Debates Sobre Ética de la Ciencia de Datos

Créditos
3
Tipos
Optativa
Requisitos
Esta asignatura no tiene requisitos , pero tiene capacidades previas
Departamento
ESSI
Web
https://learnsql.fib.upc.es/moodle/
This course explores and critically debates the societal impact of recent advances in Data Science. It focuses on the ethical challenges arising from the development and deployment of data-driven technologies, examining their implications for individuals, communities, and institutions.

The course fosters students¿ social and ethical competences by strengthening their sense of social responsibility and enhancing their ability to communicate and argue effectively about complex Data Science issues from an ethical perspective. Through structured debates and critical analysis, students develop the capacity to assess technological developments not only from a technical standpoint, but also in terms of fairness, accountability, transparency, and social good.

The overall aim of the course is to cultivate critical thinking, ethical reflection, and a responsible professional attitude toward the societal role of Data Science.

Profesorado

Responsable

Otros

Horas semanales

Teoría
0.9
Problemas
0
Laboratorio
3
Aprendizaje dirigido
0
Aprendizaje autónomo
6.85

Competencias

Competencias Transversales

Sostenibilidad y compromiso social

  • CT2 - Conocer y comprender la complejidad de los fenomenos economicos y sociales tipicos de la sociedad del bienestar; capacidad para relacionar el bienestar con la globalizacion y la sostenibilidad; habilidad para utilizar de forma equilibrada y compatible la tecnica, la tecnologia, la economia y la sostenibilidad.

    • Lengua extranjera

  • CT5 - Conocer una tercera lengua, preferentemente el inglés, con un nivel adecuado oral y escrito y en consonancia con las necesidades que tendrán los titulados y tituladas.

    • Perspectiva de género

  • CT6 - Conocer y comprender, desde el propio ámbito de la titulación, las desigualdades por razón de sexo y género en la sociedad; integrar las diferentes necesidades y preferencias por razón de sexo y de género en el diseño de soluciones y resolución de problemas.

    • Básicas

  • CB7 - Que los estudiantes sean capaces de integrar conocimientos y enfrentarse a la complejidad de formular juicios a partir de una información que, siendo incompleta o limitada, incluya reflexiones sobre las responsabilidades sociales y éticas vinculadas a la aplicación de sus conocimientos y juicios.

    • Competencias Técnicas

    Específicas

  • CE12 - Aplicar la ciencia de datos en proyectos multidisciplinares para resolver problemas en dominios nuevos o poco conocidos y que sean económicamente viables, socialmente aceptables, y de acuerdo con la legalidad vigente
  • CE13 - Identificar las principales amenazas en el ámbito de la ética y la privacidad de datos en un proyecto de ciencia de datos (tanto en el aspecto de gestión como de análisis de datos) y desarrollar e implantar medidas adecuadas para mitigar dichas amenazas.

    • Objetivos

    1. Acknowledge the current and future impact of next generation analytical systems on society
      Competencias relacionadas: CT2, CT5, CT6, CE12, CE13, CB7,
    2. Ability to study and analyze problems in a critical mood
      Competencias relacionadas: CT2, CT5, CT6, CE12, CE13, CB7,
    3. Ability to critically read texts
      Competencias relacionadas: CT2, CT5, CT6, CE12, CE13, CB7,
    4. Develop critical reasoning with special focus on ethics and social impact
      Competencias relacionadas: CT2, CT5, CT6, CE12, CE13, CB7,
    5. Develop soft skills to defend - criticize a predetermined position in public
      Competencias relacionadas: CT2, CT5, CT6, CE12, CE13, CB7,
    6. Improve the writing skills
      Competencias relacionadas: CT2, CT5, CT6, CE12, CE13, CB7,

    Contenidos

    1. Introduction: Debate Rules and Course Structure
      In this first module we will present the course, its structure and methodology.
    2. Ethics and social impact of next generation data-driven systems: Debates
      This course is structured around formal debates inspired by debate leagues.

      Students argue both sides of ethical dilemmas related to Data Science and data-driven technologies. Each debate explores the societal, legal, and moral implications of real-world data practices. Participants develop evidence-based arguments, rebuttals, and critical questioning skills. The format strengthens ethical reasoning, communication abilities, and responsible professional judgment.
    3. Applied ethical evaluation in Data Science
      A mandatory book read that will develop the ethical reasoning of the students

    Actividades

    Actividad Acto evaluativo


    Introduction

    The course is introduced. We will discuss the course structure, the methodology and the evaluation.
    Objetivos: 1
    Contenidos:
    Teoría
    3h
    Problemas
    0h
    Laboratorio
    0h
    Aprendizaje dirigido
    0h
    Aprendizaje autónomo
    8h

    Ethics and social impact of next generation data-driven systems: Debates

    You must read the available material before the debate. Then, during the debate you will assign to a group: either to defend an idea, or go against it. You may also be asked to moderate the debate. Then, the debate takes place and afterwards, each group needs to write down a report with their conclusions.
    Objetivos: 1 2 3 4 5 6
    Contenidos:
    Teoría
    2h
    Problemas
    0h
    Laboratorio
    15h
    Aprendizaje dirigido
    0h
    Aprendizaje autónomo
    15h

    Applied Ethical Evaluation on Data Science

    Conducts a real project and presents results
    Objetivos: 1 2 3 4 5 6
    Contenidos:
    Teoría
    1h
    Problemas
    0h
    Laboratorio
    6h
    Aprendizaje dirigido
    0h
    Aprendizaje autónomo
    25h

    Metodología docente

    There will be 6 face-to-face sessions. The first one introduces the course. The other will be debates. Before each debate, a proposed topic is given, together with some basic material (typically papers) to foste a debate during the next lecture.

    The students are meant to read the material, and look for additional stuff, *before* the lecture so that they can better defend their position during the debate.
    During the lecture, there will be an organized debate (pro and against groups will be configured as well as a moderator).
    After the debate, each group (pro, against and moderator) will be asked to write down their debate conclusions.

    The course methodology puts the focus on three main aspects:
    - Critical reasoning (with special focus on ethics and social impact),
    - Develop soft skills to defend - criticize a position in public,
    - Improve the writing skills summarizing an event.

    The course methodology wraps up with ta practical project.

    Método de evaluación

    Each debate entails two main parts:
    - (60%) The face-to-face debate Db (this mark is computed from the report written by the moderator group and supervised by the lecturers),
    - (40%) The written conclusions Wr.

    Thus, each debate mark (Di) is computed as Di = Db*0,6 + Wr*0,4. The final mark will be computed as the average of the debates. Those students not debating will have to write a report and their session mark will be 100% on Wr (i.e., Di = Wr).
    The final evaluation of the debates (DM) is the average mark of the debates.

    The project (P) is evaluated by means of a deliverable related to it.

    The course final mark is calculated as follows: 0,8*DM + 0,2*P.

    Bibliografía

    Básico

    Capacidades previas

    Basic knowledge in data management and analysis