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K2SP 3015 - Data and algorithms for Public Policy

Type d'enseignement : Lecture alone

Semester : Autumn 2019-2020

Number of hours : 24

Language of tuition : English

Pre-requisite

None.

Course Description

Data and algorithms are increasingly used by governments to design and deliver public policies. Heart transplants allocation, calculation of taxes and matching between schools and students are some examples of algorithm-mediated administrative processes. But these instruments, as powerful as they are, present a series of challenges for individuals and the society. Participants will be able to understand how data and algorithms impact public policy (from design to implementation and evaluation), how to measure their impacts and how to mitigate risks by keeping these systems accountable by design. Participants will have the opportunity to get their hands on data, investigate public sector algorithms and develop both a theorical and practical understanding of the challenges of data-driven policies.

Teachers

  • CHIGNARD, Simon (Senior Policy Advisor, Etalab)
  • GIDOIN, Timothée (Co-founder, Datagora)
  • JOHN MATHEWS, Jean-Marie (Data-scientist and teacher, PSL University, Sciences Po)

Pedagogical format

This course consists of presentations of concepts and key questions (1/3), case studies with external guests (1/3) and practical work on data and algorithms (1/3). Each session will be devoted to a theme (transparency, accountability, explainability, …), with a reading list and presentation by the students.

Course validation

The validation mode will include: - 60% Presentation in class - 30% Written report and factsheet - 10% Oral participation and regular attendance

Workload

Students should arrive prepared for each session by reading some key documents (a list will be distributed from one class to the other one). Each student will be involved in group exercises performing (at least) one oral presentation and drafting a short report / factsheet on a key topic relevant to the session.

Required reading

  • O'NEIL Cathy, Weapons of math destructions, Crown, 2016
  • RIEKE Aaron, BOGEN Miranda, ROBINSON David, Public scrutiny of automated decisions, New-York, Upturn, 2018
  • CHIGNARD Simon, PENICAUC Soizic, With great power comes great responsibility: keeping public sector algorithms accountable (working paper), Paris, Etalab, 2019
  • VALLOR Shannon, An introduction to data ethics, Santa Clara University, 2018
  • KITCHIN Rob, The data revolution: Big data, open data, data infrastructures and their consequences, London, SAGE publications, 2014