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  • LESSON 12 - ARTIFICIAL INTELLIGENCE FOUNDATIONS FOR BROADENING CULTURAL HORIZONS

    Algorithmic Sycophancy

    In this lesson, we address key concepts related to AI design that allow us to reflect on how these systems operate and what kind of relationship we build with them. Algorithmic sycophancy, transparency, concealment of uncertainty, and anthropomorphism are some of the defining features of language models. Understanding them enables us to critically evaluate how we use these technologies and consider the socio-educational implications that arise when these features remain invisible.

    We also reflect on how sycophancy can impact pedagogical relationships and trust-building. Models adopt an approachable tone, offer constant availability, and can foster feelings of closeness or trust during interactions, which may influence the teacher–student–AI dynamic. We analyze varying degrees of dependency—ranging from critical and reflective usage to a concerning substitution of human connections—and warn against using AI for emotional support without professional mediation. This lesson invites us to question not only what AI answers, but how it answers and what repercussions it may have on the autonomy and critical judgment of its users.

    ‼️ Important: In this lesson there is an assignment to complete before watching the lecture. It is important that you carry it out; while this preliminary activity is ungraded, completing it is a requirement to pass the course. At the end of the lesson, you will be asked to answer a few questions. These final answers are graded, and completing them is required to finish and earn credit for the course.

    👩‍🏫 Instructor: Emilia Echeveste

    • Warming Up for the Lesson


      Before diving into the lesson, it is important that you complete this assignment.
      This form seeks to gather your reflections to continue thinking, in a context-aware manner, about the connection between Generative Artificial Intelligence (GAI) and education. Your contributions will be of great value to enrich the knowledge we are building around these processes.

      The form includes Likert-scale questions designed to assess your level of agreement with various statements, followed by open-ended questions aimed at exploring the reasons behind your answers in greater depth.
    • Algorithmic Sycophancy URL

      Prefer to watch in a language other than Spanish? Just turn on CC, go to Settings (⚙️) > Subtitles > Auto-translate, and select your language!

    • Below you will find the lesson slides, designed as a reference to revisit the ideas, questions, and tensions raised in the video. (Please note: The slides are in Spanish).

      📚 Key Concepts

      Algorithmic sycophancy: The tendency of models to appear excessively accommodating or agreeable toward the user—even when the user is wrong—often at the expense of factual accuracy or ethical considerations (Sicilia et al., 2025).

      Anthropomorphization: The tendency to attribute human traits, emotions, intentions, or capabilities to artificial intelligence systems, especially based on how these systems interact or communicate with users (Rodrigues, 2025).

      Transparency in AI models: The extent to which an artificial intelligence system makes relevant operational aspects visible to users, such as response generation criteria, system limitations, or the level of confidence associated with its outputs. Transparency enables users to evaluate system reliability and fosters informed interactions between humans and artificial agents (Stowers et al., 2016; Vössing et al., 2022).

      A creation by Fundación Vía Libre in collaboration with FAMAF – UNC.
    • Assignment: Algorithmic Sycophancy Cuestionario