Summary

In many deep technology domains, innovation managers must make high-stakes prioritization decisions under extreme uncertainty. State-of-the-art knowledge is fluid, widely agreed benchmarks are absent, and performance signals are noisy or hard to interpret. In these contexts, implicit biases, reputational cues, and field-specific status hierarchies can quietly shape which technologies are deemed “promising” or “feasible.” These judgements often form long before robust evidence endorsing a particular technology choice is available.

Interpretations of "what is possible" are also further complicated by a tense geopolitical context. National security concerns, supply chain sovereignty, and strategic autonomy  shape strategic decisions that might otherwise appear purely technical or commercial.

By linking cognitive models of technology, field-specific tacit knowledge, market narratives of technological promise, and ecosystem-level incentives and consensus-building mechanisms, this project develops a critical framework to understand the socio-cognitive factors shaping deep-tech innovations at an early stage. The framework aims to model  how early – and often subjective – technology commitment decisions can exacerbate path uncertainty and early-technology locking in business sectors with high technological turnover.