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Brand the Interpreter
What if La Malinche—the Indigenous woman who famously served as interpreter and advisor to Hernán Cortés during the Spanish conquest of Mexico—could share her stories? Imagine the insights and experiences she could offer about the power of language and navigating the complexities of two worlds. That’s the spirit behind the Brand the Interpreter Podcast!
Hosted by Mireya Pérez, an interpreter and personal brand advocate, this podcast gives today’s interpreters a platform to share their own fascinating stories, challenges, and triumphs. Each episode pulls back the curtain on the world of interpreting, from navigating high-stakes conversations to facilitating cross-cultural understanding, offering listeners a glimpse into the lives of the professionals who bring meaning across languages.
Whether you’re an interpreter, a bilingual professional, or simply curious about the magic that happens behind the scenes, Brand the Interpreter immerses you in the stories of language professionals making an impact every day. It’s more than just a podcast—it’s a celebration of language, connection, and the vital human element that makes communication possible.
Join us to explore how the power of language, driven by human connection, shapes understanding, opens new worlds, and transforms perspectives, revealing the deeper truths that unite us all.
Brand the Interpreter
AI Meets Language Services: Opportunities and Dilemmas with Holly Silvestri
Unlock the secrets of integrating AI in language services with our latest episode featuring Dr. Holly Silvestri from the Safe AI Task Force. Gain insights into the innovative applications of AI in translating and interpreting, particularly in community settings. You'll discover how AI is transforming industry standards and explore the ethical and security considerations of using AI when handling sensitive materials. Dr. Silvestri shares her expertise on harnessing AI effectively, helping language professionals navigate this rapidly evolving landscape.
Our conversation takes you through the journey of AI's evolution, from early neural networks to today's sophisticated large language models like ChatGPT, and their impact on public perception. We tackle the challenges AI poses, including its role in lesser-diffused languages and the broader implications for language access. Learn about the formation of the Safe AI Task Force, which aims to implement best practices and guidelines that prioritize fairness and ethics in the language industry.
Join us as we explore the future of AI in language services, the emergence of new roles, and the importance of staying informed and adaptable. We address the misconceptions about the cost-saving nature of large language models and highlight the environmental and resource considerations. This episode also offers opportunities for involvement, inviting you to contribute to the pioneering efforts of Safe AI. Don't miss this insightful conversation that promises to equip you with the knowledge needed for informed decision-making in an AI-augmented world.
SAFEAI Taskforce: safeaitf.org
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Guidance Focument:Guidance - SAFE AI
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Welcome back, branded Bunch, to another episode of the Brandy Interpreter Podcast. This is Mireya, your host, and because I haven't spoken to you in a few weeks, happy fall. It's, as they say, suera-ueda. I say that as I'm sweating wearing a sweater that is still a bit too warm for, but nevertheless it is fall and the autumn leaves per the trees outside. Tell me so.
Speaker 1:And speaking of fall and autumn leaves, if you've never experienced the fall in the east coast, particularly out here in the northern parts of Virginia or just the DMV area, by the way, for my West Coast people DMV is not the place where you go get a ticket and await for your turn on anything related to your car. I had to learn that the long hard way because I kept not understanding what the DMV had to do with the conversation. But turns out it is an acronym for us interpreters, that is for the DC Maryland, virginia area. So there you have it Now. You won't be as lost if you ever hear the DMV out here in the East Coast. Anyway, dmv, or the East Coast, does fall very differently, very beautifully, if I may add. The colors of the trees are exactly like the scenic routes that we see in movies, with those long winding roads and rows and rows of beautiful trees in all sorts of different shades and colors. I mean, the very first time that I experienced that, I thought, oh my gosh, this is real and I felt like I was actually dreaming driving down those roads. So I would say, if you're ever going to plan on coming out to the East Coast, this particular area because you know this is where I've been driving around and spending the last year Can you believe that the last year out here, beautiful, just beautiful, during the fall. So if you make plans to come out, try coming out during the fall so you can experience it.
Speaker 1:Thank you for joining me today again, by the way, I'm always, as I hope you know, very grateful for your support and for always coming back to listen to whenever a new episode drops. I hope that with some of these long stretches between episodes, you've had the opportunity to catch up. I know that they have not been coming out as perhaps often as they were just a few months back, but I'm hoping that it's going to be picking up speed here pretty soon. So appreciate and take advantage of the time that I've slowed down just a little bit to give you enough time to catch up on just over 100 episodes in the show. If you're new to this platform, welcome and thank you so much for tuning in. I always appreciate you reaching out on social media and letting me know that you're new to the show, that their time as guests to share their stories and just generally speaking with the show in general, it always means a lot because of the algorithm. Obviously, when individuals are tuning in, it does its little magic behind the scenes to recommend it as a potential for individuals that are listening to podcasts. So thank you so very much and welcome.
Speaker 1:So for today's episode, I had the opportunity to speak with a representative from the Safe AI Task Force and we got to talking a little bit about just the understanding a bit more, or breakdown, of AI in the language services industry. I know that many of us have heard so much uproar and there are so many different, sometimes conflicting, stories of what AI may or may not be in the language services industry, and we may perhaps have gotten even to the point where we're sort of tired of hearing about AI and what it could or could not do. But I think that the more we are informed, especially the more information that is very specific or very related to the work that we do, I think, the better decisions we're able to make on it, and including decisions having to do with whether or not we want to utilize it or, better yet, how to utilize it. So whenever I have the opportunity to invite someone on the show to expand on this topic, I will, and so today's show is really going to be not just learning a bit more about the topic of AI in the language services industry, particularly in the community setting, but also learn a little bit more about a task force called Safe AI, and here with us today to talk about both topics is Holly Silvestri.
Speaker 1:Dr Silvestri has significant experience in the field of translator and interpreter training, in addition to running her own language service provider agency, as well as freelancing for other agencies and government entities. Currently, she works as a senior coordinator for translation training and curriculum at the National Center for Interpretation at the University of Arizona. Her working languages are Spanish, french and English. She is a founding member of American Association of Interpreters and Translators in Education, as well as the chair of Public Relations Committee for Stakeholders Advocating for Fair and Ethical AI in Interpreting Task Force. She is also a member of the American Translators Association and her state's professional association, arizona Translators and Interpreters, dr Silvestri regularly presents on various topics relevant to the professions for these organizations and others around the United States. So, without further ado, please welcome Dr Silvestri. On behalf of Safe AI Holly. Welcome to the show. Thank you so much for being here today.
Speaker 2:Thank you for inviting me. It was lovely.
Speaker 1:Yes, indeed, I actually am excited number one because it's so, so close to all of the information that's coming out with regards to AI and the interpreting industry and, of course, with Safe AI, which we'll get into in just a little bit. So I'm honored and I'm happy that you're here on the show with us today to give us a lot of great information on behalf of Safe AI, to give us a lot of great information on behalf of Safe AI. But before we begin, I'd like for the audience to get to know Holly a little bit more and just find out a little bit more about you and how you got involved in the language services industry, if you will.
Speaker 2:Sure, where do I start? I was born a poor no, I was born a poor no these days. I like to start with the fact that I am probably representative in some ways of the industry, in at least a population that I tend to deal with community interpreters because, like everyone else, I started out wanting to help my parents right, because they were non-native English speakers when they first came to the States. So I de facto became the one who was managing a lot of things that were going on in the household. It wasn't until much later that I realized that this could be a career, like most people, and I got some training, which is a very good thing, because I was doing all the wrong things, as everybody starts out doing. And then at that point I was thinking okay, what am I going to do with the skills that I have, because I was originally trained to be a foreign language teacher. And then I added these you know, the interpreting and translation skills on top of that and I thought, well, there must be a need in schools. There's a multilingual population there. And then that's where we met, because we all started AAITE together and that has taken off and done very nicely.
Speaker 2:And then the pandemic hit, of course, and then, around 2020, I opened the news and it was like ah, chat, cpt, ai, oh my God. And I thought, oh, this is interesting. I know that there were people in the industry that were just as concerned as I was about the impact that this might have, the disruptive impact on both translation which it has, of course and interpretation, and I thought, oh, there has to be some place I can do something about this and educate people. So I got involved with SafeAI. So that's just a short version of my trajectory so far.
Speaker 2:Yeah, like a bite-sized version right, Because yeah, we all know.
Speaker 1:We definitely have stories with regards to how we got involved in the profession. You also are with Arizona State University, is that correct?
Speaker 2:I'm with University of Arizona down in Tucson. Asu is up in the Phoenix area, but absolutely I work with NCI there. We're the ones who well, I say we because I wasn't involved at that point, because NCI has been around for probably about 50 years now was originally started as a way to do research on this topic and to sort of create a legal framework. They were very instrumental in getting the 1978 Court Interpreters Act put into law and they were the first organization that created the federal exams for Haitian, creole, spanish and Navajo. Of course, the only surviving one now is the Spanish one and we are no longer in charge. That grant has long since evaporated and another company has taken over. But that's part of the reason that NCI exists and I thought that I could do some contributing there as well, and I've brought a lot of my knowledge of educational interpreting into that fold and now we do a lot of professional development in that arena as well as the legal interpreting arena.
Speaker 1:So it's nice? Yeah, no, definitely, especially something that is offered not just at a state level, but I do believe that there's also opportunity, such as you just mentioned, with continued professional development, so others from other areas are able to also take part in the professional development, correct?
Speaker 2:Yes, and since oh, I don't know the exact date honestly, I think it was pre-pandemic which was lucky for us because we were able to continue during the pandemic that we went from an in-house, on-site program for the city, which is the Court Interpreters Training Institute, to online, so now we have a vaster number of people that come and do our trainings in the summer months, which is really nice. Yeah, that is really desperately in need of court interpreters, God that's crazy.
Speaker 1:Yeah, that's crazy. I only say that because I do remember back in the day, back in the day when I first started as well, that was my aim. My goal was to get started in the legal field, meaning I wanted to become a court interpreter. And one thing led to another, which ended up, you know, I ended up becoming a community interpreter and staying there Again. I thought, oh, it's going to be temporary, until we were going through just that economic issue back in 08, 09. Oh, yeah.
Speaker 1:And I started seeing more layoffs than demand for cordon trippers. I couldn't even Spanish in California and I was like, oh my gosh, I'm not going to have a job when I finish schooling, and that's the only reason why I made the swap. And it was thanks to the guidance of one of my instructors, actually one of my professors, that said you know, there's, there's this new certification rolling out in the medical field and, and I highly encourage you all to to just go for it you know you've had the training, you know the basic training that would, that would support you anyway. And so now to hear that it's like they're in need, like I, I went from, oh, there was, there was no need. To. Now that there is a need, it's like well, now I'm so, I'm so involved in community and to bring I don't want to go to legal.
Speaker 1:I know, I know, yeah, but you mentioned with regards to the technology and being able to bring professional development, and I think that I know I mean in the States, I want to say here in the US, but I mean really, when you go online and you go virtual, anyone at that point can join. It could become a universal program, oh sure.
Speaker 2:We've had a lot of Mexicans join our city program. I know that we've also had people from Europe, which is terrifically difficult because of the time change, but they do come to the synchronous sessions as well as the asynchronous ones. So it's been a real boon, I think, for a lot of conference interpreters who have perhaps languages that are not as popular in the United States but then can get called over here to do Zoom interpreting, mostly because obviously they're not going to fly over for a court case. But it's been a very enriching experience to interact with those people as well and talk about the European environment for interpreting, which I think is a little different than here.
Speaker 1:Yeah, and I think again I go back to this, this topic of of the technology component, because we have seen how it's been able to help the industry expand or grow its wings Right and and in all sorts of different ways. Obviously, we've seen the technology just advance and really take a huge role in our industry, and one of those technology components that just became like this buzzword was AI and, you know, chat, gpt and all these other different new technologies that have rolled out in the last, made public, I should say in the last couple of years, because I do believe, if I'm not mistaken, they've actually been around for quite a long time and it's just only been recently that it's been open to the public and that we as public have been, you know, made aware of and and basically it's like oh, here you go, try play with it and see how you like it, and it just became this uproar suddenly, right, what did you begin to see when you started to hear you personally, ai, and I started to look at know.
Speaker 2:I started to look at all of the different use cases that people were putting out there, because it was, you know, obviously you want to keep your job and I was like, okay, well, if this is a language-based, you know, performance generative AI, how good is it at translation? Because everyone keeps saying it can translate no problem. It can translate no problem. And I knew at that point we were still, and we still are, at the point of using MT really for what they call interpreting. But we'll get to that later. So you know, right, because that's computer-assisted translation by a human, that's just bringing it in as an aid, whereas mt is when the machine does it right. And that's when we started to like, right before gen ai, right, generative um, artificial intelligence, which is what chat, gpt is, came in. We had that, we have the wave of um. I don't know if you did this I used to do this I would test Google like every six months to see how good it would get Right With a, with a difficult, you know, sentence. I'd be like, okay, and I know that I was training it and that's a stupid thing to do, but there's no other way to figure out how, how good, you know, the competition is because people who don't know go and use that, and we had that. We had that initial neural net wave where Google got suddenly a whole lot better Right. And then the second wave was when they started to use LLMs, and that's when Gen AI was born, right? So that's the second part of the puzzle that allowed it to be released to the general public and to be creating this massive tool that everyone used. You know, some form of chat.
Speaker 2:Gpps and chat boxes are the things that people got all excited about and it's great. They can do all sorts of repetitive tasks really well, but the translation part is what brought me to the table. They can do all sorts of repetitive tasks really well, but the translation part is what brought me to the table and I said well, you know, is this going to be a disruptor in the industry? And what is this going to do for interpreting? Because if they accept which a lot of you know industries have machine translation with a human doing post-editing.
Speaker 2:If that was going to happen in interpreting, are we going to end up being like the court reporter and watching a you know a script appear on a screen and just correcting it as we go along, is that the end of our brains having to do the work right right for the most part. So there's good elements to that and there's bad elements to that. I thought you know there needs to be a nuanced response to this because it could potentially massively expand people's knowledge of the industry, but also language access in this country, which needs to be expanded. But it also could be really disruptive to those who have put in the time and energy and money to train. You know, if that's what interpreting ends up being, the training is going to be very different.
Speaker 1:Yeah, and we saw this massive wave of fear for many in the industry correct.
Speaker 2:Well, yes, that mirrored the general population's fear. You know, everything about ai is extremes. I think that's part of part of that is just the media hype. Anything that you put out there has to scream at you to get get in front of people's eyeballs. So it was either ai is going to save the world it's the next coming of jesus or ai is the devil and it's going to put us all into this dystopian hell.
Speaker 1:Yeah, the end of both ends of the spectrum, right, right, yeah.
Speaker 2:So that was kind of why I sort of got involved in Safe AI. When I found it, I was like, oh, this is perfect. I need more information to be able to make an informed decision about what I'm going to be talking to my clients about. Because they were coming to me going this Gen AI thing it's great, you know a lot of the school districts and I was like hold the boat.
Speaker 1:Yeah.
Speaker 2:Wait a minute, because you do not know how this works and you do not know if it's secure. Do not be running your IEPs through that. Oh my gosh, translate them please. You know to translate them, please, you know. But you, you get that in the industry, right, you have to do a lot of client education before before they get to realize like, yeah, if it's free, then you are the product, not the thing that you're translating. They are using your materials, as you know, information to train, their, train, their bot, and that's their public information. Then and it's like, oh, that's not what you want to be putting anybody's private information in there for exactly the lack of parameters immediately.
Speaker 1:It was just like people just want to jump into it quickly, like this is. This is the answer to um, yes like every new tech right, it's panacea.
Speaker 2:They've been doing this in ai. I went back and looked just because I was curious. They've been doing this in ai since, like the 1940s, even before ai had a name, because ai originally. You know, the first ai conference was in 1955, but in the 1940s, when they were messing around. You know, the first AI conference was in 1955. But in the 1940s, when they were messing around, you know, with computers, they were talking. They've been hyping this same hype. They were talking this is back when, you know, computers had like one millionth the capacity of the cell phone computer that you now have in your back pocket half the time and they were talking about it. It's, you know, can think faster than Einstein. Well, yeah, okay, here we are in 2024. And I'm pretty sure if that was the case in 1940, we would already have sentient robots.
Speaker 1:So yeah, I was thinking back actually when I saw how long ago like I'm like what do you mean They've been? They've been having these conversations and doing running, you know whatever they're running in the background since before I was born.
Speaker 2:Absolutely.
Speaker 2:Yeah, well, it's a tougher problem than most people realize. It is amazingly difficult to get something that you know that the public would accept as the answer to their prayers. Right, we've been trained all of us who have been. Well, even if you move to this country, you have the Star Trek kind of thing about technology. Right, someday we'll have the universal translator. Someday it will be able to create food out of nothing. You know, because you grew up watching this and beginning to expect this out of the tech. And now it's sort of coming true and people are like oh, there, it is Like no, not quite.
Speaker 1:I would have wished they would have started actually with, like I grew up with, the Jetsons, you know, like as a cartoon. I would have liked for them to have started with the assistant helping me fold clothes and wash dishes.
Speaker 2:Absolutely. I want the wash the dishes robot. Thank you very much, and I wouldn't mind the flying car either.
Speaker 1:Yeah, I would have been right, exactly, I would have been right behind that. Like, sign me up, I'll test it. Well in your search for, you know, trying to to learn more about how this can impact the industry, our jobs and, of course, the way in which we approach the responses to the people that we work with. You are part of, or became a part of, a task force named Safe AI. Now, if you would be so kind as to describing what Safe AI is and why this task force was formed although I imagine some of us have sort of come up with a conclusion already with an answer to that, but why don't you walk us through that?
Speaker 2:Okay. So, like I said, you know, safe AI is a task force at the current stage of its development. At the current stage of its development, and it started because a group of stakeholders which was pretty wide it included interpreters, leadership in professional organizations that do professional development for interpreters, lsps, advocates and even some tech companies all began talking and realizing that the disruption from AI would be really severe and rapid, and we wanted to make an industry-wide response to be part of the conversation and to impact policy in real time, not after the fact. No shade to translators, as I am one myself, but we wanted to avoid, kind of if we could, what happened to translators, as I am one myself, but we wanted to avoid, kind of if we could, what happened to translators who didn't really necessarily ask for a seat at the table and then just sort of primarily got stuck with doing, you know, mtpe, machine translation, post-editing. It's not 100% of the industry, but it is a large chunk now. It's not 100% of the industry, but it is a large chunk now. So we decided to form Safe AI Task Force and then, you know, we got to work thinking okay, we need something to talk about other than just the news and what we suppose this is going to you know be like and what we suppose people think about it. That's true. So we you know, because you can't you can sit around and whine in a room together, but that's only your opinion. You need data to be able to talk about. Okay, is this actually impacting the industry? What are people thinking about it? And you can glean some of that from the press. But, like we said, the press is uh, first of all, they very, very rarely know what we do, so their opinion I take it with a grain of salt a lot of the time. Um, but also, you know, we needed to understand exactly what people expected out of this in order to understand what the tech companies might want to sell. Right, because they want to match those two up right People's expectations of any kind of artificial tech and what they're making. They want there to be a match, so we needed some data.
Speaker 2:So we decided to do the survey as our first step to getting that kind of data, because our mission was to, you know, document like the state of AI capabilities in real time, language interpretation Right, and that includes for all languages, by the way, we were working with, which is unusual in the spoken language world, but we were working with signed interpreters as well, because they were also very upset at the possibility of being replaced.
Speaker 2:So we wanted to document the capabilities, which include speech-to-text, speech-to-speech multilingual captioning, translation captioning all of the elements of the language industry that could be affected by this, identify where the key use cases of AI could soon be applied to each of the domains of interpreting conference, medical, legal, educational, business, other settings and then identify, like what the positives and negatives of the impact on these use cases would be, so we could talk intelligently with our you know customers about okay, you know, because it's a give and take, there's always, you know, if there's a positive, there's always some drawback that comes from the tech and then create best practice guidance for each of the specializations. Right, because nobody was out there doing that either. They were all just sort of standing around with their mouth agape going, oh yeah.
Speaker 2:And we were like OK, well, somebody has to come up with best practices, because if left to its own devices, the industry will do that de facto and we'll be left out of the conversation. We'll be left out talking about how language access could be of poorer quality as a result, and we didn't want that to happen, right? And we would also be left out of the conversation. Like which languages is this being applied to? Right? Because everyone thinks that this is just a panacea. It's going to work for all languages. Yeah Well, no, right, surprise surprise, surprise, surprise.
Speaker 2:Everything works, you know, works out for the best. So we we wanted to get that best practice guidance targeted to practitioners, to buyers, to vendors, to training and academic organizations, and then also to end users, to get the general public educated, like, okay, you can choose this option, but this, this and this are going to be a consequence of that right, much like we did with Zoom Although Zoom, kind of, was the worst upon us because of COVID, there was no other option, whereas here you have a menu now and you have to talk people through the menu. Like, yes, you can choose it on site. Yes, you can choose Zoom. Yes, you can choose, you know AI interpreting, but here's where that's best and here's where that is perhaps not your best use of the money that you have, so let me go back a little bit and ask Holly safe AI in this context?
Speaker 1:is AI talking about artificial intelligence or is it artificial interpreting?
Speaker 2:Ah, okay. Well, yes and no. Yes and no To be clear. I love the name because it's a bit of a double entend eye, because that was also the, the, the big argument in the press Right Is AI safe, is it not safe, is it going to destroy the world, et cetera. So we want it to be fair and ethical to everyone involved Right, fair to the person that just got their MA in conference interpreting and said, oh my God, why did I just spend eighty thousand dollars to be replaced by a robot? Ethical to the end user Right, to make sure that they're still having the same level of service and the quality and also the ethics involved are being maintained. So there were a lot of factors that we wanted to address with respect to. You know, just, instead of just handing it over, here you go, robot, go ahead. So yes and no, in the sense that we also think that the response should be nuanced because there is a movement toward augmented interpreting.
Speaker 2:You know, for many, many of us, we know, as practitioners, that your memory is one of the best tools you have as an interpreter, because you need to keep a hold of a lot of information while you're doing multiple things at the same time, while you're doing multiple things at the same time. And there have been early studies not definitive, right, but early studies in how this could possibly help with the memory issue. Right, there are certain studies that say you know, with numbers, all the things that are hard numbers, names, dates, all those things that you know. You have to have that, on top of managing the two languages, all those dates, particularly in those high risk situations You're not going to. You know, in medical, you have to make sure that the dosage that you're saying in the language you're interpreting into is the same, exact dosage.
Speaker 2:So, and in court, you know, yes, you make sure that it's the exact same time, because that's when the time of the crime was supposed to be committed and you can't be changing the time just because you forgot. So it's important that those details maintain their integrity and this you know, having a running transcript that you could refer to instead of just having to go off of what you heard, could help that. So there are beginning studies that say that that could be something that this technology could be used for. I don't think we're ready yet to insert it into training programs or to actually say, yes, this is the way we want to go. I've seen how that works because I've I. Immediately, when I saw that that was a possibility, I was like, oh, it's interesting. So I have been practicing my simul with friends with the captioning and zoom running really right.
Speaker 1:If you know, I once tried that and I I felt like it just I was like there's no way.
Speaker 2:He just said beast yeah, it's not great because the the caption, the speech recognition technology is not a hundred percent, of course, but if you're, you know, but you're not feeding like I'm, I wasn't not listening, I wasn't reading the thing you are correcting like as you go along, because no, of course they're not going to say that that's stupid. Wait, she just said this and you know sometimes you burst out laughing because you'm right, you're wrong, ridiculous, absolutely.
Speaker 2:Right, but I did. You know, that was the best estimate that I could come up with to try and practice a little bit, and I thought, oh, okay, and so I wrote a script that was full of, like the numbers and the dates and things like that, and I was like this is actually really helpful to me to actually be able to see that on the screen when it came up, right right, sometimes the numbers were wrong, and then it's really so. I think the technology's not quite there yet, but once it does get there, I'd like to see that and be a very great help to conference interpreters right when they're going all day long and they need that support, even in court. I'd like to see that, if that's possible, absolutely, but that you know there's a lot of factors that need to fall into place to make that happen. I think, sure, we're not there yet.
Speaker 1:And one of those I'm hoping is the inclusion of the practitioners.
Speaker 2:you know the oh absolutely that, would you know. Then it's what I like to call augmented interpreting. Right, that's my AI. Right, that's just another way of saying a cat tool. That's just slightly different. Right, this is helping me interpret, because it's giving me all the things that I don't need in my memory anymore on a screen in front of me. Absolutely fabulous. If we actually got to the point where it just extracted it and it didn't even have the transcript and all I needed to do was look up and go, oh, that's the date and what I was interpreting. I am all for that.
Speaker 1:Only show me the dates, the names, the addresses, right as they come up, the stuff we know to write down right.
Speaker 2:If we get there and do our little pre-session and like what's that person's name, what's that person's name? And oh, when did this, when did the, the, the theft supposedly occur, or whatever you're interpreting for Um, I would like it to do that Sure.
Speaker 1:Wow, suddenly, yeah, we're not there yet. We're not there yet, right.
Speaker 2:So if it were augmented interpreting and not you know, not just replacing me, but helping me do the job. Huh, Bring it on.
Speaker 1:Help facilitate, I'll take any help I can get. Yeah, no kidding, exactly Short of actually implanting something right? Well, you know, you never know.
Speaker 2:I'd probably die before that happens. But who knows that happens. But who knows, maybe we'll have you know, maybe we'll have that now running across our eyeballs. Who knows Exactly 20 million years from now? We have no idea.
Speaker 1:You mentioned the survey then that SafeAI pushed out in trying to sort of gather information from all the stakeholders. And the stakeholders here you had also mentioned are the practitioners, so the individuals that are providing the service, language service providers, LSPs, correct? Yeah, End users, so the LEP individual that is receiving the service. And then who else was part of this survey? Do you recall? I think we tried.
Speaker 2:Well, under LSPs some of the tech companies function as both, so you know we tried also to get some tech companies to respond as well. The survey, of course, did have certain limitations. Right, it was interpreting-centric. We wanted it to focus on language interpretation, both for spoken and signed. Eventually we had to separate, unfortunately just due to time limitations, because we had to translate the survey into so many languages, including signed languages, that we had to separate the spoken survey from the deaf advisory group, which put out their own focus groups and survey, just because doing it and getting it out at the time we said we wanted to was beyond our capacity at that point. But it was interpreting centric. It was, on our side at least, a spoken language only. Right, because the deaf advisory group did their own version of the survey for signed languages. It was also US focused for the obvious reason that we're all here.
Speaker 2:That didn't mean that we didn't have international respondees. Right, because when you send out a survey you can't say no, you can't respond. And we also realized that it was like a first step. There's definitely more work to be done and more more data that we need. In fact, I'll talk about the second step that we took a little bit, but it wanted to capture the current perceptions regarding the use of AI in interpreting from all of those different stakeholders. So, but on their own right, the findings of the report are not sufficient to develop guidelines that are permanent right. We need much more data, further research into, you know, use case, scenario and industry to establish, like that strong framework of okay, when is it safe and good to use it in this particular case? Because it's a lot more complex than people realize. More complex than people realize. So we had about 2,500 respondents and definitely we had from other countries.
Speaker 2:Right, we had 82 countries represented in the responses, but 79% were from the US. Right, because that was our goal. We wanted it to be US centric, but we didn't want to say no, you can't respond. Two thirds of the respondents, of course, were interpreters, because I think they were. I'm guessing here I may be talking out of turn, but I'm guessing that they were just as nervous and they wanted to express their opinion and their fear in some way. Then it did come in, it did come through in the survey results and more than three quarters of those interpreters that did respond were working in health care. And I think that also reflects the channels that we went through, because getting people to respond to a survey I don't know if you've ever done it is a nightmare. Yeah, it really is.
Speaker 2:To get to respond, to get a balance Right, and so and we did have, we did have a challenge getting the end users as well. We got enough to make it statistically significant, the data, but of course you would always like more. But that's always the challenge when do you go to find them? How do you advertise? And of course, we didn't have money. We already had to pay for the survey, which I can tell you was not no mean feat. So, and of course, the ethics of do you want to pay people to respond to a survey were also an issue, right? So you want to get them to voluntarily respond, and how do you do that? It's a long story, but it is a difficult challenge.
Speaker 2:I think Particularly the LEP community.
Speaker 1:I feel because, interestingly enough, we are speaking about technology in this case, and in this case more advanced technology to identify the gap between the technology that's there and the people that it's supposed to service that there's a major gap, a major discrepancy, because I'm always thinking for that particular community. It would be like boots on the ground. I'm thinking the surveys that you know, back in the day we'd go knocking on the doors.
Speaker 2:You have to go knocking on doors Right, yeah, well, that's part of the problem of the digital divide in.
Speaker 1:You know, back in the day we'd go knocking on the doors. You have to go knocking on doors, right, yeah, well, that's part of the problem of the digital divide in this country.
Speaker 2:right, we often talk about that, at least in the press, on the long racial lines of Black and white communities, but it does affect the Latino communities as well. I do think that there is an element of that and, although I could get in trouble for saying this, there is an element also of particularly perhaps with the newer immigrants to this country who are in that LAT population. They may not have the educational background to understand the technology 100 percent. Not that your average American has a fuller grasp either.
Speaker 1:A hundred percent, not that your average American has a fuller grasp either.
Speaker 2:Oh yeah, that's true, right? So I don't you know. No, shade, not. Please don't write in and say, oh my God, she's a horrible racist.
Speaker 1:It's not that, it's, it's just you know your educational level does is reflected.
Speaker 2:I think in how much you read the newspaper, how much you know about it, how much you have time to research it. Right, Sometimes you're just at the stage where it's like, OK, where am I going to spend the night? And I have to survive. I don't. I'm not reading the New York Times about AI right now. I'm trying to figure out how to get a visa to stay here.
Speaker 1:Right, yeah, yeah, it's different.
Speaker 2:It's a different, a different set of priorities, I think.
Speaker 1:For sure yeah.
Speaker 2:I mean.
Speaker 1:I spoke to individuals that this was, you know, before it actually hit the mainstream media and it became like this buzzword. But as we're beginning to hear more about it in the industry, I remember one time asking another interpreter in the field and the response was I'd rather not hear about that stuff because it's like doomsday for me and I don't want to know about it. So it's like then you have the individuals that deliberately sort of put their you know, bury their heads in the ground, if you will just so that they don't hear about.
Speaker 1:And so now you've got individuals in the industry that are uninformed by choice. They don't yeah.
Speaker 2:Well, some of that was also, you know, because they were saying, you know, the press was ridiculously saying there will be some disruption. Any new technology will be disruptive. And I don't mean to be dismissive, because I had that same panic attack as everyone else, like, oh my God, I just got comfortable in this career and now it's going to disappear and now change careers yeah right, you know I've done it enough times to. And now it's going to disappear and now change careers. Yeah right, uh, you know I've done it enough times to know that it's going to be okay, but at the same time, you're just like, oh god again. So I understand that that and also I do.
Speaker 2:I do understand that people just like the whole press thing was you know, 50 of the jobs in this industry are going to be lost it was kind of doom scrolling in the beginning are going to be lost. It was kind of doom scrolling in the beginning, like when AI just was like. Everyone was just like, oh my God, chat CPT is going to be your secretary, your your doctor, your every. It's like wait, just calm down, calm down people. So, so, true, I understand that response.
Speaker 1:But I also feel like the responses from the survey, as you just mentioned, opened up the the just this practices. Necessarily, there is more work to be done, but it did demonstrate some pretty prominent findings, right? What did it reveal?
Speaker 2:Oh yeah, so okay, I'm going to group them in sort of under different categories, because I'm still in the stages of digesting, because the report was 350 pages and then the summary was like 50. I was like, well, okay. So you know, some of us have a job and we can't spend all day reading, but we do have some categories that we can talk about. So, on the use and testing of what they call automated captioning, which is sort of the overall category of this, you know, 27% of the survey respondents said that they used or tested automated captioning, either from moderately to extensively, and of those that had used it, over 50% reported their experiences. So that just highlights that there is a growing integration of AI in interpreting services. Whether we like it or not, they're already deploying it. Okay, with respect to, you know, the acceptance or, let's say, I don't want to say rejection, but skepticism of the this particular technology, the study you know revealed a combination of both, which is kind of, you know, the general public's view, I think as well. There's a consensus on the potential of AI to contribute positively under certain conditions, right, but defining those conditions and ensuring that AI's deployment respects everybody's rights and needs and preferences, that's going to be a challenge, right, there are still some ethical questions to be answered. There's going to be, you know, privacy rights that need to be addressed. Lots and lots of questions remain with respect to that.
Speaker 2:A lot of people thought, oh well, this is, you know, this is just about cost, so let's talk a little about that, because it's yeah, the financial aspect of AI was obviously, you know, and its adoption was identified as one of the driving forces. I do think, in some ways, that was a simple response by a lot of interpreters, like, oh, it's cheaper, they're going to go for that option, because a lot of us have seen that before, sadly. Right, but it wasn't only a cost reduction strategy, which was an interesting part of this survey, right, despite the potential sacrifices in quality. People did say that that was one of the factors. But the study also noted, right, a variability in acceptance based on who bears the cost of the interpreting services. Right, so they were more willing to accept AI interpreting, whatever that may mean, as opposed to no services at all. Well, yeah, of course, right, you can have a half a piece of bread or you're going to starve. Okay, yeah, I'll take it. So there is a complex interplay right between the financial considerations, the quality of service and the ethical standards you have to maintain in order to do, you know, language access properly. So, but there are other considerations.
Speaker 2:A lot of the non-interpreters, right, the LSPs were largely concerned with, you know, making sure that they filled the slot that they didn't have an interpreter for, that they could provide the service even though there's a shortage of interpreters. Quite frankly, I think that's somewhat misguided, because a lot of the time, we're looking at filling services for LLDs, languages of lesser diffusion and I got to be honest with you, the degenerative AI using LLMs is good for maybe eight languages and none of them are those LLDs. Right, it's the big European language. Well, why? Because if you look at the llms, they're trained on information scraped off the internet. Well, hello, the internet is, I think, 60 english speaking, right.
Speaker 2:And then you've got the other big countries, the developed countries, primarily european, and some, you know, larger asian countries that have a presence. You know, well, go ahead and look, see if there's any Mixteco pages on the internet. I don't think so, right. So there's no data to train them on. So there's a mismatch in the expectation. Right, this is the panacea we're going to be able to fill all these things, because the computer is going to stand in for the non-existent interpreter. Well, ok, except you have nothing to train it on. So good luck with that.
Speaker 1:Yeah, immediately, I'm thinking you know the, the unethical piece which I am certain exists out there, going with that whole notion of, hey, it's better than nothing, but then choosing that, primarily because potentially cost-driven efforts right, or cost-driven decisions, and then replacing that particular interpreter because, oh, we tried to obtain or secure an interpreter of that language. No, can do, but here's the next best thing. But it's like how do we determine whether or not that was there was reasonable effort behind that?
Speaker 2:Because it's already difficult. Well, that's part of the you know, that's part of the problem with the industry, right, right, and the guidelines, and the fact that there's just a shortage of interpreters. I mean, I even think, you know, I work in Spanish and that's the gorilla in the room, right, I still think there's a shortage of interpreters in Spanish as well. So, forget about Mexico. Or, you know, pick another LLD like Vietnamese, for instance. There's not enough material to train them on, so these bots don't exist in those languages. So I think that the companies that expect that that is going to be, you know, the AI solution is going to work for them.
Speaker 2:There are going to be sorely disappointed, but maybe I'm wrong there may come a time where the internet then has its own issues of multilingualism interesting and then there'll be enough information to train on. But we'll see. But okay, there was also. Let me go back to what I was saying. There's also issues of the transparency and informed consent issue, right? Uh? An overwhelming majority of respondents advocated for clear disclosure when AI is used in interpreting, right? And emphasize the need for transparency and informed consent that all parties should be aware of and consenting to the use of the automated solution. I think that's only fair.
Speaker 2:The ethical considerations were really a major part of this as well.
Speaker 2:The majority of the respondents agreed that replacing people with machines for interpreting is not right. Of course, the sentiment is particularly strong among interpreters and service recipients who view that shift with apprehension, which we've talked about multiple times, that makes sense. That shift with apprehension which we've talked about multiple times. That makes sense. And I think that our survey was perhaps skewed because of the number of interpreters who responded in that way, as opposed to the number of LFPs or, you know, tech people. But they also had diverse perspectives on AI use, in the sense that there was a significant divide of opinions on the use of AI when no human interpreter is available, right, it was equally split between those who prefer automated interpretation to none at all and those who would rather have no interpretation than rely on AI. I think some of that has to do with people's apprehension just with technology to begin with and then rely on AI. So it was, you know, I think some of that has to do with people's apprehension, just with technology to begin with.
Speaker 1:That's so interesting.
Speaker 2:You and I both know as trainers of interpreters. There's different levels of technological capacity amongst those people and amongst the end users. We've already talked about the fact that there could be some technological challenges, so there are a lot of factors involved.
Speaker 1:Yeah, for sure, I know that I'm thinking about it. It's so interesting that that was the result because, in thinking back, I took the survey and I remembered just pausing on that one, because it's like oh, like this, is this one's a hard one for me. Because it is, because it's like, ah, like this, is this one's a hard one for me, because it is it's like do we leave them there with no service, which you know, it's just, it's a, it's a disservice at that point, right, not not having any access or having to come back. It's like no different than hey, our interpreter's gone, right, come back at a later time, or something, right, which is often a challenge for a lot of our end users right, Come back at a later time or something Right, which is often a challenge for a lot of our end users right.
Speaker 2:Yes, yes, they don't necessarily have the funds to be coming back and forth.
Speaker 1:Yeah, that one was a tough one for me. But going back to the other one, with regards to the disclosure component, I know that that maybe potentially for other people, potentially even those that are listening, might be like well duh, well duh, yeah, they should be disclosing. But let me tell you, just out of the stories that I've been hearing thus far, it's not a duh, you know. And they're pushing it out as if an actual human gave the translation, and there's pushback between management and the people that are actually supposed to be providing the service. With hey, could we at least disclose? And management not feeling the need to have to disclose?
Speaker 2:that it was. As a lawyer I've got a lot of opinions on that that I can't really put into words right here. Yeah.
Speaker 1:So meaning to say that, yeah, that question is important because we see we absolutely see that the results of the survey. People are saying how important disclosure is. Let individuals be transparent and let individuals know that they're reading something that was created by a machine versus a human, and I feel like it's just. It creates this sort of sense of hey, if there is a mistake, I understand why, because a machine used it and I can, I can say, by the way, there's a blip, right.
Speaker 2:There's a blip, yeah, I mean the translators, right. I wouldn't want my work to be denigrated as having been done by a computer and people assuming that I made mistakes. That would be very damaging to your professional reputation.
Speaker 1:Absolutely, and I feel just that it would almost give like this sense of like okay, well, they're putting something together for me to read, they're letting me know it's a machine. And the way our communities that we service for the most part you know this is generally speaking they're appreciative of even the effort, and we see this time and time again. This is not new either.
Speaker 2:Right, we've always had to make certain adaptations, like I know well, particularly because I work primarily in the schools, and the schools never have enough money right and for anything, let alone language access. So the budgetary concerns are always primary and there's always some kind of give and take. Right, the service is not 100% coverage, 100% perfect there's always in any service right. It's based on the budget that you have and therefore you have to make some accommodations. So this is not new, it's just before. It was fairly clear, I think in a lot of the cases the use cases that, okay, we can't provide you with an interpreter for the IEP, but we're going to get you a translation after the meeting, kind of a thing. So it was clear that this was an accommodation and that this was being, this was being done, and everybody in the room, you know, assented and consented to it. So I think over time that will become more part of the conversation, because now there are multiple options, not just, you know, zoom, or in person.
Speaker 1:Yeah. So, going back, what other prominent findings did we did? We come to see that is important at least for this audience to know about what. What other things did we see that is important at least for this audience to know about what. What other things did we see that as very relevant.
Speaker 1:I really liked the idea before you answer, holly, that, um, or the notion rather, that there was a lot of medical, uh, interpreters or interpreters in the medical field that responded to the survey and I feel almost like there was not to speak for them, but you know, it gives a sense of hey, we saw it happen to us when the pandemic hit. We had to sort of evolve. For many of us that weren't we never even operated in the virtual world of you know interpreting. Not that it had just existed or come up, it'd been existing for years. But a lot of us sort of had to learn to go through the motions without anyone asking us what do you think or how should we? Or you know it was sort of like you got thrown in there and then you learn to navigate in reverse.
Speaker 2:Exactly, I think that was definitely the fact that a lot of interpreting moved to remote with COVID and, like you say, it was I won't say a forced move in the sense that there was no physical force involved, but it was an obligation given the circumstances, and people felt, I think, that, oh, this time I want to have a stay Right, and so I think that perhaps is the reason that we had a lot of medical interpreters responding as well. They were just like well, this time. Just a second, I have stuff to say.
Speaker 1:I'm given the platform. I'm yeah, I'm definitely coming in and sharing my thoughts.
Speaker 2:It's so true, so true, you know the other thing that this talked about too. As it walked you through the case uses and asked people is this okay to use AI for? Is this okay to use AI for? There was a definitive feeling and I think this is instinctive okay, this is going to work for low-risk, non-complex kinds of conversations. Non-complex kinds of conversations. That's a simple answer.
Speaker 2:The problem comes when determining what exactly is that, and anyone who knows anything about communication knows that it could be this kind of conversation in the first five minutes. And then it takes a left turn. Right, we've all been there, you have. You know. You're in the middle of a wellness exam and you're interpreting and life is going great, and then boom, a sudden cancer diagnosis. Well, that's not simple and non-complex and low risk anymore, is it Right? Or you're in the middle of the regular questions for an immigration interview and then, all of a sudden, bam comes the. I've been abused by my husband and that's why I took my children and ran up. So you know and you can't tell that in advance Nobody's walking around with a sign going I'm going to flip your world in about five minutes, right?
Speaker 2:So deciding when the best case uses are and how we decide that and at what moment it falls out of that category. Is not, first of all, that's not something I want to leave to a machine. Is not, first of all? That's not something I want to leave to a machine, like you know.
Speaker 2:Here's the list of questions that mean it's complex. Or? Or? Or even human beings like oh, all immigration interviews are fine, simple, right? Or all school intake is fine and simple. Really, uh, I can talk to you about this time that when that happened and this happened, I can talk to you about this time that when that happened and this happened, anyone who does the job knows that you can't, in real life, talk and say this conversation is going to be this category for its entirety. It just doesn't work that way. So you know, that's a simplified answer to a much more complex problem how do you decide, and how far in and at what point do you decide? Oh, this has to flip over to a human being if you start with, you know, uh, artificial intelligence, chatbot yeah I zero for customer service.
Speaker 2:Yeah, exactly and and at what? And who's going to educate the consumer? To make that press zero, right, to have that work, there has to be education all around, right? And are we gonna? What are we gonna do at the border? We're gonna be passing out pamphlets, you know. Don't forget to press zero. Yeah, exactly.
Speaker 2:So I'm not sure the people really have thought it through 100 like, oh, the robot's gonna take over. Really, I can't think it. It can't think it, just can't. So, you know, take a Xanax, take a deep breath and think about it. For a second right, even with self-driving cars, they've been promising that for years. They haven't gotten out of the suburbs of Phoenix because they still can't deal with weather, you know, other than beautiful, sunny skies. So you know, yes, this technology seems to be moving fast and there's this big hype, but we're in the honeymoon period and it's going to, you know, it's going to ebb and flow. So, deep breath and think just a little bit deeper at what you do. Can you really be replaced by a robot? I don't think so in a lot of cases.
Speaker 1:Yeah.
Speaker 2:I think we're, I think we're safe.
Speaker 1:I just believe not. Not at this point. Not at this point and, who knows, in the foreseeable future. You know to what extent, necessarily, but it definitely says a lot with regards to us as professionals. And you know that proverbial interpreter's toolbox. What are we going to be adding to this interpreter's toolbox that's going to position us in a way in which, now, we're more competitive, not necessarily at par with AI, necessarily at par with AI, but to the point where, you know, we have some knowledge and some skill sets, that sort of differentiate us in a way in which I'm demonstrating I'm not afraid, you know you actually are going to need me in this part- the other day I just saw a title for the first time.
Speaker 1:This was something that I learned a couple of years ago when we first started hearing about AI in the industry, and somebody that was Bill Glasser, if I'm not mistaken, was the one that actually was talking about what we're going to see with new, potentially new, titles that do not exist right Currently, that do not exist, and, thanks to AI, these new titles are going to come up. And it was in the news where, or on television where I saw something about, you know, the new ai chief of or chief of something, something ai component, and I was like I tried to take a snapshot. I was like live tv tried to take a snapshot. I didn't take it because it was like that's the first time not to say that they have a new job description right A new job description rolled out with regards to this, so we're starting to see that.
Speaker 2:And I do. I do think that that's the case in a lot of professions. It's like most technology is is it going to be a disruptor and are some people going to be left by the wayside? I do think so, not necessarily in only in our profession, but it's, and you see this, it's. Anyone who's been in the profession long enough knows if you're not learning, you will be left behind. That's why I kind of love this profession.
Speaker 2:You need to constantly up your game and up your skills, and that can take many forms. It can mean adding a language. It can mean adding a skill set that deals with how am I okay? If chat, tpt is the thing that people are going to be using, I better know how to use it. I better practice, get the free version, learn how to do prompts, because maybe, maybe you're going to be the one that they call on and say, hey, is ChatDPT good for this? Well, you better know the answer as their language service provider. That's what they depend upon.
Speaker 2:Right, in almost all industries, when they talk about language access, they look to the person who's doing it. So you better have the answer for them. If not doing it, so you better have the answer for them. If not, they'll go to someone who will. So, you know, experiment would be what I would say. Like you said, experiment with it, don't, don't be fearful of it and see if you can expand what services you offer. Maybe you also, in addition to interpreting, want to offer, you know, secret-like services and have chat PPT, write the letter that they want in Spanish and you edit it and then you send it back to them because they don't have a bilingual person on staff but they need to communicate something or something like that. Just don't do the deer in the headlights freeze. I think is the best response and the best advice I've ever gotten to right, don't do that in an interpreting exam and don't do that in real life, because all that means is you're frozen with fear and you're not going to process properly.
Speaker 1:You're not going to process properly. I like that. So, holly, tell us now where is Safe AI headed next, now that we've got this over 300 page document, over 2000 stakeholders that participated in this, what's next? What's to come?
Speaker 2:Well, so, the whole objective right, we talked about our objectives as an organization in the beginning is to create some sort of beginning guidance document for language access and use of SafeAI or client education, right? Exactly what I was talking about. If you don't know the answer, if they don't know the answer, they're going to come to you as a language service provider and you have to have well, general guidance says right abilities to be able to talk to them about what range of services you can offer and what the consequences of those ranges are. It's much more complex than a lot of people realize. I think I've said I've talked about the simple, low-risk conversations. I've talked about how you know, there are maybe eight to ten languages that have the large amounts of data that canLMs were trained on and then it falls off a cliff. So trying to solve for language access for languages of lesser diffusion is probably not going to work for those languages.
Speaker 2:People don't realize that there are ways that your LLMs, if you want to train them, can be trained domain specific, but it's costly. That's the other thing that people don't realize, right? This chat GPT is not $1.99 to create. It's a very expensive option. So a lot of the places that say maybe, oh, this is a cost saving factor, may end up saying, oh, it's not so much of a cost saving factor because if I have to train my chatbot with an LLM on all educational things, right, it's going to cost me X amount of dollars, and that is actually three times my human interpreter budget.
Speaker 1:So take a deep breath, LLM large language model, large language model.
Speaker 2:See the basis, all of this chat CPT, sort of generative AI, which chat CPT is a prime example of, and everyone that's the stand-in for it. The stand-in for it came about because of the LLMs right. Once I talked about having like testing Google, right, and you know, google got much better. Once we had neural machine translation right and that were like 2017, it started to like, oh, this isn't so funny anymore, like the sentence comes out, like it makes a little bit more sense and because it had more data to train on. Well, llms is when they had the gajillion amounts of data which makes that GPT sound really human, because it's trained on gajillions amount of data.
Speaker 2:Now, you know, stepping outside for a moment, that doesn't. That takes time and, by the way, a massive amount of energy. That's the other thing that people aren't talking about. If you care anything about the environment, maybe that's the best solution. Just saying it eats up a heck of a lot of water. Talk to the people in Ohio, where a lot of schools eats up a heck of a lot of water. Talk to the people in Ohio, where a lot of cool you know servers are about how much water is being eaten up to cool the servers to allow this to happen.
Speaker 2:Talk to the energy companies. Like you know, one training of one LLM is the same consumption and energy as about 30 to000 to 40,000 homes for a year. And then we talk about hmm, you know, there's a cost-benefit analysis here, that perhaps, but those are external factors that a lot of times people don't take into consideration. But the time and the money definitely right to actually train the LL, llm. If you want to maintain that privacy, uh, and the, the transparency and you know, oh well, like a lot of businesses, education may say, well, we want our own llm, then we don't have to worry about, you know, the privacy issues and so on and so forth. Okay, it's going to cost this much, oh, okay never, Never mind.
Speaker 2:Yeah, because they don't realize the the tons and tons of money that went into the dot VBP, like I said, didn't appear without billions of dollars of Elon Musk Tesla money Not my bank account anyway, unfortunately. So there's those issues as well.
Speaker 2:I think, you know, this may not be the solution that everyone's saying, like, before it was so expensive interpreting and now this is the cheaper. Have you thought about that actually? Because I don't know if that's really true in some cases. So that's, you know, the guidance is what we're looking to create a beginning guidance document, right? We're also looking at doing a different amount of research, which we've started to put money towards, so that CSA is doing round two. It's not a survey this time, but they want to come out with a much more well-researched decision tree so that people can then, you know, look at it and say, okay, in this case, use what is my best option, so that there's a way to look at how those decisions need to be thought out and not just, you know, made at the snap of a hat, like looking at all the different aspects that need to be, you know, considered when you're making that kind of a business decision. So that's where we're putting our efforts now, our efforts now, and then, of course, we're in the process of still digesting the survey results and, in addition to commissioning that work through CSA, again, we're looking at becoming, I think, a more permanent fixture in the T&I landscape, right, because we're a task force now.
Speaker 2:We don't have a structure. We're really not an organization. It's just a bunch of people that got together and said let's do this. And this isn't a one-shot deal. It's not like we're just going to say here's your guidance and we're gone. I think because TNI is always changing and AI is advancing so rapidly, we're going to have to be iterative in our responses. You know, every six months it's going to be like oh okay, now I can do this.
Speaker 2:And we have to respond this way. So we need to exist formally and we're in talks to see how we morph into something more permanent right now.
Speaker 1:I love it Great. I'm very much looking forward to that, definitely would love to continue being a part of it and just staying abreast with all the different findings and resources that hopefully will soon come to be, as a result of all the data that's being collected and eventually compiled into perhaps something that, like you just mentioned, a well-researched decision tree that would be able to be utilized by a variety of different stakeholders in the industry. I very much continue to look forward to being a part of SafeAI, continue to spreading the information on the industry to our audience here at the podcast and just being able to continue the conversation. So thank you so very much, holly, for joining us, and you are so welcome. Is there anything you would like to share with the general audience about safe AI?
Speaker 2:We are always open to new stakeholder members. Please come and join us. You know, shoot me an email through the site or you know, because they all come to me, because I'm PR, but I'm happy to put you on any of the committees. We, you know, the more hands, the better. This is the kind of thing that, on a personal level, can raise your profile, if that's your thing, but also it's very satisfying to be able to contribute to the industry and to leave a legacy of okay after I'm gone. The ethics will still be maintained, the language access, broad access in this country will still be maintained. I think it's all of our duty to move the profession forward and this is one way that you can do that. So if you have time, I could use some hands and brains. Come on over.
Speaker 1:Absolutely and I totally agree. I think it's definitely a moment in time in which we haven't had necessarily the opportunity Many of the standards, potentially in other areas, were created before some of our times in the industry, once we joined the industry, and this is definitely a great moment to take part, to be a part of the solution, to be a part of the decision making or even just to have your voice counted. There are so many different skill sets that you're able to put into service with something such as safe AI, and so I definitely agree with Holly please take part in this.
Speaker 2:Visit their website, which is what Holly Ah, yes, safe a I t forg, right.
Speaker 1:Safe a I t forg, and I'll make sure to have the the link to their website, of course, in the episode notes, as always and the ability for you to be able to look a little bit into Safe AI and its mission and hopefully, you're able to have more interested parties take part in Safe AI and volunteer their time. Once again, holly, thank you so very much for the opportunity and I look forward to sharing your episode with this audience. Thank you so much. Have a great day.
