WEBVTT - Dr. Nashlie Sephus on the Future of AI, Ethics, and Empowering Underserved Communities 0:00:02.080 --> 0:00:04.400 I'm with Lucas and this is black tech, Green money. 0:00:06.280 --> 0:00:09.360 Doctor Nashalie Cephas is the Applied Science Manager for the 0:00:09.400 --> 0:00:14.720 Amazon AI team, focusing on fairness and AI. Based in Atlanta. 0:00:15.000 --> 0:00:18.000 She formerly led the Amazon A nine visual search and 0:00:18.400 --> 0:00:22.160 AR teams, which launched part Finder, the visual search tool 0:00:22.239 --> 0:00:25.639 for replacement parts on the Amazon Shopping app, in twenty eighteen. 0:00:26.600 --> 0:00:29.479 The team for Partfinder came from the Atlanta based startup 0:00:29.560 --> 0:00:32.960 part Pick. In twenty sixteen. Shout out to Jewel Burks. 0:00:33.520 --> 0:00:38.000 Nashally was CTO. Doctor Sephus received her PhD from the 0:00:38.000 --> 0:00:41.519 School of Electrical and Computer Engineering at the Georgia Institute 0:00:41.560 --> 0:00:45.480 of Technology in twenty fourteen. There's a lot of conversations 0:00:45.520 --> 0:00:48.519 about AI happening in our general social discourse, and I 0:00:48.600 --> 0:00:51.160 wonder what's being overlooked. 0:00:51.640 --> 0:00:57.040 Yeah, So, I think we often talk about the limitations 0:00:57.080 --> 0:01:03.840 and the fear of technology. We often talk about how 0:01:03.880 --> 0:01:07.440 we don't feel like the technology was created for us 0:01:07.440 --> 0:01:11.280 and people in our communities, and to some degree, you know, 0:01:11.400 --> 0:01:15.160 I can definitely relate to that, but I do still 0:01:15.280 --> 0:01:18.679 stress the importance of not letting that be an excuse 0:01:18.840 --> 0:01:21.840 to not learn about the technology and not letting it 0:01:21.959 --> 0:01:24.600 be an excuse for us to just dig in, get 0:01:24.640 --> 0:01:27.960 your hands dirty, and see what you can do to 0:01:28.040 --> 0:01:31.759 make it work for you, because all the while, if 0:01:31.800 --> 0:01:36.959 we are continuously shine away from it, then we're just 0:01:36.959 --> 0:01:39.600 getting further and further behind. And I literally see it 0:01:39.800 --> 0:01:43.800 every day. I've been in the tech industry, in the 0:01:43.959 --> 0:01:51.120 corporate and the startup industry world since twenty thirteen or so. 0:01:52.080 --> 0:01:55.440 I started down this path when I started undergrad at 0:01:55.440 --> 0:02:00.760 Mississippi State in two thousand and three, and Georgia Tech 0:02:01.200 --> 0:02:04.440 I started in two thousand and eight, and so I 0:02:04.520 --> 0:02:07.680 literally have seen it and lived it all of my 0:02:07.760 --> 0:02:11.120 internships and all the companies you can imagine all of 0:02:11.160 --> 0:02:15.359 the research projects over the past twenty years or so, 0:02:16.200 --> 0:02:18.600 we are still left out of the conversation. We're still 0:02:18.680 --> 0:02:21.639 left behind. We're still not taking advantage of the technology 0:02:22.040 --> 0:02:24.440 and how it can work for us in our everyday lives. 0:02:24.520 --> 0:02:27.320 So that's that's the message that I try to always 0:02:27.600 --> 0:02:29.480 tell people about when I'm speaking about it. 0:02:30.400 --> 0:02:33.720 So when I when listening to you talk there, it 0:02:33.760 --> 0:02:36.320 gives me this idea that you know, when even when 0:02:36.320 --> 0:02:38.519 I have conversations on this podcast, it's about there, there's 0:02:38.800 --> 0:02:42.839 a great fear. You know, with AI, you know we 0:02:42.919 --> 0:02:45.440 hear the news talks about this is going to take 0:02:45.520 --> 0:02:48.320 jobs and not even go to restaurants now you know, 0:02:48.560 --> 0:02:50.000 you go to a drive through when you can hear 0:02:50.040 --> 0:02:51.000 AI talking to you. 0:02:51.120 --> 0:02:52.160 These auto. 0:02:53.639 --> 0:02:56.520 Order takers are taking orders now because it was for 0:02:56.520 --> 0:02:58.120 a long time it was hard to get people to 0:02:58.440 --> 0:03:01.440 fill those roles. So they true to a certain extent, 0:03:01.480 --> 0:03:05.080 these are going to take jobs. And so when you 0:03:05.400 --> 0:03:09.079 have communities of people that you deal with everyday, communities 0:03:09.120 --> 0:03:12.960 that we live in, who do see this happening? What 0:03:13.080 --> 0:03:16.040 is the offense we can play instead of just defense? 0:03:16.120 --> 0:03:19.560 And how do we play that offense strategically and just tactically, 0:03:19.600 --> 0:03:20.760 like what should we be doing? 0:03:23.480 --> 0:03:27.320 Yeah, so it can be as simple as reading a 0:03:27.400 --> 0:03:31.120 blog on AI. Letting that be a part of your 0:03:31.120 --> 0:03:35.160 regular routine, staying in the know about the news and 0:03:35.200 --> 0:03:39.800 what's new, what's to come. We recently saw that some 0:03:39.800 --> 0:03:43.760 companies have released texts to video AI and generative AI. 0:03:44.400 --> 0:03:47.680 They have now released instead of just in putting texts 0:03:47.800 --> 0:03:50.320 into a chat boy, you can now input texts and 0:03:51.000 --> 0:03:54.360 images to be able to create outputs. So they're becoming 0:03:54.400 --> 0:03:57.720 what we call multimodal. There are also new business segments 0:03:57.760 --> 0:04:01.240 that are coming out. I also talk about because people 0:04:01.520 --> 0:04:04.320 have a concern about the technology and the data that 0:04:04.360 --> 0:04:08.000 it's being trained on. We now need our and will 0:04:08.040 --> 0:04:12.520 soon be mandated by policy and government to have special 0:04:12.600 --> 0:04:16.880 companies come in and test your technology and do what 0:04:16.920 --> 0:04:19.440 we call red teaming, intentionally try to break it and 0:04:19.480 --> 0:04:22.080 see what the issues are. All these are new business 0:04:22.080 --> 0:04:26.040 opportunities and who better to come up with business opportunities 0:04:26.040 --> 0:04:28.480 to test for biases than those who are in the minority. 0:04:29.040 --> 0:04:32.880 And so we have even at my role and working 0:04:33.080 --> 0:04:37.120 as a principal AI scientist at Amazon, we have done 0:04:37.160 --> 0:04:42.200 contrasts with several minority minority businesses to help get testing 0:04:42.279 --> 0:04:46.279 data to help test our algorithms for bias, biases and 0:04:46.320 --> 0:04:50.640 bias evaluation and other areas of responsible AI. On the 0:04:50.680 --> 0:04:53.280 other hand, you look at the work that I've done 0:04:53.279 --> 0:04:56.800 in the community, for example with bean Path in Jackson, Mississippi, 0:04:56.839 --> 0:05:02.360 my hometown. We have and very intentional about going straight 0:05:02.400 --> 0:05:05.119 to the community. This is literally what you can start 0:05:05.160 --> 0:05:08.240 doing today. You can start using this for your business. 0:05:08.480 --> 0:05:11.240 Here are the tools. We even have workshops set up 0:05:11.279 --> 0:05:13.120 you can come in for free. You could be a 0:05:13.120 --> 0:05:16.640 mom and pop business. You can be a startup company, 0:05:16.960 --> 0:05:19.719 you can be a mid sized business, real estate company 0:05:19.800 --> 0:05:23.320 that's been in operation for over you know, two three decades. 0:05:23.720 --> 0:05:27.320 We have something for you. We also have a Senior 0:05:27.360 --> 0:05:30.880 Citizen program where we teach senior systems how to come in, 0:05:31.160 --> 0:05:34.599 get on the computer, not just check for their adoptor's 0:05:34.600 --> 0:05:38.200 appointments and log in and get their lab results. They 0:05:38.200 --> 0:05:40.720 are now able to engage in social media that now 0:05:40.720 --> 0:05:44.640 are able to engage in how to build a website 0:05:44.720 --> 0:05:47.760 for UH you know, a group like a Sunday school 0:05:47.760 --> 0:05:51.520 class or something like that. We also impact the youth. 0:05:51.839 --> 0:05:56.719 We have summer camps, we have UH spring camps, fill camps, 0:05:56.720 --> 0:06:00.599 we have stem Saturdays where they come in and engage 0:06:00.600 --> 0:06:03.880 in our maker space and able to use not just 0:06:04.040 --> 0:06:06.440 AI at a computer, but tangible things you can touch, 0:06:07.160 --> 0:06:10.120 like use AI to plan a guarden and use AI 0:06:10.240 --> 0:06:13.320 to design a T shirt. And so we try to 0:06:13.320 --> 0:06:16.320 make it as engaging and as culturally relevant as possible 0:06:16.600 --> 0:06:19.240 to let people know that AI is for everyone and 0:06:19.279 --> 0:06:23.040 this technology is for you. You belong here, even if 0:06:23.080 --> 0:06:27.159 you're not going to major in this field and get 0:06:27.160 --> 0:06:29.560 a computer science degree, which I want you to do, 0:06:30.279 --> 0:06:32.320 but I understand everybody's not going to do that. There's 0:06:32.320 --> 0:06:33.320 still a place for you. 0:06:34.160 --> 0:06:36.440 I love that, and so I feel like you know 0:06:37.279 --> 0:06:40.200 more and more as we have this AI conversation. You know, 0:06:40.240 --> 0:06:42.720 when people say AI, it's like saying Africa, Like we 0:06:42.880 --> 0:06:47.160 don't realize there's one hundred one hundred countries inside Africa 0:06:47.160 --> 0:06:49.239 and people just say I'm going to Africa, Like okay, 0:06:49.240 --> 0:06:51.599 where in Africa? It's like it's a whole continent. And 0:06:51.680 --> 0:06:57.000 so if you can talk about different AI use cases, 0:06:57.000 --> 0:06:59.960 different AI technologies so that we can start to part 0:07:00.080 --> 0:07:03.600 or what is happening in the world today because you've 0:07:03.600 --> 0:07:06.240 got chat botes, you got agi people are really afraid of. 0:07:06.720 --> 0:07:09.039 But can you break down what these things are? 0:07:11.000 --> 0:07:13.600 Right? So, what we like to do when just describing this, 0:07:13.720 --> 0:07:16.400 we like to put it into two different categories. So 0:07:16.440 --> 0:07:21.200 there's what we call traditional AI, excuse me, traditional AI, 0:07:21.600 --> 0:07:24.960 which is what we normally would have thought about AI 0:07:25.080 --> 0:07:30.160 before this last couple of years, where you're training models 0:07:30.560 --> 0:07:35.080 like a computer to act, think, talk, respond, et cetera, 0:07:35.240 --> 0:07:38.360 like a human based on previous data that it has 0:07:38.560 --> 0:07:41.400 learned from. So now we can make decisions about things 0:07:41.400 --> 0:07:44.320 in the future that we haven't seen before because of 0:07:44.320 --> 0:07:46.560 the things that we've learned from in the past. In 0:07:46.640 --> 0:07:49.760 this in this what we call an AI model, So 0:07:50.040 --> 0:07:53.240 using it for predictions, using it for data analytics, using 0:07:53.280 --> 0:07:56.720 it for it could be predicting what I'm saying in 0:07:56.800 --> 0:08:00.200 speech in terms of natural language processing. It can be 0:08:00.440 --> 0:08:05.720 in terms of programming or robot to move arms a 0:08:05.760 --> 0:08:10.160 certain way according to the control system that for every 0:08:10.240 --> 0:08:15.160 action is an opposite reaction. There's also we saw in 0:08:15.240 --> 0:08:18.960 terms of recognizing things in images, recognizing things in video. 0:08:19.400 --> 0:08:23.360 That's the traditional AI that we were talking about now today. 0:08:23.520 --> 0:08:26.800 Most recently the last couple of years, we've seen generative 0:08:26.880 --> 0:08:33.760 AI become really popular, and that basically means AI framework 0:08:33.960 --> 0:08:39.040 that allows you to generate keyword genitive content based on 0:08:39.120 --> 0:08:43.280 some previous data. So we can be generating a conversation 0:08:43.480 --> 0:08:46.040 like in a chatbot, we can be generating images or 0:08:46.160 --> 0:08:49.079 videos based on some prompt that you've given it. And 0:08:49.120 --> 0:08:53.000 so this is the era of genitive AI, which a 0:08:53.000 --> 0:08:56.280 lot of people use for things like marketing. If you're 0:08:56.280 --> 0:08:59.079 trying to create pictures for your website, if you're trying 0:08:59.120 --> 0:09:02.800 to get an understanding of something that you're trying to 0:09:02.800 --> 0:09:05.600 search for it can respond in a way that's very 0:09:05.640 --> 0:09:10.080 similar to a human by putting together the different uh 0:09:10.679 --> 0:09:15.079 words and a sentence that most likely, according to statistics, 0:09:15.480 --> 0:09:17.920 match the style that they think that you're looking for 0:09:18.240 --> 0:09:20.520 based on the prompt that you gave it. And so 0:09:20.600 --> 0:09:22.920 that's what we call genitive AI. And again, the use 0:09:22.960 --> 0:09:26.160 cases are pretty much endless anything that you neique content for, 0:09:26.320 --> 0:09:29.040 which is a lot of different things, Like I said, marketing, 0:09:29.160 --> 0:09:32.839 website development, coming up with ideas on how to do 0:09:32.880 --> 0:09:37.920 pretty much anything, create a vacation planner, or create a 0:09:37.960 --> 0:09:43.120 middle plan, or even understand how can you go about, uh, 0:09:43.200 --> 0:09:47.280 you know, building a dy project. Uh. Those are some 0:09:47.320 --> 0:09:50.439 of the use cases that we've seen for generative AI. 0:09:51.679 --> 0:09:54.480 So what's so funny about this is, you know, during 0:09:54.600 --> 0:09:56.760 it's not funny, I shouldn't say that. It's so interesting 0:09:56.840 --> 0:09:59.960 about this is like during COVID there was this human 0:10:00.000 --> 0:10:02.960 among iss like freelancer movement, because people say, why am 0:10:02.960 --> 0:10:04.440 I going to this job when I can just go 0:10:04.480 --> 0:10:06.120 start my own thing. I can go start my own 0:10:06.160 --> 0:10:09.319 marketing company, my own photography business, et cetera, et cetera. 0:10:10.040 --> 0:10:12.720 And then you have these technologies that are coming out 0:10:12.800 --> 0:10:16.040 and to your point, I can do my whole content 0:10:16.120 --> 0:10:18.840 calendar for social media by type and a few prompts 0:10:18.880 --> 0:10:21.920 in on chat GPT you know, four oh just came out, 0:10:22.000 --> 0:10:24.640 you know for Omni just dropped in this by this 0:10:24.760 --> 0:10:29.960 recording yesterday. And so I think about we kind of 0:10:30.000 --> 0:10:32.840 got boxed into this, you know, new world that we 0:10:32.880 --> 0:10:35.040 didn't even know, many of us didn't know we were 0:10:35.080 --> 0:10:38.120 going to. So we've taken this leap in entrepreneurship and 0:10:38.160 --> 0:10:40.079 now you have this thing coming to each at lunch. 0:10:40.600 --> 0:10:45.280 And so how how do people who have taken that 0:10:45.400 --> 0:10:50.000 leap of entrepreneurship make sure that they're, if not building, 0:10:50.200 --> 0:10:51.000 leveraging it. 0:10:54.240 --> 0:10:58.920 Absolutely. So I'll have to say this to my my MENTI. 0:10:58.960 --> 0:11:01.240 I have some mentees, you know, people that I mentored, 0:11:01.720 --> 0:11:06.160 and you know, this gen Z I'm a millennial, This 0:11:06.240 --> 0:11:10.240 gen Z generation they're different, you know, and even after them, 0:11:10.520 --> 0:11:13.920 the pandemic babies, they're different too. But I have to 0:11:13.920 --> 0:11:16.719 explain to them, you know, you have to make yourself marketable. 0:11:17.800 --> 0:11:19.319 I understand you not if you don't want to go 0:11:19.360 --> 0:11:21.360 to college. I understand you don't think it's worth it 0:11:22.040 --> 0:11:26.040 monetary wise, especially if you don't have financial aid. You know, 0:11:26.160 --> 0:11:27.920 there are ways to make money. There are ways. They're 0:11:27.960 --> 0:11:30.600 very successful people who didn't go to college, But you 0:11:30.640 --> 0:11:32.720 have to figure out how to make yourself competitive in 0:11:32.760 --> 0:11:36.880 today's world. The same is true for any large tech company. 0:11:37.080 --> 0:11:41.520 The largest most successful tech companies are successful because they 0:11:41.600 --> 0:11:44.800 figured out how to constantly adapt. They figure out how 0:11:44.840 --> 0:11:47.960 to constantly move with the times and stay relevant and 0:11:47.960 --> 0:11:50.760 stay competitive. And that's what you as an individual have 0:11:50.840 --> 0:11:54.240 to do with your business too, regardless of what it is. 0:11:54.320 --> 0:11:58.839 And so in terms of using AI, use it again, 0:11:59.000 --> 0:12:01.319 find a way to use it to your advantage. Find 0:12:01.400 --> 0:12:05.480 ways that nobody else is using it because we now 0:12:05.559 --> 0:12:08.000 have this interface on top of this, like you said, 0:12:08.000 --> 0:12:12.040 this technology. People may not have seen it coming, but 0:12:12.600 --> 0:12:14.600 for example, we were using genati of AI in the 0:12:14.640 --> 0:12:20.200 actual AI industry, you know, like years ago, and so 0:12:21.320 --> 0:12:24.720 now many people can use it because these companies have 0:12:24.720 --> 0:12:27.080 figured out, okay, let's make it easier for everybody to 0:12:27.120 --> 0:12:29.800 interface to this, which I think was a great idea 0:12:29.920 --> 0:12:33.200 because it helps level of playing field. The one thing 0:12:33.559 --> 0:12:37.280 technology does is it's cold, right, it's computer programming code. 0:12:37.320 --> 0:12:40.000 Once it's released into the world, you can't really get 0:12:40.000 --> 0:12:41.800 it back. That could be a good thing that could 0:12:41.800 --> 0:12:43.960 be a bad thing. But that's the one thing that 0:12:44.040 --> 0:12:46.600 you can't take away from us and people in our community. 0:12:46.720 --> 0:12:48.760 Once it's out there, is out there. So now we 0:12:48.800 --> 0:12:51.760 have access to it. Now we have these interfaces, we 0:12:51.800 --> 0:12:54.280 can now use it to our advantage. And like I said, 0:12:54.360 --> 0:12:57.920 there are so many ways people are innovating every day 0:12:58.559 --> 0:13:03.240 with these these new technologies and interfacing figuring out how 0:13:03.240 --> 0:13:04.760 to use it for their business, whether it's on the 0:13:04.800 --> 0:13:08.160 internal operation side, like helping make you more efficient, or 0:13:08.200 --> 0:13:11.920 even on the external side, like generating content for other 0:13:12.040 --> 0:13:15.520 people that are part of your freelance business. And so 0:13:16.400 --> 0:13:20.680 it really just takes some sitting down. You have the tools, 0:13:20.760 --> 0:13:23.400 you just have to let your mind take you to 0:13:23.480 --> 0:13:26.199 that place of innovation so that you can make a 0:13:26.240 --> 0:13:28.880 difference and you could be that competitive person in the market. 0:13:30.000 --> 0:13:34.120 I would definitely start by just educating yourself. There's no 0:13:34.280 --> 0:13:38.760 shortage of information out there, especially in today's information age. 0:13:39.440 --> 0:13:41.319 There are so many tutorials out there, a lot of 0:13:41.360 --> 0:13:45.240 them are free, and so if you're disciplined enough you 0:13:45.280 --> 0:13:47.800 want to do that, then great. If you like to 0:13:48.240 --> 0:13:52.120 enroll in a program or course or an academy of 0:13:52.160 --> 0:13:55.280 some sort. I encourage you to do that too, but 0:13:55.520 --> 0:13:59.960 just don't stop learning, and remember you have the tool 0:14:00.200 --> 0:14:01.040 now to innovate. 0:14:02.040 --> 0:14:07.480 It's particular the video on AI Generative AI. You know, 0:14:07.640 --> 0:14:10.720 it's happening so fast and so one of the critiques 0:14:10.800 --> 0:14:13.600 people have is, you know how you can tell you 0:14:13.640 --> 0:14:15.760 can look at an image and tell, okay now because 0:14:15.800 --> 0:14:17.920 the finger maybe it's eight fingers on one hand, like 0:14:17.920 --> 0:14:22.000 it's something because there's crazy stuff. But a year ago 0:14:22.720 --> 0:14:25.240 it couldn't even produce half of what is producing now. 0:14:25.280 --> 0:14:28.240 But it's happening so fast and so and I'm not 0:14:28.240 --> 0:14:29.720 going to give the negative spendity. I want you to 0:14:29.760 --> 0:14:32.440 give the positive side of this. It is what excites 0:14:32.480 --> 0:14:36.920 you most about the future we're walking into, specific to 0:14:36.960 --> 0:14:38.520 how AI is going to impact our lives. 0:14:40.960 --> 0:14:45.200 So I think it is really excited for me to 0:14:45.240 --> 0:14:49.000 have a conversation like this with just about anybody, even 0:14:49.040 --> 0:14:54.560 my grandmother in Jackson, Mississippi, because I tried for years 0:14:54.560 --> 0:14:57.280 to have this conversation with people, and you know, nobody 0:14:57.520 --> 0:14:59.440 knew what I was talking about. Nobody you know, like, 0:14:59.440 --> 0:15:01.800 oh yeah, what's these are smart girls, that's not for me. 0:15:02.320 --> 0:15:05.120 So finally we can sit at the table, we can 0:15:05.200 --> 0:15:07.360 talk about these things. At least even if it's on 0:15:07.360 --> 0:15:11.080 a high level, it's at least something. And so what 0:15:11.200 --> 0:15:14.160 we've been trying to tell people, uh for the longest, 0:15:14.240 --> 0:15:17.080 now that they're believing it, they're seeing it, and hopefully 0:15:17.760 --> 0:15:20.480 they're able to take advantage of it. I think for 0:15:20.600 --> 0:15:24.120 me in particular, I always say some of the most 0:15:24.120 --> 0:15:27.520 primitive areas and industries that I think AI can impact 0:15:28.000 --> 0:15:32.640 our healthcare and transportation. I love the applications that I'm 0:15:32.680 --> 0:15:36.040 seeing come down the line, especially in terms of look 0:15:36.040 --> 0:15:39.920 at the black community, especially black women, black women's health, 0:15:40.760 --> 0:15:44.720 mental health, you know, physical health, even even amongst the 0:15:44.840 --> 0:15:48.080 black male community, Like, there's so much innovation we can 0:15:48.120 --> 0:15:50.320 do there. That's probably one of the most untapped areas 0:15:50.520 --> 0:15:52.920 that if you have the data, you can do a 0:15:52.960 --> 0:15:55.480 lot with AI and data science to be able to 0:15:55.560 --> 0:16:00.600 help people, you know, feel better, help people you operate 0:16:00.640 --> 0:16:04.000 better in their everyday lives. And I mentioned also transportation. 0:16:04.120 --> 0:16:06.600 I'm still waiting on my my flying car so I 0:16:06.600 --> 0:16:10.040 can fly with Tavvy in Atlanta, and so I just 0:16:10.120 --> 0:16:13.120 hope that you know, someday, real soon, I could do that. 0:16:14.120 --> 0:16:17.080 So how do we get more Nashally's in places like 0:16:17.680 --> 0:16:21.960 you know, Jackson, Mississippi, because I think about what you're doing, 0:16:22.240 --> 0:16:24.920 and there's others there's people who you know, I won't 0:16:24.960 --> 0:16:26.680 mention names right now, but there's other people I know 0:16:26.720 --> 0:16:30.120 who are gone back home, back to their original hometowns 0:16:30.640 --> 0:16:33.440 and have recognized that it's not just about being in 0:16:33.440 --> 0:16:36.680 Silicon Valley, it's not just about being in Miami, but 0:16:36.760 --> 0:16:40.480 they're back there. The people back home need what the 0:16:41.000 --> 0:16:44.840 future that they're being exposed to, And so how do 0:16:44.880 --> 0:16:47.800 we get more people to recognize this opportunity? Like what 0:16:47.840 --> 0:16:50.760 did you see or what called you? Pulled you back 0:16:50.800 --> 0:16:53.200 home and said, you know what I'm doing big in 0:16:53.400 --> 0:16:56.400 Atlanta and wherever else I'm at, but there's still work 0:16:56.440 --> 0:16:57.880 for me to do here in Jackson. 0:16:59.360 --> 0:17:02.080 Yeah. Well, first of all, all my family still in Jackson, 0:17:02.400 --> 0:17:05.480 majority of all my family in Jackson and Mississippi area. 0:17:05.600 --> 0:17:11.479 So never will forget home, never will forget my people, 0:17:12.520 --> 0:17:16.280 my friends, my family. And then also it had so 0:17:16.440 --> 0:17:21.280 much potential. I remember coming back home after being in 0:17:21.320 --> 0:17:25.320 Silicon Valley, in New York City and Atlanta overseas even 0:17:25.320 --> 0:17:28.879 as close as you know, Memphis and New Orleans, and 0:17:28.920 --> 0:17:33.280 you're seeing so much progression happen all around you, But 0:17:33.880 --> 0:17:36.800 in my hometown of Jacksonssissippi, I would see, you know, 0:17:37.040 --> 0:17:39.919 just I didn't see the same rate of change that 0:17:40.000 --> 0:17:42.160 I was seeing in other areas. And so I wanted 0:17:42.160 --> 0:17:44.760 to be a part of that and at least contribute 0:17:45.080 --> 0:17:49.760 in terms of STEM education, exposure and tech because that 0:17:49.880 --> 0:17:52.680 was something I had been successful in. And so I 0:17:52.760 --> 0:17:55.680 knew that I contributed that, you know, started the nonprofit 0:17:55.720 --> 0:17:59.000 being Path and working on the real estate development to 0:17:59.040 --> 0:18:02.119 do a lot more there in Jackson. And so I 0:18:02.200 --> 0:18:05.840 knew that, you know, why not Jackson because it had 0:18:05.920 --> 0:18:08.919 definitely has the most potential probably out of any city 0:18:09.520 --> 0:18:12.199 I've seen this, and I think if we can do 0:18:12.240 --> 0:18:13.760 it there, we can do it anywhere. 0:18:14.960 --> 0:18:20.120 So a big conversation that people who are concerned about 0:18:20.200 --> 0:18:23.040 AI have is where it's getting its data from. And 0:18:23.080 --> 0:18:25.360 you mentioned this earlier, like, you know, it learns from 0:18:25.600 --> 0:18:29.399 historical you know, facts, historical deta sets, et cetera. And 0:18:29.480 --> 0:18:32.480 so I was listening to an episode of some podcasts 0:18:32.760 --> 0:18:35.280 two weeks ago maybe, and it was talking about how, 0:18:35.720 --> 0:18:38.679 you know, particularly like open AI and others have downloaded 0:18:38.760 --> 0:18:43.160 like entire Hollywood movie, you know, libraries and entire music 0:18:43.240 --> 0:18:47.280 catalogs by record labels and entire you know libraries from 0:18:47.359 --> 0:18:50.399 you know, random housing, et cetera, to feed the model. 0:18:51.560 --> 0:18:53.760 Some of that on some of that illegally because those 0:18:53.800 --> 0:18:58.080 are copywritten you know materials and can you So there 0:18:58.320 --> 0:19:01.240 they are deep ethical concerns. The point here and so 0:19:01.640 --> 0:19:04.919 what concerns you when you think about how we're building 0:19:04.960 --> 0:19:07.720 this so that you can work in your own way 0:19:07.760 --> 0:19:09.440 to ensure that we're doing this in a way that's 0:19:09.440 --> 0:19:11.119 still fair to people and creators. 0:19:11.240 --> 0:19:17.440 Even yeah, it we I mean, I can't say it enough. 0:19:17.520 --> 0:19:24.920 But so in the tech industry there's three percent. There's 0:19:24.960 --> 0:19:28.080 a stat that says three percent of the tech industry 0:19:28.160 --> 0:19:33.399 are black females, and that number has been the same 0:19:33.480 --> 0:19:38.240 for I think they said last twenty or thirty years. 0:19:39.200 --> 0:19:42.359 So that is a problem and I said black women, 0:19:42.400 --> 0:19:45.120 but the stats are similar for black men and look 0:19:45.160 --> 0:19:49.560 at any other BIPOD group. I think that until we 0:19:49.680 --> 0:19:55.359 have diversity on the tech development teams, we will continue 0:19:55.400 --> 0:19:57.640 to see a lot of these issues because that's where 0:19:57.680 --> 0:20:01.000 a lot of this is flagged that you know, upper 0:20:01.080 --> 0:20:03.679 level management. I think we're seeing a lot more black 0:20:05.040 --> 0:20:09.640 and BIPOD CEOs of tech companies which is great. I'm 0:20:09.680 --> 0:20:13.960 hoping that they can help steer, you know, more inclusion 0:20:14.160 --> 0:20:20.560 in these emerging technologies. But the person who's actually doing 0:20:20.600 --> 0:20:23.240 the coding, the person who's actually training the model, the 0:20:23.280 --> 0:20:26.159 person who's actually gathering the data and making sure that 0:20:26.160 --> 0:20:28.359 the data is good enough to go into the model. 0:20:28.800 --> 0:20:31.119 That's where we need that extra set of eyes to 0:20:31.200 --> 0:20:36.320 make sure that we're seeing the level of inclusion that 0:20:36.359 --> 0:20:38.680 we want to see and also thinking of the right 0:20:39.200 --> 0:20:44.280 bias testing that we should be adequately thinking about. Also 0:20:45.920 --> 0:20:49.879 a lot of the data. I mean, in this country, 0:20:50.240 --> 0:20:54.080 we have no policies in place. I mean they're a 0:20:54.080 --> 0:20:56.880 lot closer than what we used to be just three 0:20:56.960 --> 0:21:02.240 years ago, twenty nineteen, but we're very inching along in 0:21:02.320 --> 0:21:05.560 terms of you know, what is considered in compliance, what 0:21:05.680 --> 0:21:08.800 is not in compliance, what are how do we hold 0:21:08.840 --> 0:21:13.760 companies accountable? How do we even put some standards in place? 0:21:14.040 --> 0:21:16.720 And it's very difficult. So it's not a trivial thing, 0:21:16.760 --> 0:21:19.840 even if everyone's hearts and minds were in the right place. 0:21:20.359 --> 0:21:22.720 So it is something that we're constantly going to have 0:21:22.760 --> 0:21:24.960 to work at, and it's a what we call a 0:21:25.040 --> 0:21:28.440 shared responsibility model. Everybody has to play a part in this, 0:21:29.119 --> 0:21:32.520 But ultimately, I would say again it boils down to, 0:21:33.280 --> 0:21:38.200 you know, getting more diversity in the tech development roles. 0:21:39.359 --> 0:21:42.000 What skills are going to be most valuable in a 0:21:42.880 --> 0:21:47.680 market that's driven by largely AI models, Like what skills 0:21:47.880 --> 0:21:50.320 when you talked about those kids who were like questioning 0:21:50.480 --> 0:21:53.639 going to college, you know, what skills should they be 0:21:53.680 --> 0:21:55.879 learning to ensure that they can still find a place 0:21:55.960 --> 0:21:59.320 in the market. 0:21:59.600 --> 0:22:04.199 They they should definitely be very hands on, uh and 0:22:04.280 --> 0:22:07.040 at least somewhat tech savvy when it comes to these 0:22:07.040 --> 0:22:12.480 emergent technologies. I again, it's so much information out there, 0:22:12.680 --> 0:22:17.120 it's really no excuse to not learn. I mean, even 0:22:17.119 --> 0:22:19.320 look at social media. We've been exposed. Look at how 0:22:19.320 --> 0:22:22.000 fast something can go viral. Look at how fast a 0:22:22.119 --> 0:22:24.679 trend can catch on across the entire world, or a 0:22:24.720 --> 0:22:29.520 dance on TikTok and take off that in that same 0:22:29.640 --> 0:22:34.639 vein these technical courses on how to learn how to 0:22:34.720 --> 0:22:36.960 use your to AI for marketing, how to learn how 0:22:36.960 --> 0:22:42.560 to use basic programming skills to help you solve problems, 0:22:42.600 --> 0:22:47.280 and using different products on the market that you know, 0:22:47.359 --> 0:22:50.280 learning how to evaluate products. Even like all these skill 0:22:50.320 --> 0:22:53.879 sets are necessary and unfortunately a lot of our youth 0:22:54.440 --> 0:22:58.159 are you know, not engaging with these things, you know, 0:22:58.359 --> 0:23:00.920 at as they should be in order to be prepared. 0:23:01.400 --> 0:23:05.960 I do whole hardly believe that people can be prepared 0:23:06.320 --> 0:23:09.080 for this next wave. And just think about this is 0:23:09.080 --> 0:23:11.400 only the beginning, Like have we barely scratched the surface 0:23:11.440 --> 0:23:14.920 of because the technologies just now get into the hands 0:23:14.960 --> 0:23:17.600 of people. It's just no getting into the hands of 0:23:18.400 --> 0:23:21.400 the black community. So we barely scratched it. Serve there's 0:23:21.480 --> 0:23:24.440 so much potential here and so I just hope that they, 0:23:24.640 --> 0:23:26.200 you know, take the bull by the horns and just 0:23:26.280 --> 0:23:26.800 run with them. 0:23:27.680 --> 0:23:31.040 This is quote on your ex I wont say Twitter, 0:23:31.119 --> 0:23:32.920 but your x account where it's just maybe a couple 0:23:32.960 --> 0:23:35.320 of weeks ago, where you said tech is not black 0:23:35.400 --> 0:23:38.800