DesignationISO/IEC FDIS 24029-3
Stage50.00, FDIS registered
Planning date, an estimate16 Feb 2027
Text todayPublic record and DIS view
Home / What the introduction decides
What the introduction decides
The themes the public introduction states, and what each one asks of you.
6 pages in this group. Every page states its citation, the evidence a reviewer asks for, and what it does not cover. Last updated: 2026-10-21.
Robustness as a reliability sub-characteristic
The introduction places robustness inside an AI quality model and cites ISO/IEC 25059:2023, which treats it as a sub-characteristic of reliability. 25059 frames robustness as how far a syste
Formal methods and statistical methods are complements
The introduction says a team can show that a system keeps performing when local conditions vary by using formal methods, as Part 2 illustrates, and that statistical work adds a complement be
High-dimensional input and why exhaustive testing fails
The introduction says neural networks can handle data with many dimensions, naming perception and connected-device data, and that the space of possible inputs is variable and too large to co
Fitting the statistical line into a wider scheme
The introduction says statistical work may sit inside whatever robustness assessment a team already runs and strengthen it. No particular scheme is prescribed.
What a robustness assessment can and cannot claim
The introduction calls a robustness assessment one step toward trust in AI systems, particularly neural networks. It does not say that such an assessment establishes trust, safety or conform
What the document means by a neural network
The introduction describes neural networks as common AI systems used for detection, classification and interpolation across text, speech, images, time series and tables. Part 1 describes one