The Novelty Seeking Model (NSM) places “novelty” at center stage in characterizing the mechanisms behind curiosity. We argue that the NSM's conception of novelty is too broad, obscuring distinct constructs. More critically, the NSM underemphasizes triggers of curiosity that better unify these constructs and that have received stronger empirical support: those that signal the potential for useful learning.

The unbridled positivity toward curiosity and creativity may be excessive. Both aid species survival through exploration and advancement. These beneficial effects are well documented. What remains is to understand their optimal levels and contexts for maximal achievement, health, and well-being. Every beneficial element to individuals and groups carries the potential for harm – curiosity and creativity included.

Ivancovsky et al. provide a compelling argument for the role of curiosity in creative thinking. We argue that (a) trait-like curiosity is necessary to engage in creative actions and (b) state-like curiosity might be effectively and strategically induced during interventions. Thus, we posit that curiosity works in an agentic and strategic way in strengthening creativity.

The target article tackles an important and complicated issue of the underlying links between curiosity and creativity. Although thought-provoking, the target article overlooks contemporary theories and research on these constructs. Consequently, the proposed model is inconsistent with prior research in the developmental and educational fields and would benefit from better specification and clarity around key constructs and processes.

Ivancovsky et al. propose a novelty-seeking model linking curiosity to creativity. This commentary suggests integrating their work with a stage-based creativity model for additional insights. It also encourages readers to address knowledge gaps identified by the authors, including factors that trigger the pursuit of creative solutions. We aim to refine theory and direct future research to clarify the complex curiosity–creativity relationship.

Novelty is neither necessary nor sufficient to link curiosity and creativity as stated in the target article. We point out the article's logical shortcomings, outline preconditions that may link curiosity and creativity, and suggest that curiosity and creativity may be expressions of a common epistemic drive.

We argue that the phases identified in the novelty-seeking model can be clarified by considering an updated version of the optimal-level of arousal model, which incorporates the “arousal” and “mood changing” potentials of stimuli and contexts. Such a model provides valuable insights into what determines one's state of mind, inter-individual differences, and the rewarding effects of curiosity and creativity.

We extend Ivancovsky et al.'s finding on the association between curiosity and creativity by proposing a sequential causal model assuming that (a) curiosity determines the motivation to seek information and that (b) creativity constitutes a capacity to act on that motivation. This framework assumes that both high levels of curiosity and creativity are necessary for information-seeking behavior.

The Novelty-Seeking Model does not address the iterative nature of creativity, and how it restructures one's worldview, resulting in overemphasis on the role of curiosity, and underemphasis on inspiration and perseverance. It overemphasizes the product; creators often seek merely to express themselves or figure out or come to terms with something. We point to inconsistencies regarding divergent and convergent thought.

The Novelty-Seeking Model can explain incubation's effect on creativity by assuming an adaptive decision threshold. During an impasse, the threshold for novelty becomes too high and biased to previous neural activity, hindering progress. Incubation “resets” this threshold through attentional decoupling, allowing for spontaneous ideas to emerge from subsequent mind wandering or other activities that attract attention, facilitating progress.

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 creativity literature is replete with dualistic constructs, suggesting shared mechanisms but also tempting overinterpretation of their interrelations. An explicit list of relevant concept associations indicates substantial commonality, yet also exposes certain inconsistencies. Dual-process accounts (A and B is relevant) hold promise in resolving discrepancies to the extent that we understand the relative contributions and conditions of A and B.

We link Ivancovsky et al.'s novelty-seeking model (NSM) to computational models of intrinsically motivated behavior and learning. We argue that dissociating different forms of curiosity, creativity, and memory based on the involvement of distinct intrinsic motivations (e.g., surprise and novelty) is essential to empirically test the conceptual claims of the NSM.

We propose expanding the authors’ shared novelty-seeking basis for creativity and curiosity by emphasizing an underlying computational principle: Minimizing prediction errors (mismatch between predictions and incoming data). Curiosity is tied to the anticipation of minimizing prediction errors through future, novel information, whereas creative AHA moments are connected to the actual minimization of prediction errors through current, novel information.

By examining the shared neuro-cognitive correlates of curiosity and creativity, we better understand the brain basis of creativity. However, by only examining shared components, important neuro-cognitive correlates are overlooked. Here, we argue that any comprehensive brain model of creativity should consider multiple cognitive processes and, alongside the interplay between brain networks, also the neurochemistry and neural oscillations that underly creativity.

TA builds on the state of mind (SoM) framework to offer the novelty-seeking model (NSM). The model relates curiosity to creativity but this commentary focuses on creativity: (i) It assesses the SoM + NSM model of creativity-in-the-lab, showing that the focus on semantic networks is inadequate. (ii) It discusses architectural design to sketch ideas for a theory of “big C” creativity.

We question the perspective that curiosity and creativity stem from a shared novelty-seeking process. We emphasize that creativity has two distinct dimensions: Novelty and usefulness, each involving separate cognitive processes. These dimensions may not necessarily mutually reinforce each other. We contend that a more comprehensive model that encompasses the full scope of the creativity construct is needed.

Curiosity and creativity are central pillars of human growth and invention. Although they have been studied extensively in isolation, the relationship between them has not yet been established. We propose that both curiosity and creativity emanate from the same mechanism of novelty seeking. We first present a synthesis showing that curiosity and creativity are affected similarly by a number of key cognitive faculties such as memory, cognitive control, attention, and reward. We then review empirical evidence from neuroscience research, indicating that the same brain regions are involved in both curiosity and creativity, focusing on the interplay between three major brain networks: the default mode network, the salience network, and the executive control network. After substantiating the link between curiosity and creativity, we propose a novelty-seeking model (NSM) that underlies them and suggests that the manifestation of the NSM is governed by one's state of mind.

Our target article set out with an ambitious goal: To provide a unified account of the disparate descriptions of proxy failure across not only social and natural sciences but also engineering and artificial intelligence research. Clearly such a task could only truly be achieved by a broad transdisciplinary community. The wide range of commentaries from a remarkable array of disciplines has not only confirmed our main proposition – that the disparate cases do reflect the same core phenomenon of “proxy failure” – but suggests the viability of a new interdisciplinary undertaking that we might call “proxynomics.” Several comments highlighted key issues and extensions, others provided novel illuminating examples and, perhaps most importantly, quite a few proposed viable solutions or at least mitigation strategies.

Proxy failure in academia has progressed much ahead of what John et al. describe. We see advanced phenomena such as proxy complimentarity in which different players push each others' proxy failures; proxy exploitation in which external agents exploit players' proxies and predatory proxies that devour the goal itself. Academics need to avoid proxy failures by designing behaviorally sound systems.