Debates Sobre Ética de la Ciencia de Datos

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Créditos
3
Tipos
Optativa
Requisitos
Esta asignatura no tiene requisitos, pero tiene capacidades previas
Departamento
ESSI
Web
https://learnsql.fib.upc.es/moodle/
In this course we debate the impact on society of new advances in Data Science. We focus on ethics and the impact of Data Science on society. This course fosters the social competences of students, by building on their social responsibility, but also acquiring communication skills to debate about Data Science problems from an ethical perspective. The overall aim is to develop their critical attitude and reflection for social good.

Profesorado

Responsable

  • Alberto Abello Gamazo ( )
  • Oscar Romero Moral ( )

Otros

  • Petar Jovanovic ( )

Horas semanales

Teoría
0.6
Problemas
0.8
Laboratorio
4
Aprendizaje dirigido
0
Aprendizaje autónomo
9.6

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 analytical systems: Debates
    After presenting what will be next in the area of data science and big data, in this module we discuss the impact these new ideas will have on society. More specifically, we will discuss about ethics, personal data protection, hacking, licensing / patenting, IP rights, etc. The discussion will be on the form of debates.
  3. Read a book to develop your ethical reasoning
    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

Debates on Ethics and social impact of next generation analytical systems and Big Data

During these sessions the debates discussing ethics and social impact of next generation analytical systems and Big Data will take place. 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
0h
Problemas
0h
Laboratorio
20h
Aprendizaje dirigido
0h
Aprendizaje autónomo
19h

Read a seminal book on ethics for data science and Big Data

Reads the book and conducts the assessment provided
Objetivos: 1 2 3 4 5 6
Contenidos:
Teoría
0h
Problemas
4h
Laboratorio
0h
Aprendizaje dirigido
0h
Aprendizaje autónomo
21h

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 the read and reflection of a seminal book on ethics for data science.

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 book reading (BM) is evaluated by means of a deliverable related to it.

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

The evaluation is done on an individual basis.

Bibliografía

Básica:

Capacidades previas

Basic knowledge in Data Management and Analytics