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Good afternoon everyone thank you for joining today's webinar ER and the legal perspective
Integrating AI in the investigation process we're recording today's session and we'll share it with
You following the webinar if you have any questions please use a Q&A function on your
Zoom panel now I'd like to hand it over to our moderator for today's session HRQE CEO Deb Muller, CEO HR Acuity Mohler
Thanks Lexi Malone, Marketing & Events Manager at HR Acuity and hi everybody it's great to see everybody calling in and chatting in from where
They're coming from we have a great big group today and I'm not surprised because of the topic
And our incredible presenter that's with us but it's wonderful to scroll through and see names new
Um see names of people I know i wish I could be have a chat with all of you feel free to
Link in with me on LinkedIn i'd love to have more connections to the community all right
I'm going to start right in because it is an exciting topic we're talking about integrating
AI into our investigation processes i know it's hot topic before I start couple sec
Sele for for those of you that might be joining us for the first time we are the leading solution
In employee relations and investigations case management and we like to say that
We take you from all the way from issue all the way through allegations so our platform
Covers anonymous reporting tools for managers when they're documenting employee issues um
Proper ways to conduct investigations in the system using technology to really help you
Uh some with AI and we're going to talk about more that more today and then all the data and
Analytics to really help you be more proactive and preventative to creating safe and compliant
Workplaces so if you want to learn more about our technology we'd love to share it with you
Take you on a curiosity tour just let us know and in addition to our technology we like to say we're
The leaders in employee relation this is all we do we eat breathe drink sleep it um many of you
Are familiar with our benchmark study that we do every year this is my little prop i'm going to
Hold up the actual study you can download it you can download eight years of it because we've done
It for eight years on our website and we right now are collecting data for our ninth annual study so
Lexi Malone, Marketing & Events Manager at HR Acuity will put the links in if you have a thousand or more employees um we encourage you please to
Participate it makes our data even stronger year-over-year we have some great benchmarks
In here last year we had our study covered over 8 and a half million employees i don't know my
Personal goal for this year is 10 million so we need your participation um we also have our ERQ
Which is our employee relations quotient you can find that on our website to really see where you
Are on your journey in employee relations it is the first ever maturity model for employee
Relations and then of course we have our roundt event which we're going to be announcing very soon
Uh it's going to be in the fall uh and that's when we get together global employee relations
Leaders for really two days of collaboration brainstorming thought leadership it's really
A one-of-a-kind incredible event and finally I'm assuming but maybe I shouldn't that all of you
Are part of Empower if you do anything employee relations you should do that today it's free
To join it's an online community exclusively for employee relations professionals great live feed
Job posting sharing it's free so join we have over I think about 6,500 members right now and that
Is growing as well so please join the community continue to engage with us um I think this year
More than ever although I've said that before we're going to need to lean on each other with
All the changes that are coming out and how do we really um support our employees and our employer
Um as employee relations professionals okay next slide for those of you who this is your first
Webinar or if you're familiar with our webinar you know that as a thank you for you um coming
To listen to the webinar but uh specifically as a thank you to our experts that join us and share
With our community we like to make a donation in their honor and today I'm really excited that
We're making a donation to an organization that's really close to Lor's heart um it's the Hospice
Of Central Ohio and they really do some wonderful work it's not for-profit uh hospicees in Ohio to
Really help families and patients in their time of need so we're we're we're thankful that we're
Able to make a donation and on behalf of all of you and behalf of Lori Deem, Hughes Socol Piers Resnick & Dym, Ltd. um upcoming events
And then we'll get to our event but for those of you that are here today who are HR cutie customers
Um we're sort of having an after webinar uh panel so Lori Deem, Hughes Socol Piers Resnick & Dym, Ltd. is going to join us on February 5th at one
O'clock again so thank you again Lori Deem, Hughes Socol Piers Resnick & Dym, Ltd. to continue the conversation and do some expert Q&A on today's
Um conversation so that is an exclusive for our customers so if you're if you're part of that
That group please um join us for that i think it's going to be great and then for our entire empower
Community on February 13th our next webinar is on workplace investigations in 2025 and what you need
To know and Katherine Perez is going to be leading that she's terrific um and again 2025 just might
Be a little bit different than 2024 all right so we ready to start okay we're ready to start
So I'm really excited to get this launched off as I already alluded to we are joined I see her on
The screen by Lori Deem, Hughes Socol Piers Resnick & Dym, Ltd. Deem, Hughes Socol Piers Resnick & Dym, Ltd. Lori Deem, Hughes Socol Piers Resnick & Dym, Ltd. Deem, Hughes Socol Piers Resnick & Dym, Ltd. as many of you might know is a partner at Hughes So Piers Resnik
And DYM she's been an employment lawyer with over 20 years of experience representing individuals
In a wide range of employment matters she specializes in assisting senior executives with
Job transitions change and control situations and drafting and negotiating employment and
Severance agreements Lori Deem, Hughes Socol Piers Resnick & Dym, Ltd. has received numerous accolades for her work including being named one
Of the top 50 women lawyers in Illinois in 2022 now that's what's written here now I'm going
To tell you what I think about Lori Deem, Hughes Socol Piers Resnick & Dym, Ltd. first of all she's a plaintiff's attorney that you're going to
Love which is maybe something you've never heard before Lori Deem, Hughes Socol Piers Resnick & Dym, Ltd. has been part of our HRE roundtable
Ecosystem for many many years she's almost been to as many roundtables as me sharing her wisdom
And her outlook and her sense of humor with all of us and she has become everybody's like "Is Lori Deem, Hughes Socol Piers Resnick & Dym, Ltd.
Coming back is Lori Deem, Hughes Socol Piers Resnick & Dym, Ltd. coming back?" So she's really such a part of our community we love having her um
She's a a colleague but she's also become a very dear friend and I'm so excited for her to be here
So Lori Deem, Hughes Socol Piers Resnick & Dym, Ltd. welcome and um excited once again to have you share with our community thank you so much Deb Muller, CEO HR Acuity
Thank you everyone um like you said earlier it was nice to see so many familiar names pop up but so
Many new names as well in the participant window so um welcome everybody and thanks for joining us
Today um I promise you that my goal is not to throw um a giant bucket of ice cold water out
Of Lake Michigan where I am on um the concept of using AI in workplace investigations um I'm just
Here to give you my thoughts and my perspective um from sitting behind this desk every day and and um
Being a plaintiff's lawyer on where we need to you know create we need to be cognizant of the
Cautions and the pit potential pitfalls um but also do something about it and see if we can uh
Find a way to um integrate the technology in a way that is safe and responsible but also avoid some
Of the susceptibilities that we all know um can creep in even with us as human beings let alone
Um with a bot so um I think what I I'd like to start with before we get to how you can use AI
At each turn of the investigation life cycle is just you know first the question are you already
Using it um yeah and Lori Deem, Hughes Socol Piers Resnick & Dym, Ltd. this data here um is from our benchmark study from last year
We've been asking this question for a long time actually uh but last year finally got a little
Bit more deep into it just given everything that was going on the availability of AI really took
A big turn last year and so you can see here um only 9% are really fully embracing AI and ER and
I'm not really that surprised about that i'm not either um I think this is probably consistent with
Um how other um parts of the employment or HR ecosphere are using it and and some of the
Trepidations that everyone has um and I think we are in this phase where we can develop guidelines
And navigate the legal challenges and sort of figure this out as you know the professionals
Right and the um and the ones who hopefully are the gatekeepers of how do we use this responsibly
So um it's not it's not unusual this sort of curve is not unusual for new technologies and so the
Fact that there is more than half and I bet that's grown since this came out in June trying to figure
It out and that's part of what this discussion is all about today absolutely so um the other thing
That I want to say by the way is that I'm not I I certainly don't represent let alone have I used or
Um gravitated myself towards any particular technology so I'm not going to be really talking
That much about specific um AI products um because it's not my goal to disparrage any particular
Um you know vendor in this space um I'm just going to speak more globally about some of the some of
The um pros and cons that I see so um so starting off with just sort of a highle overview of the
General concerns that come up when we talk about integrating this into our workplace investigation
Life cycle and the first is pretty obvious it's data security and confidentiality and um I don't
Pretend to be a data or cyerspace um e expert but um many companies absolutely refuse to bring AI
Into their ecosphere for any any usage whether it be you know chat GPT to write performance
Evaluations or anything like that because they are worried about the data security and potential for
Um data breaches that come with inviting any new technology into their world um let alone
One that the vendor still has a ongoing connection with the employer um so there this is verboten in
Certain highly regulated industries period um but those that have started to adopt it have
Acknowledged that you need to be very cognizant of the difference between a closed loop data set and
An openloop data set and I think by its by its own words you understand the difference but um just so
We're clear a closed data set is your own data is what is educating the AI algorithm about um how to
Learn what your patterns are what your information is and learn how to recognize it and suggest new
Things to you versus an open data data set is taking your information and sending it out offsite
To the vendor and allowing their um their data set to be educated by your data but also then you're
Educated by all the other data um and suggestions come from there um there are obviously higher
Risks inherent in the open data set and that's why most companies that are adopting some sort of AI
Into their uh their HR or their ER platforms are opting towards a closed data set um that can be
More expensive because it requires customization and um working very closely with the vendor um to
Uh create those data sets in order to educate the bot um but it it is the preferred method if
If you're heightened if you have a heightened concern about security um but even in a closed
Loop there are still other concerns like the ones highlighted here on the slide um and the biggest
One is bias and we'll get to that in a second i'm just going to talk about the other two real fast
And then we'll we'll talk about bias because I think it's the one that we as HR ER employment
Law professionals are the most concerned about um but the other concerns are are generally how how
Are stakeholders whether we're talking senior level executives and and your um your board of
Directors but also stakeholders all throughout the organization how are they reacting when they hear
That you're considering or you're actually beta testing using AI and workplace investigations what
Are their reactions going to be what are you know how do they feel about um should we be transparent
About it or not and what's the overall workplace reaction to that to this and this can be managed
I think with a very clear communications plan and we'll talk about that later when we get to
Best practices but um usually people come to the concept of AI with their own preconceived notions
Whether it's informed or not informed um and so that's one thing you're going to have to manage
Um during the adoption phase if you decide to go this route is how is everybody reacting to it and
How much are you going to be transparent and when I when And I talk in a minute about um about bias
Um so far the um legislators that have wrestled with this have opted I or leaned in towards the
Idea of transparency they believe disclosure is very important if you're going to use AI
At the hiring phase for example or in the employee relations investigation phase you need to tell the
Employee population that that's what's happening so that they can make an informed choice about
Whether they're going to participate um and so transparency seems to be something the legislators
Are leaning into and so I think frankly from my perspective um any organization that adopts this
Should lean into transparency and I know that's music to Deb Muller, CEO HR Acuity's ears given how much um transparency
Has been uh you know an important discussion topic for HR acuity over the years um the last one and
This is me just worrying about all of you because I represent individuals who get fired all the time
Is that if we lean into this too much the first is that we're potentially diluting the um the value
That we have built the institutional knowledge the experience the um the judgment calls that we've
Made over the years we're diluting the value of those skills um but most importantly we're
Diluting our perceived institutional value and you could be it could be a bit careful what you wish
For that the more reliance on the technology the more headcounts go down and and you're
Engineering yourselves out of jobs and potent potentially engineering out of the profession
Now I don't think the the profession is going to disappear altogether whether that be a need for
In-house investigators or outside investigators but uh I do believe this over time could be an
Existential threat um to headcounts and so I really do think we need to take it seriously um
And be cautious about when and where and how we're adopting this into our processes um so I think
We'll turn to bias now because that is the one that is top of mind for most people who do what
We do next slide great thank you um so I've broken this down um and there may be uh at first glance a
Redundancy here between anchoring and confirmation but I'll explain the difference anchoring in um is
A bias that comes up early in the process when you are really trying to lay out the the plan and the
Question is you know if you lay it down a baseline of what the issues are and what the potential
Um areas of contradiction or what the areas of inquiry are um do you get too wed to that or does
The AI um algorithm get too wed to that initial baseline such that it is n keeping the focus too
Narrow and not allowing for other possibilities of either witnesses or evidence to be considered
Um versus confirmation bias is when you're later in the process and you're doing your um your
Conclusions or your assessments of the evidence and weighing the evidence um are is the AI tool
Going to gravitate towards a certain pattern and that pattern is to confirm what certain baseline
Conclusions were and so they sound similar but they're not it's a it's about what stage
Of the process you have to worry about each of those biases clicking in um false confidence
Is just not quite frankly testing any of the information or suggestions or conclusions that the
Um algorithm may send to you um but the big one is is implicit bias and um research has shown that
The um certain AI algorithms um that are used for recruiting tools for example um have been
Shown to have a bias towards hiring white males as opposed to females um or minority candidates
And why is that algorithms look for patterns and they they gravitate towards patterns anything
That's anomalous gets kicked out and so this is a situation where the AI likes repetition the
Algorithms prefer um and gravitate towards things that um fit the pattern that it's determined
Through its al through its um algorithmic analysis and the World Economic Forum has
Identified implicit bias in AI as a global concern and as I referenced earlier the the legislation
That is coming up right now um that so far has touched on this subject mostly in the hiring space
Um has uh determined has already acknowledged that this this this tendency toward implicit bias is
Something that we should be looking out for and cautioning um and perhaps even prohibiting and so
Um Illinois and Maryland for example prohibit the use of AI in job interviews unless you go through
Certain disclosure and consent phases to obtain consent from the candidate um New York City has
Gone even further has those uh disclosure and consent requirements but also requires um bias
Audits to be done every two years on any tools that are used in the hiring space um and so those
Laws were are the are the first ones of their kind um there's no law that I was able to find
In doing my research for this presentation um that specifically touches or prohibits or curtails the
Use of AI in workplace investigations um but I do think these are instructive for us in terms of as
We go forward and create our own guard rails and regulations um but one thing that is a sort of you
Know ripped from the headlines and breaking news that I wanted to bring your attention to is that
Um the state of Texas has introduced a bill called the Texas Responsible AI Governance Act um it was
Introduced in the Texas legislature just uh a week and a half ago uh by a Republican representative
Um which I think is very interesting when you contrast the this proposed bill with the most
Recent one of the executive orders um on AI that was um put forward and um and signed last week um
It seems like the um the federal government at least um is let's take off all the guard rails
And let's move very quickly so that we stay keep our competitive edge on AI um but this te this
Proposed Texas law which the acronym is is t r ai ga so I'm going to call it traasia from now on
Um to make it easy for us um Traasia is um is much more progressive in many ways than the the
The statutes that I um previously referenced um because it actually prohibits AI um if um
Certain the use of certain AI tools um where discrimination is um is a is a susceptibility
Um and that employers have to use reasonable care to prevent algorithm discrimination so it
Puts the onus on employers and on the AI creators um to be the um the gatekeepers on whether or not
Discrimination is um creeping into this process um and uh it does um propose that there would be
A task force that would do discrimination or um or bias audits um to ensure that the technologies
Um are not um are not employing um bias or or fostering bias um it also defines what
Is considered a consequential decision um where AI is um is prohibited from being used unless there's
Full disclosure and those consequential decisions include um employment or employment opportunity
Decisions so I really encourage you to take a look at the Texas statute i'm not going to go
Much further and talk about it right now because we have so much else to cover um but it is I think
Um in many ways it's putting up stronger guard rails than any of of the other laws that are
Currently on the books or that have been proposed with the exception of a law in California that was
Um that was rejected last year so um all I I think Rebecca Trotsky, Chief People Officer at HR Acuity's note in the chat is ve is
Very well taken this is moving incredibly rapidly and I think we're going to see each state um take
Its own hand and it's make its own decisions on uh whether this is going to be a state that wants to
Allow AI with no guard rails or if if the states are going to to be putting up more guard rails
Um because the executive order that was signed last week um suggests that there will be more
Discussion on the topic over the next six months and so I don't think the federal government is
In any position right now to adopt any specific regulations and I and I don't say that as that's
Not a political comment that's just um I think they're still in an assessment phase like many
Other legislators are um but the Texas law models itself by the way on the European Union AI law
Um which is is vertical and allows for each country to adopt its own specific restrictions so
I think that's where our our country is right now is that we're in a vertical model where the feds
Are not taking a very strong stance on this yet they're still in the assessment phase so states
Are filling in with their own ideas Deb Muller, CEO HR Acuity yeah I just wanted to point out I love your list here but
You flew over the false confidence one and I know you have a lot to say to I have a lot to say on
That one because I do think as employee relations professionals we bring something special to the
Table that AI has yet to prove and that sort of you use the word curiosity it's judgment it's
Understanding the context of things and that's what worries me you know people use AI they become
So reliant on it i always tell people well how you know how many of you have actually read those
Clickthroughs that you know you get before that that you all those things that you agree to and I
Fear that you know I see these systems put things in that sort of generate and they say well that's
Okay well have you checked something saying that you've reviewed it as a human and I'm like yeah
Really really are you going to do that every time and so I just I think that's one we really need to
Pay attention to i would agree and and preient as always is is Deb Muller, CEO HR Acuity Muller, CEO HR Acuity um I was going to hit on
It really hard later on okay good good wait I'm going to do because you're going to do better
Than me so I'll let you it's one of those things where I I do think you know um if you're using
The algorithm to come up with original thoughts right um conclusions or synthesize which we'll
Get to in a few minutes i I think that's where the danger lies versus using the tool as a verifier
Of ideas you've already had yourself right to make sure you didn't miss anything and that I
Mean that's one of the key takeaways I would like everyone to have today is um you know I again I
Don't think these I I don't think these should be verboten but at the same time um don't let
It uh supplant or step in for what you bring to the table um I think using it to doublech
Checkck yourself or using it to verify that you're that you've you know you haven't missed anything
Because we're so busy and our plates are so full then that is where I think it can come in handy
Um and help us so great well I'm gonna let you go on then because I know you fine no no no but it's
It's absolutely true and and I think that is the that is a bias that is inherent at every phase
Of this of the the life cycle um but particularly when you get to where you're applying the judgment
And the institutional knowledge and all of that to what you've collected awesome okay so next slide
So we're going to run through each stage of the ER life cycle um I I I'm sure I've missed something
Along the way but I tried to you know sort of stop at each of the main inflection points the
Most material inflection points and talk about both the upsides and the cautions so the first
Stage is complaint intake right um that it all it doesn't happen unless we start with a complaint
And where that comes from is obviously up to each of your individual mechanisms
Um whether it is you know an anonymous portal or whether it was an HR complaint
Um that was made to you know personto person a written complaint whatever um so the question
Is what what can AI do for you in this space and it can certainly do transcription and and
Do intake notes of hotline accounts um categorize the complaints and the nature of the allegations
Identify potential policy violations um there's a number of things that the the the AI can do
For you in this space i think where you have to be concerned is is with what I said earlier the
Anchoring bias where again if you're using the bot and you're adopting its conclusions or its summary
Or all of it blindly without looking at at the raw data or at least getting your eyes over the raw
Source material then it is it is possible that the bot has started you on too narrow of a path um or
Has mischaracterized what the complaint is really all about and that last one you know should send
Shivers up all of our spines right is that the the bot got it wrong and we didn't second guessess the
Bot and so we go down the wrong path from the beginning and get things wrong or miss things
That were material and so um I think using the AI technology at this stage um is relatively benign
So long as you're not using it blindly um and you are um putting your eyes over everything um
Okay so the next phase in investigation planning and prep um there are some tools in this space um
Uh the one that really I think most people might be most familiar with is um all voices um and uh
This is you know using the algorithms to analyze complaints draft an investigation plan from those
Basic inputs regarding the nature of the issues um coming up with the witness list the order
Um and what other other material needs to be collected whether evidence needs to be collected
Um prioritizing the investigation steps based on identified risks and sense of urgency those
Are more sophisticated um applications but they the tools do allow for that um
Anchoring bias again there's a susceptibility for that here um obviously and um I think I I
Will just say point blank that um I think that this would be considered um you know a uh this
Would be considered an inflection point in the investigation life cycle where decision making
Is it there's consequential decision-m to use the words from Traasia um is happening to determine
What the course of the investigation is going to be and what the potential outcome is going to
Be and so I think this is really um a a a moment in time where you should pause and very carefully
Consider whether you want um the algorithm or the bot to do your work for you um I say that because
You know um anchoring bias comes in um but also um do you want to have to defend um to someone
Like me in a deposition down the road that you allowed an algorithm to create the investigation
Plan decide what witnesses would be spoken to decide what documents would be obtained do you
Want to have to defend that should everything go ary and there be litigation um and you know
Should this formative step be left to an algorithm that's either learned from a closed data set or an
Open data set but hasn't learned from years of experience and knowledge of the institution and
Applied judgment um like all of you bring to the table and so I I'm not a fan to put it bluntly I'm
Not a fan of using any AI um in this part of the process um I think it's just too important um so
Uh I think that there are places where you could try to you could use it to verify your work to
Make sure you're not missing anything but if you are using it for original drafting um and
Keep in mind um you are making evidence with every choice that you make at every stage of
The investigation process um you will have to explain why you let the algorithm create your
Investigation plan from scratch um rather than you created it and used you used a bot to verify it
Um I see that some people are agreeing with me in the chat and so I appreciate that thank you
Um so moving on the next phase is uh witness interviews um and other evidence gathering and
Um so some of the products in this space that I think people are most familiar with are case text
Um and uh particularly when we talk about transcription um uh fireflies.ai AI and Rev
Or some of the technologies in this space um and so what I would say is that I have a mixed opinion
About what what the tools can do for you and and whether tools can be helpful in this space um as
You can see from the uses and and upside um part of the slide I think um you know there's the whole
Gamut from sample questions um to um transcribing witness interviews in real time and preparing
A summary for you um and to using the tool to analyze and highlight contradictions in witness
Statements either in real time or after the fact and we'll get to after the fact in a minute but
Um then there's tools that will uh offer you questions in the midst of an a witness interview
So it'll be sort of attached and working alongside of you suggesting questions to you as you're doing
Um the interview in real time um versus there's the tools that will actually again assess the
Witness um based on biometric feedback and cadence and um and you know speech patterns and uh visual
Cues uh does the person turn red like there's there's those tools that will assess credibility
In real time based on um visual verbal um feedback i have strong feelings about all of them um what
I would say is that um the um the the ones that offer you sample questions before you start your
Your interviews and things I think those are great again so long as it's not an original
Drafter and you're using it as a double check on your own work um but um the ones that are in real
Time um offering you questions um that could be disruptive um first of all and distracting
But also um depending on you know how much you have disclosed this to the witness who's being
Interviewed this could make them very nervous and it could um alter the the way that the witness
Shows up in the interview if they know that not only are you using just a transcription tool
To help you take notes but you're actually using a tool that is um responding or reacting to the
Way that they answer questions and offering you new suggestions that you didn't come up with
Yourself or you want to use that instead of your own thoughts of follow-up questions um so I I have
I have really um strong feelings that the more you are leaning into these tools to do the credibility
Assessments um I think this is where implicit bias confirmation bias all of the bad things
That we worry about um can creep in um because as we talked about earlier the facial recognition and
Biometric tools are fraught with a potential for bias again because they're looking for patterns
They're looking for the norm and so if the show if the witness shows up and doesn't act like what the
Algorithm thinks it should act like or sound like then it's going to flag it i don't think that's
Fair because there are a lot of people who have different reasons for not acting normal or not
Acting how the bot should think it should act in a witness interview whether that be nervousness
Whether that be neurode divergence whether that be speech impediments whether that be hearing
Impairments whether that be ner just plain old nervousness and anxiety um so I think that this is
Really fraught and once again Treasia identifies um biome the collection of bio biometric feedback
For the purpose of making employment decisions to be a consequential decision um in the employment
World that should be either prohibited or closely monitored and so I I'm not just the only opinion
On this i mean I never thought I would say I agree with the Texas legislature on this one but I do um
And so I think that this is something that we have to be really careful about um generally speaking
I think the transcription is fine but again if you're relying on it blindly without taking a
Look at it and making sure that the transcription is accurate um you are taking a huge risk and I
Will give you a quick cautionary tale i received a a call from a potential client um who had
Participated in an investigation they were not the subject of it they were not the complainant um but
They participated in it and they were asked to um then they were presented with a written statement
Of um summarizing what their testimony was in the interview and it was completely wrong and they
Wanted to correct all of the um inaccuracies and they were told no you can't do that
Um this was collected with technology and you know we we perceive it to be accurate and they felt
That somehow their rights were being violated by not being allowed to correct their own statement
Now I know none of you would disallow someone from correcting their statement but it just goes to
Show that you know this was a situation where it was fraught with inaccuracies and the technology
Had done the transcription and so um I just say it as a cautionary tale of these things do happen
And I think you may be adding more work to your plate if you are having to um explain or deal with
Things that are unintended consequences of the use of some of these technologies um so instead
Of you know making your lives easier I think it could um I think it could make your lives harder i
See in the chat someone asked "How could it be so wrong?" Um just to be clear this um uh this person
This potential client was um had a very heavy accent um and the transcription tool apparently
Couldn't understand their accent so there you go um so turning to the next slide um because I know
We're I'm being conscious of our time here and I want to leave time for questions at the end so the
Next phase is your case summarization synthesis and report drafting and I know that's a lot that's
Actually three stages in one but um I wanted to you know for the sake of brevity combine them all
Together um I think the the tool that we're all most familiar with in this space um is uh Case IQ
And again I'm not bashing not bashing the vendor not bashing the tool at all um and uh so I it's
Just I think that's the one that most people are familiar with and I don't know if you know anyone
Has positive experiences with Case IQ um but if you have that's terrific um I I would say
Um I am aware of some negative experiences with Case IQ as well but again um it's just the idea
That the tool can help you by summarizing witness interviews other supporting doc documentation
It can actually synthesize the evidence using preconfigured templates that you all can set up
Yourselves so I I see where that's an advantage if you have a way of collecting and sifting and
Sorting um evidence based on um standards that you and your team have developed and and templates
That you all like to use I see where this is a huge advantage um but when where the algorithm
Goes a little further is that it basically takes and it does all that sifting and sorting and
Leads to a preliminary set of conclusions um and I'm concerned about that um uh where it goes it
Can go even further is it prepares you know the first draft of the investigation reports um or
It certain other tools can take your draft and off to offer revisions or draft certain language spot
Issues with your tone where places where you might not be as neutral as you should probably be so
There's lots of different functionality that can can happen under some of these tools depending on
Whether you're asking it to do the initial draft or whether you're feeding it a draft and asking it
To do some double-checking or some verification either for synthesis or for um tone or or or
Grammatical errors or inconsistencies and so as I said before um you just take a little sip of
Water using the tool to verify um original thoughts that you yourself have had
I see no issue with so long as you are comfortable with the idea that if you somehow have reached
Certain conclusions but you change th those conclusions based on what the algorithm tells
You again you're making evidence and you will have to justify that change of conclusions or those
Alterations to your investigation um uh report and so I but I think that's much more defensible
Then the the report was drafted originally by the algorithm and then you went in and
Tailored it or retoled it based on either things that you saw that were inaccurate
Or things that were not as amplified or as or consistent with the conclusions that you reached
Um from your own judgment um I think saying allowing the bot to do the original work is
Really dangerous um in in terms of being able to defend the validity of the overall investigation
Report um and I think again it depends on how much you're letting it summarize what you're letting
It summarize from and then what are you doing with those summaries and how much of your own
Judgment your own knowledge your own impressions your own factf finding from your notes and and
Because you've been doing the investigation all along how much of that are you applying as
Original thought processes versus how much are you relying on the algorithm and I think particularly
Until we all get to some industry standards on this you're running the risk that if the case
Goes sideways and you end up in litigation you're going to be very vulnerable to someone in my shoes
Um sitting across the table from you asking you questions about why you seated certain judgments
Why you reached certain conclusions or was it the bot that reached the conclusions the bot can't sit
There and answer my questions only you can and so if you have seated your your judgment and the
Most sort of empirical parts of your job in my view to the algorithm you're going to have some
Explaining to do for that um and so I think this is and and speaking you know more existentially
About headcount and your jobs being safe and the profession being safe I think the question becomes
You know um is this the kind of non-administrative work that you should still be doing versus seeding
To the technology um because I think dividing the your your plate into What is administrative
Work that that hopefully technology can assist and aid and speed up and make more efficient for
You versus the non-administrative work that should be entirely your province is what needs to happen
Here and I assume all of you that are working and and working this through already and adopting
These technologies are thinking about it um and so um I see that someone put in the chat that you
Know the new Chinese technology provides a chain of reasoning um I still don't think that's going
To hold up in litigation um because its chain of reasoning came from data sets that are either
Internal or external it did not come from the a data set that is based on institutional knowledge
Of this particular organization and judgment calls that only humans are qualified to make um and I my
View is if you say "Oh well this data set this data set is ours." And so um it's it's working
Off of our own reasoning then I hope you be you are prepared to call someone like me when you get
Terminated um because you're basically going to be engineering yourselves out of jobs um and I don't
Mean to sound so alarmist but I believe that's actually true um because I had a friend call
Me last week and she was downsized because her company told her that AI could do her job instead
Of her which is absolutely not correct um in her opinion and mine um but you know it happened and
So I do think this is a vulnerability that we all have to look out for and it's not just about
Protecting our own jobs it's about protecting the validity of the discipline that we have spent a
Lifetime developing um but also helping employees in a way that is still very humane um and is still
Um helping employers make smart decisions um to keep the workforce you know happy and healthy and
We have a job to do and I think the more that we seed it to the technology um the worse off we're
Going to be and and that is you know that's my humble opinion but and you can agree or disagree
With me and I I I'm I'm perfectly comfortable with that so um moving to the last slide uh without all
The doom and gloom um I do have some recommended best practices for all of you to adopt and most
Of these you you would already you know think of yourselves i just wanted to capture them all in
One place for you um developing a task force and you know considering the questions that you should
Um identifying specific case types that you think this is you know something that you want to beta
Test and scenarios where this will work for you i think there's a huge difference between
Certain types of investigations where this can be extremely helpful versus the more complex ones
That you know we all ha know you know sort of have it's it's the it's the octopus investigation that
Has eight tentacles and you know it's going to lead to to this outcome or have the these ripple
Effects in this part of the organization those probably are not well suited to any um insertion
Of AI unless we're just talking about basic transcription and things like this but um but
Then you create a beta test set and go through an experimental phase and test and and and talk about
Um how it's working for you before you adopt it on a large scale you really have to in stage in
Number four you have to really put your vendor through their paces about what they're doing with
Your data um if they're creating a closed data set for your for your organization that's great
But they still have the data you know within their tool and so what steps do they take to
Protect it from data breaches and cyber crime and all of those important things so put them through
As many of the the questions as you yourselves um go through to ensure that it's it's insulated
From cyber security or pardon me pardon me from incursions um from cyber crime um uh consider a
Closed data set is the only way to go um and then the last one developing the communication plan
Um and deciding how much transparency um you want to um have both uh you know in an internal level
Um versus an ex in an external level um and you know what is the messaging going to be for why
You're adopting this technology and what being clear about what the pros and cons are but um
But also I think allowing people to opt out um for example if you're adopting a tool that is going
To be a companion while you're doing a witness interview um not having any negative consequences
For any witness that doesn't want to consent to the tool um is really important so that you're not
Accused of any sort of retaliation in the way you're conducting your um your investigations
Lori Deem, Hughes Socol Piers Resnick & Dym, Ltd. this has been great i don't know if you've been reading all the comments on the side in the
Chat can't I can't a lot of we'll make sure you get a we'll make sure we'll make sure you get
A copy of the sort of what people are saying because people are just sharing some of their
Own experiences with AI or questioning it really great discussion this is so thoughtful we do have
About 10 minutes for questions if there is some we had some slides to talk about what HR cut is
Doing for AI I don't want to go through those I mean we'll show all over here I will just tell
You that we reach out to experts like Lori Deem, Hughes Socol Piers Resnick & Dym, Ltd. to talk about it we really are taking a very thoughtful
And responsible approach you know We do have Oliver some of you familiar with he's our AI
Companion or I'm sorry ER companion um to serve up employee relations thought leadership to help
With our analytics looking at that closed data set different ways that we're working and we're trying
A lot of things and by the way we've tried a lot of things and then stopped them and said "No we
Don't like those." I remember putting in some data about an investigation into um one of our
Trials and it didn't pick up a very important nuance detail in that investigation about what
Someone had eaten at dinner which could have been verified and they just were like they went to
Dinner like it was you know those are the details we know in investigations that are so critical to
Help determining credibility so um I'm going to open up to see if there's some questions here
Um that anybody would like to ask Rebecca Trotsky, Chief People Officer at HR Acuity do you have any questions well you can join us too if
You want hi hi everybody knows Rebecca Trotsky, Chief People Officer at HR Acuity she's our chief people officer yeah we had one that I think
Was back a couple of minutes ago um Daniel was asking "What about any prompts or data sets that
You provide before the input that you're asking AI to analyze like would that change it?" like
If you're really guiding it I think it's still risky but um so let me make sure I understand the
Question so you've got some um basic information that you're feeding into the algorithm and you're
Asking it to prompt you for questions or for analyze to analyze that is what Daniel is saying
But Daniel feel free to type in uh any clarifying points there um I think it's all to be taken with
A grain of salt if I like Yeah and and and again I I'm I see no issue with this being a supplement
Or or sort of a verifier versus an originator those are my words it's not anything in the law
It's not but I was trying to you know think how how how what am I comfortable with right lawyer
And I think there's a big difference between if this is the originator of some of these crucial
Stages of the process versus if it's a verifier or if it is some uh your last double your double
Check before you move on to the next phase right so if for example you're in the planning phase and
You've already got your investigation plan mapped out and you just want to run it through the tool
To say you know am I missing anything or if you're coming up with your witness questions um and you
Want to run it through the tool to make sure you haven't missed anything based on some basic um you
Know uh prompts that you've given it on the issues at play in the investigation i see no problem with
That because you know it is it is basically supplementing what you've already brought to
The table and say you know I just wanted to make sure and that goes to the thoroughess of
An investigation right I mean we have some some words we live by prompt effective and thorough
Right and under thorough if you're using the tool to make sure you didn't miss anything I think
That is perfectly defensible yeah yeah it's the originator of all the thoughts that's that's the
Distinction yeah that's where you run the risk that you're second guessed by someone like me
Or by your boss or your CEO or whoever doesn't think this is a good idea wait a minute wait a
Minute why do we have you if you ask the bot to come up with the questions and you used those in
The interview without ever adding anything else to the mix right okay that makes you know we we try
To use the approach we still take the approach of what's a good investigation and how can we
Use technology to really you still do a great investigation sometimes faster sometimes more
Thorough or be able to do things a different time and then we think about gee just like any other
Technology is AI one of the technologies that can help us achieve that as opposed to oh great here's
This AI we now have to push it into our system because everybody's talking about it that's that's
Where you're going to get into trouble you know I see systems where they're taking in input about
Like complaints someone will write in everything that'll happen and then they'll say "Oh that's
Harassment." And as an employer I never want a system putting words legal terminology such as
That into the hands of my employees what happened we'll take care of it let's not categorize it as
Legal something that could be Well exactly and it goes to which I think was one of the big re
You know one of the big revelations that you know or one of the things I just want to drive home is
That at every stage of the of the continuum you're making evidence you're making evidence you're not
Just you're not just collecting and sorting and analyzing evidence you're making evidence that
Can either be used to the company's advantage or to its disadvantage depending on you know whether
It gets in front of someone like me and so if the algorithm has assigned legal terminology
To something that is really you know baseline you know bullying behavior and bullying isn't
Illegal yet in some in most places you know but it's called it harassment or it's called it
Hostile work environment do you want that do you want a record made of that and that you carried
I I don't that you carried it forward without correcting the terminology too right someone did
Ask um happy for it clearly but yes she is that's right let's remember Lor's role here this is the
Only time you want to be seeing her by the way or at the round table exactly then you know it's
Okay or sending me referrals i'm okay with that too that's true i think a lot of people in our
Community have experience with transcription software that they're using internally
Um and someone was asking "Are there any specific risks associated with that?" Um I think you've
Touched on that yeah I would I would just say if you're not checking its accuracy right that
Goes to that that PC that potential client that called me is that it it was pretty clear that no
One checked it for accuracy and they just adopted what the transcription tool had done um and to be
Clear I mean I I found that person to not to be so heavily accented that they were un that I couldn't
Understand them um but again the algorithms are used to a certain they're they're used to
Patterns they're used to the norm they're not used to anomalies and so you know this may be a place
Too where if you know your employee population and you know that you know this particular witness
Either has a speech impediment or has an accent or whatever you may be skeptical about using the
Transcription tool because it might spit out a bunch of anomalies and it's or it might spit
Out a bunch of junk quite frankly that's only going to make your life harder um um I saw that
Someone asked about consent and everything and and that is a big concept of all the legislators
That have dealt with this so far is that the prohibitions are not absolute they but they are
Saying disclosure and consent is really important and so I just would want you to establish a set of
Protocols that you disclose and then um if someone does not consent to the the tool being used during
Their interview or whatever that they are treated just the same as every other witness um they're
Not they're that is not a notation towards their credibility right and that is not something that
Is used to in any way distinguish the value of their testimony um simply because they opted out
Um because otherwise you know then you're you're leaving you're leaving breadcrumbs of potential
Retaliation or breadcrumbs of you didn't find them credible and so it could undercut the validity of
The entire investigation um I definitely want you to read the comments when you get a chance later
Lori Deem, Hughes Socol Piers Resnick & Dym, Ltd. because as usual our community is very wise so I encourage everyone to keep the conversation
Going in Empower everybody join Empower and keep keep the chat alive uh I think we all have a lot
To learn in real time together as this is changing so fast yeah I know I spoke a mile
A minute too i'm sorry I went so fast but I had a lot it was great and to our HRQD clients that
Are on the phone please join us on February 5th so you'll have some special time with Lori Deem, Hughes Socol Piers Resnick & Dym, Ltd. bring all
Those questions think about it we can have a real good discussion about this um to everybody else
Keep the conversation as as um Rebecca Trotsky, Chief People Officer at HR Acuity said in empower if you want to learn more about HR cutie
We'd love to share more about it um but this is as always thoughtprovoking and just so on the money
As far as what's happening today and what we're all thinking about so just a great conversation
And we're going to continue it because it's going to evolve right just because this is where it is
It doesn't mean it's not going to change doesn't mean this is all we do but you're getting a lot of
Love Lori Deem, Hughes Socol Piers Resnick & Dym, Ltd. here so um I'm not surprised thank you everyone and I really appreciate your attention
And your participation and I I wish I could answer all the questions i know there was one about
Multiple languages i mean there's so much I don't I we can't get Well if we can pick some out maybe
Get a response put it in Empower so we'll see how we can we can get to all of them but thanks
Everybody for joining us um as always come back for more to get on Empower to learn what's next
Thank you so much again Lori Deem, Hughes Socol Piers Resnick & Dym, Ltd. thank you Rebecca Trotsky, Chief People Officer at HR Acuity for monitoring the chat queen wave there you go
That's right and um we'll see everybody soon all right have a good afternoon bye thank you