June 26, 2025 • 26 mins
The ever-expanding presence of artificial intelligence in our professional lives has reached the sacred territory of research grant writing, raising profound questions about scientific integrity and the nature of academic work. As someone who's spent a fair amount of time exploring these tools firsthand, I'm sharing my perspective on how researchers can navigate the use of these tools without compromising what makes their work valuable.
Grant writing isn't just an administrative task standing between you and your research—it's a fundamental component of the scientific process where ideas crystallize and projects take shape. When we frame grant writing this way, the appeal of AI shortcuts gets more complicated.
What exactly are you saving yourself time from when you outsource this critical thinking work? The pressure to produce more grants in less time stems from structural problems in academia that technology alone cannot solve.
Most researchers face overwhelming institutional expectations to secure funding while simultaneously teaching, providing service, and for many, delivering clinical care. The solution involves setting boundaries and clarifying priorities rather than finding technological workarounds. Even practically speaking, today's AI tools remain unreliable for academic writing—producing fabricated citations and requiring extensive verification that may actually increase your workload.
What makes your research valuable is your unique perspective, critical analysis, and deep understanding of your field—the elements that cannot and should not be delegated to a large language model. AI may be here to stay, but let's ensure that it enhances rather than diminishes the human intelligence at the heart of scientific advancement.
For more content on grant writing techniques, visit my YouTube channel where I share technical advice on NIH grant writing (or just google "Sarah Dobson NIH grant writing tips" and that should get you where you want to go)
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:02):
this episode is a bit of a departure from what we
typically talk about on thepodcast, but I think it's a
really important topic to bringinto our conversations about the
k-r transition and how to,about designing your
professional life.
(00:24):
So this episode is taken from arecent YouTube video that I
posted on my channel and, yes, Ido have a YouTube channel.
If you're not aware, theYouTube channel is, I would say,
much more tips and tricks andtools for grant writing,
(00:45):
specifically NIH grant writing.
So it's a lot more, let's say,technical than what I talk about
on the podcast here, which Iwould say is more career
oriented and mindset oriented.
So if you're interested inlooking at some of the more, so
(01:28):
if you're interested in lookingat some of the more technical
and sort of nuts and bolts howdo you write a grant type
content?
You can definitely find thatover on my YouTube channel and I
will put a link to that in theshow notes so that you can find
it.
But really you could justGoogle Sarah Dobson, nih grant
writing tips, and I'm prettysure that will work.
So, yes, I have a YouTubechannel and I have recently done
a series on using AI inresearch grant writing and I
have, I think, fairlyconservative views on using AI
in grant writing, and that comesafter I've been playing around
(01:48):
with using AI tools to just seewhat they're capable of, how I
can use them and the amount oftraining that I need to use them
.
Well, and so I did a seriesbecause to me, it's unavoidable
now.
It's unavoidable that thesetools are around us.
(02:10):
It seems like they're beingforced upon us in a lot of ways.
You can't get away from them.
On search engines and invirtually every app that you're
using, there's some sort of AIassistant.
And so it felt long past timeto talk about this in the
context of research grantwriting, not only because I've
been getting a lot of questionsabout it from students and
(02:33):
clients and just inquiries frompeople who aren't really in my
community just wanting to know.
And the reason that I havedelayed doing this series for so
long is because I wanted tomake sense of it for myself
first and really again, reallysee what these tools can do and
(02:55):
how they can be used responsiblyand ethically.
And so I wanted to share withyou the first video that I did
in this YouTube series, where Italked about using these tools
ethically and responsibly, andthe reason that I think it's
important to bring into thepodcast, where we talk about the
K to R transition, we talkabout designing your career, we
(03:17):
talk about how to how toprioritize your own work and
your own impact.
The reason that I wanted tobring this AI conversation here
is because my sense of whatthese tools are, what makes
these tools really appealing isusing them to speed up the grant
(03:41):
writing process and using themto get around a problem that has
nothing to do with grantwriting.
It has everything to do withhow you organize your time and
your schedule and yourcommitments and your
responsibilities, and that issomething that I talk about in
this video and, of course,something that is highly
(04:02):
relevant to what we talk abouthere on the podcast.
Right, this is something we'vetalked about over and over and
that are placed on you by yourinstitution and the requirements
(04:33):
to churn grants out with noregard to quality, only quantity
.
Right, that AI can't solve thatproblem.
And if you look to AI to solvethat problem, you are just
handing over all of youroriginal thinking, your original
ideas, your ability to thinkcritically and your ability to
(04:56):
engage with the peer-reviewedliterature, and I think that is
extremely dangerous, and so,yeah, I may have very
conservative views about AI ingrant writing, but I don't I'm
not going to apologize for it.
I think, certainly at themoment, with where the tools are
(05:17):
at now, and obviously we areonly at the beginning, these
tools are only going to improveat the beginning.
These tools are only going toimprove, but, given where we're
at now, in my view these toolsare appealing to researchers
(05:41):
because they solve a problemthat cannot be solved by an AI
tool, and so I just want us allto be very careful about that.
So that is a long enough introto this episode.
I will hand it over to theYouTube version of myself so
that you can you can hear therest of the episode, but if you
found this interesting, if youare curious about this, I
(06:04):
encourage you to view the wholeseries over on YouTube.
But if you want me to talk moreabout this on the podcast, just
send me an email.
Let me know what you think.
I would love to hear from you.
All right, let's get into theepisode.
Welcome to the SignificantImpact Podcast, the show
dedicated to helping womenfaculty convert their NIH Career
(06:27):
Development Award into theirfirst big R01.
This period in your career issuch an important turning point,
and it's a crucial opportunityto design the kind of research
career that really works for youso that you're able to write
and lead these bigcareer-fueling research project
grants and lead these bigcareer-fueling research project
grants.
It's not easy to figure outwhat you really want when you
(06:47):
have so many different voices inyour ear telling you what to do
and how to do it, but it ispossible to design a career
that's fulfilling and meaningfulto you while also securing
enough grant funding to sustainyour lab and make an impact with
your research.
That's what we're talking abouthere.
On Significant Impact, with me,sarah Dobson, nih grant
consultant and academic careercoach, tune in for an honest
(07:10):
look at what it really takes tobe successful in the world of
NIH grant funding.
Start thinking differentlyabout what an academic career
looks like, one that's driven bypurpose and curiosity and a
healthy dose of disruptiveenergy.
(07:34):
Ai tools have been integratedinto so many of our daily
activities, professional andpersonal, that it can seem
almost impossible to avoid themat this point, and so that's why
I wanted to talk about theethical and responsible use of
AI in research grant writing.
So I have been planning to do aseries on AI in research grant
(07:54):
writing for at least a year now.
Time to observe and use some ofthe tools myself to see what
the challenges, pitfalls andopportunities are with these
tools and where we need to bereally careful, especially when
(08:17):
it comes to grant writing inresearch.
So before we dive into some ofthose considerations, I first
want to talk about my philosophyfor grant writing and how it
informs my philosophy on AI ingrant writing, because I think
(08:38):
that's really important to setthe stage for the conversation
and, obviously, for you todecide whether you agree with me
or not on this right.
I think it's fair to say that Iam cautious and conservative
about the use of these tools inresearch grant writing, for very
good reason, but let me explainwhy.
(08:59):
So if you have watched any ofthe videos on this channel or if
you have subscribed to mynewsletter and if you haven't
subscribed to my newsletter, Ihighly recommend that you do
that that's where all of my beststuff is.
So if you are familiar with mein either of those ways, you
will know that my corephilosophy when it comes to
(09:21):
grant writing is that it's yourjob to communicate the value of
your research to your reviewer,and alongside that is the idea
that your research is a busy,stressed out, tired human who is
volunteering to review a bunchof grants for scientific and
(09:42):
technical merit, and your job asan applicant is to make it as
easy as possible for yourreviewer to see the value in the
research that you're doing.
And when we think about AI inthat context, I mean unless and
until AI becomes part of thescientific review process, that
(10:30):
is a different conversation,that is a different story and
you can just ignore everythingthat I've said here.
But right now, scientific meritreview still happens through a
peer review process and it is myopinion and also my experience
that the most compellingapplications, the most
successful applications, are theones that generate enthusiasm
(10:53):
among your reviewers.
And that is a blend of having areally strong research idea but
also how you communicate thevalue and importance of that
research idea.
So that's the first sort ofcore philosophy that's
underpinning how I'm seeing theuse of AI tools in research
(11:15):
grant writing.
The other philosophy that I havethat's really important to this
conversation is the idea thatwriting a research grant is very
much part of the researchprocess.
It is not an administrativehurdle that you have to overcome
in order to be able to do yourresearch.
(11:35):
Writing a grant is what happensat the early stages, where you
are sharpening your thinking,where you are planning and
designing your project, whereyou are anticipating pitfalls
and ensuring that you havealternative strategies right,
it's all of the work that needsto be done to set yourself up
(11:57):
for success once the project isunderway, right?
And so assuming that it's justa bunch of checkboxes that you
need to hand over to a funder tobe able to get that money to do
your research is the wrong wayto think about it, in my opinion
.
Right, you can disagree with meif you want to, but then you
(12:18):
know why are you here, right?
So this is how I see grantwriting is that it is a core
piece of the work that you do asa scientist, especially when
you consider it in those sort ofearly planning stages and the
deep thinking that needs to bedone to do it well.
And of course, there's thecommunication aspect, which
(12:39):
comes into play when you arepreparing publications for
peer-reviewed journals, right,so you're getting early practice
with that.
When you are preparing a grantapplication, that can serve you
really well when you're writingup your findings to submit to a
journal, right?
So, for all of those reasons,grant writing is a core part of
(13:00):
the work that you do as ascientist and should be treated
as such.
And so, with those twofoundational pieces in mind,
let's talk a little bit abouthow that comes into play when we
think about using AI tools ingrant writing.
(13:21):
And I know that it can be reallytempting to use these tools
because you think it's going tosave you time, but I want to
challenge that assumption in twoimportant ways.
Number one is save you timefrom what?
Right?
So I just explained myphilosophy about grant writing
(13:44):
being part of the researchprocess, right?
And so, if we think about grantwriting in that way, what are
you actually saving time from ifyou are outsourcing this work
to an AI tool?
And it's important to considerthat, because most of the
(14:04):
academics I know I'm sure youknow all of the academics I know
are under tremendous pressureto fulfill the expectations that
their institutions have forthem around research and
teaching and service, and, youknow, clinical work, if that
applies right.
And so, again, it can be really,really tempting to find
(14:26):
shortcuts to be able to do morework in less time.
But what is the problem thatyou're actually solving here if
you're outsourcing some of thecore work that you need to be
doing as a researcher?
And, in my view, outsourcingthat core work is solving the
(14:47):
wrong problem.
And the problem is not even atime management problem, it's a
structural problem.
It's those expectations thatyour institution has placed on
you around securing grantfunding while also doing all of
these other things, all of theseother things.
(15:12):
And so to solve that problemrequires something different.
It requires clear priorities, aclear understanding of what
your value and impact is, and itrequires some boundary setting.
And again, I'm sure it doesseem easier to just use an AI
tool as a shortcut to avoiddoing that more difficult and
even emotional work.
(15:33):
But again, if you outsourceyour thinking to an AI tool,
what is left for you as aresearcher?
So I want you to consider thatvery carefully and challenge the
assumption that you have aroundthese tools saving you time,
because what is it actuallysaving you from?
The second challenge that I wantto suggest when it comes to
(15:57):
this idea of an AI tool savingyou time in the grant writing
process is is it actually goingto save you time?
Right?
We, you know, at the time ofthis recording, we are still
very much in the stone age of AItools, right, and who knows how
long that will last.
The developments andimprovements are happening very,
(16:20):
very quickly, but at the moment, these tools are still pretty
unreliable when it comes tosummarizing and interpreting and
even producing citations, right, and you know very famously
that has happened recently in anHHS report where there were
(16:41):
hallucinated citations, right.
So that is still very, verycommon in terms of the output
from most of these AI tools thatare available at the moment.
And so if you are planning touse one of these tools to assist
you in the grant writingprocess, to do that responsibly,
(17:02):
to do it ethically, you aregoing to have to double and
triple check all of thoseoutputs.
Double and triple check all ofthose outputs, and my question
to you is is that actually goingto save you time compared to
writing it out yourself?
So, again, I think that thisidea that these tools can save
(17:23):
us time need to be challengedbefore we can think about using
them ethically and responsibly.
So I will leave you with thatand then let's talk quickly
about some of the considerationsaround using these tools
ethically and responsibly, andwe're just going to do this very
(17:45):
briefly at a very high level,because we will get into these
in more depth throughout therest of this series.
So number one and this should gowithout saying, but I'm going
to say it anyway is that youneed to make sure that you are
in compliance with yourinstitutional guidelines and the
(18:06):
funders guidelines around theuse of AI.
So, for example, at NIH rightnow, there are guidelines around
the use of AI in the peerreview process, but not for the
development of a research grant.
But there are lots ofguidelines and regulations about
(18:28):
original research.
Right, your institution mighthave its own rules and
guidelines around the use of AIin grant writing, and so do not
pass go until you are clearabout what those guidelines are
and what that allows you toaccomplish with an AI tool.
(18:55):
So that's number one.
Number two is that, if we thinkof writing more broadly than
just generating text, and AI canbe used ethically and
responsibly in some aspects,right?
So, for example and I think oneof the most useful ways and
(19:15):
useful examples here is indeveloping timelines and
organizational structure foractually writing your grant.
So remember that writing aresearch grant is a big project
in and of itself, right.
The actual research project, ofcourse, requires project
management, but the actualwriting of the grant requires
(19:37):
project management, and so youcan use a tool like ChatGPT to
help you develop a projectmanagement plan for your grant
writing that considers yourexisting schedule, commitments
and so on and so forth.
Right, so you can create someefficiency and accountability
using an AI tool for some ofthose sort of peripheral
(19:59):
activities beyond sort of theoutput of writing that can
actually make your writing moreefficient, but that don't
compromise the integrity or theproprietary nature of any of the
writing that you're actuallydoing.
So I think there's a reallygood example.
(20:20):
Another one that I've used inprevious videos is using an AI
tool to help you identifyfunding opportunities that you
may not have considered, whetherthat's at the local, state or
national level, especially ifyou are looking beyond federal
funding sources, you might beable to use an AI tool to help
(20:43):
you identify some alternative ornew sources of funding that you
haven't considered before, somealternative or new sources of
funding that you haven'tconsidered before.
So, again, if we think aboutwriting more broadly, if we
think about grant writing andsome of the other activities
that are involved in grantwriting AI tools can be useful
(21:03):
without sort of againcompromising the integrity of
the actual writing output or theinput that you need to provide
to get anything useful fromthese AI tools.
Number three, and this is sortof in some ways reiterating what
we talked about in number one,and that is really protecting
(21:25):
confidentiality and intellectualproperty.
So remember that most of thesetools require that you provide
inputs for them to use, andthose inputs, in the case of
most research grants, wouldinvolve original work,
(21:46):
proprietary work, and that thesecorporations are retaining that
original work and proprietarywork and using it to train these
models.
And so you've just handed overyour original work to a
corporation that is using it totrain its models.
(22:09):
And so, again, use at your ownrisk or don't use at your own
risk, right, but just be reallycareful in thinking about how
you're using these tools andwhether that is, first of all,
permitted by your institutionand whether that is something
(22:32):
that you want to be doing.
And there are, of course, wayswithin a lot of these tools to
prevent them from using thatmaterial to train the AI tool.
(22:57):
However, the rules and theguidelines and the legality of
that is still a bit nebulous,because we don't know how clear
those guidelines are aroundprotecting that information from
being used for training.
(23:20):
And so the last thing is to useAI for refinement and clarity
rather than to solve the blankpage problem, and clarity rather
than to solve the blank pageproblem.
So in a lot of industries, aiis used to solve that blank page
problem.
So you have a blank page,you're not sure where to start
and you can use AI to help youkind of get started with a
(23:44):
writing project.
But in my view, that is theabsolute wrong way to use AI for
research grant writing for allthe reasons that we've talked
about.
Right, you want to retain thatoriginal deep thinking as the
work that only you can do, andso you would use AI more on the
refinement and clarity side ofthings, but again, very
(24:05):
judiciously, very carefully andin a really piecemeal way.
And if you still have that blankpage problem, that can be
solved in other ways.
So, for example, in my grantfunding formula program we have
templates that students can usethat are really kind of fill in
(24:26):
the blank to help you getstarted on clarifying the
description of your researchidea and the objectives and aims
that you have right.
So using prompts to help youstart thinking in that way
doesn't require an AI tool.
There are lots of resourcesavailable to you that can help
(24:49):
you sort of prompt yourself,interrogate yourself, to get
that information out of you inways that, again, don't
compromise your ability to think, which is one of your core
functions as a researcher, right?
So all of those elements needto be considered to use AI
(25:10):
ethically and responsibly goingforward.
And again, this is the beginningof the conversation, not the
end.
We will continue thisconversation in subsequent
videos in this series and wewill revisit this series again
and again over time to refineour thinking on how to use AI in
(25:33):
research grant writing in anethical and responsible way.
Thanks for listening to thisepisode of Significant Impact
from K Award to your first bigR01.
If you want to dig deeper intowhat we learned today and move a
significant step closer to asmooth K-R transition, visit
sarahdobsonco slash pod andcheck out all the free stuff we
(25:55):
have to help you do just that.
Don't forget to subscribe tothe show to make sure you hear
new episodes as soon as they'rereleased, and if today's episode
made you think of a colleagueor a friend, please tell them
about it.
Tune in next time and thanksagain for listening.
this episode is a bit of a departure from what we
typically talk about on thepodcast, but I think it's a
really important topic to bringinto our conversations about the
k-r transition and how to,about designing your
professional life.
(00:24):
So this episode is taken from arecent YouTube video that I
posted on my channel and, yes, Ido have a YouTube channel.
If you're not aware, theYouTube channel is, I would say,
much more tips and tricks andtools for grant writing,
(00:45):
specifically NIH grant writing.
So it's a lot more, let's say,technical than what I talk about
on the podcast here, which Iwould say is more career
oriented and mindset oriented.
So if you're interested inlooking at some of the more, so
(01:28):
if you're interested in lookingat some of the more technical
and sort of nuts and bolts howdo you write a grant type
content?
You can definitely find thatover on my YouTube channel and I
will put a link to that in theshow notes so that you can find
it.
But really you could justGoogle Sarah Dobson, nih grant
writing tips, and I'm prettysure that will work.
So, yes, I have a YouTubechannel and I have recently done
a series on using AI inresearch grant writing and I
have, I think, fairlyconservative views on using AI
in grant writing, and that comesafter I've been playing around
(01:48):
with using AI tools to just seewhat they're capable of, how I
can use them and the amount oftraining that I need to use them
.
Well, and so I did a seriesbecause to me, it's unavoidable
now.
It's unavoidable that thesetools are around us.
(02:10):
It seems like they're beingforced upon us in a lot of ways.
You can't get away from them.
On search engines and invirtually every app that you're
using, there's some sort of AIassistant.
And so it felt long past timeto talk about this in the
context of research grantwriting, not only because I've
been getting a lot of questionsabout it from students and
(02:33):
clients and just inquiries frompeople who aren't really in my
community just wanting to know.
And the reason that I havedelayed doing this series for so
long is because I wanted tomake sense of it for myself
first and really again, reallysee what these tools can do and
(02:55):
how they can be used responsiblyand ethically.
And so I wanted to share withyou the first video that I did
in this YouTube series, where Italked about using these tools
ethically and responsibly, andthe reason that I think it's
important to bring into thepodcast, where we talk about the
K to R transition, we talkabout designing your career, we
(03:17):
talk about how to how toprioritize your own work and
your own impact.
The reason that I wanted tobring this AI conversation here
is because my sense of whatthese tools are, what makes
these tools really appealing isusing them to speed up the grant
(03:41):
writing process and using themto get around a problem that has
nothing to do with grantwriting.
It has everything to do withhow you organize your time and
your schedule and yourcommitments and your
responsibilities, and that issomething that I talk about in
this video and, of course,something that is highly
(04:02):
relevant to what we talk abouthere on the podcast.
Right, this is something we'vetalked about over and over and
that are placed on you by yourinstitution and the requirements
(04:33):
to churn grants out with noregard to quality, only quantity
.
Right, that AI can't solve thatproblem.
And if you look to AI to solvethat problem, you are just
handing over all of youroriginal thinking, your original
ideas, your ability to thinkcritically and your ability to
(04:56):
engage with the peer-reviewedliterature, and I think that is
extremely dangerous, and so,yeah, I may have very
conservative views about AI ingrant writing, but I don't I'm
not going to apologize for it.
I think, certainly at themoment, with where the tools are
(05:17):
at now, and obviously we areonly at the beginning, these
tools are only going to improveat the beginning.
These tools are only going toimprove, but, given where we're
at now, in my view these toolsare appealing to researchers
(05:41):
because they solve a problemthat cannot be solved by an AI
tool, and so I just want us allto be very careful about that.
So that is a long enough introto this episode.
I will hand it over to theYouTube version of myself so
that you can you can hear therest of the episode, but if you
found this interesting, if youare curious about this, I
(06:04):
encourage you to view the wholeseries over on YouTube.
But if you want me to talk moreabout this on the podcast, just
send me an email.
Let me know what you think.
I would love to hear from you.
All right, let's get into theepisode.
Welcome to the SignificantImpact Podcast, the show
dedicated to helping womenfaculty convert their NIH Career
(06:27):
Development Award into theirfirst big R01.
This period in your career issuch an important turning point,
and it's a crucial opportunityto design the kind of research
career that really works for youso that you're able to write
and lead these bigcareer-fueling research project
grants and lead these bigcareer-fueling research project
grants.
It's not easy to figure outwhat you really want when you
(06:47):
have so many different voices inyour ear telling you what to do
and how to do it, but it ispossible to design a career
that's fulfilling and meaningfulto you while also securing
enough grant funding to sustainyour lab and make an impact with
your research.
That's what we're talking abouthere.
On Significant Impact, with me,sarah Dobson, nih grant
consultant and academic careercoach, tune in for an honest
(07:10):
look at what it really takes tobe successful in the world of
NIH grant funding.
Start thinking differentlyabout what an academic career
looks like, one that's driven bypurpose and curiosity and a
healthy dose of disruptiveenergy.
(07:34):
Ai tools have been integratedinto so many of our daily
activities, professional andpersonal, that it can seem
almost impossible to avoid themat this point, and so that's why
I wanted to talk about theethical and responsible use of
AI in research grant writing.
So I have been planning to do aseries on AI in research grant
(07:54):
writing for at least a year now.
Time to observe and use some ofthe tools myself to see what
the challenges, pitfalls andopportunities are with these
tools and where we need to bereally careful, especially when
(08:17):
it comes to grant writing inresearch.
So before we dive into some ofthose considerations, I first
want to talk about my philosophyfor grant writing and how it
informs my philosophy on AI ingrant writing, because I think
(08:38):
that's really important to setthe stage for the conversation
and, obviously, for you todecide whether you agree with me
or not on this right.
I think it's fair to say that Iam cautious and conservative
about the use of these tools inresearch grant writing, for very
good reason, but let me explainwhy.
(08:59):
So if you have watched any ofthe videos on this channel or if
you have subscribed to mynewsletter and if you haven't
subscribed to my newsletter, Ihighly recommend that you do
that that's where all of my beststuff is.
So if you are familiar with mein either of those ways, you
will know that my corephilosophy when it comes to
(09:21):
grant writing is that it's yourjob to communicate the value of
your research to your reviewer,and alongside that is the idea
that your research is a busy,stressed out, tired human who is
volunteering to review a bunchof grants for scientific and
(09:42):
technical merit, and your job asan applicant is to make it as
easy as possible for yourreviewer to see the value in the
research that you're doing.
And when we think about AI inthat context, I mean unless and
until AI becomes part of thescientific review process, that
(10:30):
is a different conversation,that is a different story and
you can just ignore everythingthat I've said here.
But right now, scientific meritreview still happens through a
peer review process and it is myopinion and also my experience
that the most compellingapplications, the most
successful applications, are theones that generate enthusiasm
(10:53):
among your reviewers.
And that is a blend of having areally strong research idea but
also how you communicate thevalue and importance of that
research idea.
So that's the first sort ofcore philosophy that's
underpinning how I'm seeing theuse of AI tools in research
(11:15):
grant writing.
The other philosophy that I havethat's really important to this
conversation is the idea thatwriting a research grant is very
much part of the researchprocess.
It is not an administrativehurdle that you have to overcome
in order to be able to do yourresearch.
(11:35):
Writing a grant is what happensat the early stages, where you
are sharpening your thinking,where you are planning and
designing your project, whereyou are anticipating pitfalls
and ensuring that you havealternative strategies right,
it's all of the work that needsto be done to set yourself up
(11:57):
for success once the project isunderway, right?
And so assuming that it's justa bunch of checkboxes that you
need to hand over to a funder tobe able to get that money to do
your research is the wrong wayto think about it, in my opinion
.
Right, you can disagree with meif you want to, but then you
(12:18):
know why are you here, right?
So this is how I see grantwriting is that it is a core
piece of the work that you do asa scientist, especially when
you consider it in those sort ofearly planning stages and the
deep thinking that needs to bedone to do it well.
And of course, there's thecommunication aspect, which
(12:39):
comes into play when you arepreparing publications for
peer-reviewed journals, right,so you're getting early practice
with that.
When you are preparing a grantapplication, that can serve you
really well when you're writingup your findings to submit to a
journal, right?
So, for all of those reasons,grant writing is a core part of
(13:00):
the work that you do as ascientist and should be treated
as such.
And so, with those twofoundational pieces in mind,
let's talk a little bit abouthow that comes into play when we
think about using AI tools ingrant writing.
(13:21):
And I know that it can be reallytempting to use these tools
because you think it's going tosave you time, but I want to
challenge that assumption in twoimportant ways.
Number one is save you timefrom what?
Right?
So I just explained myphilosophy about grant writing
(13:44):
being part of the researchprocess, right?
And so, if we think about grantwriting in that way, what are
you actually saving time from ifyou are outsourcing this work
to an AI tool?
And it's important to considerthat, because most of the
(14:04):
academics I know I'm sure youknow all of the academics I know
are under tremendous pressureto fulfill the expectations that
their institutions have forthem around research and
teaching and service, and, youknow, clinical work, if that
applies right.
And so, again, it can be really,really tempting to find
(14:26):
shortcuts to be able to do morework in less time.
But what is the problem thatyou're actually solving here if
you're outsourcing some of thecore work that you need to be
doing as a researcher?
And, in my view, outsourcingthat core work is solving the
(14:47):
wrong problem.
And the problem is not even atime management problem, it's a
structural problem.
It's those expectations thatyour institution has placed on
you around securing grantfunding while also doing all of
these other things, all of theseother things.
(15:12):
And so to solve that problemrequires something different.
It requires clear priorities, aclear understanding of what
your value and impact is, and itrequires some boundary setting.
And again, I'm sure it doesseem easier to just use an AI
tool as a shortcut to avoiddoing that more difficult and
even emotional work.
(15:33):
But again, if you outsourceyour thinking to an AI tool,
what is left for you as aresearcher?
So I want you to consider thatvery carefully and challenge the
assumption that you have aroundthese tools saving you time,
because what is it actuallysaving you from?
The second challenge that I wantto suggest when it comes to
(15:57):
this idea of an AI tool savingyou time in the grant writing
process is is it actually goingto save you time?
Right?
We, you know, at the time ofthis recording, we are still
very much in the stone age of AItools, right, and who knows how
long that will last.
The developments andimprovements are happening very,
(16:20):
very quickly, but at the moment, these tools are still pretty
unreliable when it comes tosummarizing and interpreting and
even producing citations, right, and you know very famously
that has happened recently in anHHS report where there were
(16:41):
hallucinated citations, right.
So that is still very, verycommon in terms of the output
from most of these AI tools thatare available at the moment.
And so if you are planning touse one of these tools to assist
you in the grant writingprocess, to do that responsibly,
(17:02):
to do it ethically, you aregoing to have to double and
triple check all of thoseoutputs.
Double and triple check all ofthose outputs, and my question
to you is is that actually goingto save you time compared to
writing it out yourself?
So, again, I think that thisidea that these tools can save
(17:23):
us time need to be challengedbefore we can think about using
them ethically and responsibly.
So I will leave you with thatand then let's talk quickly
about some of the considerationsaround using these tools
ethically and responsibly, andwe're just going to do this very
(17:45):
briefly at a very high level,because we will get into these
in more depth throughout therest of this series.
So number one and this should gowithout saying, but I'm going
to say it anyway is that youneed to make sure that you are
in compliance with yourinstitutional guidelines and the
(18:06):
funders guidelines around theuse of AI.
So, for example, at NIH rightnow, there are guidelines around
the use of AI in the peerreview process, but not for the
development of a research grant.
But there are lots ofguidelines and regulations about
(18:28):
original research.
Right, your institution mighthave its own rules and
guidelines around the use of AIin grant writing, and so do not
pass go until you are clearabout what those guidelines are
and what that allows you toaccomplish with an AI tool.
(18:55):
So that's number one.
Number two is that, if we thinkof writing more broadly than
just generating text, and AI canbe used ethically and
responsibly in some aspects,right?
So, for example and I think oneof the most useful ways and
(19:15):
useful examples here is indeveloping timelines and
organizational structure foractually writing your grant.
So remember that writing aresearch grant is a big project
in and of itself, right.
The actual research project, ofcourse, requires project
management, but the actualwriting of the grant requires
(19:37):
project management, and so youcan use a tool like ChatGPT to
help you develop a projectmanagement plan for your grant
writing that considers yourexisting schedule, commitments
and so on and so forth.
Right, so you can create someefficiency and accountability
using an AI tool for some ofthose sort of peripheral
(19:59):
activities beyond sort of theoutput of writing that can
actually make your writing moreefficient, but that don't
compromise the integrity or theproprietary nature of any of the
writing that you're actuallydoing.
So I think there's a reallygood example.
(20:20):
Another one that I've used inprevious videos is using an AI
tool to help you identifyfunding opportunities that you
may not have considered, whetherthat's at the local, state or
national level, especially ifyou are looking beyond federal
funding sources, you might beable to use an AI tool to help
(20:43):
you identify some alternative ornew sources of funding that you
haven't considered before, somealternative or new sources of
funding that you haven'tconsidered before.
So, again, if we think aboutwriting more broadly, if we
think about grant writing andsome of the other activities
that are involved in grantwriting AI tools can be useful
(21:03):
without sort of againcompromising the integrity of
the actual writing output or theinput that you need to provide
to get anything useful fromthese AI tools.
Number three, and this is sortof in some ways reiterating what
we talked about in number one,and that is really protecting
(21:25):
confidentiality and intellectualproperty.
So remember that most of thesetools require that you provide
inputs for them to use, andthose inputs, in the case of
most research grants, wouldinvolve original work,
(21:46):
proprietary work, and that thesecorporations are retaining that
original work and proprietarywork and using it to train these
models.
And so you've just handed overyour original work to a
corporation that is using it totrain its models.
(22:09):
And so, again, use at your ownrisk or don't use at your own
risk, right, but just be reallycareful in thinking about how
you're using these tools andwhether that is, first of all,
permitted by your institutionand whether that is something
(22:32):
that you want to be doing.
And there are, of course, wayswithin a lot of these tools to
prevent them from using thatmaterial to train the AI tool.
(22:57):
However, the rules and theguidelines and the legality of
that is still a bit nebulous,because we don't know how clear
those guidelines are aroundprotecting that information from
being used for training.
(23:20):
And so the last thing is to useAI for refinement and clarity
rather than to solve the blankpage problem, and clarity rather
than to solve the blank pageproblem.
So in a lot of industries, aiis used to solve that blank page
problem.
So you have a blank page,you're not sure where to start
and you can use AI to help youkind of get started with a
(23:44):
writing project.
But in my view, that is theabsolute wrong way to use AI for
research grant writing for allthe reasons that we've talked
about.
Right, you want to retain thatoriginal deep thinking as the
work that only you can do, andso you would use AI more on the
refinement and clarity side ofthings, but again, very
(24:05):
judiciously, very carefully andin a really piecemeal way.
And if you still have that blankpage problem, that can be
solved in other ways.
So, for example, in my grantfunding formula program we have
templates that students can usethat are really kind of fill in
(24:26):
the blank to help you getstarted on clarifying the
description of your researchidea and the objectives and aims
that you have right.
So using prompts to help youstart thinking in that way
doesn't require an AI tool.
There are lots of resourcesavailable to you that can help
(24:49):
you sort of prompt yourself,interrogate yourself, to get
that information out of you inways that, again, don't
compromise your ability to think, which is one of your core
functions as a researcher, right?
So all of those elements needto be considered to use AI
(25:10):
ethically and responsibly goingforward.
And again, this is the beginningof the conversation, not the
end.
We will continue thisconversation in subsequent
videos in this series and wewill revisit this series again
and again over time to refineour thinking on how to use AI in
(25:33):
research grant writing in anethical and responsible way.
Thanks for listening to thisepisode of Significant Impact
from K Award to your first bigR01.
If you want to dig deeper intowhat we learned today and move a
significant step closer to asmooth K-R transition, visit
sarahdobsonco slash pod andcheck out all the free stuff we
(25:55):
have to help you do just that.
Don't forget to subscribe tothe show to make sure you hear
new episodes as soon as they'rereleased, and if today's episode
made you think of a colleagueor a friend, please tell them
about it.
Tune in next time and thanksagain for listening.
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