journal article · international journal of research in computing · 2026

Computational Knightian Uncertainty: Undecidability and the Limits of Cyber Risk Quantification in Software-Intensive Firms

abstract

The paper argues that software creates a residual class of uncertainty that does not collapse neatly into ordinary probabilistic risk. Because many security, safety, and compliance questions are undecidable in the general case, even perfect code visibility and abundant classical computation cannot eliminate all uncertainty. The article names that remainder computational Knightian uncertainty (CKU), then connects it to structural opacity in codebases and to practical downstream effects such as incident severity, cyber insurance outcomes, and M&A discounting.

@article{nguyen2026computational,
  author = {Nguyen, Michel},
  title = {Computational Knightian Uncertainty: Undecidability and the Limits of Cyber Risk Quantification in Software-Intensive Firms},
  year = {2026},
  journal = {International Journal of Research in Computing},
  doi = {10.64701/ijrc/345/9117},
  url = {https://doi.org/10.64701/ijrc/345/9117}
}