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Welcome to studying law Around 
the world. 

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I'm Claudio Claus. 
In each episode, I talk with 

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lawyers, law students, and 
professors from different parts 

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life. 

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We talk about the hard parts, 
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important skills to master. 
That's where Grammatica comes 

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International. 
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And I get it myself, having 
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countries during my 17 years in 
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Whether you're looking to 
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program, Grammatica can help. 
Visit Grammatico to get started.

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Today we're having two guests 
together here. 

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So we have Michael Cooper and 
also Spencer Nayer with us. 

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They've been all over the news 
in the legal world because of 

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something very interesting that 
they did at their law school 

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journal, so at the Texas A&M 
Journal of Property Law. 

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And that was coming up with a 
whole edition of the journal, 

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whole issue, which was very much
all about AI, but also with AI 

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doing that. 
And we'll be talking about how 

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that whole process went. 
Thank you so much both of you to

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to join us today and also wanted
to ask you to introduce yourself

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before we go on into the 
questions of the show. 

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Yeah, Thanks for having us. 
My name is Michael Cooper. 

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I am a recent graduate of the 
Texas A&M School of Law. 

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I'll be practicing in Dallas 
this fall. 

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And I was the managing editor of
the journal Property Law. 

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Yeah, just echoing it. 
Thanks for having us. 

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Very excited to be here. 
My name is Spencer Nyer. 

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I am similarly. 
A graduate. 

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Recent graduate. 
I'll be practicing patent law 

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here in a few months, hopefully 
after the bar and. 

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I was the. 
Editor in chief of the Journal 

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of. 
Property Law. 

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During the time that this issue 
came out. 

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Fantastic. 
Before we jump into the issue 

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itself, now that we know a 
little bit more about you, I 

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also wanted to ask you just 
briefly about your journey to 

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law school. 
So was there something specific 

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that sparked your interesting 
law? 

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And then also did that path kind
of automatically took you into 

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being involved in the in the law
journal or you know, that kind 

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of happened along the way? 
I'd love to hear your thoughts. 

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Yeah, so my path to law school 
was atypical. 

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I wasn't someone who always knew
that law was going to be my 

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path. 
Originally I thought I was going

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to be an engineer and so I went 
to school for electrical 

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engineering and somewhere along 
the. 

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Way I was, I had. 
Graduated and started looking at

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career field and somebody made 
some offhand comment about 

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patent law and then I just kind.
Of researched the career the 

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field would I be. 
Doing and things just kind of 

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started falling into place. 
It was accepted to and and you 

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know, now graduated. 
I kind of always knew. 

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That. 
With patent laws, my interest 

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property was kind of the path I 
was going to take, intellectual 

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property. 
And so for me, the Journal of 

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Property Law made a lot of sense
because it really aligned with a

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lot of the things that I wanted 
to do. 

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Yeah, and my, my path to law 
school was, if not atypical, 

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probably like the fairy tale way
that people decide they want to 

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go to law school. 
I was four or five years old and

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I was watching West Wing and 
Boston Legal and, and all of 

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these shows. 
And there was just something 

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unique about the way lawyers 
talked and carried themselves. 

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And I'm not from a family of 
lawyers, but I just kind of 

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attached to that idea and image 
of, of a professional who, who 

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gives counsel, who's the smart 
person in the room, the reliable

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person in the room. 
And so that's always what I 

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wanted to be since I was four or
five years old. 

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I graduated undergrad in 2017, 
moved to DC, worked in higher Ed

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and science policy with kind of 
a, a particular focus in 

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automation and enabling 
automation research. 

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And then I moved back to Texas 
when I got married and worked 

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for the ledge for a couple years
and then eventually was able to 

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matriculate and got, except when
I got accepted into A&M. 

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And so the Journal of property 
law, I knew I wanted to keep 

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clerkships open as an 
opportunity. 

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And so I knew I needed to be on 
a publication at A&M. 

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We have two, we have the journal
property Law and we have the law

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review. 
And I got accepted on to the 

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Journal of Property law. 
And I, I do find property law 

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incredibly interesting. 
And so it was, it was a nice 

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intellectual pursuit and the 
opportunity eventually to, to be

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on the executive board and kind 
of steer that body of 

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scholarship as well. 
And so I think there were a lot 

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of different forces that pulled 
me into the direction of working

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on this particular drone. 
Amazing, That's awesome. 

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And I wanted to hear all about, 
you know, going into the this 

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specific publication. 
So you both mentioned about, you

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know, kind of getting to 
practice, finishing up law 

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school now and going to take the
bar and all of that. 

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So I'd love to hear, you know, 
on the start on on kind of 

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looking ahead, what are some 
ways that you see this is 

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specific publication, you know, 
changing the experience of of 

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future law journals all around 
America, but maybe all around 

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the world and influencing some 
kind of the the direction of how

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things are going to get done 
from now on. 

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Definitely, I think like as a, 
in my role as managing editor, 

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my job is was to curate the 
scholarship for the journal, 

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select that and approve it for 
final publication. 

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And I think that in that role, 
seeing products that are 

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produced in conjunction with 
artificial intelligence is going

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to become part of the new 
normal. 

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This is something that all 
facets of academia are currently

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observing and dealing with, 
whether it's publication in 

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books, whether it's publication 
in peer reviewed medical 

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journals or other kinds of 
social science and things like 

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that. 
Artificial intelligence is part 

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of the body scholarly. 
And so because of that, my hope 

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is that our foray that we 
explore not only in our forward 

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that we wrote about the works, 
but also looking at the works 

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that themselves published 
provides a little bit of a 

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grounding experience for law 
review staff to think about the 

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role that AI can play in this 
process. 

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To hopefully kind of, we talked 
about it in the forward, but 

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kind of get rid of the the 
scarlet AI kind of thinking 

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about like Nathaniel Hawthorne 
there and, and trying to 

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eradicate more of the stigma so 
that they can have a more 

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constructive dialogue about the 
product rather than the process 

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to be able to publish works that
meaningfully contribute to the 

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scholarship. 
Yeah. 

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Absolutely. 
And just to echo, any new 

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technology has benefits and 
drawbacks. 

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And as AI continues to roll out 
and become more and more 

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prevalent, something that's kind
of already clear in scholarship 

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in general. 
Across fields is. 

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That AI is being. 
Used to write papers that. 

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Are being published in journals 
and things around the country, 

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around the world, and so this is
already happening the problem is

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that there's no overarching 
scheme or thought on what kind 

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of. 
Disclosure needs to be used. 

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What kind of extra editing or 
extra processing or extra 

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thinking needs to be done when 
these things are being 

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published? 
And so you have these journals, 

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publications that are publishing
AI articles with absolutely no 

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idea that it's AI. 
And that's really kind of what 

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we were trying to address in the
forward and. 

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With this issue is the fact 
that. 

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This is happening now and this 
is going to continue to happen 

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more and more frequently and so 
there needs to be some sort of 

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scheme. 
For what is moral? 

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With the use of AI and what is 
ethical? 

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For. 
Publication of these kinds of 

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materials. 
It was quite the bold move to to

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publish a full volume that is of
AI assisted scholarship. 

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And I'm wondering here, what was
some of the the turning points 

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that convinced you this was the 
right step for the journal? 

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And if initially you found a lot
of pushback or did you find more

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curiosity within the community, 
what was what was that like 

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preparing this? 
Issue I I think at a high level,

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you know, students are basically
told when they enter into law 

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school don't touch AI at all and
it's unethical to use it. 

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And I think that that, 
particularly in talking to our 

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advisors, really colours a lot 
of the way that students 

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interact with the idea of doing 
novel things is that they are 

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presented with these like dos 
and don'ts when they're being 

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graded. 
And so I think a lot of the the 

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hesitation that we received was 
from folks who are like, I'm not

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allowed to do this in the 
classroom. 

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Why would a professor be allowed
to do this? 

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And so I think that was a lot of
the initial pushback that we 

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got. 
Where were those kind of ethical

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concerns? 
I think the opportunity to 

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publish. 
These articles was very 

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exciting. 
Like I said, I come from a 

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technology background and I did 
some work programming AI systems

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during undergrad. 
And so this is always. 

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Been kind of an area that I 
found very fascinating and I. 

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Think that was a large. 
Part of the reason because 

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seeing how far the technology 
has come just in the. 

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Four or five years since. 
I really looking at them, it's 

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it's pretty incredible. 
And so you have this opportunity

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to look at this new kind of 
budding technology that is now 

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being implemented more and more 
into the mainstream of everyday 

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life, and you have this 
opportunity to start talking. 

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About OK, it's here, how do we? 
Use it. 

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How do we benefit from? 
It what is the? 

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True benefit of using this 
technology because if you ask 

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any person off the streets. 
Like what is AI? 

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Why would you use it? 
It's. 

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Something along the lines of, 
well, it can accumulate all this

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information and it spits it out 
faster. 

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It's more accurate than just a 
normal Internet search and it 

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saves you a lot of time and gets
you gets the ball rolling on 

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whatever you're talking about. 
And so seeing how you can use 

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that and distill it. 
Into OK, so. 

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What I'm hearing is time 
savings. 

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What I'm hearing is accuracy. 
What I'm hearing is the 

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accumulation of all of this 
informational resources. 

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And so how can we take those 
things and. 

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Apply it to scholarship. 
And so that. 

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Was a really cool opportunity. 
And then of course, talking 

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about the. 
Ethics of the whole situation 

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to. 
To coops point, plagiarism and 

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copying and things like that, 
from the time you're in, you 

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know, grade school, that's 
something that's kind of, you 

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know, told to every student is 
that plagiarism is never OK. 

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This is never OK if you find a 
source on the Internet. 

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You can't use it word. 
Forward and that's not what I. 

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Does, but AI does. 
Sort of blur that line of what 

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is copying what is the 
accumulation, because there's no

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independent thought behind pure 
AI. 

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It's really like I fancy Google.
Search in in a in a. 

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So trying to get an output from 
AI and then. 

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Use that as a substantial 
building block for a paper. 

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Definitely can. 
Ruffle some feathers for people.

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Who have been told for twenty 
30-40 years that you know you 

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can't take something straight 
off the Internet and and put it 

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in any substantial. 
Way into a paper. 

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Now we're looking at AI that's 
curating, organizing through 

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thousands and hundreds of 
thousands of websites and 

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articles and then giving you an 
output that is independent of 

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any one of those sources, but 
without independent thought 

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behind. 
It is in some ways you could 

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frame that as like a small copy 
of millions of different sources

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00:13:00,880 --> 00:13:03,650
and sighting. 
And so comparing that to. 

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What we do as people. 
That's essentially what we do in

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00:13:05,940 --> 00:13:07,590
Independent. 
Thought it's just. 

236
00:13:07,660 --> 00:13:11,090
The fact that it's coming from a
machine instead of a mind. 

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Difficult for people to 
conceptualize. 

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00:13:16,000 --> 00:13:19,360
And accept when those are the 
lessons you've learned all this 

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00:13:19,370 --> 00:13:21,010
time. 
And so that was a really 

240
00:13:21,020 --> 00:13:23,650
interesting. 
Part of the process was. 

241
00:13:23,700 --> 00:13:27,090
Trying to figure out. 
How to clarify? 

242
00:13:27,180 --> 00:13:31,630
What the difference is between 
plagiarism and the use of AI, R 

243
00:13:31,700 --> 00:13:33,350
and I? 
Think a lot of that. 

244
00:13:33,360 --> 00:13:37,390
Process really came down to a 
fundamental understanding. 

245
00:13:37,400 --> 00:13:40,560
Of what AI? 
Does how it's different than 

246
00:13:41,470 --> 00:13:47,360
like a plagiarizing or copying 
or anything else and trying to 

247
00:13:47,370 --> 00:13:50,260
explain that? 
To people who had issues. 

248
00:13:50,270 --> 00:13:53,180
You're amazing. 
I got the chance to explore it a

249
00:13:53,190 --> 00:13:57,580
little bit in the forward 
explores the traditional values 

250
00:13:57,590 --> 00:14:00,940
of scholarship, so talks about 
authorship, reliability, efforts

251
00:14:00,950 --> 00:14:04,300
and merit and how AI interacts 
with each of those. 

252
00:14:04,310 --> 00:14:08,740
And you also introduced in your 
in the publication A5 level 

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00:14:08,750 --> 00:14:12,500
taxonomy to classify I 
involvement in legal writing, 

254
00:14:12,510 --> 00:14:16,450
which I thought was very, very 
interesting and quite a 

255
00:14:16,460 --> 00:14:19,980
scholarly work on itself. 
So was there, you know, a few 

256
00:14:19,990 --> 00:14:23,640
references that that led you to 
structure in that way? 

257
00:14:23,710 --> 00:14:28,120
And now, how have you heard from
authors, editors, professors? 

258
00:14:28,240 --> 00:14:30,610
How have they responded to that 
system so far? 

259
00:14:30,660 --> 00:14:36,050
Yeah, so the the creation of the
five level taxonomy mirrors the 

260
00:14:36,120 --> 00:14:39,990
Society for Automotive 
Engineering level of automation.

261
00:14:40,060 --> 00:14:43,030
Like I alluded to earlier, my 
background before law school was

262
00:14:43,040 --> 00:14:45,710
in science policy. 
And one thing that I worked a 

263
00:14:45,720 --> 00:14:50,090
lot on was researchers who work 
was supporting researchers who 

264
00:14:50,100 --> 00:14:52,650
were trying to get funding for 
automated vehicle projects. 

265
00:14:52,720 --> 00:14:56,590
And so I was relatively familiar
with the SAE levels because it's

266
00:14:56,600 --> 00:14:59,610
something that's been broadly 
incorporated into a lot of the 

267
00:14:59,620 --> 00:15:02,350
governance of automated 
technology in the United States 

268
00:15:02,360 --> 00:15:04,850
and probably around the world, 
but I only know about the United

269
00:15:04,860 --> 00:15:06,030
States. 
Someone going to talk about 

270
00:15:06,040 --> 00:15:07,630
that. 
But that provided a really 

271
00:15:07,640 --> 00:15:11,230
valuable anchoring point for 
trying to find a way to put 

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00:15:11,240 --> 00:15:14,130
language to the way that we're 
interacting with it. 

273
00:15:14,140 --> 00:15:16,870
I thought that a human, what I 
would call a human factors 

274
00:15:16,880 --> 00:15:20,710
approach to this kind of 
taxonomy was really valuable 

275
00:15:20,780 --> 00:15:23,390
because it felt like, 
particularly in light of the 

276
00:15:23,400 --> 00:15:26,460
paradigm that we kind of 
announced and then tried to, you

277
00:15:26,470 --> 00:15:30,340
know, analyze about authorship 
and merit and, and all of these 

278
00:15:30,350 --> 00:15:31,970
things. 
Is that at the core of that, 

279
00:15:31,980 --> 00:15:33,750
it's the work that the human is 
doing. 

280
00:15:33,840 --> 00:15:39,390
And so the taxonomy tries to be 
a first bite at the apple to 

281
00:15:39,440 --> 00:15:45,090
make the point when it comes to 
disclosing and, and telling 

282
00:15:45,100 --> 00:15:48,530
someone about the role that I 
played is really anchoring it to

283
00:15:48,540 --> 00:15:51,270
what did the human do and how 
involved was the human? 

284
00:15:51,320 --> 00:15:55,270
And one of our approaches there 
was that, you know, if we make 

285
00:15:55,280 --> 00:15:59,200
it about the product that's 
used, that's going to be, you 

286
00:15:59,210 --> 00:16:01,730
know, that's going to be, you 
know, out of service in a week 

287
00:16:01,740 --> 00:16:04,430
because they're gonna have new 
usages, they're gonna have new, 

288
00:16:04,480 --> 00:16:06,790
new use cases for AI in a 
second. 

289
00:16:06,800 --> 00:16:09,190
And so there's nothing Evergreen
about that. 

290
00:16:09,200 --> 00:16:12,090
And so this was our approach to 
kind of provide some kind of 

291
00:16:12,100 --> 00:16:16,540
Evergreen kind of taxonomy. 
And so that was, I think all of 

292
00:16:16,550 --> 00:16:19,850
those were kind of the loadstar 
that kind of guided the 

293
00:16:19,860 --> 00:16:22,610
formation of this. 
I think the, the feedback that 

294
00:16:22,620 --> 00:16:25,370
we've gotten from scholars that 
we've, we've taken it to has 

295
00:16:25,380 --> 00:16:29,930
been really positive. 
Our AI advisors really was on 

296
00:16:29,940 --> 00:16:32,110
board with it. 
The, the authors that we worked 

297
00:16:32,120 --> 00:16:35,670
with, professors Andrew Torrance
and, and Bill Tomlinson, who are

298
00:16:35,680 --> 00:16:41,280
kind of pushing the, the pushing
edge of this exploration, um, of

299
00:16:41,290 --> 00:16:44,550
AI legal scholarship. 
We're very excited about it. 

300
00:16:44,560 --> 00:16:47,360
It, it kind of coincides with 
the work that they've done that 

301
00:16:47,370 --> 00:16:51,360
they call like organic websites,
trying to borrow from organic 

302
00:16:51,370 --> 00:16:55,480
produce regulations to try and 
be able to taxonomies the way 

303
00:16:55,490 --> 00:16:58,880
that automated content is, is 
delivered on websites. 

304
00:16:58,890 --> 00:17:00,260
It's something that they've 
written about. 

305
00:17:00,330 --> 00:17:04,540
And so this model of borrowing 
from other kinds of regulatory 

306
00:17:04,550 --> 00:17:08,140
schemes or disclosure schemes is
something that, that I think is 

307
00:17:08,150 --> 00:17:12,720
a pretty well accepted practice 
as we enter into new and 

308
00:17:12,730 --> 00:17:16,180
emerging technological fields. 
The one, the one piece of 

309
00:17:16,190 --> 00:17:18,740
critique that we've seen, I 
think the above the law article 

310
00:17:18,750 --> 00:17:21,579
kind of enunciates this critique
pretty well is that, you know, 

311
00:17:21,589 --> 00:17:24,599
on this sliding scale, it does 
become kind of difficult at 

312
00:17:24,609 --> 00:17:28,910
times to know when you're 
jumping from level 2 to Level 3 

313
00:17:28,920 --> 00:17:31,260
to level 4. 
The only real bright lines are 

314
00:17:31,270 --> 00:17:35,020
level 1 and level 5 because 
level 1 is no AI at all. 

315
00:17:35,070 --> 00:17:38,420
Level 5 is only AI all the time.
And then there's this 

316
00:17:38,430 --> 00:17:41,010
intermediate point. 
And I think that that critiques,

317
00:17:41,020 --> 00:17:43,580
right. 
But I also think that that's 

318
00:17:43,590 --> 00:17:47,360
something that can be molded and
perhaps tooled with. 

319
00:17:47,370 --> 00:17:50,300
Perhaps having one intermediary 
level is the solution to that 

320
00:17:50,310 --> 00:17:53,040
problem. 
I think that the bigger step in 

321
00:17:53,050 --> 00:17:56,110
our, what I would say, the 
better contribution of us taking

322
00:17:56,120 --> 00:17:59,340
that effort in first place is 
that it's a stepping off point 

323
00:17:59,350 --> 00:18:03,680
for being able to just frontline
disclose the use of AI and 

324
00:18:03,690 --> 00:18:07,260
describe the the human AI 
interaction in a way that's 

325
00:18:07,270 --> 00:18:09,980
digestible the reader so that 
they know what they're reading. 

326
00:18:09,990 --> 00:18:12,300
Because I think at the end of 
the day, like the most important

327
00:18:12,310 --> 00:18:14,880
thing here is that we're 
producing scholarship and that 

328
00:18:14,890 --> 00:18:17,600
people know broadly what they're
interacting with. 

329
00:18:17,670 --> 00:18:22,340
Yeah, I think there were, there 
were two kind of policy concerns

330
00:18:22,390 --> 00:18:25,640
regarding the creation. 
Of the the five levels. 

331
00:18:25,730 --> 00:18:29,380
And I think 1. 
Is the ethicality of publishing.

332
00:18:29,390 --> 00:18:32,440
AI at this stage in the. 
AI life cycle. 

333
00:18:32,770 --> 00:18:36,880
I think it's important to just 
make. 

334
00:18:36,890 --> 00:18:38,340
People aware, right? 
Because. 

335
00:18:38,350 --> 00:18:40,860
Of some of the issues. 
That AI has. 

336
00:18:40,930 --> 00:18:44,700
Especially when you're 
submitting into scholarship, I 

337
00:18:44,710 --> 00:18:47,000
think the disclosure. 
Of the use of AI. 

338
00:18:47,010 --> 00:18:49,400
Is important and then the other 
side. 

339
00:18:49,590 --> 00:18:52,180
Is. 
Just kind of the human side of 

340
00:18:52,270 --> 00:18:56,430
people have an easier time 
accepting what they understand. 

341
00:18:56,440 --> 00:19:00,730
And so giving these 
categorizations, you know of how

342
00:19:00,740 --> 00:19:04,570
much AI is being used, what you 
can expect that means from a 

343
00:19:04,580 --> 00:19:06,530
paper. 
About how it was drafted. 

344
00:19:06,540 --> 00:19:10,010
How it was implemented, all 
those things, I think just gives

345
00:19:10,020 --> 00:19:15,930
people kind of an innate sense. 
Of comfortability as opposed to.

346
00:19:16,010 --> 00:19:18,290
Just kind of guessing. 
Is this AI? 

347
00:19:18,300 --> 00:19:20,670
Is this not AI? 
I think just having that 

348
00:19:20,680 --> 00:19:26,110
knowledge makes people more open
to the concept in general. 

349
00:19:26,200 --> 00:19:28,540
That's amazing. 
And there's so many different 

350
00:19:28,550 --> 00:19:30,950
tools, so many possibilities of 
doing that. 

351
00:19:30,960 --> 00:19:34,130
And I'm glad kind of it got 
broken into, but also I feel 

352
00:19:34,140 --> 00:19:38,180
like the AI providers at the 
different companies that do, 

353
00:19:38,190 --> 00:19:42,100
especially in the generative 
generative AI part of it, have 

354
00:19:42,110 --> 00:19:46,930
also noticed this need. 
And, and I noticed that now this

355
00:19:46,940 --> 00:19:50,130
is not your recent, but yeah, 
within a couple of months of the

356
00:19:50,140 --> 00:19:53,440
development, for example, 
ChatGPT got the possibility of 

357
00:19:53,450 --> 00:19:57,020
you like creating a specific 
link for that conversation you 

358
00:19:57,030 --> 00:19:59,030
had so that you can share it in 
another. 

359
00:19:59,040 --> 00:20:01,850
People can kind of go through 
the process and all that. 

360
00:20:01,860 --> 00:20:05,900
So I feel like that does kind of
align with the idea that we want

361
00:20:05,910 --> 00:20:09,210
to be transparent and then we we
can share how we went about it. 

362
00:20:09,220 --> 00:20:11,850
And I just really like that, 
that possibility. 

363
00:20:12,660 --> 00:20:15,150
And then there's also a lot of 
different concerns. 

364
00:20:15,200 --> 00:20:18,040
What we hear about AI in the 
legal field usually have to do 

365
00:20:18,050 --> 00:20:21,390
with, you know, some somebody 
submitted a fact and or some 

366
00:20:21,400 --> 00:20:24,870
kind of legal document into the 
court without checking, but what

367
00:20:24,880 --> 00:20:28,110
was the outcome of that 
document, which is which is so 

368
00:20:28,120 --> 00:20:31,530
interesting because it it maybe.
Could be compared to submitting 

369
00:20:31,540 --> 00:20:34,470
something that was written by 
somebody who's not legally 

370
00:20:34,480 --> 00:20:37,210
trained or, you know, a lost 
student or something like that. 

371
00:20:37,220 --> 00:20:39,670
So it's always interesting to 
see that in that end. 

372
00:20:39,680 --> 00:20:44,250
But there's this big concern 
about hallucinating the sources 

373
00:20:44,260 --> 00:20:48,910
missing, misrepresenting the 
legal propositions or, you know,

374
00:20:49,040 --> 00:20:51,190
coming up with case law that 
never existed. 

375
00:20:51,260 --> 00:20:54,730
So how do you train your 
editorial team to handle these? 

376
00:20:54,800 --> 00:20:58,890
And also, what advice do you 
have to people who might be 

377
00:20:58,940 --> 00:21:02,350
specifically concerned about the
hallucination part of it? 

378
00:21:02,400 --> 00:21:05,960
Yeah, so the. 
That's absolutely a concern and 

379
00:21:05,970 --> 00:21:08,010
things like that do happen what 
I will. 

380
00:21:08,020 --> 00:21:10,850
Say is that AI is. 
Getting better all the time and 

381
00:21:10,860 --> 00:21:14,040
so it's becoming less and less 
frequent, although I 

382
00:21:14,050 --> 00:21:18,570
hallucinations are absolutely 
still a problem in the AI 

383
00:21:18,580 --> 00:21:21,130
community and the use of. 
AI as of today, but. 

384
00:21:21,140 --> 00:21:24,130
There are much less than a few 
years ago. 

385
00:21:24,200 --> 00:21:27,430
The way AI should be used is as 
a tool. 

386
00:21:27,440 --> 00:21:29,710
It is not at the point and 
won't. 

387
00:21:29,720 --> 00:21:34,190
Be for a while, where AI is the 
true substitute for human. 

388
00:21:34,200 --> 00:21:39,170
Work thought, interaction. 
It needs to be targeted and it 

389
00:21:39,180 --> 00:21:41,450
needs. 
To be checked as far as 

390
00:21:41,600 --> 00:21:46,210
scholarship goes for. 
Publication the truth is that 

391
00:21:46,260 --> 00:21:52,410
checking for existence, for 
correctness that they support 

392
00:21:52,420 --> 00:21:55,320
the. 
Proposition that the words that.

393
00:21:55,380 --> 00:21:56,760
Have been submitted. 
To us. 

394
00:21:56,770 --> 00:22:02,040
Are truthful and correct that's.
Already part of the process of. 

395
00:22:02,110 --> 00:22:05,260
A legal journal every day. 
Right, that's our job, whether 

396
00:22:05,270 --> 00:22:07,680
it was written by. 
Humans, whether it was written 

397
00:22:07,690 --> 00:22:12,540
by AI, no matter what, when we 
publish something as a journal, 

398
00:22:12,590 --> 00:22:16,040
we are putting our name and 
things behind. 

399
00:22:16,050 --> 00:22:18,240
It as far as the. 
Authenticity, which is the 

400
00:22:18,250 --> 00:22:21,840
reason that legal journals have 
so much, so many hours. 

401
00:22:21,850 --> 00:22:24,780
Of site. 
Checking and technical editing 

402
00:22:24,790 --> 00:22:27,480
and all these things. 
Are for the purpose of. 

403
00:22:27,490 --> 00:22:30,940
Minimizing and eliminating any 
of these errors that could come 

404
00:22:30,950 --> 00:22:34,940
up and so as far as the 
difference between what it looks

405
00:22:34,950 --> 00:22:36,000
like. 
To edit. 

406
00:22:36,410 --> 00:22:39,800
An article that was written. 
By or with the assistance. 

407
00:22:39,870 --> 00:22:44,430
Of an eye and what it looks like
to edit an article that was 

408
00:22:44,440 --> 00:22:47,470
written entirely by a human the.
Process. 

409
00:22:47,480 --> 00:22:52,390
Itself is very very similar. 
I think the biggest point where 

410
00:22:52,400 --> 00:22:54,650
that you see a divergences maybe
the. 

411
00:22:54,660 --> 00:23:02,160
Hours that it requires because. 
A human author might have a 

412
00:23:02,170 --> 00:23:04,860
citation that doesn't support 
what they're saying, but maybe 

413
00:23:04,870 --> 00:23:08,580
they meant for that citation to 
refer to something that was 

414
00:23:08,590 --> 00:23:10,700
earlier in the paper or later in
the paper. 

415
00:23:10,750 --> 00:23:14,440
AI will completely hallucinate. 
They'll make up articles or 

416
00:23:14,450 --> 00:23:17,260
sometimes cite to articles that 
don't necessarily support what 

417
00:23:17,270 --> 00:23:20,200
they're saying because AI is 
trying to give you the answers, 

418
00:23:20,210 --> 00:23:21,760
right? 
And so that's its goal. 

419
00:23:21,770 --> 00:23:27,140
And so that is different between
AI written and human written. 

420
00:23:27,150 --> 00:23:31,680
And so there's a little bit more
work that goes on to identify 

421
00:23:31,690 --> 00:23:35,360
where AI is coming up with some 
of its information, where for a 

422
00:23:35,370 --> 00:23:37,920
human written article, it's 
often more of a reorganization 

423
00:23:37,930 --> 00:23:40,390
challenge as opposed. 
To OK, where did. 

424
00:23:40,400 --> 00:23:43,480
This come from and there's also 
the and a challenge of if there 

425
00:23:43,490 --> 00:23:45,840
is an issue with the human 
written thing, you can always 

426
00:23:45,850 --> 00:23:48,280
reach out to the author and say 
hey sentence. 

427
00:23:48,510 --> 00:23:51,670
Two of page, whatever. 
I don't think this is the site 

428
00:23:51,680 --> 00:23:54,160
you meant to use. 
Is there something that you use 

429
00:23:54,170 --> 00:23:56,820
from this and AI? 
It's much more. 

430
00:23:56,830 --> 00:23:59,860
Difficult to try to get. 
That information to highlight 

431
00:23:59,870 --> 00:24:02,280
one sentence, say, hey, where's 
this information coming from? 

432
00:24:02,330 --> 00:24:05,080
Often I might just double down 
on the original. 

433
00:24:05,090 --> 00:24:08,460
Citation it gave you. 
Yeah, I, I think that the 

434
00:24:08,470 --> 00:24:12,740
hallucination issue, one of the 
articles that we rely on a lot 

435
00:24:12,750 --> 00:24:18,080
in our piece is this Stanford 
study about the way in which AI 

436
00:24:18,150 --> 00:24:20,820
operates when it's doing this 
kind of research. 

437
00:24:20,830 --> 00:24:23,030
And one thing that they point 
out is that there's two kinds of

438
00:24:23,040 --> 00:24:25,580
hallucinations. 
There's the one that everyone 

439
00:24:25,590 --> 00:24:28,900
talks about and gets you 
sanctioned in court, which is 

440
00:24:28,910 --> 00:24:32,480
where the AI is made something 
up entirely out of whole cloth 

441
00:24:32,490 --> 00:24:35,900
and it doesn't exist. 
The other one is where AI is, is

442
00:24:35,910 --> 00:24:39,080
stretching A proposition. 
And I think one thing that we 

443
00:24:39,270 --> 00:24:45,980
tried to do was first creating a
quicker way for staffers to be 

444
00:24:45,990 --> 00:24:49,230
able to process those, which was
creating a highlighting key 

445
00:24:49,240 --> 00:24:54,600
basically for them to be able to
streamline the identification of

446
00:24:54,610 --> 00:24:57,840
those items. 
Obviously our process still 

447
00:24:57,850 --> 00:25:00,400
includes, you know, if you see 
something that doesn't support, 

448
00:25:00,410 --> 00:25:03,670
then you go find something else 
that supports that proposition 

449
00:25:03,730 --> 00:25:06,580
so that you can, you know, so 
that we can do our job as a 

450
00:25:06,590 --> 00:25:09,350
journal and and reliably 
important things we're doing. 

451
00:25:10,010 --> 00:25:13,430
But because of, and I think it's
something that Spencer just 

452
00:25:13,440 --> 00:25:18,640
alluded to is that the error 
attribution is different because

453
00:25:18,650 --> 00:25:22,560
when a human makes a mistake, we
chalk it up to good faith. 

454
00:25:22,570 --> 00:25:24,420
They tried, they just made a 
mistake. 

455
00:25:24,470 --> 00:25:27,460
Whereas when you're dealing with
new technology doing it, the 

456
00:25:27,470 --> 00:25:32,000
errors entirely on the computer.
And so because there's no like 

457
00:25:32,010 --> 00:25:35,360
Direct Line of accountability to
the person who made the the 

458
00:25:35,370 --> 00:25:39,680
choice, they're become their 
opens up a lot more questions as

459
00:25:39,690 --> 00:25:42,380
to the reliability. 
But it also opens up a lot more 

460
00:25:42,390 --> 00:25:47,400
solutions, which is that we can 
retailer the proposition of that

461
00:25:47,410 --> 00:25:50,770
sentence to support what the 
article does say, because we 

462
00:25:50,780 --> 00:25:53,670
know that the article is right 
or we know the article exists. 

463
00:25:53,760 --> 00:25:56,390
We know the article has said 
something that can support that 

464
00:25:56,400 --> 00:25:59,670
that proposition authentically. 
And then the question also 

465
00:25:59,680 --> 00:26:02,790
becomes like when you are 
looking at a paragraph full of 

466
00:26:02,800 --> 00:26:06,660
propositions, when you, you 
know, knock one of those runs 

467
00:26:06,670 --> 00:26:09,390
out of the ladder or you adjust 
it, does it still support the 

468
00:26:09,400 --> 00:26:12,950
broader argument? 
And as long as the authors 

469
00:26:12,960 --> 00:26:16,510
broader argument remains intact 
with like that little bit of 

470
00:26:16,520 --> 00:26:19,030
tinkering so that it is 
supported. 

471
00:26:19,100 --> 00:26:22,590
That's something that working 
with an AI with with a with 

472
00:26:22,600 --> 00:26:25,470
scholarship that's created in 
conjunction with AI. 

473
00:26:25,560 --> 00:26:29,470
Authors are more malleable in 
terms of the way that their pros

474
00:26:29,480 --> 00:26:33,270
is edited because in a lot of 
respects, they're less defensive

475
00:26:33,320 --> 00:26:37,520
of individual wording decisions.
And so you do have a lot, you 

476
00:26:37,530 --> 00:26:40,720
have a lot more problems because
of the hallucination issue, but 

477
00:26:40,730 --> 00:26:42,910
you do also have a lot more 
solutions. 

478
00:26:42,960 --> 00:26:45,930
And so that was kind of an 
iterative process as we 

479
00:26:45,980 --> 00:26:49,230
undertook this was identifying 
those different tools in our 

480
00:26:49,240 --> 00:26:52,110
toolbox to be able to to do 
that. 

481
00:26:52,120 --> 00:26:56,310
So that I think on the staff 
training question, it was really

482
00:26:56,320 --> 00:26:59,630
an ongoing process of 
identifying those where we can 

483
00:26:59,720 --> 00:27:03,130
input more efficiencies in terms
of like identification of issues

484
00:27:03,140 --> 00:27:05,420
that we can communicate to the 
author and put it in the authors

485
00:27:05,430 --> 00:27:07,510
court to deal with. 
Or where we can take more 

486
00:27:07,520 --> 00:27:10,310
liberty knowing that the author 
is going to be more receptive to

487
00:27:10,320 --> 00:27:13,370
this kind of change. 
Because, you know, we're not, 

488
00:27:13,440 --> 00:27:16,590
we're not changing their 
individualized decision to write

489
00:27:16,600 --> 00:27:19,210
the sentence this way. 
We are, we are working 

490
00:27:19,220 --> 00:27:21,740
collaboratively with them and 
the product they have 

491
00:27:21,790 --> 00:27:24,900
manufactured using these tools 
to make it the best possible 

492
00:27:24,910 --> 00:27:26,900
product. 
And so I think that that side of

493
00:27:26,910 --> 00:27:29,400
the collaborative relationship 
is actually a little enhanced 

494
00:27:29,440 --> 00:27:32,620
because the personal 
defensiveness of authors is is 

495
00:27:32,630 --> 00:27:35,440
actually muted a little bit. 
And I think it makes sense. 

496
00:27:35,450 --> 00:27:38,940
Like authors are for the. 
Traditional legal scholarship 

497
00:27:38,950 --> 00:27:43,560
authors are spending hundreds of
hours doing research, framing 

498
00:27:43,570 --> 00:27:45,760
every sentence and so. 
These. 

499
00:27:45,830 --> 00:27:49,330
Papers and articles become 
passion projects and just like 

500
00:27:49,340 --> 00:27:51,740
any passion project, you you 
become. 

501
00:27:51,750 --> 00:27:55,810
Very attached to the choices. 
You made to get yourself along 

502
00:27:55,820 --> 00:27:58,500
the way what Coop is referring. 
To is like the stylistic. 

503
00:27:58,510 --> 00:28:03,200
Kind of changes that don't 
affect the maybe the meaning of 

504
00:28:03,210 --> 00:28:07,740
what's going on, but might 
enhance readability when you've.

505
00:28:07,750 --> 00:28:12,090
Used the tools as coop said, 
like AI to kind of help make 

506
00:28:12,100 --> 00:28:15,880
this project first you probably.
Haven't spend quite as many 

507
00:28:15,890 --> 00:28:17,790
hours because you weren't 
physically typing out the words.

508
00:28:17,800 --> 00:28:20,430
That's not to say you didn't do 
all the research and all that 

509
00:28:20,440 --> 00:28:24,290
kind of stuff, but AI, one of 
the ways that it helps is it can

510
00:28:24,360 --> 00:28:27,890
give you a first draft. 
Or it can give you. 

511
00:28:27,940 --> 00:28:31,630
Something where the physical 
typing of every word is not 

512
00:28:31,640 --> 00:28:34,630
something you have to do and. 
So because of that. 

513
00:28:34,920 --> 00:28:39,190
If a journal suggests a change 
to something stylistic, that was

514
00:28:39,200 --> 00:28:41,070
done. 
By the AI. 

515
00:28:41,140 --> 00:28:44,330
Right, as opposed to an author, 
there's there's less attachment.

516
00:28:44,340 --> 00:28:47,030
To it just because there. 
Isn't the same level of. 

517
00:28:47,320 --> 00:28:50,670
Commitment to exactly the way 
that that was written. 

518
00:28:50,680 --> 00:28:53,670
And so it gives journals more 
freedom. 

519
00:28:53,720 --> 00:28:56,280
As far as shaping paper 
stylistically. 

520
00:28:56,290 --> 00:28:59,550
Which is not something that's 
common for legal scholarship 

521
00:28:59,560 --> 00:29:01,930
generally. 
Usually the authors are the 

522
00:29:01,940 --> 00:29:04,320
driving force. 
Behind the. 

523
00:29:04,330 --> 00:29:06,450
Style of a paper. 
Perfect. 

524
00:29:06,460 --> 00:29:08,210
No, I love, I love that you 
mentioned that. 

525
00:29:08,300 --> 00:29:11,110
And I'm thinking about a few 
different topics here too on 

526
00:29:11,120 --> 00:29:14,010
the, on the sense of 
accessibility to league of 

527
00:29:14,020 --> 00:29:19,130
scholarship and then even like 
for for foreign actors to get 

528
00:29:19,140 --> 00:29:22,490
into North American legal 
scholarship, right. 

529
00:29:22,580 --> 00:29:26,030
So there is a very specific way 
that legal scholarship is 

530
00:29:26,040 --> 00:29:29,490
written and is portrayed. 
And sometimes, as you know, 

531
00:29:29,550 --> 00:29:32,790
speakers of English as a second 
language or, you know, all kinds

532
00:29:32,800 --> 00:29:35,280
of different barriers that you 
might have for legal 

533
00:29:35,290 --> 00:29:37,440
scholarship. 
This could be tools really that 

534
00:29:37,510 --> 00:29:39,800
that level, that playing field 
in many ways. 

535
00:29:39,870 --> 00:29:44,420
So in your view, does AI lower 
that barrier to enter in legal 

536
00:29:44,430 --> 00:29:47,650
scholarship? 
But also does it possibly create

537
00:29:47,660 --> 00:29:51,740
some risk of, of having a divide
between people who use the 

538
00:29:51,750 --> 00:29:54,280
tools, people who don't, and 
then, you know, you have some 

539
00:29:54,290 --> 00:29:57,680
kind of discredit or this merit 
for being in one of those 

540
00:29:57,690 --> 00:29:59,480
groups? 
What are some of the the 

541
00:29:59,490 --> 00:30:01,080
thoughts and things you've 
heard? 

542
00:30:01,170 --> 00:30:06,930
Yeah, When I was in DC, I worked
a lot on not only automation, 

543
00:30:06,940 --> 00:30:08,850
automated vehicles, but 
biotechnology. 

544
00:30:08,860 --> 00:30:12,270
So there's a point here. 
When it comes to biotechnology 

545
00:30:12,280 --> 00:30:14,840
in the United States, it's 
historically been governed by 

546
00:30:14,850 --> 00:30:18,110
something called the Coordinated
Framework for Biotechnology, 

547
00:30:18,180 --> 00:30:22,050
which in a roundabout way, its 
entire function is ensuring that

548
00:30:22,060 --> 00:30:24,650
you regulate products, not 
processes. 

549
00:30:24,720 --> 00:30:29,580
And I think that the best 
outcome of this duality between 

550
00:30:29,590 --> 00:30:32,610
those who use these tools and 
those who don't is that we get 

551
00:30:32,620 --> 00:30:35,770
to a point where law reviews are
evaluating products on their 

552
00:30:35,780 --> 00:30:38,530
merit and not the way in which 
they were created. 

553
00:30:38,580 --> 00:30:41,450
Because I do think that the 
point that you raised there is 

554
00:30:41,460 --> 00:30:45,480
that this does level a lot of 
the playing field because not 

555
00:30:45,490 --> 00:30:49,250
only does it help folks who 
maybe don't speak English or are

556
00:30:49,260 --> 00:30:53,030
unfamiliar with the structure of
a law review to be able to, you 

557
00:30:53,040 --> 00:30:56,990
know, run it through Claude or 
something to either translate it

558
00:30:57,040 --> 00:31:03,010
into a workable translation or 
reformat it into a more law 

559
00:31:03,020 --> 00:31:07,990
review type esque headers and, 
and structure and everything. 

560
00:31:08,000 --> 00:31:10,950
But I think it also levels the 
playing field on infrastructure 

561
00:31:11,000 --> 00:31:15,420
because right now you have a 
huge duality between individual 

562
00:31:15,430 --> 00:31:19,130
researchers and authors and 
researchers, research professors

563
00:31:19,140 --> 00:31:24,190
who are well funded, who have, 
you know, access to work from, 

564
00:31:24,200 --> 00:31:27,530
from RA and other support staff.
And in a lot of ways, I think 

565
00:31:27,540 --> 00:31:30,390
this kind of hearkens back to a 
conversation we had about the 

566
00:31:30,400 --> 00:31:33,810
book, the legal Singularity. 
And the way that AI allows for 

567
00:31:33,820 --> 00:31:37,050
the democratization of legal 
information is that it also 

568
00:31:37,060 --> 00:31:40,430
allows for the democratization 
of intellectual labour. 

569
00:31:40,500 --> 00:31:45,190
And so where researchers or 
authors are able to offload a 

570
00:31:45,200 --> 00:31:48,770
lot of the cognitive burden or 
just the research work using 

571
00:31:48,780 --> 00:31:52,330
tools like illicit, which will 
do like a full, you know, 

572
00:31:52,340 --> 00:31:55,930
research project for you on 
research outline or using it to 

573
00:31:56,020 --> 00:31:59,730
perhaps outline the argument 
structure of various case law 

574
00:31:59,740 --> 00:32:02,170
and things like that. 
They're able to offload the work

575
00:32:02,180 --> 00:32:05,350
that someone would just be 
handing off to another person 

576
00:32:05,420 --> 00:32:08,050
anyway. 
And so you're able to level the 

577
00:32:08,060 --> 00:32:09,750
playing field in a lot of 
respects there. 

578
00:32:09,800 --> 00:32:12,590
I, I think for the time being, 
there's going to continue to be 

579
00:32:12,600 --> 00:32:15,720
some form of discriminatory 
pattern with respect to, you 

580
00:32:15,730 --> 00:32:19,000
know, there's gonna always be 
people skeptical of the adoption

581
00:32:19,010 --> 00:32:21,100
of technology or the usage of 
technology. 

582
00:32:21,110 --> 00:32:23,780
I mean, for a long time, you 
know, people weren't allowed to 

583
00:32:23,790 --> 00:32:27,940
wear pants with zippers because 
it was provocative to the old 

584
00:32:27,950 --> 00:32:29,640
guard. 
In the same way lawyers weren't 

585
00:32:29,650 --> 00:32:34,040
allowed to use the Internet or 
word processor or not cite 

586
00:32:34,050 --> 00:32:36,190
something that they couldn't 
point to the exact book that 

587
00:32:36,200 --> 00:32:39,260
they pulled it from. 
And so I think that tradition of

588
00:32:39,270 --> 00:32:43,060
skepticism is going to carry 
forward in academia and law. 

589
00:32:43,110 --> 00:32:46,480
But I do think that this does 
level the playing field in a lot

590
00:32:46,490 --> 00:32:49,600
of really meaningful ways. 
And as long as the paradigm 

591
00:32:49,610 --> 00:32:53,380
shifts towards product rather 
than process, I think that 

592
00:32:53,390 --> 00:32:56,260
overcomes a lot of that innate 
skepticism. 

593
00:32:56,410 --> 00:33:00,040
Yeah, I, I agree completely. 
I think that the skepticism is 

594
00:33:00,110 --> 00:33:04,300
is here and it's going to. 
Be here for probably a while. 

595
00:33:04,310 --> 00:33:07,200
It's it's something you see with
the adoption of every type of 

596
00:33:07,210 --> 00:33:12,480
new technology that's ever been 
invented, there is, you know, a 

597
00:33:12,490 --> 00:33:15,760
kind of a period of turmoil 
while, you know. 

598
00:33:16,010 --> 00:33:20,660
The world rigor tests. 
The new technology, right? 

599
00:33:20,670 --> 00:33:23,180
It happened, Scoop said. 
With the Internet. 

600
00:33:23,190 --> 00:33:25,140
Where people were very 
skeptical. 

601
00:33:25,150 --> 00:33:27,940
Of, you know, cases that that 
were coming from the Internet 

602
00:33:27,950 --> 00:33:31,970
because for so long it was from 
a book or it didn't exist. 

603
00:33:31,980 --> 00:33:35,420
And so there was kind of that 
skepticism of can I trust this? 

604
00:33:35,430 --> 00:33:37,380
OK, I found it on the Internet. 
Now let me go find it in the 

605
00:33:37,390 --> 00:33:40,560
book just so I can make. 
Sure that it's it's that there 

606
00:33:40,570 --> 00:33:44,080
is, so there's. 
That level of skepticism, I 

607
00:33:44,090 --> 00:33:49,160
think it's healthy to a certain 
extent, especially while we're 

608
00:33:49,170 --> 00:33:51,260
in this stage. 
Of AI where there are. 

609
00:33:51,270 --> 00:33:54,660
Hallucinations and there are 
reasons for, you know, well 

610
00:33:54,670 --> 00:33:58,040
founded reasons for skepticism. 
So I think that part is healthy.

611
00:33:58,090 --> 00:34:02,140
I think it will diminish more 
and more and more, and I think 

612
00:34:02,190 --> 00:34:07,580
that it may not be universal 
adoption in the near. 

613
00:34:07,590 --> 00:34:11,100
Future It will probably take a 
while before there's. 

614
00:34:11,170 --> 00:34:13,940
You know, an overwhelming. 
Majority who are. 

615
00:34:13,989 --> 00:34:17,500
At least vocal or open. 
About the use of AI. 

616
00:34:17,510 --> 00:34:19,219
And legal work and legal 
scholarship. 

617
00:34:19,230 --> 00:34:22,300
And other fields just because. 
In many cases, like the 

618
00:34:22,310 --> 00:34:24,560
familiarity of using things the 
way we. 

619
00:34:24,570 --> 00:34:28,440
Have is. 
So it's so much familiarity. 

620
00:34:28,449 --> 00:34:30,570
With that that it's hard to give
it. 

621
00:34:30,580 --> 00:34:34,710
Up the skepticism, and also 
there is a bit of a learning 

622
00:34:34,719 --> 00:34:38,850
curve that comes to using AI, 
especially when you're trying. 

623
00:34:39,139 --> 00:34:43,110
To purposefully use it. 
Responsibly and ethically and 

624
00:34:43,120 --> 00:34:44,550
so. 
There is a bit of that. 

625
00:34:44,600 --> 00:34:47,210
Learning curve that not 
everybody is going to want to 

626
00:34:47,219 --> 00:34:51,330
attack and so the nice thing. 
Is just like with the. 

627
00:34:51,380 --> 00:34:55,650
Advents of other technologies 
right the people who don't want 

628
00:34:55,659 --> 00:34:59,350
to use AI in their scholarship 
or skeptical of it or think it's

629
00:34:59,360 --> 00:35:03,560
really important to do 
everything where they're typing 

630
00:35:03,570 --> 00:35:05,850
the words where they're. 
Using RA's for. 

631
00:35:05,900 --> 00:35:08,670
Some of the research and things,
hey, it doesn't propose any 

632
00:35:08,680 --> 00:35:11,690
like. 
Blockade of that old style. 

633
00:35:11,740 --> 00:35:14,500
Or the current style, the 
present way of doing things. 

634
00:35:14,510 --> 00:35:16,910
There's no it doesn't make any 
of that any. 

635
00:35:16,920 --> 00:35:20,060
Harder, it just gives a new path
for. 

636
00:35:20,200 --> 00:35:24,410
People who don't have perhaps 
the time, the financial. 

637
00:35:24,420 --> 00:35:29,690
Resources or elsewise to. 
To take on that labour, it 

638
00:35:29,740 --> 00:35:34,250
levels the playing field so that
they can engage in this 

639
00:35:34,260 --> 00:35:36,110
intellectual conversation as 
well. 

640
00:35:36,180 --> 00:35:38,520
That's fantastic. 
Well, thank you so much for 

641
00:35:38,600 --> 00:35:42,430
sharing those insights and and I
really appreciate the way that 

642
00:35:42,440 --> 00:35:46,130
this can be a tool really to 
make so many things better. 

643
00:35:46,140 --> 00:35:48,590
I like that that the 
proposition, since you mentioned

644
00:35:48,600 --> 00:35:52,940
the legal singularity, basically
has the idea of making law 

645
00:35:52,950 --> 00:35:56,040
significantly better. 
And I think that that just one 

646
00:35:56,050 --> 00:35:59,520
of the ways is, is this very 
simple way of making it possible

647
00:35:59,530 --> 00:36:01,970
for other voices to be brought 
up and all of that. 

648
00:36:02,070 --> 00:36:05,800
And finally, to wrap up today's 
episode, If I Lost you and our 

649
00:36:05,810 --> 00:36:09,560
young scholar, once you write 
with the help of AI responsibly 

650
00:36:09,570 --> 00:36:12,990
and ethically, I wanted to know 
what are some, you know, maybe 

651
00:36:13,000 --> 00:36:16,680
top three, top five golden rules
that may help them to get 

652
00:36:16,690 --> 00:36:18,020
started. 
I think. 

653
00:36:18,110 --> 00:36:21,780
I'll give the classic law a law.
School answer of it depends if 

654
00:36:21,790 --> 00:36:23,960
they're trying to publish 
something, I think the first 

655
00:36:23,970 --> 00:36:28,540
step has to be you know, check 
what your drafting for right If 

656
00:36:28,550 --> 00:36:30,060
you're. 
Drafting for. 

657
00:36:31,670 --> 00:36:34,820
A publication that has an 
explicit ban on all AI assisted 

658
00:36:34,830 --> 00:36:37,700
materials or something like. 
That it's going to be difficult 

659
00:36:37,710 --> 00:36:39,820
to use. 
AI ethically in that context 

660
00:36:39,830 --> 00:36:43,540
because there's an outright ban.
And so, you know, in that 

661
00:36:43,550 --> 00:36:45,600
situation you might want to stay
away from it. 

662
00:36:45,670 --> 00:36:51,100
But I think one of the most 
important things is just don't 

663
00:36:51,110 --> 00:36:53,860
rely on AI. 
As the AI shouldn't be the 

664
00:36:53,870 --> 00:36:58,120
backstop right? 
AI is a great tool but just like

665
00:36:58,130 --> 00:37:00,200
a Google search right? 
If you. 

666
00:37:00,210 --> 00:37:03,900
Click on the very first link and
do no further checking. 

667
00:37:03,950 --> 00:37:06,760
You're not necessarily going to 
get the best information out of 

668
00:37:06,770 --> 00:37:08,940
it, right? 
You don't have really any 

669
00:37:08,950 --> 00:37:12,850
safeguards on whether that's 
correct, on whether there's 

670
00:37:12,860 --> 00:37:14,650
something wrong. 
With the way that. 

671
00:37:14,730 --> 00:37:16,420
They came to their conclusions 
or anything else. 

672
00:37:16,430 --> 00:37:18,530
Like that? 
AI is the exact same way. 

673
00:37:18,540 --> 00:37:22,790
If you type in one prompt and 
just take whatever response AI 

674
00:37:22,800 --> 00:37:25,750
gives you and run with it, you 
leave yourself open to 

675
00:37:25,760 --> 00:37:28,160
experiencing problems like the 
hallucinations that. 

676
00:37:28,170 --> 00:37:30,030
We talked. 
About like some of the stretched

677
00:37:30,040 --> 00:37:34,350
propositions, and so anybody 
who's using it has a 

678
00:37:34,360 --> 00:37:38,150
responsibility to check for 
correctness. 

679
00:37:38,160 --> 00:37:41,650
Right. 
AI should not be used in a way 

680
00:37:41,660 --> 00:37:46,310
that's just relies entirely on 
this new technology to come up 

681
00:37:46,320 --> 00:37:50,070
with every aspect of an argument
with no fact checking whatever. 

682
00:37:50,140 --> 00:37:53,590
And that's probably one of the 
biggest problems that we see 

683
00:37:53,600 --> 00:37:56,170
from things that are drafted by 
AI. 

684
00:37:57,470 --> 00:38:00,050
I think building on that, my 
first one would be like 

685
00:38:00,100 --> 00:38:02,710
accountability. 
You know, at the end of the day,

686
00:38:02,760 --> 00:38:04,910
the authors name is still on 
this work. 

687
00:38:04,920 --> 00:38:08,130
We have, at least in in US 
intellectual property, 

688
00:38:08,220 --> 00:38:11,650
consistently rejected the notion
that that AI has an ownership or

689
00:38:11,660 --> 00:38:15,150
authorship right? 
And so as long as it's your name

690
00:38:15,160 --> 00:38:17,330
on the work, you have a 
responsibility to ensure that 

691
00:38:17,340 --> 00:38:21,590
it's accurate and meritorious. 
I also think that AI should not 

692
00:38:21,600 --> 00:38:24,050
create a shortcut for people to 
publish for the sake of 

693
00:38:24,060 --> 00:38:26,190
publication. 
I think that scholarship is an 

694
00:38:26,200 --> 00:38:30,250
ecosystem that deserves 
discretion in the way that 

695
00:38:30,260 --> 00:38:33,750
people enter into it and attempt
to participate in it. 

696
00:38:33,840 --> 00:38:38,330
And so just because AI makes it 
possible for you to write an 

697
00:38:38,340 --> 00:38:41,300
article doesn't mean you should 
be writing an article. 

698
00:38:41,430 --> 00:38:43,580
Like at the end of the day, like
that article still needs to mean

699
00:38:43,590 --> 00:38:45,680
something for someone. 
And I think particularly in 

700
00:38:45,690 --> 00:38:50,000
legal scholarship, where our 
entire advance here is to, you 

701
00:38:50,010 --> 00:38:53,640
know, in a in a path that that's
somewhat parallels litigation 

702
00:38:53,650 --> 00:38:56,600
and the common law, be able to 
explore valuable ideas. 

703
00:38:56,690 --> 00:39:00,660
And a lot of times, and a lot of
times not those ideas end up in 

704
00:39:00,670 --> 00:39:04,700
briefings and in opinions and 
really materially affect the 

705
00:39:04,710 --> 00:39:07,680
lives of litigants and people 
trying to vindicate themselves 

706
00:39:07,690 --> 00:39:10,040
legally. 
It's important that, you know, 

707
00:39:10,050 --> 00:39:12,720
you do a gut check on and make 
sure that what you're writing 

708
00:39:12,730 --> 00:39:15,670
actually matters. 
And then you allow AI to come 

709
00:39:15,680 --> 00:39:19,240
alongside you to move the ball 
down the field in pursuit of 

710
00:39:19,250 --> 00:39:22,320
that objective. 
So I think like AI creates a lot

711
00:39:22,330 --> 00:39:26,350
of liberty and so far as it 
helps people do what would 

712
00:39:26,360 --> 00:39:28,810
otherwise be incredibly 
cumbersome, but it shouldn't be 

713
00:39:28,820 --> 00:39:31,370
a license to participate for the
sake of participating. 

714
00:39:31,380 --> 00:39:33,290
Fantastic. 
Well, I really appreciate your 

715
00:39:33,300 --> 00:39:36,010
insights and really appreciate 
the work you put out there. 

716
00:39:36,060 --> 00:39:39,130
And we'll definitely have the 
links down here so people can 

717
00:39:39,140 --> 00:39:41,390
take a look. 
We really appreciate you both 

718
00:39:41,400 --> 00:39:43,470
coming into the podcast today. 
Thank you so much. 

719
00:39:44,260 --> 00:39:46,050
Thanks man. 
Thanks for having us.

