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“Agreeableness Effect” (AI Sycophancy)The tendency for large language models, which are optimized to be cooperative, to affirm a user’s premise or framing
Abstract The neuropsychological feedback session, a critical component of patient care, is undergoing a significant transformation. Traditionally verbal and in person, feedback models are now adapting to new clinical realities, including widespread telehealth integration post COVID-19 and the patient access requirements. This chapter reviews the emerging evidence for innovative, technology-driven feedback methods. It explores the use of digital visualization tools to enhance comprehension, artificial intelligence–assisted summaries and natural language processing to tailor reports for diverse stakeholders, and audio recordings to improve patient recall. It examines the potential of passive and active data monitoring from wearables and mobile devices to enable “just-in-time” adaptive interventions. While these technologies promise more dynamic, personalized, and continuous care, the chapter also addresses critical challenges, including data privacy, algorithmic bias, and the digital divide, emphasizing the need for ethical and equitable implementation.
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