1 00:00:05,280 --> 00:00:10,440 This is identity at the center. If it has anything to do with 2 00:00:10,560 --> 00:00:17,960 IAM, this is the go to podcast now your hosts Jim McDonald and 3 00:00:17,960 --> 00:00:22,960 Jeff Stedman. Welcome to the Identity at the 4 00:00:22,960 --> 00:00:24,720 Center podcast. I'm Jeff and that's Jim. 5 00:00:24,720 --> 00:00:26,400 Hey, Jim. Hey, Jeff, how are you? 6 00:00:26,600 --> 00:00:28,320 Oh, not so bad yourself. Good. 7 00:00:28,720 --> 00:00:31,440 It's been an interesting week so far. 8 00:00:31,680 --> 00:00:32,880 And then we're early in the week. 9 00:00:32,880 --> 00:00:38,520 You and I have been working on the business of a nonprofit. 10 00:00:38,960 --> 00:00:41,680 And I remember we were talking about, OK, how do we set this up 11 00:00:41,680 --> 00:00:44,360 and said nonprofit. Yeah, that sounds easy. 12 00:00:44,360 --> 00:00:48,600 Let's do that. But I mean, if you think about 13 00:00:48,600 --> 00:00:54,680 it, I mean five, almost five years ago, so our unofficial 5 14 00:00:54,680 --> 00:00:57,040 year anniversary is July 2nd, right? 15 00:00:57,040 --> 00:01:00,680 That was when we launched our first episode of the podcast 16 00:01:00,680 --> 00:01:04,800 that was truly pirate radio and we operated for a couple years 17 00:01:04,800 --> 00:01:08,040 just producing podcasts. And then we said, look, we want 18 00:01:08,040 --> 00:01:12,120 to do some more things, bring some more content to our 19 00:01:12,120 --> 00:01:16,520 listeners, and we want to go to conferences like EIC. 20 00:01:16,520 --> 00:01:19,560 And none of that stuff is cheap. I mean, just running a podcast 21 00:01:19,560 --> 00:01:24,400 of high quality is not cheap. And so here we are, right? 22 00:01:24,400 --> 00:01:28,120 We have the nonprofit organization to set up to cover 23 00:01:28,120 --> 00:01:30,200 a lot of that. And it's it's a lot of work. 24 00:01:31,080 --> 00:01:33,040 It is. It has consumed my life I think 25 00:01:33,040 --> 00:01:36,680 since December. I usually take the last couple 26 00:01:36,680 --> 00:01:39,240 weeks off of December to kind of like recharge and going to get 27 00:01:39,240 --> 00:01:41,360 ready. And I spent that entire time 28 00:01:41,960 --> 00:01:43,600 getting trying to get things off the ground. 29 00:01:44,000 --> 00:01:46,760 I really wish there was a like, here's some, here's, here's a 30 00:01:46,760 --> 00:01:49,120 plea, right, for somebody out there like make an easy button 31 00:01:49,120 --> 00:01:50,960 for this. Like, hey, I want to start this 32 00:01:51,280 --> 00:01:55,080 and if you have a service that like helps do nonprofit in a 33 00:01:55,080 --> 00:01:59,280 box, reach out to me because I I would definitely consume that 34 00:01:59,280 --> 00:02:00,760 service. But it is a lot of work. 35 00:02:01,560 --> 00:02:05,640 Well, the other the other big effort now is we're putting more 36 00:02:05,640 --> 00:02:10,120 attention on our YouTube. And so I've been going out and 37 00:02:10,120 --> 00:02:12,480 watching like, how do you grow your YouTube channel? 38 00:02:12,720 --> 00:02:16,280 How do you make better videos? What's the key in here? 39 00:02:16,280 --> 00:02:20,000 OK, it's thumbnails and it's this, but really it's the things 40 00:02:20,000 --> 00:02:23,600 that we've been doing, focusing on the niche, which ours is 41 00:02:23,600 --> 00:02:26,920 digital identity and being consistent. 42 00:02:26,920 --> 00:02:30,520 So we publish an episode every Monday and then a lot of weeks. 43 00:02:30,520 --> 00:02:33,560 It's more than that. So I think we're doing the right 44 00:02:33,560 --> 00:02:35,720 things now. It's, it's tweaking. 45 00:02:36,240 --> 00:02:40,000 But there are also like, OK, well here's you know, you can go 46 00:02:40,000 --> 00:02:45,560 from what we have now like 250 subscribers to thousands. 47 00:02:46,400 --> 00:02:49,160 You can have 100,000 subscribers if you got the credit card 48 00:02:49,160 --> 00:02:53,600 you're willing to swipe. And I I propose a resolution 49 00:02:53,600 --> 00:02:56,880 that we never do that because I don't think that's what we're 50 00:02:56,880 --> 00:02:59,440 all about. I just want to have a a 51 00:03:00,000 --> 00:03:04,320 organically grown YouTube channel just like we did with 52 00:03:04,880 --> 00:03:08,240 the podcast. But I also would say that I'm 53 00:03:08,240 --> 00:03:11,800 not against like asking folks who listen like go out and 54 00:03:11,800 --> 00:03:13,760 subscribe to our YouTube. This is a shameless plug. 55 00:03:13,800 --> 00:03:15,400 Subscribe right is. That I don't mind. 56 00:03:16,040 --> 00:03:18,000 I don't mind doing the shameless plug. 57 00:03:18,000 --> 00:03:19,760 I just don't want to swipe the credit card. 58 00:03:21,120 --> 00:03:24,560 That that does not surprise me based on expense reports that 59 00:03:24,560 --> 00:03:27,400 I've been looking at. Yeah, I don't. 60 00:03:27,400 --> 00:03:31,560 I don't really enjoy spending money aimlessly. 61 00:03:32,840 --> 00:03:36,200 No, I don't think anybody does. But yes, doing more on the 62 00:03:36,200 --> 00:03:38,680 YouTube channel, go like subscribe to all that fun stuff 63 00:03:38,680 --> 00:03:40,520 took us a while to build up the audio here. 64 00:03:40,520 --> 00:03:41,800 We are now trying to build the video. 65 00:03:41,800 --> 00:03:45,320 So we'll see how it goes. But you know we are, we are a 66 00:03:45,320 --> 00:03:46,760 niche podcast. I think we're just helpful. 67 00:03:46,760 --> 00:03:49,760 It's Identity access management, but we are worldwide, we have 68 00:03:49,840 --> 00:03:52,160 listeners 10s of thousands around the world at this point. 69 00:03:52,280 --> 00:03:54,960 And I forget the last count, but I think we were heard in just 70 00:03:54,960 --> 00:03:57,440 about every country in the world, including North Korea, 71 00:03:57,440 --> 00:04:00,320 which I find really interesting. Yeah, we've got one listener 72 00:04:00,320 --> 00:04:03,200 there, I think, Kim. Jong is a IS. 73 00:04:03,240 --> 00:04:07,720 Listening, the Supreme Ruler has somebody in in some office like 74 00:04:07,720 --> 00:04:11,160 making sure that we don't talk negatively about his country and 75 00:04:11,480 --> 00:04:14,920 and we won't if if you help us grow the subscriber piece there. 76 00:04:15,600 --> 00:04:18,519 If you subscribe, we we turn a blind eye to issues like that. 77 00:04:18,519 --> 00:04:19,640 Is that what you're saying, Jim? I hope. 78 00:04:19,680 --> 00:04:21,839 Not, yeah, no. It has some integrity. 79 00:04:22,880 --> 00:04:25,680 Well, you always finish the shows by saying share it with a 80 00:04:25,680 --> 00:04:27,720 friend, share it with an enemy, we don't care as long as you 81 00:04:27,720 --> 00:04:31,280 share it. But also in this, in this day 82 00:04:31,280 --> 00:04:33,520 and age of where we're doing more video, if you look behind 83 00:04:33,520 --> 00:04:36,080 me, if you're listening to audio, you probably, you 84 00:04:36,080 --> 00:04:40,520 obviously can't see it. But I only have one diploma on 85 00:04:40,520 --> 00:04:41,800 the wall. Now I'm going to put the other 86 00:04:41,800 --> 00:04:46,480 one under it and then I'm going to take our Identiverse banner 87 00:04:46,480 --> 00:04:51,200 from last year and put it there. And I mean the biggest thing was 88 00:04:51,200 --> 00:04:54,080 this identiverse banner. It was really cool, you know, 89 00:04:54,080 --> 00:04:55,880 having a room and Identiverse last year. 90 00:04:55,880 --> 00:04:59,720 We're going to have spaces this year to do it again. 91 00:05:00,160 --> 00:05:03,720 But that placard, you know, I valued us so much. 92 00:05:04,080 --> 00:05:07,840 I carried it home all the way from Vegas, back through Atlanta 93 00:05:08,160 --> 00:05:10,600 into Augusta, GA. On foot? 94 00:05:10,840 --> 00:05:12,640 In the snow? Uphill both ways? 95 00:05:13,240 --> 00:05:17,280 No, but. I was on that tram in Atlanta, 96 00:05:17,280 --> 00:05:20,840 which you know, like how many people get on that tram and 97 00:05:20,840 --> 00:05:23,240 don't hold onto a pole or onto something. 98 00:05:23,400 --> 00:05:26,240 And then it comes to the hard stop and they fall all over. 99 00:05:26,400 --> 00:05:30,800 Happens every single time. And like, I'm guarding this 100 00:05:30,800 --> 00:05:35,360 thing with my life to make sure that people fall into the the 101 00:05:35,360 --> 00:05:38,760 Styrofoam placard. Well, it's like, you know, we'll 102 00:05:38,760 --> 00:05:42,120 we'll keep collecting those like Thanos collecting Infinity Gems. 103 00:05:42,120 --> 00:05:44,480 Since we're going to be at Identiverse later this year, I 104 00:05:44,480 --> 00:05:45,760 think we'll have some signings there too. 105 00:05:45,760 --> 00:05:47,840 So hopefully you'll be able to get another one home. 106 00:05:47,840 --> 00:05:50,200 Let's just start building like you know your background, just 107 00:05:50,200 --> 00:05:54,080 be all conference identiverse or you know conference identity at 108 00:05:54,080 --> 00:05:55,320 the center type type stuff behind. 109 00:05:55,320 --> 00:05:56,440 You. My entire home. 110 00:05:57,040 --> 00:06:02,600 My entire home. On the outside, yeah, speaking 111 00:06:02,600 --> 00:06:06,280 Identiverse, we are going to be there. 2024 is coming up and 112 00:06:06,280 --> 00:06:09,840 we've got a discount code for folks so time is running short I 113 00:06:09,840 --> 00:06:11,600 think. I'm not sure if early bird 114 00:06:11,600 --> 00:06:12,800 discount. It's really not early bird at 115 00:06:13,280 --> 00:06:14,560 this point since we're less than a month away. 116 00:06:14,560 --> 00:06:20,200 But if you're a a late attendee you can use the code IDV 2 four 117 00:06:20,200 --> 00:06:24,760 Dash IDAC 25 and then I'll get you 25% off of your 118 00:06:24,760 --> 00:06:26,760 registration. We'll have a link in our show 119 00:06:26,760 --> 00:06:28,520 notes because I know that's really easy to remember. 120 00:06:28,880 --> 00:06:31,160 But if you just check the show notes for us, or if you're 121 00:06:31,160 --> 00:06:33,680 watching on YouTube, I'll have it in the, you know, the thing 122 00:06:33,680 --> 00:06:35,880 below. You'll be able to to grab it 123 00:06:35,880 --> 00:06:38,200 from there. But that is coming up May 28th 124 00:06:38,200 --> 00:06:40,400 to the 31st. Jim, you and I will be in Vegas. 125 00:06:40,400 --> 00:06:44,720 We'll be podcasting and I'll be moderating a panel with our 126 00:06:44,720 --> 00:06:48,080 friends Sean and Atul and others, and just generally 127 00:06:48,080 --> 00:06:52,200 gallivanting around town. As the Upright Gentleman Podcast 128 00:06:52,200 --> 00:06:55,320 too, we're going to be recording podcasts and there's going to be 129 00:06:55,320 --> 00:06:58,720 live listen options. We have two locations we're 130 00:06:58,720 --> 00:07:02,720 going to be podcasting from. So I guess we haven't really 131 00:07:02,720 --> 00:07:05,680 talked about how we're going to, where we're going to publish 132 00:07:05,680 --> 00:07:08,280 those schedules. But I'm thinking on our website, 133 00:07:08,280 --> 00:07:11,920 idacpodcast.com, we can schedule, you know, put out the 134 00:07:11,920 --> 00:07:15,240 schedule so people can either sit in the room with us or 135 00:07:15,440 --> 00:07:17,720 there's another one, which I've been calling the fishbowl 136 00:07:17,720 --> 00:07:21,240 because it's a room with like, glass walls and they're putting 137 00:07:21,240 --> 00:07:26,120 headphones outside of that fishbowl that people can listen 138 00:07:26,120 --> 00:07:28,240 to the conversation that's happening inside. 139 00:07:29,400 --> 00:07:30,120 You know what? I just. 140 00:07:30,240 --> 00:07:32,360 Created more work for me to update the website with a new 141 00:07:32,360 --> 00:07:36,880 schedule and a new apparently a new page and keeping it updated 142 00:07:36,880 --> 00:07:39,360 in case things change throughout the week, which they will. 143 00:07:39,840 --> 00:07:42,080 So thank you for that. How about you do it on LinkedIn 144 00:07:42,080 --> 00:07:43,760 or Twitter or something like that instead? 145 00:07:44,280 --> 00:07:45,960 I'm well, I'll definitely do that. 146 00:07:46,440 --> 00:07:48,200 Definitely. I'll commit to doing that. 147 00:07:49,720 --> 00:07:52,560 But here's the thought I was having is we're going to be in 148 00:07:52,560 --> 00:07:54,120 this fishbowl with the headphones. 149 00:07:54,400 --> 00:07:56,560 Is there going to be some Sandy wipes? 150 00:07:56,560 --> 00:07:59,760 Sanitary wipes to? Because I don't want to put 151 00:07:59,760 --> 00:08:03,520 headphones on that may have been used by several people before 152 00:08:03,520 --> 00:08:04,800 me. Sorry, I just. 153 00:08:05,720 --> 00:08:07,080 I don't want to. That's why I bring my own 154 00:08:07,080 --> 00:08:09,120 monitors, so I'll just use those. 155 00:08:09,720 --> 00:08:14,360 OK, well everyone else will have to use use those, so. 156 00:08:14,880 --> 00:08:18,040 Yeah, the filthy unwashed peasants around us watching. 157 00:08:20,200 --> 00:08:22,320 Yeah, that's not the only conference we have coming up, 158 00:08:22,320 --> 00:08:25,800 right. We've got the a discount code 159 00:08:25,800 --> 00:08:28,640 for folks who are going to be going right to the European 160 00:08:28,880 --> 00:08:34,200 identity and Cloud conference EIC in Berlin which is the week 161 00:08:34,200 --> 00:08:37,440 after I dinner versus June 4th through 7th in Berlin. 162 00:08:38,400 --> 00:08:45,440 Discount code is EIC 24, IDAC 25 gets you 25% off. 163 00:08:45,640 --> 00:08:49,520 The link will be in the in the show notes. 164 00:08:49,520 --> 00:08:54,560 Or you can go to Cooper Coal dot com and navigate your way there, 165 00:08:54,560 --> 00:08:57,400 but the discount code will work the same either way. 166 00:08:57,800 --> 00:09:01,920 And then Identity Week. We'll be at the Identity Week 167 00:09:01,920 --> 00:09:05,360 America in Washington DC September 11th and 12th. 168 00:09:05,680 --> 00:09:10,800 There's also one in Europe June 11th through 12th in Amsterdam 169 00:09:11,080 --> 00:09:14,520 and Asia. Identity Week Asia is in 170 00:09:14,520 --> 00:09:21,320 Singapore October 22nd and 23rd. Discount code IDAC 30 which will 171 00:09:21,320 --> 00:09:24,320 give you 30% off. It's a nice round Number. 172 00:09:24,320 --> 00:09:26,040 You're getting better at reading these off this is. 173 00:09:26,120 --> 00:09:27,520 I'm getting better. It's getting better. 174 00:09:27,520 --> 00:09:29,880 The first time I tried it was like reading it word for word 175 00:09:29,880 --> 00:09:31,960 and I was like never doing that again. 176 00:09:32,120 --> 00:09:35,240 I'm trying to read off like a a super long URL. 177 00:09:35,800 --> 00:09:39,160 That's a real bad idea. My favorite is when you gave the 178 00:09:39,160 --> 00:09:41,440 wrong code for the wrong conference and I was just 179 00:09:41,440 --> 00:09:43,920 sitting here like Nope, Nope, that's not right. 180 00:09:45,120 --> 00:09:47,640 Hey, you always said we can call time out and we can. 181 00:09:48,160 --> 00:09:50,360 Yeah, we can always do it now. We'll do it live. 182 00:09:50,360 --> 00:09:52,920 We'll figure it out. What else do we want to talk 183 00:09:52,920 --> 00:09:54,880 about before we introduce our guest? 184 00:09:55,560 --> 00:09:57,520 Well, I think we should introduce our guest because 185 00:09:57,520 --> 00:09:59,600 we've been going for quite a while now. 186 00:10:00,160 --> 00:10:02,680 Yeah, let's get to it. Patrick Harding, he's a Chief 187 00:10:02,680 --> 00:10:04,520 product architect at Ping Identity. 188 00:10:04,880 --> 00:10:06,360 Welcome to Identity at the center, Patrick. 189 00:10:06,920 --> 00:10:08,080 Thank you guys. Appreciate it. 190 00:10:08,560 --> 00:10:09,920 Yeah. Thanks for taking the time. 191 00:10:10,320 --> 00:10:12,200 Let's start with a little bit about your background. 192 00:10:12,280 --> 00:10:14,560 How did you get into the IAM industry? 193 00:10:14,560 --> 00:10:16,800 Is it something that you chose or did it choose you? 194 00:10:17,400 --> 00:10:20,640 A little bit of both. I used to be way back in the 195 00:10:20,640 --> 00:10:24,080 day, a enterprise security architect at Fidelity 196 00:10:24,080 --> 00:10:28,880 Investments in Boston, and I was doing security pen testing, 197 00:10:29,920 --> 00:10:33,080 firewalls, things like that, you know, back actually before it 198 00:10:33,080 --> 00:10:35,120 was called cyber. So we're going to talk today a 199 00:10:35,120 --> 00:10:37,200 little bit about artificial intelligence. 200 00:10:37,200 --> 00:10:39,160 I know it's kind of a fad. It's probably not going to stick 201 00:10:39,160 --> 00:10:41,520 around for a while, but I'd like to talk about it a little more 202 00:10:41,520 --> 00:10:44,400 detail. One of the things that I find 203 00:10:44,400 --> 00:10:46,920 interesting is the definition of AI because I feel like my 204 00:10:46,920 --> 00:10:49,400 definition has changed, you know, within the last couple 205 00:10:49,400 --> 00:10:52,880 years with you know large language models and and things 206 00:10:52,880 --> 00:10:56,840 like that where it was. It's not just kind of behind the 207 00:10:56,840 --> 00:10:58,880 scenes right now we're using to generate, generate things 208 00:10:58,880 --> 00:11:01,920 generative AI. We want to talk about, hey, how 209 00:11:02,040 --> 00:11:05,160 AI is impacting identity space. But before we get there, how do 210 00:11:05,160 --> 00:11:08,000 you define AI today? Sure. 211 00:11:08,000 --> 00:11:12,840 So I think you know we've been sort of doing and talking about 212 00:11:12,840 --> 00:11:15,800 gene learning and I suppose many people might have called that or 213 00:11:15,800 --> 00:11:19,000 would have called that AI. But I think the term AI now is 214 00:11:19,000 --> 00:11:22,480 more associated with generative AI or Gen. 215 00:11:22,520 --> 00:11:24,040 AI. We're thinking about the use of 216 00:11:24,040 --> 00:11:26,040 generative AI, you know, basically. 217 00:11:26,680 --> 00:11:29,680 Jim, how does your definition of AI stand today? 218 00:11:30,040 --> 00:11:33,120 It's evolving. You know I thought you said to 219 00:11:33,120 --> 00:11:37,280 Patrick was a degenerate AI and I was like, oh, that's something 220 00:11:37,280 --> 00:11:40,240 I could get behind. That actually reminded me of the 221 00:11:40,240 --> 00:11:44,360 presentation that Andre Durant did last year at identiversity 222 00:11:44,800 --> 00:11:47,120 kind of showed the the bad side of AI. 223 00:11:47,120 --> 00:11:50,200 Well, how it could be used as a weapon and I thought that's a 224 00:11:50,200 --> 00:11:57,120 good term degenerate AI. But you know, I here's my, my 225 00:11:57,120 --> 00:12:04,040 hold up with AI really is that I feel like it has the potential 226 00:12:04,040 --> 00:12:08,800 to be a misused term where it's like, you know, tied laundry 227 00:12:08,800 --> 00:12:13,160 soap. Now with AI you throw it around 228 00:12:13,160 --> 00:12:15,360 too much then what does it really mean? 229 00:12:15,720 --> 00:12:19,680 But I think you know Patrick let us down the right path error, 230 00:12:20,000 --> 00:12:24,200 you know thinking of it around this generative AI more than 231 00:12:24,200 --> 00:12:28,800 just hey, we we can do business intelligence with large data 232 00:12:28,800 --> 00:12:33,240 sets because I think that's not really what AI was all about is 233 00:12:33,320 --> 00:12:37,760 around using natural language and a system being able to 234 00:12:37,760 --> 00:12:43,320 interpret that into something it can work with, right. 235 00:12:43,360 --> 00:12:47,200 And then I love the iterative capability with the language 236 00:12:47,200 --> 00:12:50,760 models, large language models as they call it, where you can keep 237 00:12:50,760 --> 00:12:55,240 ask refining questions and either zooming in or or leaning 238 00:12:55,240 --> 00:12:59,400 back to get the right answer what you're really looking for. 239 00:12:59,880 --> 00:13:06,400 But I also do think what one of the things for me that that that 240 00:13:06,400 --> 00:13:10,240 still surprised me about AI is that you could ask you something 241 00:13:10,760 --> 00:13:16,160 like a math question and it can get it absolutely wrong and you 242 00:13:16,160 --> 00:13:18,840 know it's wrong, right, because it's like not even close to what 243 00:13:18,840 --> 00:13:21,880 you were expecting. And then you ask it, Are you 244 00:13:21,880 --> 00:13:24,720 sure about that? Oh, sorry, I made a mistake. 245 00:13:24,720 --> 00:13:26,400 And then we're going to fix the problem. 246 00:13:26,680 --> 00:13:30,560 And what other computer technology do you know that does 247 00:13:30,560 --> 00:13:33,720 stuff like that? It's almost like degenerate AI. 248 00:13:33,840 --> 00:13:36,520 So there's another use for that term. 249 00:13:36,800 --> 00:13:39,280 I mean one of the other ways to think about it is that you know 250 00:13:39,520 --> 00:13:41,280 with Gen. AI, we're now talking about 251 00:13:41,280 --> 00:13:42,680 stuff that can pass the Turing test. 252 00:13:43,160 --> 00:13:46,720 And prior to prior to that I said I I think when we talked 253 00:13:46,720 --> 00:13:48,400 about machine learning, that wasn't the case. 254 00:13:48,960 --> 00:13:51,400 And you know now when you're interacting something and it's 255 00:13:51,400 --> 00:13:54,040 human like, it's actually quite exciting to be honest. 256 00:13:54,200 --> 00:13:55,720 Yeah, yeah. I mean, it's really cool. 257 00:13:55,760 --> 00:13:58,240 This is finally like a technology you could see putting 258 00:13:58,240 --> 00:14:02,840 inside a robot and now it's like more humanizing of the whole 259 00:14:02,840 --> 00:14:06,120 experience. But one of the things you said 260 00:14:06,120 --> 00:14:10,680 yesterday, Patrick, as we were talking through and preparing 261 00:14:10,680 --> 00:14:14,640 for this call, was AI is going to be everywhere. 262 00:14:15,080 --> 00:14:18,760 And I was wondering if you could explain to us what you meant by 263 00:14:18,760 --> 00:14:20,120 that. Sure. 264 00:14:20,120 --> 00:14:24,400 So I I just think that AI is going to emerge in you know all 265 00:14:24,560 --> 00:14:28,360 products and services that we end up you know leveraging. 266 00:14:28,560 --> 00:14:31,320 I think it's going to actually be fairly quickly adopted 267 00:14:31,880 --> 00:14:35,360 whether you know, whether it's into, you know things we, you 268 00:14:35,480 --> 00:14:38,680 know things, we drive the services, we're interacting with 269 00:14:40,320 --> 00:14:42,640 the, you know, everything. Yeah. 270 00:14:42,640 --> 00:14:46,240 And part of everything is how it's affecting the digital 271 00:14:46,240 --> 00:14:48,880 identity industry. I was wondering if you could 272 00:14:49,400 --> 00:14:54,320 expand a little bit on how you see AI fitting into the 273 00:14:54,320 --> 00:14:58,720 industry, the good and the bad. So the conversations we've had 274 00:14:58,720 --> 00:15:01,160 and turned that into the keynote, funnily enough, really 275 00:15:01,400 --> 00:15:03,440 from from an identity standpoint, the way we've been 276 00:15:03,440 --> 00:15:05,760 thinking about it, it sort of breaks down into two areas. 277 00:15:05,760 --> 00:15:10,520 One is to improve our products and identity capabilities in 278 00:15:10,520 --> 00:15:14,280 general, both for administrators and end users. 279 00:15:15,160 --> 00:15:19,760 Also, it's how AI can be used for bad like dark AI, dark side 280 00:15:19,760 --> 00:15:22,240 of AI. And that's really, you know the 281 00:15:22,240 --> 00:15:26,400 realm of how AI can be used. Everybody knows and understands 282 00:15:26,400 --> 00:15:31,320 deep fakes, things like that. But also how AI can be used to 283 00:15:31,480 --> 00:15:34,400 perform other fraud. You know, whether it's 284 00:15:34,400 --> 00:15:37,800 automating the generation of phishing emails, using 285 00:15:37,800 --> 00:15:40,800 information that the AI can go and collect off the dark web, or 286 00:15:40,800 --> 00:15:44,040 or just off the web in general in ways you can't imagine. 287 00:15:44,360 --> 00:15:48,920 No longer are you going to see emails from Nigerian fraudsters. 288 00:15:48,920 --> 00:15:51,720 Basically that misspells words and stuff like that. 289 00:15:51,720 --> 00:15:55,240 So again I see it both the good but going to be used for fraud 290 00:15:55,240 --> 00:15:57,520 too. Yeah, I mean, you're seeing that 291 00:15:57,520 --> 00:16:00,040 already, right? The phishing emails are becoming 292 00:16:00,040 --> 00:16:04,640 less obvious. Let's say that it's I I always 293 00:16:04,640 --> 00:16:07,840 like, shake my head. Like the attacks are still 294 00:16:07,840 --> 00:16:14,000 social engineering and phishing. They're still one and two, and I 295 00:16:14,000 --> 00:16:17,120 kind of feel like, you know, on the social engineering side, the 296 00:16:17,120 --> 00:16:24,480 use of video and voice over, you know, that seems to be probably 297 00:16:24,480 --> 00:16:28,000 the most dangerous combination when it comes to AI for bad. 298 00:16:28,240 --> 00:16:33,000 An employee in Hong Kong was joined on Zoom by a deep fake 299 00:16:33,000 --> 00:16:38,240 video of their CFO and was basically talked into moving $25 300 00:16:38,240 --> 00:16:41,480 million do a you know, fraudulent account basically. 301 00:16:41,480 --> 00:16:45,480 So it's extremely real and a survey I think that were 302 00:16:45,520 --> 00:16:50,200 released today or imminently where you know over 50% of the 303 00:16:50,200 --> 00:16:53,680 respondents are very concerned about deep fakes right now. 304 00:16:54,200 --> 00:16:58,640 And so it's it's a very top of mind issue across the across the 305 00:16:58,640 --> 00:17:01,360 lobe right now. So we definitely have to get on 306 00:17:01,360 --> 00:17:03,120 top of this. Yeah, absolutely. 307 00:17:03,160 --> 00:17:07,079 And Jeff, I mean are there, do you have any thoughts in this 308 00:17:07,079 --> 00:17:12,560 area about where you're seeing AI for either good or evil? 309 00:17:13,319 --> 00:17:16,200 Well, the, you know, the the best example was our show opener 310 00:17:16,200 --> 00:17:20,800 for April 1st where I took AI voices and turned that into sort 311 00:17:20,800 --> 00:17:23,040 of how we open up the show. But sure, it's like anything 312 00:17:23,040 --> 00:17:24,640 else, right? AI is a tool. 313 00:17:24,720 --> 00:17:26,800 It will be used for good. It will be used for bad. 314 00:17:27,040 --> 00:17:28,960 Patrick, you mentioned the Hong Kong scenario. 315 00:17:28,960 --> 00:17:32,560 I mean 25 million or whatever. It was out the door because of a 316 00:17:32,560 --> 00:17:36,880 very heavily invested attack. That's not cheap to do to get 317 00:17:36,880 --> 00:17:41,880 like a bunch of people deep faked on a team's call and then, 318 00:17:42,400 --> 00:17:44,680 you know, have to target essentially one person. 319 00:17:44,680 --> 00:17:46,920 That seems to me like that was pretty targeted. 320 00:17:46,920 --> 00:17:47,960 I know what they wanted to do there. 321 00:17:48,600 --> 00:17:51,960 That took a lot of investment. But I mean A is everywhere now 322 00:17:51,960 --> 00:17:54,600 at this point. It's helping us write emails, It 323 00:17:54,600 --> 00:17:57,080 is helping us configure our security tools. 324 00:17:57,480 --> 00:18:01,080 It is, you know, cleaning up voices and now people are 325 00:18:01,080 --> 00:18:02,640 starting to use it to generate videos. 326 00:18:02,640 --> 00:18:07,960 So I'm still a glass half full person when it comes to it, but 327 00:18:08,000 --> 00:18:11,240 I think we do need to be careful about how it's used and to be 328 00:18:11,240 --> 00:18:14,360 able to identify the provenance of how some of these things are 329 00:18:14,360 --> 00:18:16,920 coming along. You know, is this really Jeff 330 00:18:16,920 --> 00:18:19,960 talking on the screen, you know, and what you're hearing or is it 331 00:18:20,000 --> 00:18:21,840 AI, How, how do you confirm that? 332 00:18:21,840 --> 00:18:24,960 Is there a way to kind of, you know, make make that 333 00:18:24,960 --> 00:18:28,920 authenticity known? So I you're landing in that in 334 00:18:28,920 --> 00:18:31,080 that area, I I completely agree Jeff. 335 00:18:31,200 --> 00:18:33,920 It's just going to be a constant cat and mouse game like it has 336 00:18:33,920 --> 00:18:36,560 been in security for, you know, 20 years. 337 00:18:37,120 --> 00:18:40,120 What we're going to actually, I think, have to actually change 338 00:18:40,120 --> 00:18:44,640 the way that we think about using certain channels of 339 00:18:44,640 --> 00:18:47,040 communication. Traditionally we've had this 340 00:18:47,040 --> 00:18:51,080 implicit trust where the voice I'm listening to, I recognize 341 00:18:51,080 --> 00:18:53,800 therefore it must be Jeff or it must be Andre. 342 00:18:54,280 --> 00:18:58,640 The face or the the face I see on the screen looks like Andre. 343 00:18:58,640 --> 00:19:00,320 So it's Andre. Basically. 344 00:19:00,760 --> 00:19:04,160 We're going to have to start to get used to I think looking to 345 00:19:04,280 --> 00:19:07,200 establish explicit trust but but doing it out of band. 346 00:19:07,720 --> 00:19:13,720 So actually you know if I'm on a a voice call with Andre sending 347 00:19:13,760 --> 00:19:16,960 me something out of band to say hey it's me Andre, I'm like that 348 00:19:18,000 --> 00:19:21,440 we're seeing it a little bit in in in sort of that to me is like 349 00:19:21,440 --> 00:19:23,800 peer-to-peer interactions. We're seeing it a little bit 350 00:19:23,800 --> 00:19:27,800 more in sort of business to consumer interactions to a 351 00:19:27,800 --> 00:19:33,040 certain extent where you know even though I'm talking to the 352 00:19:33,040 --> 00:19:35,240 bank, the bank still needs to confirm it's me. 353 00:19:35,240 --> 00:19:38,320 So they might ask me for a voice authentication for some sort of 354 00:19:38,320 --> 00:19:40,960 other transaction. They might basically ask me for 355 00:19:40,960 --> 00:19:42,640 a PIN. Yeah I think there's there's a 356 00:19:42,640 --> 00:19:45,880 lot of good points and you think about the approach you just 357 00:19:45,880 --> 00:19:49,280 talked about there reminds me of multi factor authentication. 358 00:19:50,080 --> 00:19:55,320 You know it's multi factor and and realistically just like with 359 00:19:56,120 --> 00:20:00,520 social engineering, just like with phishing, none of the 360 00:20:00,880 --> 00:20:03,960 safeguards we put in place are going to be catch alls unless 361 00:20:04,320 --> 00:20:09,040 people are skeptical enough to ask themselves a question. 362 00:20:09,040 --> 00:20:11,520 Really. Should I click on the link and 363 00:20:11,520 --> 00:20:14,160 type in my credentials and give this information? 364 00:20:14,680 --> 00:20:19,320 Should I do secondary checks? Should I be skeptical and just 365 00:20:19,320 --> 00:20:23,320 think a little bit of skepticism before sending 25 million even 366 00:20:23,320 --> 00:20:25,320 though at all the people on the phone? 367 00:20:25,800 --> 00:20:28,160 How about a text message to one of the people you know? 368 00:20:28,160 --> 00:20:30,400 How about a a follow up phone call? 369 00:20:31,000 --> 00:20:33,200 I don't think it, it doesn't necessarily need to be all the 370 00:20:33,200 --> 00:20:36,880 time, but it's recognizing on certain certain interactions 371 00:20:36,880 --> 00:20:40,880 transactions, requests that maybe that's worthy of an 372 00:20:40,880 --> 00:20:45,960 outbound thing and exchange essentially to to confirm and 373 00:20:45,960 --> 00:20:49,920 it's that confirmation step that I think it's important but it's 374 00:20:49,920 --> 00:20:51,480 difficult. I mean it's it's going to we're 375 00:20:51,480 --> 00:20:53,320 going to have to retrain people to not. 376 00:20:53,320 --> 00:20:55,240 No, we don't. We tried to train people not to 377 00:20:55,240 --> 00:20:58,840 trust every e-mail they see. We're going to have to, you know 378 00:20:58,840 --> 00:21:01,600 train people not to trust every phone call, every video call, 379 00:21:01,600 --> 00:21:05,360 stuff like that they see too. So that's again, it's going to 380 00:21:05,360 --> 00:21:08,840 be challenging, which is why we need to set up sort of 381 00:21:09,400 --> 00:21:12,200 established processes where people get used to the notion 382 00:21:12,360 --> 00:21:15,560 of, you know, confirming out of band that they're interacting 383 00:21:15,560 --> 00:21:17,040 with certain people and stuff like that. 384 00:21:17,200 --> 00:21:19,720 It it's going to have to become second nature to them, otherwise 385 00:21:19,720 --> 00:21:22,320 they'll forget. Let's talk about AI governance 386 00:21:22,320 --> 00:21:26,400 because they, you know, I feel like the first time this topic 387 00:21:26,400 --> 00:21:31,200 came up was really around things like ChatGPT becoming available 388 00:21:31,200 --> 00:21:35,760 on the Internet and folks like us kind of discovering them and 389 00:21:35,760 --> 00:21:38,680 being able to start to query information. 390 00:21:38,680 --> 00:21:42,640 Then you start to think about, well, everything we're feeding 391 00:21:42,640 --> 00:21:45,240 into this becomes part of the model, right? 392 00:21:46,040 --> 00:21:50,120 And if we start putting proprietary information either 393 00:21:50,120 --> 00:21:54,360 on purpose or by accident proprietary information, it 394 00:21:54,360 --> 00:21:58,320 becomes part of the model. And so you know that's where I 395 00:21:58,320 --> 00:22:02,840 first kind of became aware of where companies need to put 396 00:22:02,840 --> 00:22:05,520 together some kind of governance, some kind of policy. 397 00:22:06,640 --> 00:22:11,080 But I also see now AI is much bigger than just ChatGPT. 398 00:22:11,080 --> 00:22:16,160 It's we're implementing products that have AI kind of baked into 399 00:22:16,160 --> 00:22:19,040 them. We are maybe building products 400 00:22:19,200 --> 00:22:22,280 that have AI built into them, maybe our end products that we 401 00:22:22,280 --> 00:22:26,520 sell to consumers have AI. So given all that, where do you 402 00:22:26,520 --> 00:22:32,560 see the AI governance, what's important and who are kind of 403 00:22:32,560 --> 00:22:35,440 the the folks that need to be involved when you think about a 404 00:22:35,440 --> 00:22:38,040 corporation? We ended up realizing that we 405 00:22:38,040 --> 00:22:41,080 already have data governance like policies in place. 406 00:22:41,080 --> 00:22:44,920 So we added some AI governance and then got everybody to sort 407 00:22:44,920 --> 00:22:46,760 of re sign the data governance policies. 408 00:22:47,160 --> 00:22:49,640 That's grown a little bit because it's it's expanded 409 00:22:49,640 --> 00:22:52,680 beyond chat. GPT now where we've asked people 410 00:22:52,920 --> 00:22:55,480 to basically let us know, are you looking what other services 411 00:22:55,480 --> 00:23:00,200 are you looking at using to understand what their terms and 412 00:23:00,200 --> 00:23:03,520 conditions look like the how they leverage you know the data 413 00:23:03,560 --> 00:23:05,320 that we provide and share with them. 414 00:23:05,760 --> 00:23:10,120 So again we, you know again we're being very cautious and 415 00:23:10,120 --> 00:23:13,320 careful there. We definitely want to use Gen. 416 00:23:13,400 --> 00:23:18,080 AI with confidential data, not PII but confidential data. 417 00:23:18,120 --> 00:23:21,200 And in that case we're you know we're looking at just using 418 00:23:21,200 --> 00:23:26,080 services like Open AI sort of enterprise capability where they 419 00:23:26,080 --> 00:23:31,840 isolate the use of that data just to a model that's under 420 00:23:32,120 --> 00:23:34,680 under sort of our control. So there's no leakage of that 421 00:23:34,680 --> 00:23:37,360 information into other areas. So we're being very, very 422 00:23:37,360 --> 00:23:38,960 cautious there. Obviously we can take it a step 423 00:23:38,960 --> 00:23:41,320 further and say look we're not comfortable with any of that. 424 00:23:41,320 --> 00:23:44,600 We're just going to run the open source models ourselves and 425 00:23:44,600 --> 00:23:47,160 that's something else we'll we're we're evaluating too. 426 00:23:47,400 --> 00:23:50,480 Is that realistic? I mean, in your mind, because I 427 00:23:50,560 --> 00:23:53,040 I kind of expected the answer you just gave there, which is 428 00:23:53,040 --> 00:23:56,840 that say you're building an identity management solution, 429 00:23:57,160 --> 00:24:02,120 leveraging one of the big AI tech platforms for your AI 430 00:24:02,120 --> 00:24:08,000 engine and then kind of carving out some kind of tenant if you 431 00:24:08,000 --> 00:24:11,640 will, for lack of a better term. But is it realistic to think 432 00:24:11,640 --> 00:24:18,200 that a company that specializes in one area of technology that's 433 00:24:18,200 --> 00:24:22,160 not AI could build enough robust AI? 434 00:24:23,560 --> 00:24:26,640 Or you're only looking at that because that's potentially the 435 00:24:26,640 --> 00:24:29,080 only solution. When you're talking about the 436 00:24:29,080 --> 00:24:35,520 use of say open A, let's say the GPT 4 APIs for example, they're 437 00:24:35,520 --> 00:24:37,760 they're not, I mean they're they're slow. 438 00:24:38,080 --> 00:24:41,680 They respond very, very slowly today, obviously likely that 439 00:24:41,680 --> 00:24:44,960 will improve over time, but they they don't respond very quickly. 440 00:24:45,160 --> 00:24:48,040 That's OK if we're talking about you know, sort of natural 441 00:24:48,040 --> 00:24:50,520 language processing queries and stuff like that where people are 442 00:24:50,520 --> 00:24:52,880 comfortable you know waiting for that response to come back. 443 00:24:53,400 --> 00:24:57,440 But for other real time use where we're talking about 444 00:24:57,440 --> 00:25:00,600 needing to get responses back in, you know milliseconds, 445 00:25:01,120 --> 00:25:04,960 that's where we might need to evaluate the use of models that 446 00:25:04,960 --> 00:25:07,800 might have been trained by the bigger models like the the, the 447 00:25:07,800 --> 00:25:11,440 larger LLMS. But but you know where we're 448 00:25:11,440 --> 00:25:14,280 running them locally ourselves and again these things don't 449 00:25:14,280 --> 00:25:17,000 actually have to be very big but they can respond faster and they 450 00:25:17,000 --> 00:25:20,240 become the. The way I think about it is, you 451 00:25:20,240 --> 00:25:25,920 know I say ChatGPT, it is a is a an encyclopedia of knowledge. 452 00:25:25,920 --> 00:25:28,600 It has vast knowledge of across lots and lots of things. 453 00:25:29,120 --> 00:25:32,600 But you can start to think about trading models with far more 454 00:25:32,640 --> 00:25:35,880 localized knowledge that might be very, very specific but very 455 00:25:35,880 --> 00:25:39,560 good to certain tasks and you ask them to become experts in 456 00:25:39,560 --> 00:25:42,840 something much narrower. Therefore they can respond much 457 00:25:42,840 --> 00:25:45,400 quicker. And that and and being an expert 458 00:25:45,400 --> 00:25:47,680 in something very narrower, maybe we can use an open source 459 00:25:47,680 --> 00:25:49,760 model to do that and and run it locally ourselves. 460 00:25:50,160 --> 00:25:52,600 Yeah, it yeah. So open source model makes 461 00:25:52,600 --> 00:25:55,640 sense. I guess what I'm it's 462 00:25:55,640 --> 00:25:59,000 interesting going back to when Jeff asked me what's my 463 00:25:59,000 --> 00:26:01,760 definition of AI? And I don't think it gave great 464 00:26:01,760 --> 00:26:04,320 answers. Like I know it when I see it and 465 00:26:04,320 --> 00:26:09,920 I know when it's fake AI. Like fake AI to me is like, hey, 466 00:26:09,920 --> 00:26:13,680 did you know that 80% of the people who are like Jeff Sedman 467 00:26:14,240 --> 00:26:17,840 also have this, this role? And why don't you just give that 468 00:26:17,840 --> 00:26:20,040 role to Jeff Stedman that's not AI. 469 00:26:20,720 --> 00:26:23,040 Because then if I say, well, what if I give Jeff Stedman the 470 00:26:23,040 --> 00:26:26,080 role, then what's going to happen is sorry, that input is 471 00:26:26,080 --> 00:26:27,880 invalid. Like you've totally lost 472 00:26:27,880 --> 00:26:31,480 credibility with me. And that's to me like the state 473 00:26:31,480 --> 00:26:34,880 of of AI in identity products that I see. 474 00:26:35,000 --> 00:26:38,160 There are other ways to think about how AI might be used in in 475 00:26:38,200 --> 00:26:42,880 identity. And for example if you have a 476 00:26:42,880 --> 00:26:48,280 set of prisation policies that are applicable to a certain 477 00:26:48,840 --> 00:26:53,160 regulation and that regulation gets updated, you could ask the 478 00:26:53,160 --> 00:26:57,120 AI to, you know, reread that regulation and make the 479 00:26:57,120 --> 00:26:59,560 suggestions on how the authorization policies get to 480 00:26:59,560 --> 00:27:01,720 change. Basic dated regulatory framework 481 00:27:01,840 --> 00:27:07,080 it sees and therefore you start to basically just provide you 482 00:27:07,080 --> 00:27:09,560 know it. It eliminates a lot of the human 483 00:27:09,560 --> 00:27:13,200 work and allows you to basically, you know, get to, 484 00:27:13,200 --> 00:27:16,240 yeah, get to get get to meet the requirements and to compliance 485 00:27:16,240 --> 00:27:17,840 more quickly in those situations. 486 00:27:18,360 --> 00:27:21,000 So I I think it's very good at looking at these data sets, 487 00:27:21,240 --> 00:27:24,400 whether it's you know, regulatory frameworks, security 488 00:27:24,400 --> 00:27:27,160 policies, things like that, analyzing it and making 489 00:27:27,160 --> 00:27:30,280 recommendations much like a business analyst might do who 490 00:27:30,280 --> 00:27:32,640 has been asked to actually learn and understand these things as 491 00:27:32,640 --> 00:27:36,440 well. I think this whole topic of the 492 00:27:36,520 --> 00:27:42,000 idea of like so for me and here would be a great example of what 493 00:27:42,000 --> 00:27:45,720 an AI could do. If I could say, hey, tell me all 494 00:27:45,720 --> 00:27:49,840 the people who can place orders on this system and it's like OK, 495 00:27:49,840 --> 00:27:52,800 I don't know. And then you start asking you a 496 00:27:52,800 --> 00:27:55,040 follow up questions or maybe giving you a follow up 497 00:27:55,040 --> 00:27:59,520 information to define what roles can place orders on this 498 00:27:59,520 --> 00:28:02,080 systems. Now I can tell you, OK, yeah, 499 00:28:02,120 --> 00:28:05,520 these people have these roles and then you could say, all 500 00:28:05,520 --> 00:28:09,040 right, well, you know what else is included in those roles? 501 00:28:09,040 --> 00:28:12,960 Like you can start actually getting meaningful information 502 00:28:12,960 --> 00:28:19,080 by having a conversation like with AAI interface. 503 00:28:19,360 --> 00:28:22,240 Now here's where I was going with the walls need to be 504 00:28:22,240 --> 00:28:25,240 defined. What if I were to say I'm used 505 00:28:25,240 --> 00:28:27,720 ping for an example since that that's your company? 506 00:28:28,040 --> 00:28:34,520 What if I were to say OK how many of my users have multi 507 00:28:34,520 --> 00:28:38,360 factor authentication? Says 80%, how does that compare 508 00:28:38,360 --> 00:28:45,760 to other ping customers? Now if it said 75% have 80% or 509 00:28:45,760 --> 00:28:51,280 more of their users with that, I don't think that violates any 510 00:28:51,280 --> 00:28:54,320 kind of non confidentiality that you would have with your other 511 00:28:54,320 --> 00:28:55,720 customers, at least for my money. 512 00:28:56,120 --> 00:29:00,800 But if I were to say, hey, I know that corporation XYZ is on 513 00:29:00,800 --> 00:29:06,120 Ping and I said how many corporation XYZ users use multi 514 00:29:06,120 --> 00:29:09,520 factor authentication Were giving you the answer that would 515 00:29:09,520 --> 00:29:12,560 not be good. So there's not only just my 516 00:29:12,560 --> 00:29:18,200 opinion or not only like Ping's tenant, but it would be each 517 00:29:18,200 --> 00:29:20,760 customer has. You'd have to have some data 518 00:29:21,000 --> 00:29:25,040 segmentation within those customers and the AI would have 519 00:29:25,040 --> 00:29:32,520 to be smart enough to basically apply rules to make sure that if 520 00:29:32,520 --> 00:29:37,320 you were going to have any kind of like cross customer 521 00:29:37,320 --> 00:29:40,680 information that it would be generic enough not to be 522 00:29:40,680 --> 00:29:45,520 revealing anything that's proprietary to those customers. 523 00:29:45,840 --> 00:29:48,160 That's that's what I wanted to throw out there. 524 00:29:48,880 --> 00:29:51,600 I actually agree with you. I think that's a great example. 525 00:29:52,200 --> 00:29:54,920 Asking for that in terms context of like, you know, locally it's, 526 00:29:55,000 --> 00:29:56,960 you know, my organization. But how does that compare to 527 00:29:56,960 --> 00:29:59,280 other organizations? Is completely reasonable use of 528 00:29:59,280 --> 00:30:02,200 the tech, the notion of having an assistant for access 529 00:30:02,200 --> 00:30:05,960 certifications or access reviews or an access review on someone 530 00:30:06,360 --> 00:30:08,840 to be able to query. All right, when you know, when 531 00:30:08,840 --> 00:30:11,880 was this person granted that access in, in what's in who 532 00:30:11,880 --> 00:30:14,040 granted it, what was the, you know, what was the 533 00:30:14,040 --> 00:30:16,440 rationalization for it? How much have, how much have 534 00:30:16,440 --> 00:30:18,280 they used it in this period of time? 535 00:30:18,840 --> 00:30:21,400 Being able to sort of query and ask for, ask me for that 536 00:30:21,400 --> 00:30:24,680 information to very quickly be able to reach a decision I think 537 00:30:24,680 --> 00:30:27,520 would have huge utility. Actually, we're talking about 538 00:30:27,520 --> 00:30:32,520 being able just to ask natural language queries that can be 539 00:30:32,520 --> 00:30:36,280 parsed and actually turned into, you know, real, real questions 540 00:30:36,280 --> 00:30:38,520 you ask of the system. It becomes very much more of a 541 00:30:39,120 --> 00:30:40,800 interface that people can be comfortable with. 542 00:30:40,800 --> 00:30:43,840 Just, you know, asking for asking for information is going 543 00:30:43,840 --> 00:30:45,640 to help them make decisions in certain ways. 544 00:30:46,000 --> 00:30:51,200 What do you see as a is destiny when it comes to the identity 545 00:30:51,200 --> 00:30:54,840 and access management space? And then what do you think is 546 00:30:54,840 --> 00:30:57,480 going to hold it back from achieving that destiny? 547 00:30:57,880 --> 00:31:01,400 One of the things that we've been thinking about here a 548 00:31:01,400 --> 00:31:04,680 little bit is recognizing that AI Gen. 549 00:31:04,680 --> 00:31:08,560 AI is a little different to some of the other core capabilities 550 00:31:08,560 --> 00:31:11,120 we've been relying on to deliver identity services. 551 00:31:11,120 --> 00:31:16,240 Things like you know compute and storage and CPUI think it's 552 00:31:16,240 --> 00:31:18,520 going to look very different in 18 months and very different 553 00:31:18,520 --> 00:31:23,240 again in three years. So it it it's really like a 554 00:31:23,240 --> 00:31:26,280 little we're sort of like moving in a little bit to the unknown 555 00:31:26,280 --> 00:31:28,360 because we haven't necessarily thought about the art of the 556 00:31:28,360 --> 00:31:30,080 possible here based on where Gen. 557 00:31:30,160 --> 00:31:35,240 AI might be in 18 months. So, you know, realistically, 558 00:31:35,760 --> 00:31:40,120 could we be talking about authentication and authorization 559 00:31:40,120 --> 00:31:47,040 services that really can just be queried and they recognize who 560 00:31:47,040 --> 00:31:51,200 you are and are able to essentially return a 561 00:31:51,240 --> 00:31:55,160 authorization decision based on who you are in the context of 562 00:31:55,160 --> 00:31:57,960 what you're going to try and do without necessarily having to 563 00:31:57,960 --> 00:31:59,760 write any rules? All right. 564 00:31:59,760 --> 00:32:01,880 Can the Gen. AI be as smart as what a 565 00:32:01,880 --> 00:32:05,120 security admin might be if you was to be given that query or 566 00:32:05,120 --> 00:32:07,440 the person writing the security policies or the business 567 00:32:07,440 --> 00:32:10,120 analytics for the business application. 568 00:32:11,200 --> 00:32:14,040 Could the AI be smart enough to be able to respond here in real 569 00:32:14,040 --> 00:32:16,880 time? And the other thing is we talk 570 00:32:16,880 --> 00:32:19,760 about the identity infrastructure sort of being 571 00:32:19,760 --> 00:32:20,720 Gen. AI based. 572 00:32:21,080 --> 00:32:24,080 What does it look like for a bank Ledger to now be basically 573 00:32:24,080 --> 00:32:27,640 you know based on a Gen. AI that's the bank Ledger or 574 00:32:27,760 --> 00:32:30,680 ACRM application interacting with an identity infrastructure. 575 00:32:30,680 --> 00:32:35,960 So it it completely reshapes the way we think about I think how 576 00:32:36,320 --> 00:32:38,800 applications are actually going to interact with each other. 577 00:32:38,800 --> 00:32:43,040 The AI is become, they evolve, they become even smarter and 578 00:32:43,040 --> 00:32:45,840 they become faster at responding stuff like that. 579 00:32:46,560 --> 00:32:50,320 I I'm very concerned about them becoming self learning, like 580 00:32:50,320 --> 00:32:53,000 recursive self learning where they become smarter on their own 581 00:32:53,280 --> 00:32:58,240 sort of thing because that's you know what was it war games circa 582 00:32:58,240 --> 00:33:02,080 1985 that like that movie or something like that. 583 00:33:02,080 --> 00:33:04,360 How, how does this evolve and how do we put some checks and 584 00:33:04,360 --> 00:33:06,240 balances in place basically as well. 585 00:33:07,040 --> 00:33:09,800 So again I I think this is going to happen over the next few 586 00:33:09,800 --> 00:33:11,160 years. What you know I I think the 587 00:33:11,160 --> 00:33:14,160 second-half of this, what's going to hold it back, I I think 588 00:33:14,160 --> 00:33:18,760 it is going to be people's natural aversion to significant 589 00:33:18,760 --> 00:33:21,960 change. And you know, it's a little like 590 00:33:21,960 --> 00:33:26,240 the late 2000s, early twenty 10s where a lot of, you know, 591 00:33:26,720 --> 00:33:29,640 generally a lot of smaller businesses that were less risk 592 00:33:29,640 --> 00:33:33,120 averse were willing to adopt the cloud because they saw the cost 593 00:33:33,120 --> 00:33:37,120 benefit of doing that. And over time as the cloud 594 00:33:37,120 --> 00:33:39,840 infrastructure basically, you know, they put more security 595 00:33:39,840 --> 00:33:42,400 around it, you know, more regularly, you know, regulation 596 00:33:42,400 --> 00:33:44,200 around it and they got comfortable with it. 597 00:33:44,400 --> 00:33:46,800 You started to see larger enterprises taking advantage of 598 00:33:46,800 --> 00:33:48,480 it. I could see similar things of 599 00:33:48,480 --> 00:33:50,120 all these here in Gen. AI as well. 600 00:33:50,760 --> 00:33:54,040 I'd be remiss if I didn't ask you the question. 601 00:33:54,040 --> 00:33:57,320 I'm sure that's on everybody's mind is that, you know, paying 602 00:33:57,320 --> 00:34:01,200 Identity and Ford Rock came together to create this super 603 00:34:01,200 --> 00:34:05,680 company, super identity company. And with everything that's going 604 00:34:05,680 --> 00:34:09,040 on with AI as a little thing that's happening in the 605 00:34:09,040 --> 00:34:14,000 background, what does the product road map look like? 606 00:34:14,000 --> 00:34:16,719 Is it a merger of these two platforms? 607 00:34:17,000 --> 00:34:19,239 Is it they each have their own road map? 608 00:34:19,239 --> 00:34:20,560 How? How's it going to work in the 609 00:34:20,560 --> 00:34:23,719 future? Ping and Ford Rock had sort of a 610 00:34:23,719 --> 00:34:26,719 common base sort of actor between our products. 611 00:34:27,159 --> 00:34:29,239 We can you know both be innovating. 612 00:34:29,239 --> 00:34:34,880 So the core access management functionality we have, we're 613 00:34:34,880 --> 00:34:39,360 basically continuing to support that across our customer base, 614 00:34:39,679 --> 00:34:43,280 whether you're on the Four Drop, original 4 Drop platform or 615 00:34:43,280 --> 00:34:46,480 whether you're on the original Ping platform, sort of Ping 616 00:34:46,480 --> 00:34:50,280 Federate or you know Access Manager, those will continue to 617 00:34:50,280 --> 00:34:52,880 evolve and we'll invest in those going forward. 618 00:34:52,880 --> 00:34:56,480 So they're not going anywhere. We also had tenant cloud 619 00:34:56,480 --> 00:34:59,680 infrastructure that Four Drop had built out that we are 620 00:34:59,680 --> 00:35:02,240 continuing to support as well as on the Ping side. 621 00:35:02,760 --> 00:35:05,600 And then Ping had basically invested in our Ping One multi 622 00:35:05,600 --> 00:35:08,520 tenant SAS platform that we're continuing to invest in. 623 00:35:08,520 --> 00:35:12,360 So now that it's changing all of that is, is, is, is continuing 624 00:35:12,360 --> 00:35:14,200 forward. On the Ping side, we've been 625 00:35:14,200 --> 00:35:18,640 innovating more in the area of threat protection, identity 626 00:35:18,640 --> 00:35:21,840 verification, whereas on the Ford Rock side, they'd be more 627 00:35:21,840 --> 00:35:25,400 innovating in areas of identity management, life cycle 628 00:35:25,400 --> 00:35:29,120 management, those areas. So we now basically bring all of 629 00:35:29,120 --> 00:35:31,400 that stuff together and I I think we've got actually a 630 00:35:31,400 --> 00:35:35,000 pretty exciting and fairly broad platform that we can actually 631 00:35:35,000 --> 00:35:35,960 talk to people about. Right now. 632 00:35:36,160 --> 00:35:38,680 Yeah, I agree. I mean, from my standpoint, 633 00:35:39,080 --> 00:35:43,200 these were two really good products and each had their own 634 00:35:43,200 --> 00:35:46,080 strengths and some overlap. But you know, each of them were 635 00:35:46,200 --> 00:35:50,040 showing their own areas. I can't speak for your 636 00:35:50,040 --> 00:35:54,960 customers, but if I were to try, I would say exactly what you 637 00:35:54,960 --> 00:35:58,360 said, which is don't repeat what Oracle did because I was there 638 00:35:58,360 --> 00:36:05,320 for that and you know I there were I I don't want to get 639 00:36:05,320 --> 00:36:08,640 myself in trouble by by saying what I really think, but I'm 640 00:36:08,640 --> 00:36:12,280 going to say don't repeat what they did and I'm sure you can 641 00:36:12,800 --> 00:36:14,840 get plenty of perspective on what that was. 642 00:36:15,120 --> 00:36:18,520 Ping sort of took an approach where we wanted to be very we 643 00:36:18,520 --> 00:36:21,720 we're sort of expecting it. Was IT driven, Admin driven? 644 00:36:22,040 --> 00:36:25,480 We need it to be fairly easy to use and configure essentially 645 00:36:25,480 --> 00:36:28,640 with the approach, whereas we want to make it very flexible, 646 00:36:28,640 --> 00:36:31,840 very easy for developers to interact and use it so they can 647 00:36:31,840 --> 00:36:33,960 get comfortable. Now obviously there's overlap 648 00:36:33,960 --> 00:36:35,000 here. This isn't the perfect 649 00:36:35,000 --> 00:36:36,680 distinction. It's like kind of like a van. 650 00:36:37,040 --> 00:36:39,920 But that's still why I I'm sort of comfortable that we have the 651 00:36:39,920 --> 00:36:41,920 right tool no matter what situation that is. 652 00:36:42,040 --> 00:36:45,080 Yeah. It's kind of a lot like the the 653 00:36:45,120 --> 00:36:48,240 distinction you made there of IT driven versus developer driven 654 00:36:48,800 --> 00:36:54,640 reminds me a lot of the Octa Auth 0 combination Octa, IT 655 00:36:54,640 --> 00:36:59,840 driven, all 0 developer driven, a lot of similarities. 656 00:37:00,120 --> 00:37:02,520 And obviously, a lot of their customers were kind of upset 657 00:37:02,520 --> 00:37:07,200 that we didn't have something sooner, but we were sort of, you 658 00:37:07,200 --> 00:37:09,680 know, trapped a little bit because we actually couldn't 659 00:37:09,760 --> 00:37:12,080 talk to Ford Rock until we actually had permission, you 660 00:37:12,320 --> 00:37:14,440 know, after the Justice Department approved it. 661 00:37:14,440 --> 00:37:16,560 So we sort of had a standing start to actually make that 662 00:37:16,560 --> 00:37:19,640 happen. But yeah, I think it's actually 663 00:37:20,080 --> 00:37:23,880 turned out well. I culturally the the Ford Rock 664 00:37:23,880 --> 00:37:26,960 and team teams are very, very similar culturally. 665 00:37:27,120 --> 00:37:29,440 So that it it hasn't been an issue in terms of bringing 666 00:37:29,840 --> 00:37:32,200 these, you know, everybody together and sort of now you 667 00:37:32,200 --> 00:37:34,880 know working as one team. I've always been impressed by 668 00:37:34,880 --> 00:37:38,520 the the the the the talent and the work at at at Ford Rock. 669 00:37:39,280 --> 00:37:40,800 I've known a number of them for a long time. 670 00:37:40,800 --> 00:37:43,000 So it's actually quite fun out of you working with a bunch of 671 00:37:43,000 --> 00:37:45,280 these guys too. Guys and gals too, actually. 672 00:37:45,640 --> 00:37:47,280 So it's great. It's never a dull moment in the 673 00:37:47,280 --> 00:37:49,560 identity business. And this is what I like to say. 674 00:37:49,560 --> 00:37:51,440 This is exciting when you see like companies come together 675 00:37:51,440 --> 00:37:53,280 like that and and see what turns out of it. 676 00:37:53,280 --> 00:37:56,200 But I think we'll probably leave it there, Patrick, because I 677 00:37:56,200 --> 00:37:59,720 know you're a very busy guy, but we definitely want to end a 678 00:37:59,720 --> 00:38:01,520 lighter note. I want to ask you a golf 679 00:38:01,520 --> 00:38:03,000 question because I know you play golf. 680 00:38:03,720 --> 00:38:06,960 If you could play a round of golf with any historical figure, 681 00:38:07,120 --> 00:38:10,800 who would it be and why? So I had to spend a little time 682 00:38:10,800 --> 00:38:13,640 thinking about that. So one of my heroes as a kid 683 00:38:13,800 --> 00:38:17,080 watching golf was a guy called Greg Norman who's kind of like a 684 00:38:17,080 --> 00:38:19,640 kind of got a little bit of a issue going on right now with 685 00:38:19,640 --> 00:38:22,280 live golf. But back in the day he was 686 00:38:22,280 --> 00:38:26,480 pretty good and he he, he obviously had some challenges 687 00:38:26,480 --> 00:38:28,080 and ups and downs and stuff like that. 688 00:38:28,160 --> 00:38:31,080 But I it would be fascinating to be able to spend some time with 689 00:38:31,080 --> 00:38:34,080 him, just, you know, learning about what his experiences were 690 00:38:34,080 --> 00:38:36,080 like, the challenges he faced back in the day. 691 00:38:36,160 --> 00:38:39,040 So that'll probably be the guy I I'd be most interested in 692 00:38:39,040 --> 00:38:40,800 playing with, I think called a hero of mine. 693 00:38:40,840 --> 00:38:42,800 So that's kind of why. It's interesting you selected 694 00:38:42,800 --> 00:38:44,480 another golfer, which I think is kind of cool. 695 00:38:44,640 --> 00:38:46,880 Jim, How about yourself? Who would you pick to play 696 00:38:46,880 --> 00:38:49,200 around in golf with? It's great that you said that 697 00:38:49,200 --> 00:38:52,560 because I was thinking the same thing because I picked a a 698 00:38:52,560 --> 00:38:55,600 person who I'm pretty sure could beat in golf. 699 00:38:56,760 --> 00:39:00,080 But it's probably my favorite historical character, which is 700 00:39:00,080 --> 00:39:04,440 Abraham Lincoln. I mean if you obviously all the 701 00:39:04,720 --> 00:39:08,800 things he did, but also the the things he said, you've realized 702 00:39:08,800 --> 00:39:13,760 this person was operating at like a genius level 703 00:39:13,760 --> 00:39:17,960 intelligence. But I also think I could wolf 704 00:39:17,960 --> 00:39:19,960 them pretty good in golf, because golf wasn't even the 705 00:39:19,960 --> 00:39:25,120 concept back in the 1860s. So but we'd have a good time 706 00:39:25,120 --> 00:39:28,400 together. Maybe enjoy a few beers during 707 00:39:28,400 --> 00:39:31,120 the during the rounds as well. What about you, Jeff? 708 00:39:31,360 --> 00:39:35,120 Let's see, I would I'm, I'm going to go back to Leonardo da 709 00:39:35,120 --> 00:39:39,680 Vinci only because I want to see where the human race would be 710 00:39:39,880 --> 00:39:42,040 with some of the concepts that we're bringing from golf with 711 00:39:42,040 --> 00:39:45,960 like dynamics and physics and things like that. 712 00:39:46,040 --> 00:39:49,280 And just see how much, how, how how further along could we've 713 00:39:49,280 --> 00:39:52,720 accelerated human, human beings with that knowledge shifted 714 00:39:52,720 --> 00:39:54,520 forward, you know, a few 100 years. 715 00:39:55,000 --> 00:39:56,200 That's the way that I would look at it. 716 00:39:57,360 --> 00:39:59,280 I think that's probably a good spot where we'll be at for this 717 00:39:59,280 --> 00:40:01,080 week. Patrick, thank you so much for 718 00:40:01,080 --> 00:40:03,640 spending time with us today and looking forward to 719 00:40:03,640 --> 00:40:05,360 conversations. Hopefully we'll see you at an 720 00:40:05,360 --> 00:40:08,600 upcoming conference. Jim, as always, a pleasure. 721 00:40:08,680 --> 00:40:12,960 You can visit us on the web, IDC, podcast.com and go to our 722 00:40:12,960 --> 00:40:14,880 YouTube channel. It's really easy to find, just 723 00:40:14,880 --> 00:40:18,440 type at IDAC podcast into the search at the top and our 724 00:40:18,440 --> 00:40:19,920 YouTube channel will pop right at the top. 725 00:40:19,920 --> 00:40:23,520 But like subscribe to all that fun social media stuff that 726 00:40:23,520 --> 00:40:25,600 helps us grow the channel and grow the show and get great 727 00:40:25,600 --> 00:40:28,160 guests like Patrick. So we'll have links in our show 728 00:40:28,160 --> 00:40:29,680 notes for people to connect with Patrick. 729 00:40:29,960 --> 00:40:32,920 Going more about Ping as well as all of the discount codes that 730 00:40:32,920 --> 00:40:34,640 we talked about early on in the show. 731 00:40:34,640 --> 00:40:37,160 So it'll be all there in a nice neat little package for people 732 00:40:37,160 --> 00:40:40,240 to check that afterwards. So with that, we'll go ahead and 733 00:40:40,240 --> 00:40:42,680 leave it for this week. Thanks everyone for listening 734 00:40:42,680 --> 00:40:44,400 and we'll talk with everyone in the next one. 735 00:40:45,280 --> 00:40:48,320 You've been listening to Identity at the Center. 736 00:40:48,640 --> 00:40:52,760 We hope you've enjoyed the show. Make sure to like, rate and 737 00:40:52,760 --> 00:40:56,400 review and we'll be back soon. But in the meantime, hit the 738 00:40:56,400 --> 00:41:00,520 website at identity@thecenter.com and find 739 00:41:00,520 --> 00:41:07,920 us on Twitter at IDAC Podcast. See you next time on Identity at 740 00:41:07,920 --> 00:41:08,920 the Center.