Employee Survival Guide® - S6: Ep133: The Hidden Dangers of Using AI to Predict Your Employment Discrimination Case

Starting point is 00:00:00 Hey, it's Mark here, and welcome to the next edition of the Employee Survival Guide, where I tell you, as always, what your employer does definitely not want you to know about, and a lot more. Hey, it's Mark, and welcome back to an edition of the Employee's Survival Guide. Today's topic is the hidden dangers of using AI to predict your employment discrimination case. In today's world, employees can turn to artificial intelligence, AI, for almost anything, even legal advice. Some employees are beginning to use AI tools to, quote-unquote, predict whether they have in a strong employment discrimination case. Employees are tempted with the immediate feedback that AI provides in analyzing their legal cases. We have recently seen employees who conducted their own legal research and put together what they've been to believe are the correct legal citations,

Starting point is 00:00:59 mostly statutes in prominent U.S. Supreme Court decisions, along with their own legal analysis as to why they have a case of employment discrimination and retaliation. This is their pitch to implement lawyers, like myself, to review their cases or their actual, or they're actually filing it with the state and federal and city agencies regarding their claims of employment discrimination, hostile work environment, and retaliation. this came up, this topic came up because I receive quite a few of these type of emails where people are trying to pitch a story to me and they, you know, no fault of their own. I mean, AI is out there. It's, you know, it's new and novel and employers are using, of course, but, you know, people have access to a Google notebook or chat GDP or. or something. And the technology itself is relatively new and it's based upon, you know,

Starting point is 00:02:03 what you fed into the system. And so when I read these emails and they give me the cut and paste of what their research was. And we all know what this looks like. It's like this chat or this AI type of production of work product that it looks like. It's usually a list or that's kind of stale. It's not very emotional. It's just a matter of fact, whatever. But it's only based upon what the AI device has captured in its learning. And the funny thing about this topic is that the AI devices, these algorithms, can pick up, you know, information related to agency websites and devour that. But the case law material, the case decisions from our courts, state courts, federal courts, they're not readily accessible and they're behind paywall. where you have to go in and access it.

Starting point is 00:02:58 Now, there are cases reported out there that there are various websites that put it out. But the vast majority of case decisions are locked behind paywalls for websites called, like, you know, Westlaw and Lexis. And so the AI devices that the employees are accessing don't have that wealth of depth. So that information is missing from its analysis. Now, this is a technology in infancy, so you can imagine that if employees are putting together their case analysis today, it might get more robust as the technology increases, maybe what they feed into it. I would love to see the AI devices, you know, like a chat GDP, have all of the case material decisions going back, let's say just give it 10 years. I mean, these devices can learn, machine learn very, very quickly. So why would you put that information into the AI device so the employees could access it?

Starting point is 00:04:00 Because the employees would basically be able to read public court decisions because courts are public and read these decisions and decide for themselves if they have, you know, a case or not. Remember, lawyers are not the only parties that have an angle or, you know, the access. to the law, the, you know, everybody has access to the law. And at least that's my opinion. And that's why I try to put the slant I do on these podcast episodes. I, you know, I give you case decisions. You can hear about it. So the, so having employees access and case decisions is really uber important to leveling the, you know, the playing field between employers and employees, which is not. not even, which is uneven. You know, the whole at-will debate you hear about me raise all the time. So back to the point of employees trying to figure out their cases before they confirm a lawyer or file before an agency and they're doing their AI research. I'm not saying don't do this.

Starting point is 00:05:07 I'm saying just do this with the eye wide open about what you're looking at. And, you know, it's okay to begin to learn like a lawyer. And this podcast is really designed to kind of tell you. some pitfalls, but also tell you, you know, approach, how do you approach it to do it better? You know, how do you take your AI research and create it in such a way that it's more accurate than it wasn't? So first is, you know, read. Now, I got a lot of material on my website and a lot of podcasts, you know, talk about it.

Starting point is 00:05:41 For example, hostile at work environment. Everybody loves that topic on my website and the podcast. And so there's a lot of information about that. but how do you interpret a hostile work environment with respect to the you know a fact pattern that you're currently going through so what I encourage you to do is this why don't you write out your fact pattern and put it in long form you know your narrative from A to Z chronological order what happened what happened next who knew about it whatever and write it out you might want to not include names of the employer and use fictional name of characters, because you're putting this information publicly out there into a domain AI device that's learning it, and you have confidentiality provisions of your, when you sign up unemployment, so you would be careful what you're putting out there. I mean, it's like the black hole, this AI device.

Starting point is 00:06:36 So just caution you, just choose write a narrative of facts and then put it into the algorithm, the chat GDP, and ask it to assess based upon, let's say, you live in New York City? And you say AI, chat GDP, once you assess it under New York City law, human rights law, New York State Human Rights Law, and Title VII, a 1964 Civil Rights Act, in New York State. And let's see how that chat GDP device pushes out the outcome. Now, we can't trust what it's going to say, but hopefully if you're using your fact pattern, and you might get a closer vantage point to illegality. Sometimes when I do the searches on chat GDP,

Starting point is 00:07:26 I'll get warnings that they're not on a lawyer and they can't make legal or give legal advice. You might see that as well. But play around with it, and you might be able to come very close to, let's say, your fact pattern directing you to the conclusion that you have a hostile work environment. And everybody knows what a hostile work environment is.

Starting point is 00:07:45 It's, you know, a pervasive use of discriminatory comments or, you know, comparison of you versus others that are given, you've received more favorable treatment. It's typically in a sexual connotation or sometimes it's in a racial connotation where you have, like, you know, pictures of nooses for a racial case or lightning bolts for the KKK or some pervasive, hostile, like, extreme situation, which is, and. And maybe the computer can spit out that assessment for you. So to go through that exercise, but again, to learn more, if you spend the time, you can figure out that there's information out there. And I'm going to tell you this. You know, the next chat GDP search should be give me notable, let's say, New York's Southern District of New York cases in the last five years involving hostile work environment related to sex. and see what those decisions come up with. And let's say you get five, six decisions.

Starting point is 00:08:49 And you push those case names back into a Google search and see if you can come across like a Cornell decision. They have a website that has case decisions. Justia is another site that has, you know, PDFs. You can read the actual decision. But use the devices, the search in a way that you can use ChatTP to identify cases. You can use, you know, a variety of sources to identify cases. cases on sexual or hostile environment in the Southern District of New York. It's a federal court

Starting point is 00:09:20 and see if you can find the cases themselves to read through them. What you're trying to do here is read through the narrative of fact in the decision, but then also look at the court's analysis of that. And that's where I really want to bring your attention. What's wrong with the AI use by employees today is that the employees don't have any understanding of the analysis as it relates to, you know, being a lawyer and giving the assessment. Now, I'm not saying that employees have to become, you know, quick off-the-cuff attorneys to identify their cases. It's much simpler than that. I think you have the ability to look at, here's what a case decision is from a judge and says, here's the law I'm applying to this narrative of this case decision you just

Starting point is 00:10:08 found using research. And you can see how the judge moves through that analysis using the fact and then applying the law to the fact to establish the conclusion. Well, there you have it. You've just gone to law school. You've learned what the facts are. You've learned the law part of it. And you've learned the analysis of fact and law. That's called issue spotting.

Starting point is 00:10:30 Or I don't want to give anything to the law school. It's just looking at facts, look into law, seeing how the facts apply and how the law may apply. And it's a very generic way of looking at, you know, the strength, weakness of a case. Now, you would have to see a lot more of those cases to decide, well, do I have a case or not, or is it, how strong it is? I think you're better off writing a fact pattern and using your research saying, okay, I found a sexual harassment case with a hostile workman analysis by, you know, judge, you know, so-and-so, and I put that into my analysis. And maybe I'm going to search further because I want to find some more cases. And here's a trick. Once I start to find a

Starting point is 00:11:13 commonality of case decisions about the same thing in different court cases in the same district, let's say, the Southern District of New York, which I'm admitted to, I stop. And I realize I have the basic foundation of what sexual harassment, hostile, and work environment is for the Southern District. And you want to move further into the analysis of, and you look at possible other claims that might exist. And you use the case decision you're reading or researching to identify more cases. Now, I'll give you a sheet, okay? Employment discrimination cases fall into the protected category, okay, and it's age, sex, whatever, race, religion, national origin, disability, and, you know, if you're by and large, you're going to fall into one of those buckets

Starting point is 00:12:01 or retaliation or whistleblowing. And you want to do that search by those different categories of discrimination to find cases that are applicable to yours. Now, you're not going to find the exact case applicable on point, they call it. That takes a little bit deeper dive into the case law, spending hours trying to locate cases. But you're going to get a quick assessment using AI, using Google search, using Justia, the website, to locate cases to read. You have to read this stuff. Don't expect chat GDP to push out the analysis for you like we're used to because that's not the way it works. What are you missing? You're missing the subtleties that the law is. You're missing the subtleties to which an employment lawyer will give you, but I think you can come close.

Starting point is 00:12:47 I think you can educate yourself about the laws, because I've seen clients do this before AI got involved. I've seen clients go and do the research at law schools and law libraries, and they came pretty close to what the actual analysis is. So there's a lot of commonality of case claims that you can pick up very quickly to put in. I know that, chat GDP will push out, here's what sexual hostile work environment will mean, and you'll start to, you know, because you put it in several times, you get the same answer, that's not the case. If you actually read a court decision by doing your deep die research, you can actually figure out how the courts are, you know, laying out the elements of the claim for hostile

Starting point is 00:13:30 work environment. Then the next stage of that is, well, just step back and look at your fact pattern in the analysis and see, you know, are there inferences? in your fact pattern that support the possibility that you have a claim of hostile workman discrimination. We're looking for strong inferences. So we're going to take all. There's two types of evidence here. There's direct statements.

Starting point is 00:13:55 We don't like you because, you know, you're an F and whatever, and they start to do extreme things in the office and there's just hostility, whatever. And then there's, that's all direct statement stuff from a boss. And then you have this, and that's like 5% of the case. So it's out there, but it's smoking on the evidence, and it's not really what you're targeting. You're targeting circumstantial evidence. It's how you're treated differently than other people who are treated more favorably, who are the different category. So if it's sex, hostile work environment, you're looking at, and you're female, you're looking at someone who's a male who's treated better.

Starting point is 00:14:32 And you want to do this compare and contrast assessment in your own fact pattern looking for inferences of how they're treated differently. I mean, that's really where the part of, I want you to pick up on, you know, look at chat GDP, get your data, your information about what the law is, do some additional research to confirm you're correct, because AI is not perfect yet, get an understanding of working knowledge of what hostile work environment is, look at your fact pattern, and then begin to do your analysis. I think five things stand out, five circumstantial pieces of evidence point out of comparing contrast, and I was fired because I didn't receive the same treatment. they did. Let's not make it complicated, okay? Put your facts together. Do your research. What's going to happen to you is when you do your research and you spend the time reading like lawyers do in these cases or listening to a podcast about hostile work environment on my podcast, you're going to begin to become familiar, like with anything, the subject matter that you're working with. And you'll start to see the nuances of things. You'll start to see things pop up for you factually that you may want to put

Starting point is 00:15:39 back into your narrative. Spend some time. Don't just shotgun the approach of saying, you're a strat GDP. I'm going to put my information and bang, I'm sending that to the lawyer. Okay, I'm not kidding. That does happen. It irritates me. What I'm trying to say is you can figure out and come pretty darn close to what your case is if you go about this process of assessing what lawyers do. They ask people to write the fact pattern, write the narrative chronologically, don't provide conclusions, just state the facts, ma'am, and then do some research and understanding what this is. Because if you're going to ask a lawyer, if you're going to ask a lawyer to take a case on contingency, which is even worse, you want to be convincing. And if you're not convincing in your initial, you know, email, it's going to take about two seconds for me to realize it.

Starting point is 00:16:29 And I'm going to basically dispense with the, you know, I'm not going to write back to you. I'm just going to say that's not a case interest of spending my time on. If you're going to hire a lawyer on an hourly basis and you're throwing your own money at it, you know, you want to know that you're, you know, hiring an employment lawyer and you're spending your money wisely, there you become a collaborative effort with the employment attorney. And I've seen clients who are bright and they're pretty savvy and they can, you know, they work in a kind of a collaborative effort to push along a case and they understand it. And so you can age yourself in the process of understanding the legal service you're receiving and understand your case. But if you go about this aspect of the strategy of pushing things into chat GDP, it's going to be met with like false left and right red flags. People pick it up pretty quickly. Employers and their counsel can read it very quickly say, oh, that was obviously AI produced, etc.

Starting point is 00:17:31 So people are doing that, but here's the things to avoid. So get down on the nitty-gritty. And it's, you know, when you're creating your narrative and you're doing your research and you're, you know, going the extra mile to figure out what it is and it is not a sexual harassment, hostile environment, beware of the following issues, okay? AI oversimplifies the law. Implement discrimination is complex, fact-specific, and constantly evolving. Now, I told you kind of the basic primer of how to look at these cases in terms of your claims, because I'm doing that deliberately. I want to dumb it down because I want to make it more accessible to you. The law has a tendency to make it really complex, but I'm trying to, you know, make it easier to absorb.

Starting point is 00:18:17 And there are a lot of commonalities amongst claims. And you can only see that when you look at it long enough, experience it. So AI tends to be applied broad, rigid rules, missing exceptions or subtleties that I would understand as an employment lawyer. And they are exceptions that might make or break your case. I'll give me an example. So you have a claim. You are 365 days, 365 days since you were fired. And it's well, and you decided finally to do something about it.

Starting point is 00:18:55 What you don't know is that, you know, when you filed your USC charge, you were a little bit late because the statute of limitations says 300 days. So you wouldn't know that. So that's an exception. So just AI oversimplifies the law, so be very, very careful. Let's take a quick break. It's Mark Kim. We have a new product for you. It's called the Employees Survival Guide or Employees Survival.com.

Starting point is 00:19:25 And it's a site that you can obtain PDF products that I've created myself. It's spending too many hours, way too many, researching and writing about it, for example, the performance improvement plan or beating them. And the second one about negotiating severance negotiation agreements to the most important topics that we see in terms of the web traffic and podcast traffic we have. So check out Employeeservival.com and see if this can try to help you

Starting point is 00:19:51 and you don't need an attorney to use it. Thank you. Next thing is wrong predictions, wrong decisions. I start this off with the famous. set of cases that came out of the Southern District of New York, this involved lawyers. It's a true story. It was reported in the press. Two cases of lawyers who were before the federal judges in two separate cases, both had conducted AI research on legal cases. And the judge got a little bit upset in both cases and said, and they were sanctioned because the AI that they

Starting point is 00:20:33 were using, whatever that was, had made up case names and made up case decisional analysis, meaning made it up. I don't know what they were using, but both lawyers in both cases got, you know, reprimanded. And it's very embarrassing. The judges look at every single citation that we give to them because we're looking at the cases and saying this is supportive of our client's case. So likewise, I'm asking you to do the same thing when you do a research through chat. GDP, follow up and read the case.

Starting point is 00:21:05 You know, these lawyers in that case that I'm citing, the two cases, they didn't read the decisions that this research chat box had created for them. It's embarrassing, but it proves the point that even lawyers could do the same screw-up mistake, so don't do that. So, and that's an example of non-existing cases and non-existent case decision analysis. So AI isn't trained on your unique facts or the latest court rulings. That means it can give false confidence, quote, I will win the case or unnecessary discouragement. I don't have a case, leading you to make damaging choices.

Starting point is 00:21:46 So AI is in its infancy. Like I explained before, it doesn't have all the thousands and hundreds of thousands of case decisions across the country in its data bank because it's on a paywall. yeah you're like well that's unfair why is that why courts are open why aren't they why can't we access it well it's a larger question i think that we uh we should have access to all the case decisions in both state and federal courts um but maybe there's a reason why that's not that case right because more information is power more power you have the more damage you can do on any corporation so maybe that's the case um there's also westlaw and lexas who serve this provide the services and i pay you know a good dollar for that service of my lawyers myself.

Starting point is 00:22:32 The next item for what AI is not to be trusted is missed deadlines and lost rights. Like the example I gave you, if you come up with your, hey, I want to file a EOC case, 365 days after the adverse action meaning you got fired, you're too late. You've got to file your decision or your claim to exhaust your administrative remedies in 300 days or within 300 days. So EAS is missed claims because you didn't understand the filing requirements in terms of deadlines. I'll give you a basic primer 180 days and 300 days on employment discrimination cases, okay? Let's just follow that. So the adverse actions have to occur within that.

Starting point is 00:23:12 Most state and federal agencies work on what's called a work sharing agreement. And so you get the benefit of a 300-day window. And I would always encourage you to file the EOC first. and then have the EOC file the claim with the local state agency. So you get the borrowed, you get the 300-day window time period. The next item is the, I spoke about before, is when you create your written narrative and you put it into the chat GDP to figure it out, use generic names. Don't use company information that's identifying of the company. When you type your story into a public AI system, you expose sensitive details, names,

Starting point is 00:23:53 names, dates, medical history, you can't take it back. AI doesn't guarantee a privacy, and you sign most likely confidentiality agreements with your employers not to, you know, share the information with publicly. You're putting the information in the chat GDP or an AI device. You have disseminated information out there publicly. So be very careful because it's not about if, it's about when these systems and employees, that they can figure out, you know, who disclosed the information. So be generic with your names and company information and what you're talking about. So you can't, it can't be disclosed

Starting point is 00:24:34 in the narrative when you write it, before you submit it, what your company name is and who the players are. The next item on the, you know, what chat GDP or AI devices can't do for it. They can't provide strategy or advocacy. AI can identify discrimination, but it can't file in a U.S.C. case. You need to have a working knowledge of the EOC process, which I'll basically give it to you. Go to the EOC.gov, grab the form 5, fill it out, and notarize it, say see attached affidavit, write your fact pattern, get it notarized, and then submit that. That's your filing of the EOC charge. Anything else beyond that, it's like leave the agency to figure it out, you know, how to deal with it, but generally they will request mediation and you want to submit to

Starting point is 00:25:20 that. They can't negotiate with your employer. Well, you need somebody to do that for you. An employment lawyer can do that. I have to encourage people to negotiate directly with their employers, and people do it and successfully do it. It's just simply, you know, you get your severance package, and they say, no, we're not going to revise that. They give it to you in a PDF, and it's, you know, it's intentional. And you basically say, well, you know, here's my fact pattern. I have claims here, and I'm going to try to leverage this and push on you, you know, make believe to the employer. that you have an attorney. You don't have to disclose the name of your attorney to your employer. You can just, you know, if you go through this process I've described, you can come down to a very professionally written thing on your own. You may not just use your affidavit with a form five charge affidavit to it, notarize it. You can convince your employer because the facts in the affidavit are the most important. It's not what the lawyer is doing. It's not what I'm writing about. It's what the client says in the fact pattern that's damaging to the employer. And maybe just, you know, not disclosing you have an employment attorney and just writing

Starting point is 00:26:26 in a very cohesive and methodical and detailed format from A to Z chronologically speaking about what the claims were, I've seen clients negotiate for money and close out a deal without having to hire an attorney. And I love that. Because law is, you know, it should be free and open. Why not? You know, before there were lawyers, there were just, you know, the law. So, you know, lawyers like to curb the market.

Starting point is 00:26:53 I'm like, I'm saying enough for the guardrails, let's, you know, open access to everybody. And so you can negotiate with your employer if you try, but just you have to basically look at what you're trying to do, think smart about it. The next item, they can't rep—the AI can't represent you in court. So at some jumping off point, you need to hire an employment lawyer. If you want to file a lawsuit, yes, the courts are set up. The federal courts are set up for you to file a pro se action. state courts the same way. And they will work for you to do that. It's a very simplified approach, but you can actually file your own lawsuit. But you don't want to avoid that

Starting point is 00:27:27 because filing means, you know, notoriety on Google. You can't ever take it back. It's always there. So be careful. So at some point, you're going to have to step off and hire an employment lawyer if you feel you really need to do that. So next item is hidden claims left all on the table. This one's easy. Employment lawyers have A variety of claims, in addition to employment claims, employment discrimination claims, I'm sorry, that they are looking at when they're looking at the same fact pattern. It's just by experience. And so if you don't use an attorney, you're not going to get that analysis to help your situation and you're going to leave the claim on the table. The employer will see it because they know about it.

Starting point is 00:28:08 The employers know what they do. You know, if you don't clue into that aspect, they know exactly what they're doing. They want to see if you know. And if you're better at spotting the issue and seeing what happened, that gives you leverage. And that narrative can spell out that you do know what they did. That's what the narrative does. It has to do that. The other aspect of AI, whether it comes in your own individual research like this, but AI reinforces bias.

Starting point is 00:28:39 AI relies on historical case data. It may undervalue claims by women, minorities, or other groups who already face. systemic under reporting, the result, bad predictions rooted in the past injustices. Now, you know, AI, I don't know if it's smart enough to realize, you know, claims that case decisions occurred a long time ago, it's not, you know, whether it's using current information. I don't know how they train it, but you don't believe the presumption that they did train it correctly because you have no idea.

Starting point is 00:29:09 I mean, they, I don't know of a product that's out there yet to let's provide AI related efforts to case decisions to help employees like yourself. I don't think that exists. I'd love to create that to, you know, harden your skill set with knowledge based on cases. If you want to dive into it, you can, like I said before, you can research using chat GDP. You can go to Justia.com and find reported decisions. There are other sites that provided reported PF decisions for free of charge. But the AI reinforces bias issue, that's the whole argument that, you know, humans created the machine learning, gave it what its source data to absorb, but there's inherent bias built into what it's reading. The other part of a bias has to do with algorithmic interviewing. There's some recent cases we've talked about before where the programming itself, the actual coding, is.

Starting point is 00:30:14 is biased in some way. And there's some court decisions, some cases currently ongoing right now. Emotional blind spots. This issue has to do with, you know, if you're going to go all the way, you know, or at any extent with your legal case, it really is about the issue of, you know, handling your emotions. People don't understand this, and they get tripped up really easily, and I have to redirect them back to center. AI, when you're researching and developing your case, it gives you cold technical answers. I mean, it's not saying, sorry this happened to you. Now, I've seen other examples where AI has gotten more emotionally connected to the user, and that's kind of a development I'm seeing. I guess the more it knows you, it can get more predictable. It depends on what device or AI device you're using.

Starting point is 00:31:17 So you're trying to navigate the issue of your employment discrimination case with your employer, and you've got a lot of fear, anger, anxiety about what they're doing to you. The same goes when you hire me as an employment lawyer. It's very emotionally charged. I mean, you name it, I've seen it. I've seen great people go through the process. gracefully delegate to us to do something, manage it, and they understand, and they're managing, and they're managing expectations, they're communicating fine. I've seen then the

Starting point is 00:31:49 opposite continuum where people are just over-absorbed with their anxiety about what happened to them, their own personal issues. I mean, this truism that I know why you got fired when they interact with you over a period of time, or look at your cases, I can see why your employer or fired you. If you don't know that, that you may be exhibiting behaviors that tell others and you can't see it, I've seen it. I mean, this is like 28 years. I've seen exactly the behavior why people acted where they did and they got fired. So you got to look at the emotionality of what you're about to engage, what you're doing currently if you're still working. Take a hard look at it. Don't just assume like you're perfect and you're normal and, you know, everybody else is, you know, F and wrong and, you know, they got issues.

Starting point is 00:32:45 So it's something that needs to be checked and I try to draw people into the transactional analysis of their situation. Like, you know, okay, you have something happened to you. Yes, I know it's emotional, but you're going to dump it all down in your narrative. But when you come to the transaction, you know, using AI to research and help you research and present your kids. case, you want to do it in a very transactional mindset of, hey, I'm asking for, you know, a year's pay here. Okay. I'm using this piece of narrative that I wrote as leverage against the employer. And I'm doing some research here to help me pinpoint that, you know, I'm correct and they're incorrect about why, you know, what happened to me and see if you can influence them.

Starting point is 00:33:27 Now, I can't help this issue. This one issue is that if you show up at the table and there's no reference to who you're an attorney is, you might get called out. on it because the employer is expecting to see your attorney show up. And you have to, you know, you have to fluff this one. You have to say, well, I'm working with an attorney and, you know, and you're going to go through me directly. The employer is going to assume that you don't have an attorney. And they're going to alter their dynamics that they're negotiating with you based upon that. And I know that sucks, but employers do that. You have to figure out a way to make your narrative very, very convincing based on actual facts in your research about what's

Starting point is 00:34:07 taking place, you may get their attention, and they may want to bury that affidavit that you provided to them in exchange for a settlement of claims. So you're very powerful, and you have leverage to work with. Just slow down, take a hard look at what you're being offered in terms of your chat GDP production results and think, you know, transactionally about this. Take the motions out of it. If you're wanting more severance and you think you have a right to claim to do it on, take your time and research things.

Starting point is 00:34:47 Maybe, you know, there are law clinics from law schools. These folks have students with skills who can assess what you're doing, possibly help you, ghost write stuff for you. I've seen this done. I've seen a lot of stuff done. Go beyond just what GDP is given to you. The AI devices in its infancy, and you need to basically, you know, this is about you and your career and what's happening to you. So if you're going down that pipeline, that rabbit hole of, you know, using AI, this whole podcast was designed to make you say, wait a minute, stop, take a breath, look what you're using.

Starting point is 00:35:24 I recognize that it's in an infancy state. learn about cases in your jurisdiction. That's what lawyers do. You know, Supreme Court case decisions are available for all to see on the U.S. Supreme Court's website. Other case decisions come out of various kind of wonky websites like Justia, but the information is out there and read about these cases and begin to learn about how law is applied to your set of specific facts and maybe you might come out with what the possibilities are. You know, just could be a little further cheat. I'm not going to know the result of every single case that I proposition to an employer in terms of what's potentially might happen. You know, the case might just settle.

Starting point is 00:36:08 I never know. There's thousands of cases. I never know the result of what could have should have been of that case. That's the cheat. You don't really need to know that answer. What you do need to know is, what do your facts say? Pick at AI for a second. What do your facts say after you've spent the time learning about what?

Starting point is 00:36:26 what sexual harassment is and what hostile work environment is in the Southern District of New York under New York State law, New York City Code, by the way, the premier area to be in both New York City, Southern District, New York State, eh, meh. But New York City, definitely. And, you know, if you really do your research, you can be a powerful device for yourself in your negotiations with the employer. I've seen it done. And, you know, forget about the future of the case. What may happen in results of the, what a jury will do. It's not about that. It's about influencing your employer to pay you money before the lawsuit ever gets the light of day. So hopefully that answers something for you. You do have to have a set of facts. Those facts govern the entirety of the case. You know, take your time. All the information is there. You've witnessed things and, you know, put it together. Make it compelling. But don't make it this drama-infused, you know, thing of what you watch on TV. It's just, matter of fact, to say the facts, A through Z, chronologically speaking, quote people what they said to you, you know, and go over it and just, you know, perfect that fact pattern if you're going to do that. Use AI to help you, but just have all these kind of safeguards that, you know, you're going to do your research and double check what you're doing.

Starting point is 00:37:46 And if eventually you need an employment lawyer, well, you can always hire one. There's lots of them around. So I hope this helps you understand, you know, using AI from the employee's perspective, some hidden problems with it, but you still can use it as a tool to help you get to where you want to go. And really, at the end of the day, it's about severance, okay? It's not about getting your justice. And people say it to me, I'm like, I'm sorry, you know, I go about this issue in discussions with judges as well. This is the best we can do, okay, our justice system. And it's really about awarding money to people through negotiations and settlement, okay?

Starting point is 00:38:26 Because people, you can't afford the legal process. Unfortunately, it's made too cumbersome financially to do it. So there's a way we go through this. Even if you go through litigation, we still end up settling cases before a jury trial. Okay. The courts are not, there's very few jury trials. You don't understand that. There's more probably in state court, less or so in federal court.

Starting point is 00:38:48 So you do have access to the system in the way I've been describing. You do have tools at your disposal, which I have gone through. You can use AI, but with caution. But it's really, and the end of the day, it's about you, you writing your facts, and you looking up the law. Maybe you want to go to law school. Hey, here's a shout out to going to law school, okay? It's rewarding. You can help other people like you in the future if you do it.

Starting point is 00:39:14 And people go to law school all the time. But understand, if you want to go to law school for employment law, you know, a worthwhile profession. You know, there's more need for them, okay? But there's lawyers are aging out. More lawyers are coming in. But so employment law is very valuable to help people like yourself. So it's just, you know, maybe that's, maybe you're calling. Maybe that's what sparked something here for you and you go run with it.

Starting point is 00:39:37 So with all that said, use AI with caution, know the pitfalls. But, you know, do your research. And it's okay. You're not going to get all the answers. that's okay. And so hope you found it interesting. I'll talk to you soon. If you like the Employees Survival Guide, I'd really encourage you to leave a review. We try really hard to produce information to you that's informative, that's timely that you can actually use and solve problems on your own and at your employment. So if you like to leave

Starting point is 00:40:07 a review anywhere you listen to our podcast, please do so. And leave five stars because anything less than five is really not as good, right? I'll keep it up. I'll keep the standards up. I'll keep the information flowing at you. If you'd like to send me an email and ask me a question, I'll actually review it and post it on there. You can send it to m-C-A-R-U-I at C-A-P-C-Law.com. That's capclaw.com.

Employee Survival Guide® - S6: Ep133: The Hidden Dangers of Using AI to Predict Your Employment Discrimination Case

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