# Bridging the AI Trustworthiness Gap between Functions and Norms

arXiv: https://arxiv.org/abs/2512.20671 · HTML: https://mlsanity.com/paper/2512.20671/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 25 references that are in the map.
- First posted on arXiv 19 Dec 2025.

## Builds on (most cited first, 6 of 6)

- [Modular Design Patterns for Hybrid Learning and Reasoning Systems: a taxonomy, patterns and use cases](https://mlsanity.com/paper/2102.11965/) (2021)
- [Global AI Ethics: A Review of the Social Impacts and Ethical Implications of Artificial Intelligence](https://mlsanity.com/paper/1907.07892/) (2019)
- [Requirements Engineering for Artificial Intelligence Systems: A Systematic Mapping Study](https://mlsanity.com/paper/2212.10693/) (2022)
- [Are we there yet? Understanding the challenges faced in complying with the General Data Protection Regulation (GDPR)](https://mlsanity.com/paper/1808.07338/) (2018)
- [Why developers cannot embed privacy into software systems? An empirical investigation](https://mlsanity.com/paper/1805.09485/) (2018)
- [I'm all Ears! Listening to Software Developers on Putting GDPR Principles into Software Development Practice](https://mlsanity.com/paper/2103.01371/) (2021)

## Abstract (arXiv)

Trustworthy Artificial Intelligence (TAI) is gaining traction due to regulations and functional benefits. While Functional TAI (FTAI) focuses on how to implement trustworthy systems, Normative TAI (NTAI) focuses on regulations that need to be enforced. However, gaps between FTAI and NTAI remain, making it difficult to assess trustworthiness of AI systems. We argue that a bridge is needed, specifically by introducing a conceptual language which can match FTAI and NTAI. Such a semantic language can assist developers as a framework to assess AI systems in terms of trustworthiness. It can also help stakeholders translate norms and regulations into concrete implementation steps for their systems. In this position paper, we describe the current state-of-the-art and identify the gap between FTAI and NTAI. We will discuss starting points for developing a semantic language and the envisioned effects of it. Finally, we provide key considerations and discuss future actions towards assessment of TAI.