Urbidata: Responsible Design for Fair Data Cities

In this course we explore the main principles of data ethics, and the relevance of applied ethics in the domain of the data-driven city.

Eight billion people and their devices produce unimaginable amounts of data, seven days a week, 24 hours a day. Data on all aspects of human existence. Data, processed by AI and increasingly powerful computers, that promise mankind the opportunity to influence all aspects of life, especially in the urban setting. The concept of the 'smart city' assumes that big data leads to better (after all smart) solutions for planners, designers, industry and, at the end, citizens. Urbidata, the data-driven city of 2050, will be optimally planned, with smart mobility that allows for efficient and safe use of space and time, and citizens living in smart homes and working in smart offices that cater optimally their needs, based on their personal profiles.

Does this technology driven perspective provide the answer how we want the life in the future city of Urbidata to look like? Should all developments of data-driven solutions (e.g. by architects, urban planners and geo-specialists) and their use be permissible in the light of the consequences? The choices we make today determine our world of tomorrow.

Taking a critical, responsible design perspective it's clear that our data-driven future cannot be just a question of engineering and economic models. How about values as autonomy, privacy, transparency and consent?

At first sight this interpretation of the city of tomorrow appears to be a question of policy. Policy that might lead to a normative (legal) framework setting standards. However in this course we focus on the preceding fundamental discussion. What are the ethical concepts and principles that guide us to determine what solutions are right or wrong? And next: how to apply data ethics in a given situation? This in order to make the future city of Urbidata a fair data city.

The student will design an artefact and submit a written report, providing explanation of the artefact and containing a reflection. The artefact itself can be a video (min 5 minutes, max 10 minutes), an animation (min. 5 minutes, max. 10 minutes) or a model. The student needs to give one presentation on an assigned topic during the course in order to pass the course. The course is concluded with an oral exam.

The final grade is constructed as follows: artefact: 40%, written report: 40%, oral exam: 20%. A rubric will be used for grading. The rubric will be available on the course specific Brightspace page.

Students should achieve a minimum grade of 5,75 to pass this course.

The assignments (artefact and written report) and the exam are awarded a grade between 1.0 and 10.0. The final grade is rounded off to a whole or half number. Students pass the course with a final grade of 6.0 or higher (a 5.8 is rounded up a 6.0).

In case of an insufficient grade for the assignments: students who handed in assessable work during the course can choose to hand in an improved assignment (repair) during the next exam period to change the grade into a ‘pass’. An assignment can be repaired only once. If the repair is unsuccessful, the student needs to follow the entire course again.

In case of an insufficient grade for the exam: student can choose to do a retake, which is offered during the next exam period. The retake is also awarded a grade between 1.0 and 10.0 (in case grades are specified to one decimal place, the graded is rounded off to a whole or half number). Students that initially received a passing grade can only do a retake once.

When the repaired assignment is graded with a ‘pass’, the final grade is also turned into a ‘pass’.

Partial grades between 5.0 and 6.0 can be compensated to obtain a passing final grade. Partial grades expire after one calendar year. If a partial grade lower than 5.0 is not improved within that time, it expires and the student needs to follow the entire course again.