Presenter: Aidan Jalbert
Faculty Sponsor: Youngbin Kwak
School: UMass Amherst
Research Area: Psychology and Behavioral Sciences
ABSTRACT
Nowadays, humans increasingly collaborate with artificial intelligence (AI) across multi-stage decision processes, yet little is known about how specific AI roles shape people’s subjective sense of agency (SoA), performance, and evaluations of AI partners. Sense of agency (SoA) is the perception of being in control of one’s actions and their consequences. This project explores how ‘AI’ influences the SoA experience at the neural network level. Guided by existing literature, this study examines alpha-band connectivity between the supplementary motor area (SMA) and right inferior frontal gyrus (rIFG). Participants will complete a behavioral paradigm in which AI is involved at various stages of decision making, resulting in the following four conditions: No AI, AI-assisted sampling, AI-assisted placing, and Full AI. Participants’ neural activity is recorded using a 64-channel electroencephalogram (EEG) during task completion. SoA, performance ratings, and baseline AI attitudes are also collected. Preliminary analyses with 12 participants indicate SoA is lowest when the entire task is completed using AI (Full AI condition: 𝜇̂mean = 2.21). Participants were most satisfied in the AI-assisted placing condition compared to all others. Alpha-band activity Human-AI differences are trending toward insignificance; however, Human-AI differences in theta power gradually emerge throughout the task. Initial results indicate that the context of AI inclusion matters to the human-AI interaction experience. Furthermore, temporal data coinciding with behavioral patterns suggest that effects accumulate through interaction. AI is a proliferating presence in our society, making it imperative for the scientific community to understand its impact on the brain.RELATED ABSTRACTS