1 00:00:00,160 --> 00:00:03,840 So my final take is that in using AI avatars in your videos, 2 00:00:03,840 --> 00:00:07,000 you really need to know your audience and know your purpose of your video. So 3 00:00:07,000 --> 00:00:10,000 if you are creating a video that is long, 4 00:00:10,400 --> 00:00:14,240 instructional screen based, it's okay to have some flexibility to try 5 00:00:14,240 --> 00:00:17,280 and add an AI avatar. But if you're creating a personal 6 00:00:17,840 --> 00:00:21,480 or sensitive or small team recording, just an update, 7 00:00:21,480 --> 00:00:25,240 it's not appropriate to replace a human presenter with AI avatars. So make sure that 8 00:00:25,240 --> 00:00:28,880 you know your audience, know your message and act appropriately in your 9 00:00:28,880 --> 00:00:32,560 videos. Good morning, good evening, good 10 00:00:32,560 --> 00:00:36,280 afternoon, wherever you are and wherever you're watching. My name is Matt Pierce, Sosa Visual 11 00:00:36,280 --> 00:00:40,040 Lounge and we are back with more AI research. That's right. If you 12 00:00:40,120 --> 00:00:43,800 listen to or watch the last episode, we talked about AI voices, 13 00:00:43,880 --> 00:00:47,480 AI voice generation and some of the impact there, some what people thought about 14 00:00:47,480 --> 00:00:51,280 them, how it can affect learning. Today we're going the next step further. We're going 15 00:00:51,280 --> 00:00:55,080 to be talking about AI avatars. So you might be on the fence here. You 16 00:00:55,080 --> 00:00:58,670 might be like, I don't know, I don't know about AI avatars. You might be 17 00:00:58,670 --> 00:01:01,510 on the side of you love them because they make your work faster and easier 18 00:01:01,510 --> 00:01:04,870 and you can produce more content. Or you might be on the other side where 19 00:01:04,870 --> 00:01:08,030 you're like, no way, I will never use an AI avatar. I don't like them. 20 00:01:08,030 --> 00:01:11,470 Whatever it might be, there is information here that you might find valuable 21 00:01:11,710 --> 00:01:15,350 based on research. So let's go ahead and jump back in and introduce our 22 00:01:15,350 --> 00:01:18,750 guest today, Stephanie Warnhoff. She's a market researcher for 23 00:01:18,750 --> 00:01:22,280 TechSmith and she has done this great research study. So Stephanie, Stephanie, 24 00:01:22,280 --> 00:01:26,120 welcome back to the Visual Lounge. Oh, thank you. Thank you very much. 25 00:01:26,120 --> 00:01:29,920 Good afternoon, Matt. Yeah, good afternoon. Well, we're going to dive in because there's 26 00:01:29,920 --> 00:01:33,760 so much here I think that's worth covering and I think this is so 27 00:01:33,760 --> 00:01:37,320 everyone for context, this is part of our AI research. We'll post the link in 28 00:01:37,320 --> 00:01:40,960 the context below so you can find that blog post in the PDF. So 29 00:01:40,960 --> 00:01:44,640 Stephanie, as you started going part through this research and you started learning from what 30 00:01:44,640 --> 00:01:48,410 people were saying, particularly with AI avatars, we what surprised you 31 00:01:48,410 --> 00:01:52,250 most in particular about what you found. So 32 00:01:52,250 --> 00:01:56,010 we ran basically the same, similar type of study. We 33 00:01:56,010 --> 00:01:59,370 had five different videos that we showed each 34 00:01:59,370 --> 00:02:02,930 individual participant. One. So one was using a human 35 00:02:02,930 --> 00:02:06,650 avatar in picture, in picture, so small circle kind of taking up, you 36 00:02:06,650 --> 00:02:09,930 know, a quarter of the screen. Then we had the human full screen which was 37 00:02:09,930 --> 00:02:13,530 more like half and half. Then we had an AI avatar that was also 38 00:02:13,530 --> 00:02:17,170 picture in Picture an AI avatar that was full screen, which is about half the 39 00:02:17,170 --> 00:02:20,270 screen. And then we had an audio visualizer, which is a 40 00:02:20,670 --> 00:02:24,270 feature that you can include in your Camtasia videos. But it is basically a still 41 00:02:24,270 --> 00:02:28,030 image with a bubble around it, for lack 42 00:02:28,030 --> 00:02:31,150 of a better word, that shows kind of the waveforms when someone is speaking. So 43 00:02:31,150 --> 00:02:34,950 it's not a moving video, but it is movement and engaging for your 44 00:02:34,950 --> 00:02:38,670 eyes. So we had those five videos and I think the thing that 45 00:02:38,670 --> 00:02:42,430 surprised me the most was that on the AI avatar side 46 00:02:42,430 --> 00:02:46,190 that participants felt like the smaller picture in picture avatar was 47 00:02:46,190 --> 00:02:49,930 actually higher quality than the full screen AI avatar. I think 48 00:02:49,930 --> 00:02:53,730 I was thinking, okay, bigger is better. So the bigger the avatar is, 49 00:02:53,730 --> 00:02:56,370 the bigger the human is, the higher quality they're going to think it is. And 50 00:02:56,370 --> 00:03:00,050 that was just not correct. It was not correct in terms of what they 51 00:03:00,050 --> 00:03:03,610 felt like for high quality. And it wasn't, it wasn't 52 00:03:03,610 --> 00:03:07,290 the biggest. When we talk about learning retention, which we'll get to later on, 53 00:03:07,450 --> 00:03:11,090 but 31% more participants felt that the smaller AI 54 00:03:11,090 --> 00:03:14,690 avatar was either good or excellent quality versus that full screen 55 00:03:14,690 --> 00:03:18,300 AI avatar. And we did have an open ended comment section there as well that 56 00:03:18,300 --> 00:03:21,900 let us know that basically with that larger on screen avatar, the tiny 57 00:03:21,900 --> 00:03:25,580 motions that make AI avatars look, I mean, kind of fake 58 00:03:25,580 --> 00:03:28,940 were more noticeable. So like the facial expressions, the kind of 59 00:03:28,940 --> 00:03:32,660 imperfect eye contact, kind of robotic sounding voice was more 60 00:03:32,660 --> 00:03:36,100 noticeable because that avatar was taking up more of the screen real estate 61 00:03:36,260 --> 00:03:40,020 on the screen. So although it's the most surprising thing, 62 00:03:40,100 --> 00:03:43,220 once I looked at the data and read through those comments, I could completely understand 63 00:03:43,220 --> 00:03:46,420 why people focused on felt that way. Yeah, well, we actually 64 00:03:46,740 --> 00:03:50,500 have the, the snippets of those. I think we're gonna. Let's play those now 65 00:03:50,500 --> 00:03:53,740 since you've described them so we can see them now. If you're a podcast listener, 66 00:03:53,740 --> 00:03:57,420 you can't see obviously through the podcast. I recommend you go check out our YouTube 67 00:03:57,420 --> 00:04:00,860 channel or on the Visual Lounge. We've been starting to post the videos from YouTube 68 00:04:00,860 --> 00:04:04,140 so you can check it out there. Anything we should know before we watch this 69 00:04:04,140 --> 00:04:07,980 beside beyond what you've already said, Stephanie? I don't think so. 70 00:04:07,980 --> 00:04:11,540 But just remember that each participant only saw one of these videos. This is kind 71 00:04:11,540 --> 00:04:14,900 of a montage of all five smashed together. So you'll notice kind of the cuts 72 00:04:14,900 --> 00:04:17,960 of, you know, or so seconds. It'll flip to another one. So this is not 73 00:04:17,960 --> 00:04:21,800 exactly what they saw, but it's one part of what they saw. We 74 00:04:21,800 --> 00:04:25,080 get the benefit of seeing all of them. But yeah, participants only saw a month, 75 00:04:25,080 --> 00:04:28,840 so. Well, let's go ahead and watch that. Google search results can be 76 00:04:28,840 --> 00:04:32,080 a bit much sometimes. A simple search like what is the best 77 00:04:32,080 --> 00:04:35,360 sunscreen? Is full of ads and profit driven biases. 78 00:04:35,680 --> 00:04:39,440 Google search results can be a bit much sometimes. A simple search like 79 00:04:39,520 --> 00:04:43,000 what is the best sunscreen? Is full of ads and profit driven 80 00:04:43,000 --> 00:04:46,760 biases. Google search results can be a bit much sometimes. 81 00:04:46,760 --> 00:04:50,600 A simple search like what is the best sunscreen? Is full of ads and 82 00:04:50,600 --> 00:04:54,120 profit driven biases. Google search results can be a bit 83 00:04:54,120 --> 00:04:57,840 much. A simple question like what is the best sunscreen? Is 84 00:04:57,840 --> 00:05:01,560 full of ads and profit driven biases. Google search results can 85 00:05:01,560 --> 00:05:04,800 be a bit much. A simple question like what is the best 86 00:05:04,800 --> 00:05:08,000 sunscreen? Is full of ads and profit driven biases. 87 00:05:09,600 --> 00:05:13,400 Okay, so we've got a few, few different options there. Obviously there's a 88 00:05:13,400 --> 00:05:16,760 human in there. There's the audio 89 00:05:16,760 --> 00:05:20,520 visualizer with the rings around it of a still image. Got lots to look 90 00:05:20,520 --> 00:05:24,320 at. Now one thing, Stephanie, you've worked on some of our other research projects 91 00:05:24,320 --> 00:05:27,960 as well. And in past research we've seen like, you know, 92 00:05:27,960 --> 00:05:31,560 most people prefer a real human over some type of 93 00:05:31,560 --> 00:05:35,240 AI avatar. Yet when we actually did this test, you know, 94 00:05:35,240 --> 00:05:39,040 this experiment here, this research, it looks like learners actually 95 00:05:39,040 --> 00:05:42,640 rated AI avatars equally or as 96 00:05:42,800 --> 00:05:46,000 equal professional kind of level as those as the humans. 97 00:05:46,720 --> 00:05:50,140 So one thing that stands out to me is that I think it was like 98 00:05:50,140 --> 00:05:53,580 92% of viewers rated avatar videos as professional 99 00:05:53,740 --> 00:05:57,020 and they would watch another video from that creator. 100 00:05:57,580 --> 00:06:01,020 What's the explanation between kind of that gap of what we've seen in past research 101 00:06:01,900 --> 00:06:05,660 and now how people are kind of judging the quality of the overall 102 00:06:05,660 --> 00:06:09,300 videos that are with avatars in them? Any sense of what's 103 00:06:09,300 --> 00:06:13,100 changing out there for people? You know, we deal with this a lot 104 00:06:13,100 --> 00:06:16,820 in research. The difference between what people either say or what they 105 00:06:16,820 --> 00:06:20,640 say they're going to do versus what they either actually do or their actual behavior 106 00:06:20,640 --> 00:06:24,160 shows. So there's research that says that the best predictor of future 107 00:06:24,160 --> 00:06:27,960 behavior is actually your past behavior. Right? So if you say I'm going 108 00:06:27,960 --> 00:06:31,520 to go to the gym every day this year, but actually the better predictor would 109 00:06:31,520 --> 00:06:33,920 be how many days out of the week did you go to the gym last 110 00:06:33,920 --> 00:06:36,440 year is a better predictor of actually what you're going to do in the future. 111 00:06:36,760 --> 00:06:40,280 So we have trouble reconciling this often with research. You know, do we, do we 112 00:06:40,280 --> 00:06:44,080 listen to what they say or do we watch what they do? And for 113 00:06:44,080 --> 00:06:47,920 this example, I'M not saying that people were incorrect when they said what they 114 00:06:47,920 --> 00:06:51,580 prefer, but I do want to point out that although this video viewer research is 115 00:06:51,580 --> 00:06:55,380 not old by any stretch, there has been huge 116 00:06:55,380 --> 00:06:59,180 advancements in AI between. Even when we ran that study at the end of 117 00:06:59,180 --> 00:07:02,860 2024 and this study that we're sharing now at the beginning of 2026, I 118 00:07:02,860 --> 00:07:05,940 mean, 18 months, things have changed so much. 119 00:07:06,819 --> 00:07:10,660 And so saying that they did prefer a human visual presenter at 120 00:07:10,660 --> 00:07:14,220 that time versus actual higher quality AI avatar 121 00:07:14,220 --> 00:07:17,930 presenter during the study is a little bit off. So they're 122 00:07:17,930 --> 00:07:21,770 not exactly comparing the AI avatars versus each other in this new study. 123 00:07:21,770 --> 00:07:24,970 Right. I mentioned they only saw one of these videos. They're not comparing the human 124 00:07:24,970 --> 00:07:28,490 to the AI, they're seeing one in isolation and basically had to 125 00:07:28,490 --> 00:07:32,290 evaluate the professionalism without comparing to what everyone else was seeing. So when 126 00:07:32,290 --> 00:07:34,930 they actually view a video and are trying to learn from it, they look at 127 00:07:34,930 --> 00:07:38,450 the screen content, they look at the size of the avatar, the voice that was 128 00:07:38,450 --> 00:07:41,810 used, you know, the facial movements, the tone of voice, everything. So this 129 00:07:41,810 --> 00:07:45,330 entire package is what viewers are evaluating when they say a video is 130 00:07:45,330 --> 00:07:48,570 professional. And I will point out that actually in this study, almost 131 00:07:48,650 --> 00:07:52,330 50% of them did not know it was an AI avatar. So the 132 00:07:52,330 --> 00:07:55,610 knowledge of it being an AI avatar didn't really affect their 133 00:07:55,610 --> 00:07:59,210 perception certainly of the professionalism or their perception of the quality. 134 00:07:59,930 --> 00:08:03,690 Yeah, which is, which is super interesting that people couldn't tell for whatever, for 135 00:08:03,690 --> 00:08:06,490 whatever reason. But you're right, the gap between 136 00:08:06,890 --> 00:08:10,650 2024 and beginning here of 2026 is, 137 00:08:11,050 --> 00:08:14,780 it's huge for AI. And so I think, yeah, it does 138 00:08:14,780 --> 00:08:18,380 make sense that maybe people's perceptions are changing. I know when you look at the 139 00:08:18,380 --> 00:08:22,220 quality of avatars or the quality of the technology, what it's able to 140 00:08:22,220 --> 00:08:25,060 produce is just a different scale, Right? 141 00:08:25,780 --> 00:08:29,140 Absolutely. So in the research, 142 00:08:29,780 --> 00:08:33,300 one of the questions or I guess we alluded to or looked at was 143 00:08:33,460 --> 00:08:37,100 when to use an avatar and when not to use avatars. Because I think this 144 00:08:37,100 --> 00:08:40,380 is important because I think a lot of us who are in the learning and 145 00:08:40,380 --> 00:08:44,210 development space, not everything is as clear cut as like just use 146 00:08:44,210 --> 00:08:47,410 it, or maybe it's not use it. We're looking for that guidance. We're still trying 147 00:08:47,410 --> 00:08:50,850 to figure these norms out of what makes sense. Are there any 148 00:08:50,850 --> 00:08:54,410 highlights from the research about when we should use avatars, not use 149 00:08:54,410 --> 00:08:58,009 avatars, any impact on maybe or 150 00:08:58,009 --> 00:09:01,450 perceived impact on trust when we are or are not using them? 151 00:09:02,570 --> 00:09:06,370 Yeah, that's a great question. We pretty much specifically did address that exact 152 00:09:06,370 --> 00:09:09,290 fact in the survey. So there was a question that basically said, 153 00:09:10,430 --> 00:09:14,190 when is it acceptable? In what style of video is it acceptable to use an 154 00:09:14,190 --> 00:09:17,950 AI avatar to you? And we got pretty clear answers on that. So in 155 00:09:17,950 --> 00:09:21,710 our study, our viewers were most accepting of an AI avatar in 156 00:09:21,710 --> 00:09:25,390 an instructional or a video that heavily featured screen 157 00:09:25,390 --> 00:09:28,990 based content. They were least comfortable when a personal 158 00:09:29,070 --> 00:09:32,750 presence was needed, like a welcome video from a CEO 159 00:09:32,750 --> 00:09:36,510 or a team update video, for example. Now, we didn't specifically ask 160 00:09:36,510 --> 00:09:39,830 about trust, but you can kind of infer that if they found an AI 161 00:09:39,830 --> 00:09:43,190 avatar acceptable, they would be like more okay with that video 162 00:09:43,190 --> 00:09:46,830 overall. So if an AI avatar is used in a video that was 163 00:09:46,830 --> 00:09:50,630 meant to distribute maybe personal or sensitive information, it could 164 00:09:50,630 --> 00:09:54,070 really turn off your viewers. So our advice here at least is to be 165 00:09:54,070 --> 00:09:57,790 intentional about the message of the videos, know your audience, and 166 00:09:58,110 --> 00:10:01,310 kind of proceed, you know, with that information in mind. 167 00:10:02,220 --> 00:10:05,820 Well, if I could follow up a little bit on that. It also seems like 168 00:10:05,980 --> 00:10:09,340 the thing that you said earlier that 50% of people didn't know 169 00:10:09,980 --> 00:10:13,340 when something was an avatar also maybe plays into 170 00:10:13,740 --> 00:10:17,579 that kind of trust issue. If I don't know it's an avatar 171 00:10:17,579 --> 00:10:21,380 and all of a sudden it's delivered maybe a very serious message that's 172 00:10:21,380 --> 00:10:25,060 maybe inappropriate for an avatar that causes potentially real issues, 173 00:10:25,060 --> 00:10:28,540 right? Yeah, absolutely. I mean, there's the 174 00:10:28,540 --> 00:10:31,860 knowledge of whether it's an AI avatar to begin with and then there's the message 175 00:10:31,860 --> 00:10:35,600 or the content that's trying to be delivered. So that's two separate factors there. And 176 00:10:35,600 --> 00:10:39,160 you're right. If they don't necessarily know it's an avatar, it can 177 00:10:39,160 --> 00:10:43,000 definitely seem sneaky, for lack of a better word. 178 00:10:43,000 --> 00:10:46,800 If you're trying to, you know, use AI as a blanket for every human 179 00:10:46,800 --> 00:10:50,600 visual presenter and every style of video and your viewers. And 180 00:10:50,600 --> 00:10:53,840 especially if it's something like I mentioned, like a sensitive topic or a small team 181 00:10:53,840 --> 00:10:57,680 update that's really going to make people, you know, sour on 182 00:10:57,680 --> 00:11:01,440 your video because it's just not the appropriate metric. You should have spent, you 183 00:11:01,440 --> 00:11:04,870 know, maybe an extra several minutes or however long it would take to be a 184 00:11:04,870 --> 00:11:08,710 visual presenter in that video to kind of humanize that video quite a bit more. 185 00:11:09,590 --> 00:11:13,350 Yeah, I'm waiting for the news articles to talk about the organization. 186 00:11:13,670 --> 00:11:17,270 Hopefully never. But you know, use uses the AI to 187 00:11:17,350 --> 00:11:20,990 avatar to lay off the workers or major 188 00:11:20,990 --> 00:11:24,670 changes. We don't look forward to that day. But obviously there are some impacts 189 00:11:24,670 --> 00:11:28,430 here. One, one of the impacts I think my audience is really interested in 190 00:11:28,430 --> 00:11:32,230 is the learning aspect. Right. So You've got lots of 191 00:11:32,230 --> 00:11:35,910 ways you could present content for people to learn from, particularly 192 00:11:35,910 --> 00:11:39,390 from what you found in this research. Was there anything interesting about the type of 193 00:11:39,390 --> 00:11:43,110 presentation of humans versus avatars and kind of 194 00:11:43,110 --> 00:11:46,230 overall effectiveness in being able to perform a task? 195 00:11:47,350 --> 00:11:50,030 Yeah, I mean, I kind of hit on this a little bit earlier too. But 196 00:11:50,030 --> 00:11:53,710 in terms of the actual learning retention, the differences between four of the five 197 00:11:53,710 --> 00:11:57,290 video types were very slight. Between the human full screen, human 198 00:11:57,290 --> 00:12:00,690 picture in picture, the avatar full screen, and the audio visualizer. 199 00:12:01,250 --> 00:12:04,330 We basically asked them kind of a pop quiz to answer a question that they 200 00:12:04,330 --> 00:12:07,450 saw in the video. And between those four types of video, there was only really 201 00:12:07,450 --> 00:12:10,890 a 3% difference in the amount of people that got the correct answer. So the 202 00:12:10,890 --> 00:12:14,690 difference was very slight. But one of them really excelled above those, and that 203 00:12:14,690 --> 00:12:18,330 is the avatar picture in picture, which actually performed 13% 204 00:12:18,330 --> 00:12:21,890 better than any of those other four examples. So 205 00:12:22,210 --> 00:12:24,970 I talked about this a little bit at the beginning, but people really rated that 206 00:12:24,970 --> 00:12:28,800 video as higher quality. But alongside that, they got, you 207 00:12:28,800 --> 00:12:32,480 know, the information that they received from that video. They were able to, you know, 208 00:12:32,640 --> 00:12:36,360 internalize and answer a question later on in the survey more correctly with 209 00:12:36,360 --> 00:12:40,000 that style of video. So like I said, they also had that 210 00:12:40,000 --> 00:12:43,680 video also had the highest number of people that felt it was 211 00:12:43,680 --> 00:12:47,160 professional, and it also had a higher learning retention. That's kind of like two stars 212 00:12:47,160 --> 00:12:50,560 for that style of video, for sure. Yeah. And, you know, I 213 00:12:50,800 --> 00:12:54,560 can think about different research from a different era. Right. Not looking 214 00:12:54,560 --> 00:12:58,190 at avatars at all, but about on camera presence and, um, 215 00:12:58,190 --> 00:13:01,470 you know, I think one thing that's always been interesting to me that with on 216 00:13:01,470 --> 00:13:05,310 camera presence and again, not avatars, the research typically shows that 217 00:13:06,030 --> 00:13:09,870 performance doesn't change, but people have a preference for it. Right. They 218 00:13:09,870 --> 00:13:13,310 like having a person there or face there, but it's never. 219 00:13:13,870 --> 00:13:17,150 It's, you know, usually a picture in picture, not all the time on screen. So 220 00:13:17,150 --> 00:13:20,550 there are some elements that I think we could probably translate. But it is interesting 221 00:13:20,550 --> 00:13:24,350 that they actually still perform better on the task. It's one of those ones. I'm 222 00:13:24,350 --> 00:13:27,950 like, Stephanie, let's do more research on that. Let's find somebody to help us do 223 00:13:27,950 --> 00:13:31,790 that, because that's super interesting about why that might be. And I know 224 00:13:31,790 --> 00:13:35,470 we don't have answers for that, but something I'm definitely, definitely curious about. 225 00:13:36,350 --> 00:13:39,870 And it does lead to the question of, like, as people are 226 00:13:40,030 --> 00:13:42,510 leaning in here, maybe using more 227 00:13:43,390 --> 00:13:46,670 avatars or want to use more avatars in their work, 228 00:13:47,390 --> 00:13:51,070 is there advice that you can give us? Obviously, you're not an instructional 229 00:13:51,070 --> 00:13:54,430 designer, you're not creating training videos. But from the research that you're seeing, 230 00:13:55,580 --> 00:13:58,780 any advice that you could give people to help them use them maybe more strategically 231 00:13:58,860 --> 00:14:02,460 or more effectively, I would say. Just 232 00:14:02,460 --> 00:14:06,140 overall, and I think I said this with the AI voice research as well, is 233 00:14:06,140 --> 00:14:09,820 if you have the flexibility and the buy in, you should try 234 00:14:09,820 --> 00:14:13,460 it. It's not a you should never use this or you should always 235 00:14:13,460 --> 00:14:17,180 use this. But my advice is to give it a try, kind of see 236 00:14:17,180 --> 00:14:20,260 how it works out for you and your audience. And this study proves to me 237 00:14:20,260 --> 00:14:23,900 that viewers are willing to watch videos with AI avatars, 238 00:14:24,060 --> 00:14:27,880 accept the style, and really believe that the qual is sometimes good or even better 239 00:14:27,880 --> 00:14:31,160 than with a human presenter. So for most cases, using an ar, 240 00:14:31,560 --> 00:14:35,120 excuse me, AI avatar will not harm your video. It could even help 241 00:14:35,120 --> 00:14:38,880 increase the information that your viewers retain. Now, there is an exception to 242 00:14:38,880 --> 00:14:42,520 that which I touched on earlier, which is if your video is personal 243 00:14:42,760 --> 00:14:46,440 or sensitive or something that really does need a human touch, we would not 244 00:14:46,440 --> 00:14:50,240 recommend using an AI avatar for that situation because the viewers have told us 245 00:14:50,240 --> 00:14:53,870 that that is not an acceptable use of that style. So I 246 00:14:53,870 --> 00:14:57,710 certainly wouldn't say replace 100% of your human presenters with AI avatars. 247 00:14:57,710 --> 00:15:01,510 But like I said earlier, I'd say know your video message, know your audience, 248 00:15:01,510 --> 00:15:04,790 and basically proceed within reason. It's, 249 00:15:05,270 --> 00:15:08,510 there's a comedian out there. I won't go into the whole story, but I'll rephrase. 250 00:15:08,510 --> 00:15:11,110 One of the things that he would say and make it for this is like, 251 00:15:11,110 --> 00:15:14,550 don't go avatar ing where you don't need no avatar in. Right? Like, 252 00:15:15,270 --> 00:15:19,120 just don't, don't, don't go there. I, 253 00:15:19,120 --> 00:15:22,800 I think there's, there's, like I mentioned at the kind of the opening, there are 254 00:15:22,800 --> 00:15:26,440 people who are very skeptical and maybe hesitant 255 00:15:26,440 --> 00:15:29,280 about avatars. And, and I love the advice, like if you have the means, you 256 00:15:29,280 --> 00:15:32,760 have the kind of go ahead to try. But 257 00:15:32,760 --> 00:15:36,400 anything specific out there for those people who are maybe saying no, I, 258 00:15:36,560 --> 00:15:39,280 I'm negative towards these. I don't. Why would I want to use them 259 00:15:40,640 --> 00:15:44,240 that we might. I. Look, I'm not trying to shift anyone's opinion here. We're not 260 00:15:44,240 --> 00:15:47,990 trying to make giant waves, but I'm curious that it's a new technology, looks like 261 00:15:47,990 --> 00:15:51,230 it has some potential. So what would we say to those folks who are a 262 00:15:51,230 --> 00:15:54,950 little bit still on that, who are on that negative side? I 263 00:15:54,950 --> 00:15:58,630 would kind of think about why they're skeptical. I'd say is it because they have 264 00:15:58,630 --> 00:16:02,190 a mistrust of AI in general. There's kind of a sentiment towards that just in 265 00:16:02,190 --> 00:16:05,630 culture today. Or is it because they have seen 266 00:16:05,710 --> 00:16:09,510 videos where the AI avatar is terrible and it turned them off 267 00:16:09,510 --> 00:16:13,190 from a video? So I think it's important to stay up to date on 268 00:16:13,190 --> 00:16:16,950 what avatars look like and how far they have advanced to look human like, 269 00:16:16,950 --> 00:16:20,570 as well as understanding basically what AI avatars can and cannot do. 270 00:16:20,730 --> 00:16:24,370 As I mentioned with the particular types of videos earlier, you cannot replace 271 00:16:24,370 --> 00:16:28,130 or you should not replace an AI avatar for a sensitive 272 00:16:28,130 --> 00:16:31,930 or personal or, you know, small group video. But if 273 00:16:31,930 --> 00:16:35,330 you're making a, you know, an instructional video that 274 00:16:35,330 --> 00:16:39,090 primarily has a lot of screen content and you're looking 275 00:16:39,090 --> 00:16:42,850 for something to provide a little visual interest or help engage 276 00:16:42,850 --> 00:16:46,490 your viewers a little bit more, our research shows that viewers would be accepting of 277 00:16:46,490 --> 00:16:50,090 an AI avatar in that situation. So if that's the type of video you're creating, 278 00:16:50,090 --> 00:16:53,870 I think you have more leeway in terms of trying to include that in 279 00:16:53,870 --> 00:16:57,510 your videos, but not on the alternative. As I mentioned, personal, 280 00:16:57,590 --> 00:17:00,790 sensitive, you know, human touch. Don't do it. 281 00:17:01,190 --> 00:17:05,030 Yeah, absolutely, Absolutely. Okay, so we've covered a lot 282 00:17:05,030 --> 00:17:08,870 of research and again, it's out there on the TechSmith blog. I'm curious, 283 00:17:09,110 --> 00:17:12,870 any questions that let's say we're looking at doing this again? 284 00:17:12,870 --> 00:17:16,390 I hope we do. I hope we look at some other kind of related 285 00:17:16,550 --> 00:17:20,260 areas. But any questions you'd want to try to answer if 286 00:17:20,260 --> 00:17:24,020 and when you get a chance to do research again? Yeah, I 287 00:17:24,020 --> 00:17:27,780 think the first thing is I would like to try and kind of compare these 288 00:17:27,780 --> 00:17:30,940 videos to each other. Now I mentioned we did not do that in the study. 289 00:17:30,940 --> 00:17:34,100 We had them watch one video and answer the questions. But I'd like to kind 290 00:17:34,100 --> 00:17:37,940 of play around with trying to have them watch maybe a human 291 00:17:37,940 --> 00:17:41,500 full screen and a human pip video and, you know, use that high 292 00:17:41,500 --> 00:17:44,940 quality voice and kind of have them rate them versus each other 293 00:17:45,100 --> 00:17:48,620 and kind of look at different aspects of that, whether, you know, we already talked 294 00:17:48,620 --> 00:17:52,440 about learning, retention, maybe engagement, you know, which one do they feel 295 00:17:52,440 --> 00:17:55,800 is more professional so that we can kind of evaluate one versus the other. 296 00:17:56,360 --> 00:17:59,840 I'd also like to dig a little bit more deeper on engagement. We did not 297 00:17:59,840 --> 00:18:03,520 really talk very much about engagement in this survey at all. But that 298 00:18:03,520 --> 00:18:06,760 is primarily the focus of the video viewer study, which we did at the end 299 00:18:06,760 --> 00:18:10,520 of 2024. So probably what my dream state would be would to 300 00:18:10,520 --> 00:18:14,320 rerun this study but include a ton of metrics about engagement 301 00:18:14,320 --> 00:18:18,040 and have them, you know, do multiple Videos versus each other, human versus 302 00:18:18,040 --> 00:18:21,850 AI engagement, professionalism, quality, and probably be a 303 00:18:21,850 --> 00:18:24,690 mega study. I don't know if my stakeholders will go for that because that seems 304 00:18:24,690 --> 00:18:26,610 like a really big project. But I think it would be cool to kind of 305 00:18:26,610 --> 00:18:30,450 mix those two and make one big study. Well, you've got my 306 00:18:30,450 --> 00:18:33,810 support. Not that that means much, but I love the research 307 00:18:33,970 --> 00:18:37,730 that you've done. And Stephanie, I think that 308 00:18:37,730 --> 00:18:41,370 the thing that's really interesting to me about this is that one, we are in 309 00:18:41,370 --> 00:18:45,130 this new era of this new technology that it is still a very 310 00:18:45,130 --> 00:18:48,830 wide open, we don't know what we don't know kind of space. 311 00:18:49,150 --> 00:18:52,830 And I'm. And I think there's a lot to learn and lot to understand. 312 00:18:52,910 --> 00:18:56,510 So I'm grateful that you were willing to dive in. You and Troy 313 00:18:56,510 --> 00:19:00,150 Stein really spearheaded this. And I'm just 314 00:19:00,150 --> 00:19:03,870 blown away that it gives me at least something, at least for now, 315 00:19:04,030 --> 00:19:07,870 knowing that in all of its imperfections, all the questions it doesn't answer because 316 00:19:07,870 --> 00:19:11,350 that's good research. It never answers all the questions. It just creates more questions. 317 00:19:11,350 --> 00:19:14,900 Typically. I love that it gives me at least a little bit of 318 00:19:14,900 --> 00:19:18,580 guidance and direction because I'll be honest, I was a little 319 00:19:18,580 --> 00:19:22,220 skeptical of avatars. And this has given me a little bit of that 320 00:19:22,220 --> 00:19:24,900 impetus to feel like, yeah, I can, I can try doing that. I should try 321 00:19:25,140 --> 00:19:28,740 using those a little bit more to see what's going to be most effective, particularly 322 00:19:28,740 --> 00:19:32,580 on those repeatable things that change often because that's, you know, 323 00:19:33,060 --> 00:19:36,860 if you got me, I can't record the same video a year 324 00:19:36,860 --> 00:19:40,060 from now and have it look and feel the same. But an avatar, pretty sure 325 00:19:40,060 --> 00:19:43,690 I can get them to be the same. So. Well, Stephanie, before 326 00:19:43,690 --> 00:19:47,530 we go into our closing, anything else that we missed or didn't cover 327 00:19:47,530 --> 00:19:51,290 that we should talk about for avatars? Probably 328 00:19:51,290 --> 00:19:54,850 not the only my last kind of final two things I like to think about 329 00:19:55,170 --> 00:19:58,650 is if you're interested in using AI avatar in video, my 330 00:19:58,650 --> 00:20:02,490 advice would be to do some research and stay up to date on 331 00:20:02,490 --> 00:20:06,210 what you can and, you know, what's out there and what's available for you. Matt, 332 00:20:06,210 --> 00:20:09,930 as you mentioned, it's moving so fast that probably the research you've done 333 00:20:09,930 --> 00:20:13,310 on Avatars 2 months ago is now may of date. 334 00:20:13,710 --> 00:20:16,470 So try and immerse yourself if you want to use it. Make sure you can 335 00:20:16,470 --> 00:20:20,190 understand how high quality they can be or, you know, what you want to include 336 00:20:20,190 --> 00:20:23,710 in your video. And my other piece of advice, as we learned from the study, 337 00:20:23,710 --> 00:20:27,510 is they are not applicable to all videos so make sure that you 338 00:20:27,510 --> 00:20:31,350 know your message and you know your audience and you choose what is 339 00:20:31,350 --> 00:20:35,030 appropriate for that video versus either, you know, going all in. We 340 00:20:35,030 --> 00:20:38,510 would not necessarily recommend that. All right, well, thank you, 341 00:20:38,510 --> 00:20:42,150 Stephanie. And so if people want to get involved in TechSmith research, we gave this 342 00:20:42,150 --> 00:20:45,210 link last episode, but I think it's helpful to do it again. And where, where 343 00:20:45,210 --> 00:20:48,850 can people connect with you and TechSmith Research? Sure. 344 00:20:48,850 --> 00:20:52,490 So you can connect with me through my personal LinkedIn page, Stephanie Warnhoff. 345 00:20:52,570 --> 00:20:56,170 Or if you are interested in more research at TechSmith, you can 346 00:20:56,250 --> 00:20:59,250 send an email to our research email address, which is just 347 00:20:59,250 --> 00:21:02,650 researchexmith.com we can get you signed up for, 348 00:21:02,970 --> 00:21:06,650 you know, in depth interviews, for beta programs, for receiving some 349 00:21:06,650 --> 00:21:10,290 surveys like this in the future. We have a lot of different research opportunities, so 350 00:21:10,290 --> 00:21:13,140 emailing that email address and we'll basically get you on the list, so. 351 00:21:13,780 --> 00:21:17,620 Perfect. Well, as we like to end most shows, Stephanie, we'd love 352 00:21:17,620 --> 00:21:21,180 to hear from you on your final take. So Stephanie Warhol, what 353 00:21:21,180 --> 00:21:24,980 is your final take? So my final take is that 354 00:21:24,980 --> 00:21:28,660 in using AI avatars in your videos, you really need to know your audience 355 00:21:28,660 --> 00:21:32,420 and know your purpose of your video. So if you are creating a video that 356 00:21:32,420 --> 00:21:36,260 is long, instructional screen based, it's okay 357 00:21:36,260 --> 00:21:39,940 to have some flexibility to try and add an AI avatar. But if you're creating 358 00:21:39,940 --> 00:21:43,420 a personal or sensitive or small team 359 00:21:43,420 --> 00:21:47,180 recording, just an update, it's not appropriate to replace a human presenter with 360 00:21:47,180 --> 00:21:50,660 AI avatars. So make sure that you know your audience, know your message 361 00:21:50,740 --> 00:21:54,540 and act appropriately in your videos. Perfect. Well, 362 00:21:54,540 --> 00:21:58,220 thank you, Stephanie. Thanks for the great research. Awesome. Thank you very much, 363 00:21:58,220 --> 00:22:01,700 Matt. You bet. All right everybody, if you're looking for 364 00:22:01,700 --> 00:22:05,460 AI avatars, also just recommend go try TechSmith 365 00:22:05,460 --> 00:22:09,170 Audio Camtasia Audit. It's got so many great cool features with the app. Got the 366 00:22:09,170 --> 00:22:12,410 avatars, you can try those. You got the new 11 lab voices which sounds so 367 00:22:12,410 --> 00:22:16,130 good. Hard to believe that they are AI. I can see why people 368 00:22:16,130 --> 00:22:19,810 maybe said that's not AI, that's a real person. So go check those out. You 369 00:22:19,810 --> 00:22:23,570 can try it for free. Or if you are using Camtasia, there's a 370 00:22:23,570 --> 00:22:26,730 bunch of audio features that are available to you. The AI features are at the 371 00:22:26,730 --> 00:22:30,570 higher level though, of course. But with that said, you know, part of this, why 372 00:22:30,570 --> 00:22:34,050 we bring forth this research is to help you get better, make better decisions, think 373 00:22:34,050 --> 00:22:37,280 through creating critically about what's going to make for good instruction, what's going to make 374 00:22:37,280 --> 00:22:40,600 for good video. And of course in doing that process, you got to just keep 375 00:22:40,600 --> 00:22:44,360 working at it. Keep trying and keep exploring and keep trying to get better 376 00:22:44,360 --> 00:22:47,760 every single day. And with that said, I hope you take a little time 377 00:22:47,920 --> 00:22:50,720 to level up every single day. Thanks, everybody.