Can Artificial Intelligence Support Goals It Cannot Contextualize? The Case for EEG-Derived Human Context
Year: 2026
Type: preprint
Abstract: Artificial intelligence is increasingly used to support human goals, but the usefulness of its guidance depends on the context it has about the person pursuing them. Knowing what a user wants does not necessarily reveal their current cognitive state, recent behavior, constraints, or the conditions affecting their ability to act. This paper presents a conceptual framework for goal contextualization and examines whether EEG-derived information can provide an additional source of human context for AI. Rather than treating neural state as an objective to optimize, we propose using EEG-derived features alongside user-established goals, behavior, history, and current circumstances to inform context-dependent AI reasoning. We distinguish this approach from conventional neuroadaptive systems and review relevant evidence from EEG, self-regulation, context-aware AI, and neuroadaptive language models. ANKH BrainStudio and ANKH AI are presented as a practical implementation of the proposed architecture, designed for ordinary people pursuing self-defined goals in everyday settings. The central falsifiable question is simple: does an AI become meaningfully more useful to the user when EEG-derived context is added to everything it could already know without it? Project: Learn more about ANKH BrainStudio and ANKH AI at weareankh.com, or view ANKH BrainStudio on Kickstarter.
Author: Rogozea, Alex
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7210264537
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