Using art and aesthetics as context, we explore the notion that curiosity and creativity emanate from a single novelty-seeking mechanism and outline support for the idea. However, we also highlight the importance of learning progress tracking in exploratory action and advocate for a nuanced understanding that aligns novelty-seeking with learnability. This, we argue, offers a more comprehensive framework of how curiosity and creativity are related.
Ivancovsky et al. argue that the neurocognitive mechanisms of creativity and curiosity both rely on the interplay among brain networks. Research to date demonstrates that such inter-network dynamics are further complicated by functional fractionation within networks. Investigating how networks subdivide and reconfigure in service of a task offers insights about the precise anatomy that underpins creative and curious behaviour.
The novelty-seeking model suggests that curiosity and creativity originate from novelty processes. However, different types of novelty exist, each with distinctive relationships with memory, which potentially influence curiosity and creativity in distinct ways. We thus propose expanding the NSM model to consider these different novelty types and their specific involvement in creativity.
We argue that a diverse and dynamic pool of agents mitigates proxy failure. Proxy modularity plays a key role in the ongoing production of diversity. We review examples from a range of scales.
Decision-making heuristics rely on proxies so the elements of heuristics appear to map well to the elements of proxies identified by John et al. However, unlike proxy failure, heuristics do not fail because of feedback. This may be because for successful heuristics the goals of regulators and agents are aligned, but this is not the case for proxy failure.
Reductionist methodologies reduce phenomena to some of their lower-level components. Researchers gradually shift their focus away from observing the actual object of study toward investigating and optimizing such lower-level proxies. Following reductionism, these proxies progressively diverge further from the original object of study. We vividly illustrate this in the evolution of target-based drug discovery from rational and phenotypic drug discovery.
Natural selection is slow, so behavioral goals must be based on patterns of reward. Addictions are rewarded in the same way as adaptive choice, so they can be distinguished only by their time course. In addition, the reward process is more plastic than is generally recognized, so abstract goals are shaped by the "legibility" of their proxies.
The analysis of proxy failure given by John et al. provides a good starting point for interdisciplinary discussions. Here, the discussion of teleonomy is extended and updated to include more recent discourse on the topic.
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