119 citations · 308 across the 15 of their papers we have counts for
4 papers · 1 filter
An Affective-Taxis Hypothesis for Alignment and Interpretability
Eli Sennesh, Maxwell Ramstead
AI alignment is a field of research that aims to develop methods to ensure that agents always behave in a manner aligned with (i.e. consistently with) the goals and values of their…
A Path Towards Legal Autonomy: An interoperable and explainable approach to extracting, transforming, loading and computing legal information using large language models, expert systems and Bayesian networks
Axel Constant, Hannes Westermann, Bryan Wilson +6
Legal autonomy - the lawful activity of artificial intelligence agents - can be achieved in one of two ways. It can be achieved either by imposing constraints on AI actors such as…
Designing explainable artificial intelligence with active inference: A framework for transparent introspection and decision-making
Mahault Albarracin, Inês Hipólito, Safae Essafi Tremblay +4
This paper investigates the prospect of developing human-interpretable, explainable artificial intelligence (AI) systems based on active inference and the free energy principle. We…
Designing Ecosystems of Intelligence from First Principles
Karl J Friston, Maxwell J D Ramstead, Alex B Kiefer +17
This white paper lays out a vision of research and development in the field of artificial intelligence for the next decade (and beyond). Its denouement is a cyber-physical ecosyste…