| Title: |
Metaphors for Designers Working with AI |
| Authors: |
Murray-Rust, D.S. (author); Nicenboim, I. (author); Lockton, D (author) |
| Publication Year: |
2022 |
| Collection: |
Delft University of Technology: Institutional Repository |
| Subject Terms: |
metaphors; Machine Learning; conceptual foundations; computer science provocations |
| Description: |
In this paper, we explore the use of metaphors for people working with artificial intelligence, in particular those that support designers in thinking about the creation of AI systems. Metaphors both illuminate and hide, simplifying and connecting to existing knowledge, centring particular ideas, marginalising others, and shaping fields of practice. The practices of machine learning and artificial intelligence draw heavily on metaphors, whether black boxes, or the idea of learn-ing and training, but at the edges of the field, as design engages with computational practices, it is not always apparent which terms are used metaphorically, and which associations can be safely drawn on. In this paper, we look at some of the ways metaphors are deployed around machine learning and ask about where they might lead us astray. We then develop some qualities of useful metaphors, and finally explore a small collection of helpful metaphors and practices that illuminate different aspects of machine learning in a way that can support design thinking. ; Human Information Communication Design |
| Document Type: |
conference object |
| Language: |
English |
| Relation: |
DRS Conference Proceedings 2022; DRS 2022--0e1bc9ec-8b39-4b60-a3c4-e2a31bf5713b; https://doi.org/10.21606/drs.2022.667 |
| DOI: |
10.21606/drs.2022.667 |
| Availability: |
http://resolver.tudelft.nl/uuid:7a9d5900-943c-4bcd-a570-e69bd88d13d3; https://doi.org/10.21606/drs.2022.667 |
| Rights: |
© 2022 D.S. Murray-Rust, I. Nicenboim, D Lockton |
| Accession Number: |
edsbas.83EAA53F |
| Database: |
BASE |