ScaDS.AI Dresden/Leipzig announces and welcomes you to join its public colloquium session on Wednesday, January 21, 2026 at 1:15 pm CET (11:00 am). The colloquium takes place at seminar room “Zwenkauer See” at ScaDS.AI Dresden/Leipzig (details below) and parallel online (link to Zoom session).

AI-Standardisation in Econometric Research Models

Econometric models are usually used to understand real market scenarios and then applied to predict the result of policies. Today the use of AI-Agents and the advanced computational power is changing the landscape of economic simulations. Gains in precision and forecasting are huge. The ability to simulate markets has been proved feasible with compatibility to economic theory. Some examples are monopolies, duopolies, oligopolies and perfect competition [1]. The main problem of these simulations is the comparability within each other and the replicability. To address that situation we introduce a framework for creating models based on recent ISO standards [2]. The goal is to generate a Dynamic Non-Stochastic General Nomologic Model (DNSGNM) [work-in-progress] using multiple agents reinforced learning [1]. Applications of these models are destined to education and policy making.

About Cristian von Matuschka

His most recent research interests lie at the boundary between AI and econometrics. His work has been published in these peer-reviewed journals [titles translated]: Cuyonomics – Research in Regional Economics (Faculty of Economics, UNCuyo), InTer (Journal for Innovation and Technology Law edited by the Faculty of Economics, TU Chemnitz), and RTI (Journal of Tourism and Identity by the Faculty of Philosophy, UNCuyo). He usually gives guest lectures and expositions throughout Argentina and Germany.

Born in Mendoza in 1985, he received a PhD from the National University of Cuyo in collaboration with the Technical University of Chemnitz in 2020. He was awarded the distinction of the highest degree. His research has been funded with international grants.

References

[1] Von Matuschka, C. (2025). Use of symbolic artificial intelligence for understanding market behaviour. Cuyonomics – Research in Regional Economics, 9(15):135-166. [in Spanish]
DOI:10.48162/rev.42.075

[2] relevant ISO standards      ([IT] for Information technology, [AI] for Artificial intelligence)

ISO/IEC TS 6254:2025	[IT] – [AI] – Objectives and approaches for explainability and interpretability of machine learning (ML) models and artificial intelligence (AI) systems
ISO/IEC 12792:2025	[IT] – [AI] – Transparency taxonomy of AI systems
ISO/IEC TR 20226:2025	[IT] – [AI] – Environmental sustainability aspects of AI systems
ISO/IEC TR 21221:2025	[IT] – [AI] – Beneficial AI systems
ISO/IEC 42005:2025	[IT] – [AI] – AI system impact assessment
ISO/IEC 42006:2025	[IT] – [AI] – Requirements for bodies providing audit and certification of artificial intelligence management systems
ISO/IEC TS 42119-2:2025	[AI] – Testing of AI – Part 2: Overview of testing AI systems
ISO/IEC 5259-5:2025	[AI] – Data quality for analytics and machine learning (ML) – Part 5: Data quality governance framework
ISO/IEC 25642:2025	[IT] – Data governance – Data collaboration framework
ISO 24635-1:2025	Language resource management – Corpus annotation project management – Part 1: Core model
ISO 19178-1:2025	Geographic information – Training data markup language for artificial intelligence – Part 1: Conceptual model
ISO 37114:2025	Sustainable cities and communities – Appraisal framework for datasets and data processing methods that create urban management information
ISO 18374:2025	Dentistry – Artificial intelligence (AI) and augmented intelligence (AuI) based 2D radiograph analysis – Data generation, data annotation and data processing

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Location

ScaDS.AI Dresden/Leipzig
Löhrs Carré, Humboldtstrasse 25, 04105 Leipzig
3rd floor, large seminar room (A 03.07 “Zwenkauer See”)