Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

Students will learn how machines think, how we think with them and use machines to think. In doing so they will be acquainted with a cross-disciplinary production of knowledge, in which knowing –being practical or theoretical – does not originate from only one position, or field of studies. Students will therefore experience how any science and/or artistic knowledge production progresses by taking inputs from other fields of research, how theories from "outside" can play a crucial role in the development for a new work. The hands-on workshops provide time for the students to directly relate with the tools, equipment, and material in use. Visit to artists and technology experts will give insights in concrete approaches and practical uses of the machine respectively in an artistic practice and a scientific process.

Credits: 5

Schedule: 29.10.2020 - 03.12.2020

Teacher in charge (valid 01.08.2020-31.07.2022):

Teacher in charge (applies in this implementation): Alejandro Pedregal Villodres, Gregoire Rousseau

Contact information for the course (applies in this implementation):

CEFR level (applies in this implementation):

Language of instruction and studies (valid 01.08.2020-31.07.2022):

Teaching language: English

Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content
  • Valid 01.08.2020-31.07.2022:

    From the discovery of electricity till the rise, development and deployment of Artificial Intelligence, the use of the machine has only increased within society. Looking for an understanding of the function, the role and the intelligence of machines the course will pursue a cross-disciplinary investigation on the creative processes involved in any new knowledge production and specifically in technological development. We will cover a variety of issues, including the complex dynamic between abstract thinking and materialistic approaches to produce new scientific steps forward. We will review the effects of the machine on the dissemination of information, along with questions related to ethics, discrimination, and architectures of control. We will aim to understand the space, the use and the problematics produced by contemporary algorithmic decisions. Moreover, the course will provide a strong insight in current technological developments and a better understanding of its implementation process, its implication in society and of the possibility to think its future.

    The course implies an intense array of learning and teaching methods, including hands-on workshops. Students will be expected to participate in a variety of activities, and be ready to develop a related final work.

Assessment Methods and Criteria
  • Valid 01.08.2020-31.07.2022:

    - Attendance 30%, - Participation in class 30%, - Own critical and self-reflective thinking 10%, - Final work/presentation/exhibition 30%.

Workload
  • Valid 01.08.2020-31.07.2022:

    The course operates around the three following axis:

    1. lectures and readings to present the ideas and concepts of the machine and machine thinking that will form a starting point for discussion and further investigations,
    2. Practical oriented workshops to actually work with the material,
    3. Visits to meet relevant actors in the field. We will visit artists, and practitioners in and outside Aalto University.

    I expect a minimum of 80% attendance, however I understand that special occasions can happen and special agreement can be arranged with student.

DETAILS

Study Material
  • Valid 01.08.2020-31.07.2022:

    We will read texts related to a historical genealogy of the concept and use of the machine. The selection comprises philosophical, scientific, technical, law/ethics related, and critical approaches to machines and technology.

    Here is a short list:

    “Discourse on the Method”, René Descartes, 1637,

    Futurist manifestos.

    "Computing Machinery and Intelligence" by Alan Turing.

    "Radical Technology" by Adam Greenfield.

    "Machine Learning and the Law: Five Theses" by Thomas Burri.

    Videos:

    "The Trouble with Bias" by Kate Crawford.

    "The Ethics and Governance of Artificial Intelligence" by Jonathan Zittrain.

Prerequisites
  • Valid 01.08.2020-31.07.2022:

    None

SDG: Sustainable Development Goals

    3 Good Health and Well-being

    7 Affordable and Clean Energy

    8 Decent Work and Economic Growth

    9 Industry, Innovation and Infrastructure

    10 Reduced Inequality

    12 Responsible Production and Consumption