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#40994 / #1

SoSe 2020 - WiSe 2024/25

English

Ethics, data science, and networked AI

6

Berendt, Bettina

Benotet

Portfolioprüfung

English

Zugehörigkeit


Fakultät IV

Institut für Telekommunikationssysteme

34332900 FG Internet und Gesellschaft

Keine Angabe

Kontakt


Keine Angabe

Berendt, Bettina

berendt@tu-berlin.de

http://www.berendt.de/teaching.html

Lernergebnisse

Students who have successfully taken this course know the basics of methods of philosophy and argumentation theory that are relevant for ethical assessments of socio-technical systems involving computational technology, and they can describe them. They are able to distinguish between fields such as normative and applied ethics, and between schools such as deontological and consequentialist ethics, and to explain these fields and the differences between them with regard to ethical assessments of technology. They are able to position ethics with regard to other regulation systems. They know and are able to analyse the main arguments brought forward by different positions with regard to exemplary current fields of socio-technical systems involving computational technology, in particular data science and networked AI, and the effects these systems have on individuals and society. They can describe, compare and assess exemplary frameworks and techniques intended to integrate (explicit) values into systems “by design”. They can make and argue choices they would (or do) make as data scientists. They are able to take a critical attitude to the choices they make with regard to these dimensions, and to argue their position. They know relevant professional codes of conduct, they know how to compare them with one another, and they are able to assess and argue to what extend and why they are bound to them. Students are able to read, understand and present state-of-the-art research in a selected field of data science / AI with ethical impact. They are able to independently and systematically connect their substantiated understanding of the technological aspects of these research works with the competencies learned in the present course. They are also able to read this work critically, i.e. to identify where the authors position themselves (whether explicitly or implicitly) with regard to the ethical impact of their work, to question this stance, and to identify gaps and opportunities for future work. They are able to present their analysis in a way that exposes relevant inherent dilemmas and that engages their seminar audience in an exploration of the multifaceted nature of the ethical problems raised.

Lehrinhalte

The impact of computer science and related fields on our society and everyday life has increased tremendously, and computer scientists should therefore be aware of the societal and morally relevant impact of the artifacts they build and of the systems they contribute to. This awareness can be trained and sharpened. Furthermore, computer scientists ought to have the necessary competencies for making morally acceptable and professional decisions in the development processes they are participating in. The thoughts and insights of academic ethics - i.e. the field professionally concerned with ethics and morals - are a necessary precondition for these competencies, and they are a necessary counterpart to the technical understanding and competencies that computer scientists bring to design. This course aims at bringing these two perspectives together. It will introduce relevant knowledge from the field of academic moral philosophy as well as soft skills needed to argue clearly, precisely, and convincingly (i.e. beyond the level of everyday discussions at bars and parties). You will learn how to apply these skills to problems that will surface at many points in your career -  whether in research, industry, or other fields. The ideas will be explained, and the skills trained, through analyses of several currently much discussed fields and phenomena linked to technologies from data science and networked AI. Ethical problems often present dilemmas and raise substantial controversy. In the seminar component of this course, you will evaluate state-of-the-art research papers and present them in ways that demonstrate your competencies and involve the audience in a meaningful controversy, showing how intellectually stimulating and fun a serious engagement with ethics can be. This course covers:  - an introduction to the methods of philosophy, argumentation theory, and the basics of normative as well as applied ethics; - an introduction to the schools of ethics that are commonly used to assess what is “right” or “wrong” in choices related to computational technology; - the role of ethics in relation to other regulations such as law and industry self-regulation; - starting points to evaluate practices and technologies already in use or not that far away, such as: surveillance and tracking (online, GPS, CCTV, …); big data, machine learning and predictive analytics and phenomena created by them, including filter bubble effects/echo chambers and bias/discrimination; autonomous vehicles; - an overview of relevant choices that need to be made by data scientists, and principled approaches to making these choices based on ethical reasoning; - selected design frameworks and techniques that are intended to “bake ethics into” systems, such as value-sensitive design or privacy by design; - a guide through the multitude of ethics-related codes of professional associations; - an outlook onto the question of whether machines themselves can be ethical agents.

Modulbestandteile

Compulsory area

Die folgenden Veranstaltungen sind für das Modul obligatorisch:

LehrveranstaltungenArtNummerTurnusSpracheSWS ISIS VVZ
Ethics, data science, and networked AIVL3433 L 10611WiSe/SoSeen2
Ethics, data science, and networked AISEM3433 L 10612WiSe/SoSeen2
ISIS-Kurssuche nach Veranstaltungen des Moduls

Arbeitsaufwand und Leistungspunkte

Ethics, data science, and networked AI (VL):

AufwandbeschreibungMultiplikatorStundenGesamt
Attendance15.02.0h30.0h
Pre/post processing15.04.0h60.0h
90.0h(~3 LP)

Ethics, data science, and networked AI (SEM):

AufwandbeschreibungMultiplikatorStundenGesamt
Attendance15.02.0h30.0h
Pre/post processing15.04.0h60.0h
90.0h(~3 LP)
Der Aufwand des Moduls summiert sich zu 180.0 Stunden. Damit umfasst das Modul 6 Leistungspunkte.

Beschreibung der Lehr- und Lernformen

- listening to presentations - reading scientific literature and news media - participating in interactive discussions - giving presentations - organising and leading interactive discussions - writing scientific essays - "Co-Referat" and joint authoring of essays: close cooperation with a team colleague on the above tasks

Voraussetzungen für die Teilnahme / Prüfung

Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen:

Students have a background in data science and/or AI, as acquired through a Bachelor degree in Computer Science or a related field. Student have a sufficient level of competency in English to follow and participate in discussions of Computer Science and interdisciplinary topics, to read scientific papers, and to write scientific essays. (At least CEFRL level B2 or equivalent.)

Verpflichtende Voraussetzungen für die Modulprüfungsanmeldung:

Dieses Modul hat keine Prüfungsvoraussetzungen.

Abschluss des Moduls

Benotung

Benotet

Prüfungsform

Portfolio examination

Art der Portfolioprüfung

100 Punkte insgesamt

Sprache(n)

English

Prüfungselemente

NamePunkteKategorieDauer/Umfang
Essay part 121schriftlich5 pages
Essay part 2 ("Co-essay")20schriftlich3 pages
Essay part 3 (jointly authored synthesis)20schriftlich3 pages
Interactive presentation 113mündlich20 minutes
Interactive presentation 2 ("Co-Referat")13mündlich10 minutes
Interactive presentation 3 (joint element)13mündlich30 minutes

Notenschlüssel

Notenschlüssel »Notenschlüssel 2: Fak IV (2)«

Gesamtpunktzahl1.01.31.72.02.32.73.03.33.74.0
100.0pt95.0pt90.0pt85.0pt80.0pt75.0pt70.0pt65.0pt60.0pt55.0pt50.0pt

Prüfungsbeschreibung (Abschluss des Moduls)

Students team up in groups of 2. They select topics and research works that are independent of each other, but together create a coherent theme. Together, they are responsible for one seminar slot. Each team member presents an analysis of their respective topic/research works (20 minutes), and answers the other team member's presentation ("Co-Referat", 10 minutes). The two team members together jointly create the remaining 30 minutes. They engage the audience in the joint part and, if applicable, also already in the first parts. The team then writes up the results of their work and of the presentation: Each team member writes 5 pages about their own part and 3 pages in response to the other one's part. The team also co-authors a synthesis part of a further 3 pages.

Dauer des Moduls

Für Belegung und Abschluss des Moduls ist folgende Semesteranzahl veranschlagt:
1 Semester.

Dieses Modul kann in folgenden Semestern begonnen werden:
Winter- und Sommersemester.

Maximale teilnehmende Personen

Die maximale Teilnehmerzahl beträgt 26.

Anmeldeformalitäten

The registration procedure will be published and made available on the supplementary Web page of this module. You need to register with the course director. Depending on your course of studies, registration may include further registration steps at your examination office ("Prüfungsamt") or via QISPOS. Registration with the course director: Please register by the first Monday of the semester in order to attend this course. Please register by the fourth Monday of the semester in order to take this course for credit. Students who have not registered by that day CANNOT take the examination and CANNOT get credit for this course.

Literaturhinweise, Skripte

Skript in Papierform

Verfügbarkeit:  nicht verfügbar

 

Skript in elektronischer Form

Verfügbarkeit:  nicht verfügbar

 

Literatur

Empfohlene Literatur
Keine empfohlene Literatur angegeben

Zugeordnete Studiengänge


Diese Modulversion wird in folgenden Studiengängen verwendet:

Studiengang / StuPOStuPOsVerwendungenErste VerwendungLetzte Verwendung
Dieses Modul findet in keinem Studiengang Verwendung.

Sonstiges

Materials will be made available online beginning at the start of the semester.