QUATER-1-PE-HEALTH-LC2- this is just a sample of unpacked lesson
Writing as academic practice short.pdf
1. Writing as academic practice
in a time of Generative AI
A c a d e m i c P r a c t i c e w i t h T e c h n o l o g y C o n f e r e n c e J u n e 2 0 2 3
Helen Beetham | University of Wolverhampton
@helenbeetham | helenbeetham.substack.com
H.A.Beetham@wlv.ac.uk | H.Beetham@ucl.ac.uk
3. Purposes of GenAI as a
writing tool
1. Enhance productivity of text-based work (Who benefits? Who loses?)
2. Accessible interface on information (by narrowing range, discouraging
source-checking, repressing minority knowledge)
3. Search engine optimisation (rapid
generation of proven clickbait)
4. Gather textual data from users
What is happening to search engines and
online information sources, as auto-
generated text proliferates online?
4. Purposes of student writing
1. Express their own understanding and responses to a topic
2. Connect a topic with their own experience and interests
3. Decide ‘what matters’ for themselves, from extended reading
4. Practice epistemic methods e.g. analysis, evaluation, argumentation
5. Construct and reconstruct concepts
6. Communicate original research or new
solutions to real-world problems
7. Develop understanding of audiences,
purposes, genres and writing styles
8. Develop a voice and identity of their own
9. Encounter alternative perspectives and
know how to negotiate a position…
5. Their language model is normative,
amplifying writing from the mainstream
(i.e. wealthy, English-speaking,
disproportionately white and male)
internet. It is extractive, treating
language as a resource to be mined, not
an act of connection and communication.
It is unaccountable, with no body to
stand behind its utterances, no community
to feel the consequences, no needs to
negotiate. It has no intentions or values
of its own.
helenbeetham.substack.com
Underlying model of writing and
language
6. Their language model is normative,
amplifying writing from the mainstream
(i.e. wealthy, English-speaking,
disproportionately white and male)
internet. It is extractive, treating
language as a resource to be mined, not an
act of connection and communication. It is
unaccountable, with no body to stand
behind its utterances, no community to
feel the consequences, no needs to
negotiate. It has no intentions or values
of its own.
Accountable assignments centre
aspects of human writing that
LLMs are not only bad at in
their present iteration, but
will always be bad at, and so
the rewards for using them will
always be limited
helenbeetham.substack.com
Underlying model of writing and
language
7. Accountable writing assignments
Writing from a standpoint
Writing to make a difference
(real change, real readership)
Writing collaboratively Writing as identity work
Writing as process
including peer processes
Live writing
Writing up authentic research Writing as (topic) mapping
helenbeetham.substack.com
9. helenbeetham.substack.com
“any attribution of authorship carries with
it accountability for the work, and AI
tools cannot take such responsibility”.
Nature editorial, January 2023
Being critical in our own
academic practice
10. Assistance purely with the
language of the paper
Does not need to be disclosed
Short form predictive text Does not need to be disclosed
Low novelty text Check for accuracy and
include any citations
New ideas Acknowledge use of the model
New ideas + new text Discouraged
helenbeetham.substack.com
Being critical in our own
academic practice
11. Assistance purely with the
language of the paper
Does not need to be disclosed
Short form predictive text Does not need to be disclosed
Low novelty text Check for accuracy and
include any citations
New ideas Acknowledge use of the model
New ideas + new text Discouraged
helenbeetham.substack.com
Being critical in our own
academic practice
‘you are welcome to make the case to
the reviewers that this should be
allowed, and that the new content is in
fact correct, coherent, original and does
not have missing citations’
ACL Submission Guidelines 2023
12. Encouraging critical uses of GenAI
• How does generative AI produce its outputs?
• What are the human labour models behind the
production and use of GenAI?
• What is the environmental impact?
• Who is pro
fi
ting and who is being exploited or
excluded?
• What are the risks to human writing, thinking,
and intellectual work in different scenarios of
widespread use?
• How might these models amplify bias, inequality,
and concentration of wealth/power/data, as well
as improving access and productivity?
• How might they impact on individual wellbeing?
