Month: October 2024

Current description based on NYUAD iteration of the course (https://github.com/jbenno/nyuad_politics_of_code). Please be advised this is in the process of being-updated by the instructor.

Deconstructing the design and implementation of software as a political medium and re-building functional alternatives.

Code is political. It is a means of political processes and activism. It is political inherently by the ethical choices often hidden in the black box of The Algorithm. In the course we aim to deconstruct the design, implementation, and data of software as a political medium. We will work through political applications such as simulations, ownership of intangible assets, predictive policing, algorithmic recommendations, suggestions, and filters, social networks, and the blockchain.

Along with an introduction to the related political theory and media studies, students will work on several hands-on projects to offer actual or speculative alternatives to the existing systems. To that end, this course will include several workshops in JavaScript, Python, and other tools.

Current description based on NYUAD iteration of the course (https://github.com/jbenno/nyuad_politics_of_code). Please be advised this is in the process of being-updated by the instructor.

Deconstructing the design and implementation of software as a political medium and re-building functional alternatives.

Code is political. It is a means of political processes and activism. It is political inherently by the ethical choices often hidden in the black box of The Algorithm. In the course we aim to deconstruct the design, implementation, and data of software as a political medium. We will work through political applications such as simulations, ownership of intangible assets, predictive policing, algorithmic recommendations, suggestions, and filters, social networks, and the blockchain.

Along with an introduction to the related political theory and media studies, students will work on several hands-on projects to offer actual or speculative alternatives to the existing systems. To that end, this course will include several workshops in JavaScript, Python, and other tools.

Generative AI and other digital media affect people in unexpected
ways. This is a course in the skills of responsible design and development of all forms of
media covered by IMA and ITP. We will look critically at the belief systems that affect
design, and will build skills for assessing the unexpected implications and consequences
of any new digital project, including generative AI projects. Together, we will create
personal and group processes to bring these issues safely to the surface, and create
standards and guardrails (a “calculus of intentional risk”) that you can apply to your own
work and to work you do in the future.
This course is structured around three comprehensive group assignments:
1. Group project: Produce a case study of an ethical dilemma in a real-world tech
company, based on news reports and other sources. How did this dilemma come
about? How did the company respond? What could they have done differently?
We will discuss these cases, and others, in class.
2. Group or solo project: Produce work in any format [not too elaborate] that brings
an ethical issue to light.
3. Solo project: Propose a design practicum – a set of ethical standard – that would
help you evaluate the impact of one or more pieces of your own work (or
someone else’s you know well). Use this “calculus of intentional risk” to explore
how you would change the design and use of these projects.
The class lectures will cover themes related to these three assignments, drawing on the
instructors’ extensive research in the fields of organizational and technological ethics and
responsibility. The recently published book, The AI Dilemma: The 7 Principles of
Responsible Technology, will be one resource for the class. We will also draw on work
on responsible technology going on elsewhere throughout NYU.

Current description based on NYUAD iteration of the course (https://github.com/jbenno/nyuad_politics_of_code). Please be advised this is in the process of being-updated by the instructor.

Deconstructing the design and implementation of software as a political medium and re-building functional alternatives.

Code is political. It is a means of political processes and activism. It is political inherently by the ethical choices often hidden in the black box of The Algorithm. In the course we aim to deconstruct the design, implementation, and data of software as a political medium. We will work through political applications such as simulations, ownership of intangible assets, predictive policing, algorithmic recommendations, suggestions, and filters, social networks, and the blockchain.

Along with an introduction to the related political theory and media studies, students will work on several hands-on projects to offer actual or speculative alternatives to the existing systems. To that end, this course will include several workshops in JavaScript, Python, and other tools.

Current description based on NYUAD iteration of the course (https://github.com/jbenno/nyuad_politics_of_code). Please be advised this is in the process of being-updated by the instructor.

Deconstructing the design and implementation of software as a political medium and re-building functional alternatives.

Code is political. It is a means of political processes and activism. It is political inherently by the ethical choices often hidden in the black box of The Algorithm. In the course we aim to deconstruct the design, implementation, and data of software as a political medium. We will work through political applications such as simulations, ownership of intangible assets, predictive policing, algorithmic recommendations, suggestions, and filters, social networks, and the blockchain.

Along with an introduction to the related political theory and media studies, students will work on several hands-on projects to offer actual or speculative alternatives to the existing systems. To that end, this course will include several workshops in JavaScript, Python, and other tools.