Course ObjectiveAfter completing this course, students will
Understand the role of smart algorithms for big data, in digital
interactions, and in physical manifestations such as robots and the
Know broad classes of algorithms and how they are used for prediction,
social sorting, curating, recommending, gatekeeping, experimentation,
Be familiar with some of the main contemporary thinkers and issues in
the ethics of algorithms
Know and understand the ethical implications of (classes of) algorithms
on privacy, surveillance, discrimination, access to information,
security, free will, human rights, social norms, etc.
Be able to identify stakeholders and ethical implications in healthcare,
design, crime, education, science, job markets, business, journalism,
Course ContentDigital innovation involves both the accumulation of large amounts of
data (so-called Big Data) through various new sensors (such as
smartphones and social networks) as well as artificially intelligent
algorithms (software, but also robots) that can analyze and interpret
that data (i.e. analytics) and act upon it. The main objective of this
course is to develop “algorithmic literacy” which is an understanding of
how (intelligent and adaptive) algorithms influence the way we
communicate, work, obtain information, date, travel, and so on, but also
how we can tackle grand challenges such as crime, healthcare and
education in new, innovative ways. Algorithms are not neutral or
objective, but come with many biases, choices, and political influences
built-in, which heavily determine how people are “seen” by these
algorithms, and how they are treated.
The course covers specifically the various implications algorithms have
on fundamental values in society dealing with privacy, surveillance,
free will, and so on. For each implication typically several competing
stakeholders are involved with opposing viewpoints, value systems or
business models. This requires a delicate balancing of interests. Ethics
deals with finding this balance, with identifying issues and
stakeholders, with employing social and legal solution frameworks, and
possibly with judging whether some developments are good or bad.
The course features lectures on algorithms, ethical issues and domains.
In addition we will read and discuss relevant literature, for which
active participation is required. Each student needs to write an
individual essay about a (self-chosen) ethical problem in a particular
domain. Furthermore, each student participates in a multidisciplinary
design team consisting of students to find a practical solution for an
ethical issue caused by the use of intelligent algorithms.
Teaching MethodsLectures and (interactive) literature discussions.
Method of AssessmentIndividual assignment, group assignments, active participation in group
sessions, and written exam.
LiteratureVarious articles that will be made available through Canvas.
|Language of Tuition||English|
|Faculty||School of Business and Economics|
|Course Coordinator||drs. F.E.J.M. Derksen|
|Examiner||drs. F.E.J.M. Derksen|
You need to register for this course yourself
Last-minute registration is available for this course.
|Teaching Methods||Seminar, Lecture|
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