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Dr Agnieszka Kulacka

  • Overview

    Overview

    Qualifications

    Web profiles

  • Research

    Research

    Research interests

    • Artificial Intelligence in Legal Context

    Research overview

    Dr Kulacka is currently researching the legal personhood of Artificial Intelligence (AI) within the framework of Intellectual Property (IP) Law. Her work focuses on whether and how AI can be recognised as a legal entity, particularly in relation to authorship rights over creative works and patents. By analysing the criteria for legal personhood and comparing AI to non-human entities such as corporations, Dr Kulacka aims to propose practical legal reforms to address the challenges posed by AI-generated works. This interdisciplinary study integrates law, technology, and ethics to develop adaptable legal frameworks for the evolving role of AI in society.

    In Mathematical Fuzzy Logic, Dr Kulacka proved a strong completeness theorem for an extended axiomatic system of BL with respect to all continuous t-norms, without altering BL's language. This extended Hájek’s foundational work on BL, which unifies Product, Łukasiewicz, and Gödel logics within a single framework. Additionally, she developed a tableau calculus for BL and its extensions, including the Baaz connective and involutive negation, enabling the construction or refutation of models for sets of formulas. The calculus, based on the decomposition theorem for continuous t-norms, was further applied to decision methods in fuzzy description logics, achieving optimal computational complexity.

    In Statistical Linguistics, Dr Kulacka investigated the statistical properties and patterns of language, contributing to synergetic linguistics through the application of mathematical models such as the Menzerath-Altmann Law. Her work explored phenomena such as the relationship between linguistic unit lengths and complexity, validated statistical language laws, and examined clitics in Polish syntax to reveal dependencies on grammatical case. By employing advanced quantitative methods, she provided insights into linguistic structures and dynamics, influencing natural language processing and the theoretical underpinnings of computational linguistics. Her research emphasised the integration of statistical analysis with linguistic theory to address both foundational and applied linguistic questions.



  • Supervision and teaching

    Supervision and teaching

    Teaching

    Teaching modules

    • Quantitative Techniques (BUEM027S6)
    • IT and Data Skills for Economics (BUEM113H3)
    • Quantitative Economic Methods (Fast Track) (FFEC911S4)
  • Publications

    Publications

    Article