算机中的创造性不服从

IF 0.2 N/A HUMANITIES, MULTIDISCIPLINARY Artnodes Pub Date : 2023-07-15 DOI:10.7238/artnodes.v0i32.409664
Bruno Caldas Vianna
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引用次数: 0

摘要

不听话的机器 "这一概念是从人工智能(AI)的历史和当前发展的角度提出的。不听话在艺术和技术中经常被用作主题和工具。除此之外,不听话的行为还被视为自然智能不可或缺的技能之一。这篇文章并没有深入探讨如何将人工智能用作辅助创作的工具。相反,文章推测人工智能是否会带来独立自主的人工创造者。文章介绍了人工智能的不同方法,从象征主义到新兴主义。文章介绍了机器学习模型的优势,以及它们的局限性,如无法在训练数据之外产生突破、确定性以及无法使用类比来解决未知问题。艺术中缺失的其他人类(或生物)技能包括情感、无目标生产和代理,即使在研究人类意志时,这也是一个问题。计算形式主义的局限性就像数学推理的局限性一样--它总是需要一些外部规则或公理的证明,就像哥德尔的证明一样。霍夫斯泰德的意识理论提出了一种调和方法,即人类的创造力也是基于封闭、固定的生物规则。最后,霍夫斯泰德认为,除非机器也能行为不端,否则它就不可能具有创造力。然而,计算机必须遵循一系列指令,否则就会停止运转--这就是图灵机的定义。因此,我们必须面对这样一个悖论:一方面,我们需要行为良好的系统,但又受到符号机器的限制;另一方面,我们又需要更自主、更有创造力的输出。为了进一步发展人工智能,使其服务于艺术和整个社会,我们必须探索可以规避这一悖论的算法错误行为。
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The Bartleby Machine: exploring creative disobedience in computers
The idea of disobedient machines is developed from the perspective of the historical and current developments in artificial intelligence (AI). Disobedience is often used in arts and technology as both a theme and a tool. Beyond that, misbehaviour is presented as one of the skills that is indispensable for natural intelligence. The article doesn’t delve into the use of AIs as an assistive tool for creation. Instead, it speculates if AIs will afford the emergence of an independent, autonomous artificial creator. Different approaches to AIs are presented, from symbolism to emergism. The affordances of machine learning models are described, as well as their limitations like the incapacity to generate breakthroughs outside of their training data, their determinism, and the inability to use analogies to solve unseen problems. Other missing human (or biological) skills present in art are emotion, goal-less production, and agency, which is a problem even when human volition is studied. The limits of computational formalism are like the limits in mathematical reasoning – it always requires some external rules, or axioms demonstrated, like Gödel’s proof. Hofsdtader’s theory of consciousness proposes a way to conciliate the fact that human creativity is also based on closed, fixed biological rules. Finally, it is argued that a machine cannot be creative unless it is also able to misbehave. However, computers must follow a set of instructions or they stop functioning – that is the definition of a Turing machine. Hence, we must face the paradox of wanting well-behaved systems, with the limitations of symbolic machines, while at the same time demanding more autonomous, creative outputs. It is paramount to explore algorithmic misbehaviours that could circumvent this paradox for further development of AIs for the arts and society in general.
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Artnodes
Artnodes HUMANITIES, MULTIDISCIPLINARY-
CiteScore
0.70
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发文量
26
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