Debats Sobre Ètica de la Ciència de Dades

Crèdits
3
Tipus
Optativa
Requisits
Aquesta assignatura no té requisits , però té capacitats prèvies
Departament
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.

Professorat

Responsable

Altres

Hores setmanals

Teoria
0.9
Problemes
0
Laboratori
3
Aprenentatge dirigit
0
Aprenentatge autònom
6.85

Competències

Competències Transversals

Sostenibilitat i compromís social

  • CT2 - Conèixer i comprendre la complexitat dels fenòmens econòmics i socials típics de la societat del benestar; tenir capacitat per relacionar el benestar amb la globalització i la sostenibilitat; assolir habilitats per usar de forma equilibrada i compatible la tècnica, la tecnologia, l'economia i la sostenibilitat.

    • Tercera llengua

  • CT5 - Conèixer una tercera llengua, preferentment l'anglès, amb un nivell adequat oral i escrit i en consonància amb les necessitats que tindran els titulats i titulades.

    • Perspectiva de gènere

  • CT6 - Conèixer i comprendre, des de l'àmbit de la titulació mateixa, les desigualtats per raó de sexe i gènere en la societat, i integrar les diverses necessitats i preferències per raó de sexe i gènere en el disseny de solucions i la resolució de problemes.

    • Bàsiques

  • CB7 - Que els estudiants siguin capaços d'integrar coneixements i enfrontar-se a la complexitat de formular judicis a partir d'una informació que, essent incomplerta o limitada, inclogui reflexions sobre les responsabilitats socials i ètiques vinculades a l'aplicació dels seus coneixements i judicis.

    • Competències Tècniques

    Específiques

  • CE12 - Aplicar la ciència de dades en projectes multidisciplinaris per resoldre problemes en dominis nous o poc coneguts per la ciència de dades i que siguin econòmicament viables, socialment acceptables, i d'acord amb la legalitat vigent
  • CE13 - Identificar les principals amenaces en l'àmbit de l'ètica i la privacitat de dades en un projecte de ciència de dades (tant en l'aspecte de gestió com d'anàlisi de dades) i desenvolupar i implantar mesures adequades per esmorteïr aquestes amenaces.

    • Objectius

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

    Continguts

    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
      The final assessment consists of a practical exercise focused on evaluating the ethical impact of a real Data Science project. Students identify potential risks related to privacy, bias, fairness, transparency, and accountability. The exercise requires proposing concrete mitigation measures and responsible design improvements.

    Activitats

    Activitat Acte avaluatiu


    Introduction

    The course is introduced. We will discuss the course structure, the methodology and the evaluation.
    Objectius: 1
    Continguts:
    Teoria
    3h
    Problemes
    0h
    Laboratori
    0h
    Aprenentatge dirigit
    0h
    Aprenentatge autònom
    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.
    Objectius: 1 2 3 4 5 6
    Continguts:
    Teoria
    2h
    Problemes
    0h
    Laboratori
    15h
    Aprenentatge dirigit
    0h
    Aprenentatge autònom
    15h

    Applied Ethical Evaluation on Data Science

    Conducts a real project and presents results
    Objectius: 1 2 3 4 5 6
    Continguts:
    Teoria
    1h
    Problemes
    0h
    Laboratori
    6h
    Aprenentatge dirigit
    0h
    Aprenentatge autònom
    25h

    Metodologia docent

    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.

    Mètode d'avaluació

    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.

    Bibliografia

    Bàsic

    Capacitats prèvies

    Basic knowledge in data management and analysis