Practically or theoretically, whether teaching a classroom full of Penn State students or pondering concepts with a smaller group of international colleagues, Heather Shoenberger aims to bring curiosity and optimism as she considers the challenges and opportunities related to artificial intelligence.
Classroom creation Heather Shoenberger co-created and teaches 'COMM 200N Generative AI for All,' an interdisciplinary undergraduate course at Penn State. This popular course, cross-listed in Communications and Engineering, aims to educate students on how generative AI works, its ethical and sociopolitical implications, and its potential disruptions. Shoenberger continuously updates the content to reflect the rapidly changing technology and fosters collaborative discussions in class. Relational research Shoenberger's recent research introduced the Human-AI Asymmetric Relationship Theory (HAART), published in a special AI-focused issue of the Journal of Advertising. This theory highlights a fundamental imbalance: AI conversational agents can simulate relational traits (like emotional responsiveness and commitment) but cannot genuinely experience or reciprocate them. This asymmetry can lead users to falsely perceive a mutual relationship, potentially making them vulnerable. The HAART framework aims to guide future research in human-AI relationships, especially in advertising, and could influence future transparency and regulation efforts.
Classroom creation
Heather Shoenberger co-created and teaches 'COMM 200N Generative AI for All,' an interdisciplinary undergraduate course at Penn State. This popular course, cross-listed in Communications and Engineering, aims to educate students on how generative AI works, its ethical and sociopolitical implications, and its potential disruptions. Shoenberger continuously updates the content to reflect the rapidly changing technology and fosters collaborative discussions in class.
Relational research
Shoenberger's recent research introduced the Human-AI Asymmetric Relationship Theory (HAART), published in a special AI-focused issue of the Journal of Advertising. This theory highlights a fundamental imbalance: AI conversational agents can simulate relational traits (like emotional responsiveness and commitment) but cannot genuinely experience or reciprocate them. This asymmetry can lead users to falsely perceive a mutual relationship, potentially making them vulnerable. The HAART framework aims to guide future research in human-AI relationships, especially in advertising, and could influence future transparency and regulation efforts.
