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Deutsch(DE) Time-Series Forecasting in Safety-Critical Environments: An EU-AI-Act-Compliant Open-Source Package / Zeitreihenprognose in sicherheitskritischen Umgebungen: Ein KI-VO-konformes Open-Source-Paket

New open-source package ensures AI forecasting tools meet EU AI Act compliance

By PulseAugur Editorial · [1 sources] ·

A new open-source Python package, spotforecast2-safe, has been released to address time-series forecasting in safety-critical environments. It integrates compliance with the EU AI Act, IEC 61508, ISA/IEC 62443, and the Cyber Resilience Act directly into the library's design. The package enforces strict development and process rules, deliberately excluding features like AutoML and LLMs to maintain determinism and minimize attack surfaces, with a traceability matrix mapping regulations to code mechanisms. AI

IMPACT Provides a framework for developing AI forecasting tools that meet stringent regulatory requirements in safety-critical sectors.

RANK_REASON Release of an open-source package with a focus on regulatory compliance for AI applications.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New open-source package ensures AI forecasting tools meet EU AI Act compliance

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Release of an open-source package with a focus on regulatory compliance for AI applications.
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 Deutsch(DE) · Thomas Bartz-Beielstein, Eva Bartz ·

    Time-Series Forecasting in Safety-Critical Environments: An EU-AI-Act-Compliant Open-Source Package

    arXiv:2604.23859v1 Announce Type: new Abstract: With spotforecast2-safe we present an integrated Compliance-by-Design approach to Python-based point forecasting of time series in safety-critical environments. A review of the relevant open-source tooling shows that existing compli…

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