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ACM Transactions on Computer-Human Interaction
Article . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
https://dx.doi.org/10.6082/1nq...
Article . 2024
License: CC BY
Data sources: Datacite
https://dx.doi.org/10.6082/chb...
Article . 2024
License: CC BY
Data sources: Datacite
DBLP
Article . 2024
Data sources: DBLP
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Unmaking Electronic Waste

Authors: Jasmine Lu; Pedro Lopes 0001;

Unmaking Electronic Waste

Abstract

The proliferation of new technologies has led to a proliferation of unwanted electronic devices. E-waste is the largest-growing consumer waste-stream worldwide, but also an issue often ignored. In fact, HCI primarily focuses on designing and understanding device interactions during one segment of their lifecycles—while users use them. Researchers overlook a significant space—when devices are no longer “useful” to the user, such as after breakdown or obsolescence. We argue that HCI can learn from experts who upcycle e-waste and give it second lives in electronics projects, art projects, educational workshops, and more. To acquire and translate this knowledge to HCI, we interviewed experts who unmake e-waste. We explore their practices through the lens of unmaking both when devices are physically unmade and when the perception of e-waste is unmade once waste becomes, once again, useful . Last, we synthesize findings into takeaways for how HCI can engage with the issue of e-waste.

Country
United States
Related Organizations
Keywords

hardware, upcycling, Electronic waste, unmaking, 004, reuse

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    13
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Top 10%
Top 10%
Top 10%
hybrid