Syllabus (Designing A.I.)

David Young
Jan 26, 2017 · 5 min read

This is a public-facing version of the course syllabus. The reading list and weekly schedule are separate documents in the class’ Google Drive folder. Note that some of this may evolve or change over the course of the semester.

PSDS 5330, Spring 2017
Parsons School of Design, School of Design Strategies, Transdisciplinary Design Program


Course Description

Emerging technologies are a significant driver of what and why we design. But technologies don’t develop in isolation. They are influenced and shaped by how we choose to utilize and engage with them. Design connects new technologies to unmet user needs — discovering unimagined opportunities and creating innovative products, services, and platforms. The results have the potential to change behaviors, economies, and cultures.

Artificial Intelligence (A.I.) technologies in general, and Machine Learning specifically, are without dispute on the verge of going mainstream; however how they manifest is still in question. A.I. has the potential to launch a new era in computing that will enable the development of previously unimagined possibilities.

Frequently businesses look to apply new technologies to their largest or most profitable sectors, supporting existing customers. But scale is not a requirement for innovation or driving technical progress; cultural engagement and the popular imagination are just as important. Popular culture and fiction (film, television, books and comics) often depict the impact of A.I. in a systemic way but neglect the small, immediate or highly contextual ways A.I. could impact our lives. And it is often the outlier or unexpected uses that generate the most interest and advance the technology the fastest.

Our futures are being established by technologies being developed today. If we do not seriously consider and engage with these emergent technologies, we risk the unwitting consequences. Design should be leading us forward.


In this course we will begin by surveying the current landscape of A.I. technologies and the surrounding questions of social and cultural bias. We will work to develop non-technical language, metaphors, intuitions or methods to help communicate what is possible with the technology.

Then, taking an underserved, alternate, or creative community as a partner, students will explore how an A.I. technology could be applied in service to the aspirations of that group. It is through that use that we can then ask how our understanding of the technology, or its future development may change. And it is through this specific community that we can evolve towards unique and desired future states.

Students will conceive and design projects that prototype new applications or tools. Projects will explore alternatives to code-based demos, developing new ways for non-technical stakeholders to benefit from, and contribute to, emerging technologies.


Our methodological approach is based on system design, human-centered design, design and social innovation, and service design. Throughout the course we will examine A.I. through three parallel lenses:

  • TECHNOLOGY: We will survey the current landscape of A.I. technologies and the surrounding questions of social and cultural bias. Throughout, we will ask how the technology works, what tools currently exist to use it, what data is required, what are its limitations, and where can bias or errors be introduced into the system.
  • BRIDGING: We will consider the opportunities for developing new languages, metaphors, or intuitions for communicating the technology and working with non-technical stakeholders. We will consider how existing human-centered design methods adapt to these new technologies, or what new methods may emerge.
  • SOLUTIONS: Through engagement with target communities we will work to understand their needs and propose ways in which A.I. might provide new tools or solutions for them. How does working with the community revise our bridging work? How can we prototype and create demonstrations of these new systems without coding? We will emphasize solutions that focus on real-world needs utilizing contemporary technologies.

Expected Outcomes

  • Produce a research report/presentation with findings from the research phase, which frames ways for non-technical stakeholders to understand A.I., how it works, and methods, or “bridging strategies,” for engaging these stakeholders in the development of new AI-based opportunities.

Learning Outcomes

1. Be comfortable with working with NEW TECHNOLOGIES AND INFLUENCING them.

  • Gain experience at working with new technologies, understanding the voice that design has in determining how new technologies are used and in what direction they develop, and be able to apply a critical lens on their social and cultural impact.
  • Envision a specific and localized future state and build towards that future vision.
  • Frame language or methods for engaging non-technical stakeholders to engage with new technologies.
  • Use learnings to recommend new technology features, tools, or directions for its future development.


  • Be able to define a complex design problem, problem framing, and apply research methods to studio work;
  • Be able to investigate and utilize precedent, contextual and literary research to shape design questions and processes.
  • Articulate concepts, critique arguments, manage the creative process and work as a team member.
  • Apply this knowledge toward the development of original, insightful, critical explorations using a transdisciplinary approach of design and emerging technologies.

3. Know how to use PROTOTYPING for communication and learning.

  • Make artefacts to communicate, validate, devise feedback strategies and iteration.
  • Be able to design methods to quickly prototype and test concepts using simulation or developing/current versions of emerging technologies.
  • Understand how to measure effectiveness and impact of prototypes, and apply learnings to iterate, refine or update design concept.

4. Be able to understand, manage and develop DESIGN PROCESSES.

  • Be able to conceptualize a product design roadmap and corresponding technology requirements.
  • Understand different design processes (i.e. 4d, lean/agile, etc), the rationale for choosing one vs another, and be able to manage a project using that process.

5. Understand the landscape of existing design methods & tools (i.e. journey mapping, service blueprints, contextual research, etc) and be able to utilize those that are appropriate to the project — or, if necessary, develop new methods that better serve the project’s needs.

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Course flow, and areas of emphasis over the semester. Note that for the second half of the course, students can choose which area to focus.
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Weekly schedule.
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Designing A.I. - Spring 2017

Graduate Studio, Spring 2017, The New School, Parsons…

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