iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://doi.org/10.48550/arXiv.2308.02399
[2308.02399] The Glamorisation of Unpaid Labour: AI and its Influencers
Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Computer Science > Computers and Society

arXiv:2308.02399 (cs)
[Submitted on 31 Jul 2023 (v1), last revised 16 Sep 2023 (this version, v2)]

Title:The Glamorisation of Unpaid Labour: AI and its Influencers

Authors:Nana Mgbechikwere Nwachukwu, Jennafer Shae Roberts, Laura N Montoya
View PDF
Abstract:To harness the true potential of Artificial Intelligence (AI) for societal betterment, we need to move away from prioritising corporate interests which exploit Global South workers in the digital age. The unpaid labour and societal harms which are generated by Digital Value Networks (DVNs) disproportionately affect workers in Africa, Latin America, and India and need to be regulated. In this research, we discuss unethical practices to automate Human Intelligence Tasks (HITs) through gig work platforms and the capitalisation of data collection utilising influencers in social media. These are important areas of study in worker and user data practices, where ethical AI could be impactful. We provide suggestions for a path forward focused on responsible AI development.
Comments: 4 pages, 2 pages of references, Deep Learning Indaba 2023 Short Paper
Subjects: Computers and Society (cs.CY); Social and Information Networks (cs.SI)
Cite as: arXiv:2308.02399 [cs.CY]
  (or arXiv:2308.02399v2 [cs.CY] for this version)
  https://doi.org/10.48550/arXiv.2308.02399

Submission history

From: Laura Montoya [view email]
[v1] Mon, 31 Jul 2023 06:44:25 UTC (58 KB)
[v2] Sat, 16 Sep 2023 03:48:27 UTC (59 KB)
Full-text links:

Access Paper:

  • View PDF
  • TeX Source
  • Other Formats
license icon view license
Current browse context:
cs.CY
< prev   |   next >
new | recent | 2023-08
Change to browse by:
cs
cs.SI

References & Citations

export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)