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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Computational creativity | 3/8 | https://en.wikipedia.org/wiki/Computational_creativity | reference | science, encyclopedia | 2026-05-05T16:31:23.728483+00:00 | kb-cron |
=== Language models and hallucination === Language models like GPT and LSTM are used to generate texts for creative purposes, such as novels and scripts. These models demonstrate hallucination from time to time, where erroneous materials are presented as factual. Creators make use of their hallucinatory tendency to capture unintended results. Ross Goodwin's 1 the Road, for example, uses an LSTM model trained on literature corpora to generate a novel that refers to Jack Kerouac's On the Road based on multimodal input captured by a camera, a microphone, a laptop's inner clock, and a GPS throughout the road trip. Brian Merchant commented on the novel as "pixelated poetry in its ragtag assemblage of modern American imagery". Oscar Sharp and Ross Goodwin created the experimental sci-fi short film Sunspring in 2016, written with an LSTM model, trained on their scripts and 1980-1990 sci-fi movies. Rodica Gotca critiqued their overall lack of focus on the narrative and intention to create based on the background of human culture. Nevertheless, researchers highlight the positive side of language models' hallucination for generating novel solutions, given that the correctness and consistency of the response could be controlled. Jiang et al. propose the divergence-convergence flow model for harnessing the hallucinatory effects. They summarize the types of such effects in current research into factuality hallucinations and faithfulness hallucinations, which can be divided into smaller classes like factual fabrication and instruction inconsistency. While the divergence stage involves generating potentially hallucinatory content, the convergence stage focuses on filtering the hallucinations that are useful for the user with intent recognition and evaluation metrics.
== Key concepts from literature == Some high-level and philosophical themes recur throughout the field of computational creativity, for example as follows.
=== Important categories of creativity === Margaret Boden refers to creativity that is novel merely to the agent that produces it as "P-creativity" (or "psychological creativity"), and refers to creativity that is recognized as novel by society at large as "H-creativity" (or "historical creativity").
=== Exploratory and transformational creativity === Boden also distinguishes between the creativity that arises from an exploration within an established conceptual space, and the creativity that arises from a deliberate transformation or transcendence of this space. She labels the former as exploratory creativity and the latter as transformational creativity, seeing the latter as a form of creativity far more radical, challenging, and rarer than the former. Following the criteria from Newell and Simon elaborated above, we can see that both forms of creativity should produce results that are appreciably novel and useful (criterion 1), but exploratory creativity is more likely to arise from a thorough and persistent search of a well-understood space (criterion 3) -- while transformational creativity should involve the rejection of some of the constraints that define this space (criterion 2) or some of the assumptions that define the problem itself (criterion 4). Boden's insights have guided work in computational creativity at a very general level, providing more an inspirational touchstone for development work than a technical framework of algorithmic substance. However, Boden's insights are also the subject of formalization, most notably in the work by Geraint Wiggins.
=== Generation and evaluation === The criterion that creative products should be novel and useful means that creative computational systems are typically structured into two phases, generation and evaluation. In the first phase, novel (to the system itself, thus P-Creative) constructs are generated; unoriginal constructs that are already known to the system are filtered at this stage. This body of potentially creative constructs is then evaluated, to determine which are meaningful and useful and which are not. This two-phase structure conforms to the Geneplore model of Finke, Ward and Smith, which is a psychological model of creative generation based on empirical observation of human creativity. Jordanous and Keller emphasize the need for a "tractable and well-articulated model of creativity". They extracted 694 creativity words derived from a corpus of empirical studies in psychology and creativity research spanning 60 years and clustered them based on lexical similarity. As a result, they identify 14 key components of creativity, which form the basis of the framework "Standardised Procedure for Evaluating Creative Systems" (SPECS). These components include aspects like "dealing with uncertainty", "independence and freedom", "social interaction and communication", and "spontaneity & subconscious processing".
=== Co-creation === While much of computational creativity research focuses on independent and automatic machine-based creativity generation, many researchers are inclined towards a collaboration approach. This human-computer interaction is sometimes categorized under the creativity support tools development. These systems aim to provide an ideal framework for research, integration, decision-making, and idea generation. Recently, deep learning approaches to imaging, sound and natural language processing, resulted in the modeling of productive creativity development frameworks.