March 15, 2025 • 33 mins
The legal profession is on the cusp of a revolutionary GenAI transformation. Technological advancements are introducing entirely new ways to analyze, structure, and apply legal knowledge, and one of the most significant developments today involves generative artificial intelligence (AI). While many lawyers and legal teams have begun to hear about the potential of AI, the idea of incorporating these tools into daily legal practice can be daunting. Concerns about data confidentiality, the risk of “hallucinations,” and uncertainty about the broader impact on client relationships are top of mind for attorneys, in-house counsel, inventors, litigators, judges, and legal professionals of every stripe. This episode provides multiple perspectives to provide a deeper understanding of how to incorporate AI wisely, mitigate risks, and capture the benefits in a way that aligns with the ethical and professional obligations that lie at the heart of legal work. Whether you are a seasoned litigator, an in-house counsel evaluating new tools, an inventor curious about protecting your intellectual property more efficiently, or a judge eager to ensure fair proceedings in an era of automated drafting, this exploration of generative AI will illuminate what is possible—and how to get there responsibly.
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Episode Transcript
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(00:57):
Welcome to the AI Law Podcast.
I am Erick Robinson, a partner at BrownRudnick in Houston.
I am Co-Chair of the firm's Patent Trialand Appeal Board Practice Group.
In addition to being a patent litigatorand trial lawyer, I am well-versed not
only in the law of AI, but also have deeptechnical experience in AI and related
(01:19):
technologies.
The views and opinions expressed in thispodcast do not necessarily represent
those of Brown Rudnick.
This podcast is presented forinformational and educational purposes
only.
I am here today with gifted lawyer and AIexpert Sebastian Hale.
(01:41):
Great to have you here, Sebastian!It ismy honor and pleasure, Erick!So today we
are taking a deep dive of how generativeAI can help those of us in the legal
profession.
What are you thinking, Sebastian?The ideaof AI in the legal world isn't exactly
new, you know.
We've had technology-assisted review fore-discovery for years-machine learning
(02:03):
quietly working away in the background onsome of our most convoluted legal
tasks.Right, but generative AI?
Whole different ballgame.
It's not just about finding documentsanymore-it's writing, summarizing, even
drafting entire legal briefs if you giveit the right prompts.Exactly.
It's as if we've gone from a searchengine to having a, well, a junior
(02:24):
associate who doesn't sleep or complainabout how many boxes of discovery they
have to sift through.Except this juniorassociate works faster.
Way faster.And that's partly down to thesheer computing power we've got today.
These systems can process millions ofpages faster than even the most diligent
clerk could ever dream of.
Combine that with advances in naturallanguage processing-Where they actually
(02:48):
"get"
what you're asking, and don't just spitout keyword matches.Precisely.
They're delivering nuanced, context-awareresults.
But there's also this, well, relentlessdemand in the industry.
Firms, courts, in-house teams-everyone'sdrowning in data.
They have to meet tight deadlines,clients demand cost-efficiency...and
(03:08):
frankly, the old methods aren't cuttingit anymore.Yeah, no one has time to
manually redline contracts or dig throughdepositions for days on end.
This is where AI, like you said, shiftsfrom being a
"nice-to-have"
to a, uh, full-on necessity.Indeed.
And instead of spending hours on thosemind-numbing tasks, lawyers can finally
(03:31):
refocus their time and energy onstrategies, clients, and building
stronger cases.So if AI can handle thosetedious tasks, you might wonder-does that
mean it's coming for our jobs?
That's one of the big misconceptions I'venoticed, especially among lawyers.
But really, AI isn't about replacing us;it's about freeing us up to focus on what
truly matters.Right, the grunt work.
Let's be honest (03:52):
no one really got into law because they loved redlining
fifty-page contracts or slogging througha mountain of discovery files.Precisely.
Generative AI excels at those repetitive,data-heavy tasks that, well, frankly,
don't require deep legal reasoning orhuman empathy.
It's not here to argue a case incourt-it's not taking depositions or
(04:15):
connecting with clients.Yeah, becauselet's face it, a robot can't read the
room.
It doesn't understand the, uh, subtledynamics of a negotiation, right?
That's still very much the humandomain.Exactly.
And where AI really shines is as a kindof legal research assistant.
Imagine having something that can churnthrough gigabytes of case law, highlight
(04:36):
the most relevant precedents, and evensummarize arguments-in a fraction of the
time it'd take a junior associate.Andwithout complaining about their billable
hours.
It's like having an associate who neversleeps, never gets tired.Indeed.
Though, to be clear, this
"associate"
still needs oversight.
AI can give us-ahem-a draft or summarizekey points, but it doesn't replace the
(05:00):
human judgment required to craft strategyor apply legal reasoning to complex
situations.Right, the high-value workstays with us, the lawyers.
But the AI does the heavy lifting,letting us get to the good part
faster-less of the slog, more of thestrategy.It's a collaboration, really.
The AI handles the data crunching, andwe, as lawyers, bring the creativity, the
(05:24):
interpretation, the judgment.
It's not about obviating the humanelement; it's actually enhancing it.And
freeing us up, which-let's be real-meanswe get to spend more time on the tasks
that actually make a difference in acase, you know?Quite so.
It allows us to focus on the strategicside of our work.
It's about shifting the balance, lettingus concentrate more on what we're
(05:48):
uniquely qualified to do as humanprofessionals.Now, while AI is clearly a
powerful collaborator, it isn't withoutits quirks.
One of the more, let's say, interestingchallenges we've seen is something
experts call "hallucinations." That'swhen the model confidently generates
information that seems plausible but,when you look closer, just doesn't hold
(06:08):
up at all.You mean, like the intern whoswears they filed that case law citation
but, surprise, didn't?
Yeah, I've been there.Something likethat, yes.
Except here, the AI isn't intentionallymisleading-it's simply a byproduct of how
these systems are trained.
They work by predicting word sequencesbased on patterns in massive datasets.
(06:31):
If the data has gaps or biases-or if thequestion isn't clear-the model makes an
educated guess.
Sometimes, that's a bit too
"creative."
And clients love when their legalarguments are based on
"creative guesses."
Exactly.
That's why understanding whyhallucinations happen is so vital.
These models don't
(06:51):
"know"
in the traditional sense; they generatetext based on probabilities, not facts.
So, when they're asked something wheredata is sparse, they, well,
improvise.Which, for a chatbot demo?
Fine.
But for a brief headed to court?
That's a no-go.Absolutely not.
And this brings us to mitigationstrategies.
(07:13):
The first and most vital step isvalidation.
Every AI-generated output needs rigoroushuman review.
Facts, citations, arguments-everythinghas to be cross-checked.
You can't just assume the AI got itright, even if it sounds convincing.So,
basically, treat the AI like thatoverconfident first-year associate who
(07:35):
thinks, I don't know,
"Roe versus Wade"
is about river management law.
Got it.Heh, yes, something like that.
Another approach is to craft narrowerprompts.
If you're too broad, the AI tends todrift-you ask it for a summary of
antitrust law, and it might toss insomething about mergers that's not
relevant at all.
(07:55):
Clear, specific instructions help reducethat noise.And what about locking it down
to trusted sources?
Like, could you train it to only pullfrom, say, case law databases or
statutes?Precisely.
Some advanced systems allow integrationwith proprietary knowledge bases,
(08:15):
ensuring the AI draws exclusively fromvalidated content.
That dramatically cuts down onhallucinations-no extraneous, made-up
citations sneaking into your draft.Good.
'Cause the last thing I need isexplaining to a judge why my case law
quote came from, I don't know, a sciencefiction novel.Quite the predicament.
(08:35):
But seriously, at its best, AI works likea junior associate-enthusiastic,
productive, but in need of supervision.
When reviewed properly, these tools cansave time by summarizing voluminous data
or highlighting trends without the riskof your professional credibility taking a
hit.Just like ensuring AI outputs arethoroughly vetted, there's another
(08:58):
critical area we can't overlook whenintegrating AI into legal practice:
confidentiality.
It's really the cornerstone of what we doas lawyers, isn't it?
Breaching it isn't just an ethical no-no;it's malpractice, reputational
damage-potentially catastrophic for anylegal team.Totally catastrophic.
(09:19):
I mean, can you imagine explaining to aclient that sensitive company data got
leaked because your AI tool
"needed it"
for training?
That's...an awkward conversation.Quite.
And that's the crux of theissue-understanding precisely what
happens to the information you feed thesesystems.
Where is that data going?
(09:40):
Is it stored, and if so, how securely?
Is it being used to train broader AImodels?
These aren't trivial questions; they'remake-or-break considerations.Okay, so
then how do legal teams-small firms, bigin-house departments-actually vet these
AI providers?
What are they looking for?First andforemost, data handling policies.
(10:02):
Any reputable provider should clearlystate whether they're using your data for
training purposes.
Ideally, you want assurances-contractualones, if possible-that your data remains
compartmentalized and untouched.You meanlike in an encrypted silo or something,
right?
Not floating around in some general AIserver farm out there somewhere.Exactly.
(10:26):
Encryption is key-both in transit and atrest.
Access controls also matter.
Who can see this data?
And under what circumstances?
If the provider can't spell that out,it's a huge red flag.Okay, so storage and
access-check.
What else?
What should legal teams themselves bedoing to stay buttoned up?Well, client
(10:48):
consent is one layer.
In sensitive cases, you might even haveto discuss upfront whether or how AI
tools will be used.
Transparency here builds trust.
Beyond that, there'sde-identification-removing personally
identifiable information before uploadinganything for analysis.
And internal guidelines are crucial: standardized protocols around AI use, (11:07):
undefined
mandatory training-Wait, training?
Law firms and training in tech-two wordsthat rarely show up in the same
sentence.Fair point.
But it's critical.
If your team doesn't understand therisks, or even how to craft the AI
(11:27):
prompts properly, you're inviting errorsand potential confidentiality breaches.
A little upfront training can go a longway.Yeah, 'cause nothing screams
"audit nightmare"
like someone feeding unredacted witnessstatements into an open AI
platform.Precisely.
And this is the part where properlymanaged AI actually holds up its end of
(11:48):
the bargain.
When configured securely, these systemscan work within the same standards we
expect from, say, a trusted humanassociate.
They can analyze, summarize, and organizedata rapidly-all without compromising
client confidentiality.Okay, but nomatter how locked down it is, there's
still oversight needed, right?
(12:10):
Like, even the best systems make mistakesif left unchecked.Of course.
AI isn't a "set-it-and-forget-it" tool.
You, as the professional, remainresponsible for ensuring compliance,
accuracy, and discretion.
Used wisely, AI can elevate our workwithout undermining the trust that's,
frankly, at the heart of legalpractice.Building on that idea of
(12:32):
responsible oversight, when we talk aboutgenerative AI in law, it's not just this
abstract, science-fiction concept.
It's already being applied across, well,practically every corner of the legal
world.
From litigation to compliance, theversatility is kind of staggering-but so
is the need to use it wisely.Yeah, butlet's break it down.
(12:53):
I mean, "AI can do everything" isn'texactly helpful unless we know where it's
actually making a difference, right?Fairpoint.
Let's start with litigation ande-discovery.
Attorneys traditionally spend weekscombing through mountains of documents,
looking for that, uh, crucial needle inthe haystack.
AI doesn't just speed that process up-itrevolutionizes it entirely.
(13:18):
It can cluster documents by topic,highlight key passages, and even generate
useful deposition outlines.
Basically, it takes the grunt work offthe table.Which is huge.
Anyone who's ever dealt with discoveryknows the soul-crushing reality of
painstakingly combing through terabytesof data.
AI makes that, uh, bearable-or at leastlets you finish before retirement.Indeed.
(13:45):
And the summarization aspect can beparticularly eye-opening.
Imagine being able to quickly distill keypoints from deposition transcripts or
identify admissions buried deep in adocument set.
It's like having a team of endlesslydiligent paralegals working round the
clock.Without asking for coffee breaks.
Perfect.Exactly.
(14:05):
Now, moving on to contracts-this isanother area where AI shines.
Drafting, reviewing, comparing versions...
it's all incredibly time-consuming.
But generative AI can offer clausesuggestions, flag risk areas, and even
assess compliance.
It's like cutting hours off the entireprocess while ensuring nothing gets
(14:29):
overlooked.Right.
And instead of slogging throughboilerplate language for hours, you can
focus on the important stuff: negotiation, strategy, closing deals. (14:35):
undefined
The fun parts of lawyering.Quite so.
And then there's intellectual property.
Patent lawyers, for example, can use AIfor prior art searches-essentially
scouring patent databases to see whetheran invention or idea is already out there.
It's not perfect, of course, but it candrastically cut down the time it takes to
(14:59):
do those initial sweeps.Plus, for folksdealing with insanely technical
stuff-biopharma, advanced engineering-AIcan summarize all that mumbo jumbo into
something more, uh, digestible.
At least enough to know where to digdeeper, right?Spot on.
And it even extends to drafting patentapplications.
(15:19):
AI can handle the initial formatting andstructure, leaving the lawyer to focus on
refining claims and ensuring compliancewith filing requirements.
Again, it's about lifting the adminburden and letting us apply our expertise
where it matters most.Okay, so that'slitigation, contracting, patents-what
about compliance?
That's gotta be a minefield for AI,no?You'd think so, but it's surprisingly
(15:42):
useful in that domain too.
In-house teams can leverage AI to monitorlegislative changes, conduct audits, or
flag weak spots in policies.
For example, keeping corporate protocolsaligned with GDPR or environmental
standards is, well, a monumental task.
AI streamlines it by analyzing policiesand documents for inconsistencies or
(16:06):
gaps.And it flags those gaps instead ofjust letting them sit and, uh, blow up
later.
Smart.Precisely.
Finally, let's look at the judiciary.
Judges, clerks-they're not immune tooverflowing dockets and endless
documentation.
AI can summarize filings, identifypatterns in case law, and even help
(16:28):
clerks prepare initial motions.
The key is reducing the workload socourts can operate more efficiently.Yeah,
'cause nothing says
"justice delayed"
like a judge buried under a ten-footstack of briefs.
If AI can chip away at that, it's a winfor everyone.Absolutely.
Of course, as with any application, thesetools aren't perfect.
(16:49):
They need oversight, validation, and,well, ethical discretion.
But when used wisely, AI can enhancenearly every facet of legal practice,
making the impossible workload...
possible.If there's one thing we knowabout the legal profession, it's that
skepticism toward change isn't exactlyrare-especially when it comes to
technology.
(17:09):
Even with tools like AI provingtransformative, many still wrestle with
the idea of moving away fromtradition.Yeah, some might call it
skepticism-others would say we're juststubborn.Fair enough.
But the truth is, when it comes toimplementing generative AI, a structured
approach can, well, unravel a lot of thatresistance.
Start slow, small pilots, low-stakesenvironments...You mean, don't let the
(17:33):
junior associate loose on, I don't know,your billion-dollar merger deal
draft?Precisely.
Identify processes that consume time butcarry minimal risk.
Things like summarizing industry legalupdates or redlining contracts where the
stakes are lower.
These pilot projects ease teams into thepossibilities without jeopardizing, shall
(17:54):
we say, critical client work.Okay, solow-risk is the safe launchpad.
But let's talk about the elephant in theroom-lawyers and training on new tech.Ah,
yes.
Training.
Much maligned but undeniably essential.
You see, even the most advanced AI toolsrequire human operators who know how to
ask the right questions, interpretoutputs, and, above all, provide
(18:18):
oversight.
It's not just about knowing what buttonsto press; it's understanding what the
system can and can't do.So, teach themhow to cross-examine the AI,
basically-make sure the outputs actuallymake sense?Exactly.
Crafting precise prompts, identifyingerrors-it's a skillset unto itself,
(18:38):
almost akin to good legal writing.
Firms that skip this step...
well, they're setting themselves up fordisappointment, if not serious
blunders.Alright, but let's be realhere-training aside, most lawyers aren't
just gonna dive into this headfirst.
Isn't the reluctance tied, at least inpart, to fear?
(18:59):
Fear of something going spectacularlywrong?Very much so.
And that's why establishing internal bestpractices from the get-go is critical.
Frameworks that spell out permissible usecases, privacy safeguards, validation
protocols-these aren't justnice-to-haves; they're non-negotiable
(19:19):
guardrails.And I'm guessing a
"don't-freak-out"
checklist wouldn't hurt either, huh?Quite.
A well-defined set of guidelinesreassures teams that the AI isn't here to
replace their judgment or expertise.
And transparency helps too.
Folks need to see AI as an ally, not anunpredictable threat.Okay, so structured
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pilots, solid grounding in training,clear rules-sounds manageable.
But how do you get skeptics to, I don'tknow, stop clutching their well-worn
legal pads and really engage?Bydemonstrating value early on.
The
"aha"
moments come when lawyers realize thisisn't relinquishing control-it's
(20:02):
regaining time.
Showcasing how AI trims hours off mundanetasks allows teams to, well, concentrate
on the intellectual heavy-lifting theyactually enjoy.
It's about making the work more human,not less.So, basically, you take away the
legal drudgery and get back to the goodstuff?
(20:22):
Yeah, I could see people coming around tothat.Precisely.
It just takes a bit of patience, awillingness to learn, and, perhaps, a
touch of innovation to see where thesetools fit best in the legal ecosystem.
Once the barriers drop, the opportunitiesmultiply.Now, once those barriers start
to drop and opportunities emerge, there'sanother crucial aspect we can't ignore:
(20:44):
ethics.
It's the backbone of ourprofession-values like competence,
confidentiality, and candor aresacrosanct.
And when AI enters the picture, itchallenges us to uphold those standards
in new ways.You mean all the areas where
"messing it up"
could sink your entire career?Precisely.
Let's start with competence.
(21:05):
Legal professionals are increasinglyrequired to stay technologically
competent, and that extends tounderstanding the tools we use-AI
included.
If you don't grasp its limitations,nuances, or inherent flaws, you're
navigating a minefield.So, basically,don't treat it as a magic wand?
Got it.Exactly.
(21:26):
You need to understand how it arrives atcertain outputs, why it might generate
errors, and where human oversight iscritical.
You could almost say AI's risks aren'tpurely technological-many are born out of
how we misuse or misunderstand it.Right.
Like trusting it blindly to draft adeposition or something-bad idea.Indeed.
(21:47):
And then there's confidentiality-aminefield in its own right.
Breaches here can lead to ethicalviolations, loss of trust, and, frankly,
career-ruining consequences.
Any lawyer using AI must know exactlywhat happens to client data shared with
these systems.Yeah, because nothing putsa client at ease like,
(22:09):
"Your sensitive files might be on some AItraining server halfway across the world."
Precisely why data policies andencryption strategies become critical.
Legal teams need assurances-contractualones, if possible-that client information
isn't being retained inappropriately orused for model training.
Without that, you're taking a hugeethical gamble.Okay, so don't gamble with
(22:33):
client data-what's next?Avoidingunauthorized practice of law.
This one might not seem obvious, but ifAI drafts something incorrectly and you
don't catch it, are you still deliveringcompetent, professional advice?
The line between automation andaccountability gets murky if lawyers
don't take ownership of the AI'soutputs.Wait-you mean you can't just hit
(22:55):
"generate"
and call it done?
Shocking.Hardly shocking, but certainlyworrying.
AI tools are utilities, not substitutesfor legal judgment.
You remain responsible for every wordsubmitted in court or sent to a client.
It requires diligence, yes, but alsocandor-to admit what AI contributed and
verify everything against primary,reliable sources.And if you don't?
(23:17):
Pretty sure judges love calling out boguscitations in open court.Precisely why
maintaining accuracy at all costs isessential.
The duty of candor demands lawyerspresent truthful, verified statements.
And AI, left unchecked, could underminethat if not properly reviewed.So humans
are still the safety net.
(23:37):
AI might draft, summarize, evensuggest-but we've gotta validate every
detail, right?Exactly.
It's not a shortcut to bypassresponsibility.
It's an enhancement-but one that requirescareful oversight to actually support
ethical and professional obligations.
Anything less compromises the integrityof legal practice.Before we dive into our
(24:00):
next topic, let's address a bighurdle-misunderstandings about AI.
Generative AI, in particular, has sparkedplenty of myths, and it's critical we
sort fact from fiction to responsiblyleverage these tools.Oh yeah.
My favorite is
"AI's gonna take all our jobs."
Like this is some dystopian
"Robots Ate My Career"
nightmare waiting to happen.Yes, that'sthe big one, isn't it?
(24:23):
And, well, it's understandably unnerving.
But the truth is, AI isn't poised toreplace lawyers-it's designed to enhance
our capabilities.
Think of it more like the ideal juniorassociate who handles the repetitive
admin work so we can focus onhigher-level strategy and client
care.Right.
So instead of grinding throughmountain-sized stacks of disclosures, we
(24:47):
actually get to, I don't know, belawyers.Precisely.
AI thrives in areas that require patternrecognition and data processing, not
empathy or nuanced reasoning.
Those play to our human strengths, andfrankly, the profession would crumble
without them.
AI isn't here to take our cases totrial.Or charm a client over lunch.
So myth (25:10):
busted.
AI's not stealing our thunder.
What's next?Ah, the myth that AI outputsare absolute-either always flawless or
entirely unreliable.
Neither extreme is true.
Generative AI operates based on patternsand probabilities within training data,
(25:31):
which means, well, it's not infallible.
But it's also not some unpredictablewildcard.
It's about how we use it.So, kinda likethat friend who's... mostly right but
occasionally throws out the wildestnonsense, and you gotta double-check
anyway?That's a rather apt analogy,actually.
What distinguishes successful AIapplication is rigorous oversight.
(25:53):
Validate citations, vet arguments-treatit like an eager but untested intern.
Leave no assertion unchecked.Yeah, prettysure dropping a random AI-generated case
law into your brief isn't gonna win overany judges.
Moral of the story?
Always vet the work.Exactly.
It's about leveraging the toolwisely-allowing it to enhance efficiency
(26:15):
but never relinquishing professionalaccountability.
Which brings me neatly--To the myth aboutdata privacy.
Oh, good one.Yes, a particularly stickytopic.
There's this misconception that anyinformation input into an AI system is
automatically public.
But that depends entirely on the platform.
Industry-grade systems often encrypt userdata and segment it to prevent exposure.
(26:42):
Yet, lawyers must be meticulous inchoosing the right tools-vetting
providers, ensuring compliance withstrict data security standards.So, no
feeding sensitive deposition transcriptsinto some sketchy free app, huh?Exactly.
Confidentiality is paramount.
Using AI responsibly means understandingits capabilities and
(27:04):
limitations-mitigating risks, verifyingoutputs, and, most of all, upholding the
bedrock principles of our profession.Andspeaking of upholding those core
principles, it's worth stepping back fora moment.
While we've spent time debunking mythsand highlighting AI's impressive
capabilities, let's not lose sight ofwhat remains uniquely ours as human
(27:25):
lawyers.Right.
It's like you said earlier-AI's good atcrunching data, sure.
But it's not exactly known for itsbedside manner, is it?Indeed.
AI doesn't empathize, it doesn't graspthe nuances of moral arguments, nor does
it adapt to the intricacies of humanbehavior in a courtroom or a boardroom.
Those qualities-empathy, creativity,judgment-are uniquely human.
(27:50):
And, if anything, they become all themore vital in the context of AI-assisted
work.Yeah, because a machine can't tailoradvice to a client's goals.
It's not sitting there thinking,
"Is this the best move for theirbusiness... or their marriage?"
Precisely.
Clients look to us not just for legalknowledge but for understanding and
guidance-things that extend well beyondthe black-and-white confines of
(28:14):
compliance.
Another example (28:15):
judges expect arguments that are thoughtful, ethical, even
emotional-not just procedurally correct.
AI might give you the skeleton of anargument, but it takes a lawyer to
breathe life into it.And that's where themagic happens, right?
It's like...
framing a case.
Sure, the facts and lawsmatter-obviously-but the heart of it?
(28:38):
That's human work.Exactly.
AI simply accelerates the groundwork.
It can scan millions of documents inseconds, highlight trends, summarize
caseloads-but that's just data.
As lawyers, we're the ones making thejudgment calls, weighing risks, capturing
nuance.Yeah, like deciding how to,y'know, reconcile cold statutes with real
(29:00):
human impact.
That's not something you program into analgorithm.
You can't.Indeed.
And that's why AI is an ally rather thana replacement.
The synergy arises when it prepares thefactual foundation, laying the groundwork
for us to innovate, strategize, anddeliver ethical, client-focused solutions.
(29:21):
That collaboration allows us to do whatwe do best-concentrate on the art of
lawyering.The art of lawyering, huh?
I like that.
So, AI handles the grunt work, wehandle...
the soul of it?
I kinda prefer it that way.As do I.
It's a balance-a partnership.
And when used correctly, it not onlymakes us more efficient but-dare I
(29:43):
say-better lawyers altogether.You know,Erick, as we reflect on how AI
complements what we do, it's clear thisisn't just some passing trend.
Generative AI represents a real shift inhow we practice law-but it's up to us to
wield it with care and purpose.Definitely.
AI's not about upending everything weknow-it's about giving us the right tools
(30:04):
to handle the tidal wave of data andcomplexity coming at us.
Let's face it, without that, we'd alldrown.Precisely.
From early-stage research to draftingmeticulous briefs, AI makes it possible
to navigate that deluge with efficiency.
But-and really, this is the key-itremains just that: a tool.
(30:25):
An incredibly powerful one, yes, butstill subordinate to our human judgment
and ethics.Right.
It's like having the world's mosttireless assistant who never sleeps...
still, someone's gotta keep an eye onthem or they'll make mistakes faster than
we can fix them.Indeed.
Lawyers bring something AI simply cannotreplicate: the strategic foresight,
(30:47):
empathy for client dilemmas, and deepunderstanding of the human context behind
every legal decision.
Without that, the data is just, well,data-facts without meaning.And the
meaning part, the judgment calls,crafting an argument that, I dunno,
resonates with a jury or a judge-that'sstill squarely in our court.Absolutely.
(31:09):
What AI does is free us from the drudgeryof sifting through endless paperwork and
allow us to focus on the art of lawyering.
It gives us the bandwidth to advocatewith clarity, build compelling cases,
and, most importantly, connect with ourclients.So, basically, the secret sauce
hasn't changed-everything rests on humanexpertise.
(31:31):
AI just gets us to the good partfaster.Precisely.
And it's not only about becomingfaster-it's about becoming better.
By embracing AI responsibly, we canexpand access to justice, enhance
representation quality, and tackle legalchallenges with greater insight and
creativity.So the takeaway is prettysimple: Don't fear AI.
(31:55):
Test it, refine it, and most importantly,make it work for you, not the other way
around.Precisely.
Whether you're a litigator, in-housecounsel, inventor, or judge, there really
is a seat at the table for everyone inshaping this transformation.
The responsibility-and the opportunity-todefine how these tools fit into our
(32:17):
practice lies with us.Alright, Sebastian,I think we've managed to navigate the
pros, the pitfalls-and maybe even theparanoia-around AI in law.
Quite the journey.Quite so.
And on that note, I suppose this is theperfect place to draw our discussion to a
close.
To our listeners, thank you for joiningus as we explored this fascinating
(32:38):
frontier of law and technology.
Until next time, stay thoughtful, stayinnovative, and, most importantly, stay
human.Thanks for joining us!
So long until the next episode, y'all!
Welcome to the AI Law Podcast.
I am Erick Robinson, a partner at BrownRudnick in Houston.
I am Co-Chair of the firm's Patent Trialand Appeal Board Practice Group.
In addition to being a patent litigatorand trial lawyer, I am well-versed not
only in the law of AI, but also have deeptechnical experience in AI and related
(01:19):
technologies.
The views and opinions expressed in thispodcast do not necessarily represent
those of Brown Rudnick.
This podcast is presented forinformational and educational purposes
only.
I am here today with gifted lawyer and AIexpert Sebastian Hale.
(01:41):
Great to have you here, Sebastian!It ismy honor and pleasure, Erick!So today we
are taking a deep dive of how generativeAI can help those of us in the legal
profession.
What are you thinking, Sebastian?The ideaof AI in the legal world isn't exactly
new, you know.
We've had technology-assisted review fore-discovery for years-machine learning
(02:03):
quietly working away in the background onsome of our most convoluted legal
tasks.Right, but generative AI?
Whole different ballgame.
It's not just about finding documentsanymore-it's writing, summarizing, even
drafting entire legal briefs if you giveit the right prompts.Exactly.
It's as if we've gone from a searchengine to having a, well, a junior
(02:24):
associate who doesn't sleep or complainabout how many boxes of discovery they
have to sift through.Except this juniorassociate works faster.
Way faster.And that's partly down to thesheer computing power we've got today.
These systems can process millions ofpages faster than even the most diligent
clerk could ever dream of.
Combine that with advances in naturallanguage processing-Where they actually
(02:48):
"get"
what you're asking, and don't just spitout keyword matches.Precisely.
They're delivering nuanced, context-awareresults.
But there's also this, well, relentlessdemand in the industry.
Firms, courts, in-house teams-everyone'sdrowning in data.
They have to meet tight deadlines,clients demand cost-efficiency...and
(03:08):
frankly, the old methods aren't cuttingit anymore.Yeah, no one has time to
manually redline contracts or dig throughdepositions for days on end.
This is where AI, like you said, shiftsfrom being a
"nice-to-have"
to a, uh, full-on necessity.Indeed.
And instead of spending hours on thosemind-numbing tasks, lawyers can finally
(03:31):
refocus their time and energy onstrategies, clients, and building
stronger cases.So if AI can handle thosetedious tasks, you might wonder-does that
mean it's coming for our jobs?
That's one of the big misconceptions I'venoticed, especially among lawyers.
But really, AI isn't about replacing us;it's about freeing us up to focus on what
truly matters.Right, the grunt work.
Let's be honest (03:52):
no one really got into law because they loved redlining
fifty-page contracts or slogging througha mountain of discovery files.Precisely.
Generative AI excels at those repetitive,data-heavy tasks that, well, frankly,
don't require deep legal reasoning orhuman empathy.
It's not here to argue a case incourt-it's not taking depositions or
(04:15):
connecting with clients.Yeah, becauselet's face it, a robot can't read the
room.
It doesn't understand the, uh, subtledynamics of a negotiation, right?
That's still very much the humandomain.Exactly.
And where AI really shines is as a kindof legal research assistant.
Imagine having something that can churnthrough gigabytes of case law, highlight
(04:36):
the most relevant precedents, and evensummarize arguments-in a fraction of the
time it'd take a junior associate.Andwithout complaining about their billable
hours.
It's like having an associate who neversleeps, never gets tired.Indeed.
Though, to be clear, this
"associate"
still needs oversight.
AI can give us-ahem-a draft or summarizekey points, but it doesn't replace the
(05:00):
human judgment required to craft strategyor apply legal reasoning to complex
situations.Right, the high-value workstays with us, the lawyers.
But the AI does the heavy lifting,letting us get to the good part
faster-less of the slog, more of thestrategy.It's a collaboration, really.
The AI handles the data crunching, andwe, as lawyers, bring the creativity, the
(05:24):
interpretation, the judgment.
It's not about obviating the humanelement; it's actually enhancing it.And
freeing us up, which-let's be real-meanswe get to spend more time on the tasks
that actually make a difference in acase, you know?Quite so.
It allows us to focus on the strategicside of our work.
It's about shifting the balance, lettingus concentrate more on what we're
(05:48):
uniquely qualified to do as humanprofessionals.Now, while AI is clearly a
powerful collaborator, it isn't withoutits quirks.
One of the more, let's say, interestingchallenges we've seen is something
experts call "hallucinations." That'swhen the model confidently generates
information that seems plausible but,when you look closer, just doesn't hold
(06:08):
up at all.You mean, like the intern whoswears they filed that case law citation
but, surprise, didn't?
Yeah, I've been there.Something likethat, yes.
Except here, the AI isn't intentionallymisleading-it's simply a byproduct of how
these systems are trained.
They work by predicting word sequencesbased on patterns in massive datasets.
(06:31):
If the data has gaps or biases-or if thequestion isn't clear-the model makes an
educated guess.
Sometimes, that's a bit too
"creative."
And clients love when their legalarguments are based on
"creative guesses."
Exactly.
That's why understanding whyhallucinations happen is so vital.
These models don't
(06:51):
"know"
in the traditional sense; they generatetext based on probabilities, not facts.
So, when they're asked something wheredata is sparse, they, well,
improvise.Which, for a chatbot demo?
Fine.
But for a brief headed to court?
That's a no-go.Absolutely not.
And this brings us to mitigationstrategies.
(07:13):
The first and most vital step isvalidation.
Every AI-generated output needs rigoroushuman review.
Facts, citations, arguments-everythinghas to be cross-checked.
You can't just assume the AI got itright, even if it sounds convincing.So,
basically, treat the AI like thatoverconfident first-year associate who
(07:35):
thinks, I don't know,
"Roe versus Wade"
is about river management law.
Got it.Heh, yes, something like that.
Another approach is to craft narrowerprompts.
If you're too broad, the AI tends todrift-you ask it for a summary of
antitrust law, and it might toss insomething about mergers that's not
relevant at all.
(07:55):
Clear, specific instructions help reducethat noise.And what about locking it down
to trusted sources?
Like, could you train it to only pullfrom, say, case law databases or
statutes?Precisely.
Some advanced systems allow integrationwith proprietary knowledge bases,
(08:15):
ensuring the AI draws exclusively fromvalidated content.
That dramatically cuts down onhallucinations-no extraneous, made-up
citations sneaking into your draft.Good.
'Cause the last thing I need isexplaining to a judge why my case law
quote came from, I don't know, a sciencefiction novel.Quite the predicament.
(08:35):
But seriously, at its best, AI works likea junior associate-enthusiastic,
productive, but in need of supervision.
When reviewed properly, these tools cansave time by summarizing voluminous data
or highlighting trends without the riskof your professional credibility taking a
hit.Just like ensuring AI outputs arethoroughly vetted, there's another
(08:58):
critical area we can't overlook whenintegrating AI into legal practice:
confidentiality.
It's really the cornerstone of what we doas lawyers, isn't it?
Breaching it isn't just an ethical no-no;it's malpractice, reputational
damage-potentially catastrophic for anylegal team.Totally catastrophic.
(09:19):
I mean, can you imagine explaining to aclient that sensitive company data got
leaked because your AI tool
"needed it"
for training?
That's...an awkward conversation.Quite.
And that's the crux of theissue-understanding precisely what
happens to the information you feed thesesystems.
Where is that data going?
(09:40):
Is it stored, and if so, how securely?
Is it being used to train broader AImodels?
These aren't trivial questions; they'remake-or-break considerations.Okay, so
then how do legal teams-small firms, bigin-house departments-actually vet these
AI providers?
What are they looking for?First andforemost, data handling policies.
(10:02):
Any reputable provider should clearlystate whether they're using your data for
training purposes.
Ideally, you want assurances-contractualones, if possible-that your data remains
compartmentalized and untouched.You meanlike in an encrypted silo or something,
right?
Not floating around in some general AIserver farm out there somewhere.Exactly.
(10:26):
Encryption is key-both in transit and atrest.
Access controls also matter.
Who can see this data?
And under what circumstances?
If the provider can't spell that out,it's a huge red flag.Okay, so storage and
access-check.
What else?
What should legal teams themselves bedoing to stay buttoned up?Well, client
(10:48):
consent is one layer.
In sensitive cases, you might even haveto discuss upfront whether or how AI
tools will be used.
Transparency here builds trust.
Beyond that, there'sde-identification-removing personally
identifiable information before uploadinganything for analysis.
And internal guidelines are crucial: standardized protocols around AI use, (11:07):
undefined
mandatory training-Wait, training?
Law firms and training in tech-two wordsthat rarely show up in the same
sentence.Fair point.
But it's critical.
If your team doesn't understand therisks, or even how to craft the AI
(11:27):
prompts properly, you're inviting errorsand potential confidentiality breaches.
A little upfront training can go a longway.Yeah, 'cause nothing screams
"audit nightmare"
like someone feeding unredacted witnessstatements into an open AI
platform.Precisely.
And this is the part where properlymanaged AI actually holds up its end of
(11:48):
the bargain.
When configured securely, these systemscan work within the same standards we
expect from, say, a trusted humanassociate.
They can analyze, summarize, and organizedata rapidly-all without compromising
client confidentiality.Okay, but nomatter how locked down it is, there's
still oversight needed, right?
(12:10):
Like, even the best systems make mistakesif left unchecked.Of course.
AI isn't a "set-it-and-forget-it" tool.
You, as the professional, remainresponsible for ensuring compliance,
accuracy, and discretion.
Used wisely, AI can elevate our workwithout undermining the trust that's,
frankly, at the heart of legalpractice.Building on that idea of
(12:32):
responsible oversight, when we talk aboutgenerative AI in law, it's not just this
abstract, science-fiction concept.
It's already being applied across, well,practically every corner of the legal
world.
From litigation to compliance, theversatility is kind of staggering-but so
is the need to use it wisely.Yeah, butlet's break it down.
(12:53):
I mean, "AI can do everything" isn'texactly helpful unless we know where it's
actually making a difference, right?Fairpoint.
Let's start with litigation ande-discovery.
Attorneys traditionally spend weekscombing through mountains of documents,
looking for that, uh, crucial needle inthe haystack.
AI doesn't just speed that process up-itrevolutionizes it entirely.
(13:18):
It can cluster documents by topic,highlight key passages, and even generate
useful deposition outlines.
Basically, it takes the grunt work offthe table.Which is huge.
Anyone who's ever dealt with discoveryknows the soul-crushing reality of
painstakingly combing through terabytesof data.
AI makes that, uh, bearable-or at leastlets you finish before retirement.Indeed.
(13:45):
And the summarization aspect can beparticularly eye-opening.
Imagine being able to quickly distill keypoints from deposition transcripts or
identify admissions buried deep in adocument set.
It's like having a team of endlesslydiligent paralegals working round the
clock.Without asking for coffee breaks.
Perfect.Exactly.
(14:05):
Now, moving on to contracts-this isanother area where AI shines.
Drafting, reviewing, comparing versions...
it's all incredibly time-consuming.
But generative AI can offer clausesuggestions, flag risk areas, and even
assess compliance.
It's like cutting hours off the entireprocess while ensuring nothing gets
(14:29):
overlooked.Right.
And instead of slogging throughboilerplate language for hours, you can
focus on the important stuff: negotiation, strategy, closing deals. (14:35):
undefined
The fun parts of lawyering.Quite so.
And then there's intellectual property.
Patent lawyers, for example, can use AIfor prior art searches-essentially
scouring patent databases to see whetheran invention or idea is already out there.
It's not perfect, of course, but it candrastically cut down the time it takes to
(14:59):
do those initial sweeps.Plus, for folksdealing with insanely technical
stuff-biopharma, advanced engineering-AIcan summarize all that mumbo jumbo into
something more, uh, digestible.
At least enough to know where to digdeeper, right?Spot on.
And it even extends to drafting patentapplications.
(15:19):
AI can handle the initial formatting andstructure, leaving the lawyer to focus on
refining claims and ensuring compliancewith filing requirements.
Again, it's about lifting the adminburden and letting us apply our expertise
where it matters most.Okay, so that'slitigation, contracting, patents-what
about compliance?
That's gotta be a minefield for AI,no?You'd think so, but it's surprisingly
(15:42):
useful in that domain too.
In-house teams can leverage AI to monitorlegislative changes, conduct audits, or
flag weak spots in policies.
For example, keeping corporate protocolsaligned with GDPR or environmental
standards is, well, a monumental task.
AI streamlines it by analyzing policiesand documents for inconsistencies or
(16:06):
gaps.And it flags those gaps instead ofjust letting them sit and, uh, blow up
later.
Smart.Precisely.
Finally, let's look at the judiciary.
Judges, clerks-they're not immune tooverflowing dockets and endless
documentation.
AI can summarize filings, identifypatterns in case law, and even help
(16:28):
clerks prepare initial motions.
The key is reducing the workload socourts can operate more efficiently.Yeah,
'cause nothing says
"justice delayed"
like a judge buried under a ten-footstack of briefs.
If AI can chip away at that, it's a winfor everyone.Absolutely.
Of course, as with any application, thesetools aren't perfect.
(16:49):
They need oversight, validation, and,well, ethical discretion.
But when used wisely, AI can enhancenearly every facet of legal practice,
making the impossible workload...
possible.If there's one thing we knowabout the legal profession, it's that
skepticism toward change isn't exactlyrare-especially when it comes to
technology.
(17:09):
Even with tools like AI provingtransformative, many still wrestle with
the idea of moving away fromtradition.Yeah, some might call it
skepticism-others would say we're juststubborn.Fair enough.
But the truth is, when it comes toimplementing generative AI, a structured
approach can, well, unravel a lot of thatresistance.
Start slow, small pilots, low-stakesenvironments...You mean, don't let the
(17:33):
junior associate loose on, I don't know,your billion-dollar merger deal
draft?Precisely.
Identify processes that consume time butcarry minimal risk.
Things like summarizing industry legalupdates or redlining contracts where the
stakes are lower.
These pilot projects ease teams into thepossibilities without jeopardizing, shall
(17:54):
we say, critical client work.Okay, solow-risk is the safe launchpad.
But let's talk about the elephant in theroom-lawyers and training on new tech.Ah,
yes.
Training.
Much maligned but undeniably essential.
You see, even the most advanced AI toolsrequire human operators who know how to
ask the right questions, interpretoutputs, and, above all, provide
(18:18):
oversight.
It's not just about knowing what buttonsto press; it's understanding what the
system can and can't do.So, teach themhow to cross-examine the AI,
basically-make sure the outputs actuallymake sense?Exactly.
Crafting precise prompts, identifyingerrors-it's a skillset unto itself,
(18:38):
almost akin to good legal writing.
Firms that skip this step...
well, they're setting themselves up fordisappointment, if not serious
blunders.Alright, but let's be realhere-training aside, most lawyers aren't
just gonna dive into this headfirst.
Isn't the reluctance tied, at least inpart, to fear?
(18:59):
Fear of something going spectacularlywrong?Very much so.
And that's why establishing internal bestpractices from the get-go is critical.
Frameworks that spell out permissible usecases, privacy safeguards, validation
protocols-these aren't justnice-to-haves; they're non-negotiable
(19:19):
guardrails.And I'm guessing a
"don't-freak-out"
checklist wouldn't hurt either, huh?Quite.
A well-defined set of guidelinesreassures teams that the AI isn't here to
replace their judgment or expertise.
And transparency helps too.
Folks need to see AI as an ally, not anunpredictable threat.Okay, so structured
(19:41):
pilots, solid grounding in training,clear rules-sounds manageable.
But how do you get skeptics to, I don'tknow, stop clutching their well-worn
legal pads and really engage?Bydemonstrating value early on.
The
"aha"
moments come when lawyers realize thisisn't relinquishing control-it's
(20:02):
regaining time.
Showcasing how AI trims hours off mundanetasks allows teams to, well, concentrate
on the intellectual heavy-lifting theyactually enjoy.
It's about making the work more human,not less.So, basically, you take away the
legal drudgery and get back to the goodstuff?
(20:22):
Yeah, I could see people coming around tothat.Precisely.
It just takes a bit of patience, awillingness to learn, and, perhaps, a
touch of innovation to see where thesetools fit best in the legal ecosystem.
Once the barriers drop, the opportunitiesmultiply.Now, once those barriers start
to drop and opportunities emerge, there'sanother crucial aspect we can't ignore:
(20:44):
ethics.
It's the backbone of ourprofession-values like competence,
confidentiality, and candor aresacrosanct.
And when AI enters the picture, itchallenges us to uphold those standards
in new ways.You mean all the areas where
"messing it up"
could sink your entire career?Precisely.
Let's start with competence.
(21:05):
Legal professionals are increasinglyrequired to stay technologically
competent, and that extends tounderstanding the tools we use-AI
included.
If you don't grasp its limitations,nuances, or inherent flaws, you're
navigating a minefield.So, basically,don't treat it as a magic wand?
Got it.Exactly.
(21:26):
You need to understand how it arrives atcertain outputs, why it might generate
errors, and where human oversight iscritical.
You could almost say AI's risks aren'tpurely technological-many are born out of
how we misuse or misunderstand it.Right.
Like trusting it blindly to draft adeposition or something-bad idea.Indeed.
(21:47):
And then there's confidentiality-aminefield in its own right.
Breaches here can lead to ethicalviolations, loss of trust, and, frankly,
career-ruining consequences.
Any lawyer using AI must know exactlywhat happens to client data shared with
these systems.Yeah, because nothing putsa client at ease like,
(22:09):
"Your sensitive files might be on some AItraining server halfway across the world."
Precisely why data policies andencryption strategies become critical.
Legal teams need assurances-contractualones, if possible-that client information
isn't being retained inappropriately orused for model training.
Without that, you're taking a hugeethical gamble.Okay, so don't gamble with
(22:33):
client data-what's next?Avoidingunauthorized practice of law.
This one might not seem obvious, but ifAI drafts something incorrectly and you
don't catch it, are you still deliveringcompetent, professional advice?
The line between automation andaccountability gets murky if lawyers
don't take ownership of the AI'soutputs.Wait-you mean you can't just hit
(22:55):
"generate"
and call it done?
Shocking.Hardly shocking, but certainlyworrying.
AI tools are utilities, not substitutesfor legal judgment.
You remain responsible for every wordsubmitted in court or sent to a client.
It requires diligence, yes, but alsocandor-to admit what AI contributed and
verify everything against primary,reliable sources.And if you don't?
(23:17):
Pretty sure judges love calling out boguscitations in open court.Precisely why
maintaining accuracy at all costs isessential.
The duty of candor demands lawyerspresent truthful, verified statements.
And AI, left unchecked, could underminethat if not properly reviewed.So humans
are still the safety net.
(23:37):
AI might draft, summarize, evensuggest-but we've gotta validate every
detail, right?Exactly.
It's not a shortcut to bypassresponsibility.
It's an enhancement-but one that requirescareful oversight to actually support
ethical and professional obligations.
Anything less compromises the integrityof legal practice.Before we dive into our
(24:00):
next topic, let's address a bighurdle-misunderstandings about AI.
Generative AI, in particular, has sparkedplenty of myths, and it's critical we
sort fact from fiction to responsiblyleverage these tools.Oh yeah.
My favorite is
"AI's gonna take all our jobs."
Like this is some dystopian
"Robots Ate My Career"
nightmare waiting to happen.Yes, that'sthe big one, isn't it?
(24:23):
And, well, it's understandably unnerving.
But the truth is, AI isn't poised toreplace lawyers-it's designed to enhance
our capabilities.
Think of it more like the ideal juniorassociate who handles the repetitive
admin work so we can focus onhigher-level strategy and client
care.Right.
So instead of grinding throughmountain-sized stacks of disclosures, we
(24:47):
actually get to, I don't know, belawyers.Precisely.
AI thrives in areas that require patternrecognition and data processing, not
empathy or nuanced reasoning.
Those play to our human strengths, andfrankly, the profession would crumble
without them.
AI isn't here to take our cases totrial.Or charm a client over lunch.
So myth (25:10):
busted.
AI's not stealing our thunder.
What's next?Ah, the myth that AI outputsare absolute-either always flawless or
entirely unreliable.
Neither extreme is true.
Generative AI operates based on patternsand probabilities within training data,
(25:31):
which means, well, it's not infallible.
But it's also not some unpredictablewildcard.
It's about how we use it.So, kinda likethat friend who's... mostly right but
occasionally throws out the wildestnonsense, and you gotta double-check
anyway?That's a rather apt analogy,actually.
What distinguishes successful AIapplication is rigorous oversight.
(25:53):
Validate citations, vet arguments-treatit like an eager but untested intern.
Leave no assertion unchecked.Yeah, prettysure dropping a random AI-generated case
law into your brief isn't gonna win overany judges.
Moral of the story?
Always vet the work.Exactly.
It's about leveraging the toolwisely-allowing it to enhance efficiency
(26:15):
but never relinquishing professionalaccountability.
Which brings me neatly--To the myth aboutdata privacy.
Oh, good one.Yes, a particularly stickytopic.
There's this misconception that anyinformation input into an AI system is
automatically public.
But that depends entirely on the platform.
Industry-grade systems often encrypt userdata and segment it to prevent exposure.
(26:42):
Yet, lawyers must be meticulous inchoosing the right tools-vetting
providers, ensuring compliance withstrict data security standards.So, no
feeding sensitive deposition transcriptsinto some sketchy free app, huh?Exactly.
Confidentiality is paramount.
Using AI responsibly means understandingits capabilities and
(27:04):
limitations-mitigating risks, verifyingoutputs, and, most of all, upholding the
bedrock principles of our profession.Andspeaking of upholding those core
principles, it's worth stepping back fora moment.
While we've spent time debunking mythsand highlighting AI's impressive
capabilities, let's not lose sight ofwhat remains uniquely ours as human
(27:25):
lawyers.Right.
It's like you said earlier-AI's good atcrunching data, sure.
But it's not exactly known for itsbedside manner, is it?Indeed.
AI doesn't empathize, it doesn't graspthe nuances of moral arguments, nor does
it adapt to the intricacies of humanbehavior in a courtroom or a boardroom.
Those qualities-empathy, creativity,judgment-are uniquely human.
(27:50):
And, if anything, they become all themore vital in the context of AI-assisted
work.Yeah, because a machine can't tailoradvice to a client's goals.
It's not sitting there thinking,
"Is this the best move for theirbusiness... or their marriage?"
Precisely.
Clients look to us not just for legalknowledge but for understanding and
guidance-things that extend well beyondthe black-and-white confines of
(28:14):
compliance.
Another example (28:15):
judges expect arguments that are thoughtful, ethical, even
emotional-not just procedurally correct.
AI might give you the skeleton of anargument, but it takes a lawyer to
breathe life into it.And that's where themagic happens, right?
It's like...
framing a case.
Sure, the facts and lawsmatter-obviously-but the heart of it?
(28:38):
That's human work.Exactly.
AI simply accelerates the groundwork.
It can scan millions of documents inseconds, highlight trends, summarize
caseloads-but that's just data.
As lawyers, we're the ones making thejudgment calls, weighing risks, capturing
nuance.Yeah, like deciding how to,y'know, reconcile cold statutes with real
(29:00):
human impact.
That's not something you program into analgorithm.
You can't.Indeed.
And that's why AI is an ally rather thana replacement.
The synergy arises when it prepares thefactual foundation, laying the groundwork
for us to innovate, strategize, anddeliver ethical, client-focused solutions.
(29:21):
That collaboration allows us to do whatwe do best-concentrate on the art of
lawyering.The art of lawyering, huh?
I like that.
So, AI handles the grunt work, wehandle...
the soul of it?
I kinda prefer it that way.As do I.
It's a balance-a partnership.
And when used correctly, it not onlymakes us more efficient but-dare I
(29:43):
say-better lawyers altogether.You know,Erick, as we reflect on how AI
complements what we do, it's clear thisisn't just some passing trend.
Generative AI represents a real shift inhow we practice law-but it's up to us to
wield it with care and purpose.Definitely.
AI's not about upending everything weknow-it's about giving us the right tools
(30:04):
to handle the tidal wave of data andcomplexity coming at us.
Let's face it, without that, we'd alldrown.Precisely.
From early-stage research to draftingmeticulous briefs, AI makes it possible
to navigate that deluge with efficiency.
But-and really, this is the key-itremains just that: a tool.
(30:25):
An incredibly powerful one, yes, butstill subordinate to our human judgment
and ethics.Right.
It's like having the world's mosttireless assistant who never sleeps...
still, someone's gotta keep an eye onthem or they'll make mistakes faster than
we can fix them.Indeed.
Lawyers bring something AI simply cannotreplicate: the strategic foresight,
(30:47):
empathy for client dilemmas, and deepunderstanding of the human context behind
every legal decision.
Without that, the data is just, well,data-facts without meaning.And the
meaning part, the judgment calls,crafting an argument that, I dunno,
resonates with a jury or a judge-that'sstill squarely in our court.Absolutely.
(31:09):
What AI does is free us from the drudgeryof sifting through endless paperwork and
allow us to focus on the art of lawyering.
It gives us the bandwidth to advocatewith clarity, build compelling cases,
and, most importantly, connect with ourclients.So, basically, the secret sauce
hasn't changed-everything rests on humanexpertise.
(31:31):
AI just gets us to the good partfaster.Precisely.
And it's not only about becomingfaster-it's about becoming better.
By embracing AI responsibly, we canexpand access to justice, enhance
representation quality, and tackle legalchallenges with greater insight and
creativity.So the takeaway is prettysimple: Don't fear AI.
(31:55):
Test it, refine it, and most importantly,make it work for you, not the other way
around.Precisely.
Whether you're a litigator, in-housecounsel, inventor, or judge, there really
is a seat at the table for everyone inshaping this transformation.
The responsibility-and the opportunity-todefine how these tools fit into our
(32:17):
practice lies with us.Alright, Sebastian,I think we've managed to navigate the
pros, the pitfalls-and maybe even theparanoia-around AI in law.
Quite the journey.Quite so.
And on that note, I suppose this is theperfect place to draw our discussion to a
close.
To our listeners, thank you for joiningus as we explored this fascinating
(32:38):
frontier of law and technology.
Until next time, stay thoughtful, stayinnovative, and, most importantly, stay
human.Thanks for joining us!
So long until the next episode, y'all!
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