Course syllabus
Den smarta stadens styrning: AI och etik i en spatial kontext
Smart City Governance: AI Ethics in a Spatial Context
VFTN75, 7,5 credits, A (Second Cycle)
Valid for: 2020/21
Decided by: PLED L
Date of Decision: 2020-03-27
General Information
Elective for: A5, C5, D5-mai, L5-fr, L5-gi
Language of instruction: The course will be given in English
Aim
Artificial intelligence (AI) is increasingly being used to
change our cities and manage traffic and movement, meet the needs
of commerce, combat crime, monitor individuals and improve our
everyday lives. At the same time, legal, democratic and ethical
interests need to be balanced against technical needs for
optimization. How may individuals' privacy and rights to
codetermination be balanced against development and employment of
learning technologies (machine learning / AI) dependent on a lot of
data? What is the main legal framework and what ethical guidelines
should preferrably be adhered to? What degree of explainability and
transparency is reasonable towards citizens, and in what ways do
expectations and perceived benefits differ in different parts of
the world?
In line with the need for responsible design and ethical
reflection on digitalisation, this course aims to give an
understanding of the role of individuals' data and autonomous and
self-learning technologies (artificial intelligence) in an urban
and spatial context. By looking at concrete and mainly
international cases of development and control of so-called smart
cities, including applications such as facial recognition in public
environments or how "the city as a platform" has had an impact in
urban planning, knowledge can be gained about what interests need
to be balanced and what level of governance is reasonable for
managing individuals' data in an urban context.
The course will thus, in a general sense, provide insights into
the importance of digitalisation and the societal significance of
new technologies with a focus on legal and ethical challenges, with
a specific focus on cities and spatial contexts. It includes
phenomena such as data capture and collection of large
individual-based data sets, the growth and importance of digital
platforms, and autonomous and self-learning technologies in the AI
field - and the forces operating therein between private and
international as well as public and national actors. The course is
thus intended to give technical students and engineers an in-depth
knowledge of the consequences of how technology is applied in, and
interacts with, society - with a focus on smart cities, governance
and ethics.
Learning outcomes
Knowledge and understanding
For a passing grade the student must
- be able to explain theoretical frameworks on digital platforms
and smart cities
- master basic English terminology in critical social science
research on artificial intelligence, focusing on the field of
Fairness, Accountability and Transparency (FAT).
- demonstrate a basic understanding of digital and data-driven
business models and their significance for design and technology
development
- demonstrate a basic understanding of the most central legal
considerations in urban data collection and the use of AI in a
spatial context
Competences and skills
For a passing grade the student must
- be able to describe the basic content and importance of
European data protection regulation for a spatial context
- be able to describe key benefits, but also conflict areas that
a development towards so-called smart cities brings
- understand, analyze and describe urban planning challenges in
the light of ethical and legal governance of smart cities in a
global context
- be able to present their project work (thesis) orally and
oppose another thesis.
Judgement and approach
For a passing grade the student must
- demonstrate a critical, independent and multidisciplinary
approach to data collection and automation in urban
environments.
- be able to make credible balances of interest between different
interests in urban implemented artificial intelligence, with a
particular focus on legal and ethical approaches.
Contents
The course is designed as a lecture and seminar series, as well
as independent written work in a smaller group based on concrete
development projects / cases where AI and data are central to urban
planning. The course offers guest lectures from multidisciplinary
as well as practical fields, where eg. city representatives
present their work and their challenges with digitization and the
use of autonomous and self-learning technologies.
The following steps are addressed:
- AI and machine learning, what does the field(s) mean and what
does the application to urban environments look like;
- The basics of trustworthy artificial intelligence -
transparency, fairness, accountability and explainability: what
would a trusted use entail?
- Digital platforms and platformization: what does a data-driven
organizational form mean in general, and for a spatial context in
particular?
- The basics of European data protection, in general, and for a
spatial context in particular
- AI governance - what are the regulatory ideas for the
development and application of AI, both legally but also in the
form of ethical guidelines
- International cases, as well as Swedish, on so-called smart
cities and their development are presented and problematised.
Examination details
Grading scale: UG - (U,G) - (Fail, Pass)
Assessment: Compulsory participation in seminars and exercise classes, including notes/reports. Final written report and presentation in group at public seminar. At the closing presentation the students are expected to oppose and critically assess another essay / presentation. At the seminar, both the course director and external lecturer attend, to the extent possible, to comment on the presentation and essay.
The examiner, in consultation with Disability Support Services, may deviate from the regular form of examination in order to provide a permanently disabled student with a form of examination equivalent to that of a student without a disability.
Admission
Admission requirements:
- ASBF10 Sustainable Urban Design or ETSF25 The Business of Software or FMIF45 Sustainability and Resource Use with Perspectives on Information and Communication Technology or VFTF10 Real Property Formation
The number of participants is limited to: 40
Selection: The course has 10 places for applicants from each of the programs A, C, D and L. Selection within each program is based on the number of higher education credits achieved within the program. In case there are places left after regular selection, these are distributed, according to the same selection principle, to the remaining applicants.
Reading list
- IEEE: Ethically Aligned Design. 2019. Selected pages from this document.
- High-Level Expert Group on AI: Ethics Guidelines for Trustworthy AI. EU Commission, 2019. Additional course material.
- Kitchin, R., Cardullo, P., and Di Feliciantonio, C. : Citizenship, Justice, and the Right to the Smart City. Emerald Publishing, 2019. Chapter, pp. 1-24.
- Schwarz, J. A., & Larsson, S. : A Platform Society. Fores, 2018. Chapter, p. 114-140.
- Crawford, K.: Halt the use of facial-recognition technology until it is regulated. Nature, 2019. Additional reading.
- Breslow, H. (2020). The smart city and the containment of informality: The case of Dubai. Urban Studies, 0042098020903233. https://journals.sagepub.com/doi/pdf/10.1177/0042098020903233.
- Brauneis, R., & Goodman, E. P. (2018). Algorithmic transparency for the smart city. Yale JL & Tech., 20, 103. https://heinonline.org/HOL/Page?handle=hein.journals/yjolt20&div=4&g_sent=1&casa_token=&collection=journals.
- Barns, S. (2020). "City Bricolage: Imagining the City as a Platform". In Platform Urbanism (pp. 171-191). Palgrave Macmillan, Singapore. https://link.springer.com/content/pdf/10.1007%2F978-981-32-9725-8_9.pdf.
- Cardullo, P., & Kitchin, R. (2019). Being a ‘citizen’in the smart city: up and down the scaffold of smart citizen participation in Dublin, Ireland. GeoJournal, 84(1), 1-13. http://mural.maynoothuniversity.ie/9228/1/RK-Being-2017.pdf.
- Goodman, E. P., & Powles, J. (2019). Urbanism under google: Lessons from sidewalk Toronto. Fordham L. Rev., 88, 457. https://heinonline.org/HOL/Page?handle=hein.journals/flr88&div=19&g_sent=1&casa_token=&collection=journals.
- Kitchin, R., Cardullo, P., and Di Feliciantonio, C. (2019) “Citizenship, Justice, and the Right to the Smart City”, in Cardullo et al., eds. The Right to the Smart City, Emerald Publishing, First edition, pp. 1-24. http://www.kitchin.org/wp-content/uploads/2019/04/PCP-WP-41-citizenship-social-justice-and-right-to-the-smart-city.pdf.
- Morozov, E., & Bria, F. (2018). Rethinking the smart city. New York: Rosa Luxemburg Stiftung. https://onlineopen.org/media/article/583/open_essay_2018_morozov_rethinking.pdf.
- Larsson, S. & Heintz, F. (forthcoming) Transparency in Artificial Intelligence, Internet Policy Review.
- Schwarz, J. A., & Larsson, S. (2018). A Platform Society. In Developing Platform Economies: A European Policy Landscape (pp. 114-140). European Liberal Forum asbl. http://lup.lub.lu.se/search/ws/files/55024264/Andersson_Schwarz_Larsson_2018_A_Platform_Society.pdf.
Contact and other information
Course coordinator: Stefan Larsson, stefan.larsson@lth.lu.se
Course homepage: http://www.lantm.lth.se