Speaker 1: I'm with Lucas and this is black tech, Green money.
Speaker 1: Doctor Nashalie Cephas is the Applied Science Manager for the
Speaker 1: Amazon AI team, focusing on fairness and AI. Based in Atlanta.
Speaker 1: She formerly led the Amazon A nine visual search and
Speaker 1: AR teams, which launched part Finder, the visual search tool
Speaker 1: for replacement parts on the Amazon Shopping app, in twenty eighteen.
Speaker 1: The team for Partfinder came from the Atlanta based startup
Speaker 1: part Pick. In twenty sixteen. Shout out to Jewel Burks.
Speaker 1: Nashally was CTO. Doctor Sephus received her PhD from the
Speaker 1: School of Electrical and Computer Engineering at the Georgia Institute
Speaker 1: of Technology in twenty fourteen. There's a lot of conversations
Speaker 1: about AI happening in our general social discourse, and I
Speaker 1: wonder what's being overlooked.
Speaker 2: Yeah, So, I think we often talk about the limitations
Speaker 2: and the fear of technology. We often talk about how
Speaker 2: we don't feel like the technology was created for us
Speaker 2: and people in our communities, and to some degree, you know,
Speaker 2: I can definitely relate to that, but I do still
Speaker 2: stress the importance of not letting that be an excuse
Speaker 2: to not learn about the technology and not letting it
Speaker 2: be an excuse for us to just dig in, get
Speaker 2: your hands dirty, and see what you can do to
Speaker 2: make it work for you, because all the while, if
Speaker 2: we are continuously shine away from it, then we're just
Speaker 2: getting further and further behind. And I literally see it
Speaker 2: every day. I've been in the tech industry, in the
Speaker 2: corporate and the startup industry world since twenty thirteen or so.
Speaker 2: I started down this path when I started undergrad at
Speaker 2: Mississippi State in two thousand and three, and Georgia Tech
Speaker 2: I started in two thousand and eight, and so I
Speaker 2: literally have seen it and lived it all of my
Speaker 2: internships and all the companies you can imagine all of
Speaker 2: the research projects over the past twenty years or so,
Speaker 2: we are still left out of the conversation. We're still
Speaker 2: left behind. We're still not taking advantage of the technology
Speaker 2: and how it can work for us in our everyday lives.
Speaker 2: So that's that's the message that I try to always
Speaker 2: tell people about when I'm speaking about it.
Speaker 1: So when I when listening to you talk there, it
Speaker 1: gives me this idea that you know, when even when
Speaker 1: I have conversations on this podcast, it's about there, there's
Speaker 1: a great fear. You know, with AI, you know we
Speaker 1: hear the news talks about this is going to take
Speaker 1: jobs and not even go to restaurants now you know,
Speaker 1: you go to a drive through when you can hear
Speaker 1: AI talking to you.
Speaker 2: These auto.
Speaker 1: Order takers are taking orders now because it was for
Speaker 1: a long time it was hard to get people to
Speaker 1: fill those roles. So they true to a certain extent,
Speaker 1: these are going to take jobs. And so when you
Speaker 1: have communities of people that you deal with everyday, communities
Speaker 1: that we live in, who do see this happening? What
Speaker 1: is the offense we can play instead of just defense?
Speaker 1: And how do we play that offense strategically and just tactically,
Speaker 1: like what should we be doing?
Speaker 2: Yeah, so it can be as simple as reading a
Speaker 2: blog on AI. Letting that be a part of your
Speaker 2: regular routine, staying in the know about the news and
Speaker 2: what's new, what's to come. We recently saw that some
Speaker 2: companies have released texts to video AI and generative AI.
Speaker 2: They have now released instead of just in putting texts
Speaker 2: into a chat boy, you can now input texts and
Speaker 2: images to be able to create outputs. So they're becoming
Speaker 2: what we call multimodal. There are also new business segments
Speaker 2: that are coming out. I also talk about because people
Speaker 2: have a concern about the technology and the data that
Speaker 2: it's being trained on. We now need our and will
Speaker 2: soon be mandated by policy and government to have special
Speaker 2: companies come in and test your technology and do what
Speaker 2: we call red teaming, intentionally try to break it and
Speaker 2: see what the issues are. All these are new business
Speaker 2: opportunities and who better to come up with business opportunities
Speaker 2: to test for biases than those who are in the minority.
Speaker 2: And so we have even at my role and working
Speaker 2: as a principal AI scientist at Amazon, we have done
Speaker 2: contrasts with several minority minority businesses to help get testing
Speaker 2: data to help test our algorithms for bias, biases and
Speaker 2: bias evaluation and other areas of responsible AI. On the
Speaker 2: other hand, you look at the work that I've done
Speaker 2: in the community, for example with bean Path in Jackson, Mississippi,
Speaker 2: my hometown. We have and very intentional about going straight
Speaker 2: to the community. This is literally what you can start
Speaker 2: doing today. You can start using this for your business.
Speaker 2: Here are the tools. We even have workshops set up
Speaker 2: you can come in for free. You could be a
Speaker 2: mom and pop business. You can be a startup company,
Speaker 2: you can be a mid sized business, real estate company
Speaker 2: that's been in operation for over you know, two three decades.
Speaker 2: We have something for you. We also have a Senior
Speaker 2: Citizen program where we teach senior systems how to come in,
Speaker 2: get on the computer, not just check for their adoptor's
Speaker 2: appointments and log in and get their lab results. They
Speaker 2: are now able to engage in social media that now
Speaker 2: are able to engage in how to build a website
Speaker 2: for UH you know, a group like a Sunday school
Speaker 2: class or something like that. We also impact the youth.
Speaker 2: We have summer camps, we have UH spring camps, fill camps,
Speaker 2: we have stem Saturdays where they come in and engage
Speaker 2: in our maker space and able to use not just
Speaker 2: AI at a computer, but tangible things you can touch,
Speaker 2: like use AI to plan a guarden and use AI
Speaker 2: to design a T shirt. And so we try to
Speaker 2: make it as engaging and as culturally relevant as possible
Speaker 2: to let people know that AI is for everyone and
Speaker 2: this technology is for you. You belong here, even if
Speaker 2: you're not going to major in this field and get
Speaker 2: a computer science degree, which I want you to do,
Speaker 2: but I understand everybody's not going to do that. There's
Speaker 2: still a place for you.
Speaker 1: I love that, and so I feel like you know
Speaker 1: more and more as we have this AI conversation. You know,
Speaker 1: when people say AI, it's like saying Africa, Like we
Speaker 1: don't realize there's one hundred one hundred countries inside Africa
Speaker 1: and people just say I'm going to Africa, Like okay,
Speaker 1: where in Africa? It's like it's a whole continent. And
Speaker 1: so if you can talk about different AI use cases,
Speaker 1: different AI technologies so that we can start to part
Speaker 1: or what is happening in the world today because you've
Speaker 1: got chat botes, you got agi people are really afraid of.
Speaker 1: But can you break down what these things are?
Speaker 2: Right? So, what we like to do when just describing this,
Speaker 2: we like to put it into two different categories. So
Speaker 2: there's what we call traditional AI, excuse me, traditional AI,
Speaker 2: which is what we normally would have thought about AI
Speaker 2: before this last couple of years, where you're training models
Speaker 2: like a computer to act, think, talk, respond, et cetera,
Speaker 2: like a human based on previous data that it has
Speaker 2: learned from. So now we can make decisions about things
Speaker 2: in the future that we haven't seen before because of
Speaker 2: the things that we've learned from in the past. In
Speaker 2: this in this what we call an AI model, So
Speaker 2: using it for predictions, using it for data analytics, using
Speaker 2: it for it could be predicting what I'm saying in
Speaker 2: speech in terms of natural language processing. It can be
Speaker 2: in terms of programming or robot to move arms a
Speaker 2: certain way according to the control system that for every
Speaker 2: action is an opposite reaction. There's also we saw in
Speaker 2: terms of recognizing things in images, recognizing things in video.
Speaker 2: That's the traditional AI that we were talking about now today.
Speaker 2: Most recently the last couple of years, we've seen generative
Speaker 2: AI become really popular, and that basically means AI framework
Speaker 2: that allows you to generate keyword genitive content based on
Speaker 2: some previous data. So we can be generating a conversation
Speaker 2: like in a chatbot, we can be generating images or
Speaker 2: videos based on some prompt that you've given it. And
Speaker 2: so this is the era of genitive AI, which a
Speaker 2: lot of people use for things like marketing. If you're
Speaker 2: trying to create pictures for your website, if you're trying
Speaker 2: to get an understanding of something that you're trying to
Speaker 2: search for it can respond in a way that's very
Speaker 2: similar to a human by putting together the different uh
Speaker 2: words and a sentence that most likely, according to statistics,
Speaker 2: match the style that they think that you're looking for
Speaker 2: based on the prompt that you gave it. And so
Speaker 2: that's what we call genitive AI. And again, the use
Speaker 2: cases are pretty much endless anything that you neique content for,
Speaker 2: which is a lot of different things, Like I said, marketing,
Speaker 2: website development, coming up with ideas on how to do
Speaker 2: pretty much anything, create a vacation planner, or create a
Speaker 2: middle plan, or even understand how can you go about, uh,
Speaker 2: you know, building a dy project. Uh. Those are some
Speaker 2: of the use cases that we've seen for generative AI.
Speaker 1: So what's so funny about this is, you know, during
Speaker 1: it's not funny, I shouldn't say that. It's so interesting
Speaker 1: about this is like during COVID there was this human
Speaker 1: among iss like freelancer movement, because people say, why am
Speaker 1: I going to this job when I can just go
Speaker 1: start my own thing. I can go start my own
Speaker 1: marketing company, my own photography business, et cetera, et cetera.
Speaker 1: And then you have these technologies that are coming out
Speaker 1: and to your point, I can do my whole content
Speaker 1: calendar for social media by type and a few prompts
Speaker 1: in on chat GPT you know, four oh just came out,
Speaker 1: you know for Omni just dropped in this by this
Speaker 1: recording yesterday. And so I think about we kind of
Speaker 1: got boxed into this, you know, new world that we
Speaker 1: didn't even know, many of us didn't know we were
Speaker 1: going to. So we've taken this leap in entrepreneurship and
Speaker 1: now you have this thing coming to each at lunch.
Speaker 1: And so how how do people who have taken that
Speaker 1: leap of entrepreneurship make sure that they're, if not building,
Speaker 1: leveraging it.
Speaker 2: Absolutely. So I'll have to say this to my my MENTI.
Speaker 2: I have some mentees, you know, people that I mentored,
Speaker 2: and you know, this gen Z I'm a millennial, This
Speaker 2: gen Z generation they're different, you know, and even after them,
Speaker 2: the pandemic babies, they're different too. But I have to
Speaker 2: explain to them, you know, you have to make yourself marketable.
Speaker 2: I understand you not if you don't want to go
Speaker 2: to college. I understand you don't think it's worth it
Speaker 2: monetary wise, especially if you don't have financial aid. You know,
Speaker 2: there are ways to make money. There are ways. They're
Speaker 2: very successful people who didn't go to college, But you
Speaker 2: have to figure out how to make yourself competitive in
Speaker 2: today's world. The same is true for any large tech company.
Speaker 2: The largest most successful tech companies are successful because they
Speaker 2: figured out how to constantly adapt. They figure out how
Speaker 2: to constantly move with the times and stay relevant and
Speaker 2: stay competitive. And that's what you as an individual have
Speaker 2: to do with your business too, regardless of what it is.
Speaker 2: And so in terms of using AI, use it again,
Speaker 2: find a way to use it to your advantage. Find
Speaker 2: ways that nobody else is using it because we now
Speaker 2: have this interface on top of this, like you said,
Speaker 2: this technology. People may not have seen it coming, but
Speaker 2: for example, we were using genati of AI in the
Speaker 2: actual AI industry, you know, like years ago, and so
Speaker 2: now many people can use it because these companies have
Speaker 2: figured out, okay, let's make it easier for everybody to
Speaker 2: interface to this, which I think was a great idea
Speaker 2: because it helps level of playing field. The one thing
Speaker 2: technology does is it's cold, right, it's computer programming code.
Speaker 2: Once it's released into the world, you can't really get
Speaker 2: it back. That could be a good thing that could
Speaker 2: be a bad thing. But that's the one thing that
Speaker 2: you can't take away from us and people in our community.
Speaker 2: Once it's out there, is out there. So now we
Speaker 2: have access to it. Now we have these interfaces, we
Speaker 2: can now use it to our advantage. And like I said,
Speaker 2: there are so many ways people are innovating every day
Speaker 2: with these these new technologies and interfacing figuring out how
Speaker 2: to use it for their business, whether it's on the
Speaker 2: internal operation side, like helping make you more efficient, or
Speaker 2: even on the external side, like generating content for other
Speaker 2: people that are part of your freelance business. And so
Speaker 2: it really just takes some sitting down. You have the tools,
Speaker 2: you just have to let your mind take you to
Speaker 2: that place of innovation so that you can make a
Speaker 2: difference and you could be that competitive person in the market.
Speaker 2: I would definitely start by just educating yourself. There's no
Speaker 2: shortage of information out there, especially in today's information age.
Speaker 2: There are so many tutorials out there, a lot of
Speaker 2: them are free, and so if you're disciplined enough you
Speaker 2: want to do that, then great. If you like to
Speaker 2: enroll in a program or course or an academy of
Speaker 2: some sort. I encourage you to do that too, but
Speaker 2: just don't stop learning, and remember you have the tool
Speaker 2: now to innovate.
Speaker 1: It's particular the video on AI Generative AI. You know,
Speaker 1: it's happening so fast and so one of the critiques
Speaker 1: people have is, you know how you can tell you
Speaker 1: can look at an image and tell, okay now because
Speaker 1: the finger maybe it's eight fingers on one hand, like
Speaker 1: it's something because there's crazy stuff. But a year ago
Speaker 1: it couldn't even produce half of what is producing now.
Speaker 1: But it's happening so fast and so and I'm not
Speaker 1: going to give the negative spendity. I want you to
Speaker 1: give the positive side of this. It is what excites
Speaker 1: you most about the future we're walking into, specific to
Speaker 1: how AI is going to impact our lives.
Speaker 2: So I think it is really excited for me to
Speaker 2: have a conversation like this with just about anybody, even
Speaker 2: my grandmother in Jackson, Mississippi, because I tried for years
Speaker 2: to have this conversation with people, and you know, nobody
Speaker 2: knew what I was talking about. Nobody you know, like,
Speaker 2: oh yeah, what's these are smart girls, that's not for me.
Speaker 2: So finally we can sit at the table, we can
Speaker 2: talk about these things. At least even if it's on
Speaker 2: a high level, it's at least something. And so what
Speaker 2: we've been trying to tell people, uh for the longest,
Speaker 2: now that they're believing it, they're seeing it, and hopefully
Speaker 2: they're able to take advantage of it. I think for
Speaker 2: me in particular, I always say some of the most
Speaker 2: primitive areas and industries that I think AI can impact
Speaker 2: our healthcare and transportation. I love the applications that I'm
Speaker 2: seeing come down the line, especially in terms of look
Speaker 2: at the black community, especially black women, black women's health,
Speaker 2: mental health, you know, physical health, even even amongst the
Speaker 2: black male community, Like, there's so much innovation we can
Speaker 2: do there. That's probably one of the most untapped areas
Speaker 2: that if you have the data, you can do a
Speaker 2: lot with AI and data science to be able to
Speaker 2: help people, you know, feel better, help people you operate
Speaker 2: better in their everyday lives. And I mentioned also transportation.
Speaker 2: I'm still waiting on my my flying car so I
Speaker 2: can fly with Tavvy in Atlanta, and so I just
Speaker 2: hope that you know, someday, real soon, I could do that.
Speaker 1: So how do we get more Nashally's in places like
Speaker 1: you know, Jackson, Mississippi, because I think about what you're doing,
Speaker 1: and there's others there's people who you know, I won't
Speaker 1: mention names right now, but there's other people I know
Speaker 1: who are gone back home, back to their original hometowns
Speaker 1: and have recognized that it's not just about being in
Speaker 1: Silicon Valley, it's not just about being in Miami, but
Speaker 1: they're back there. The people back home need what the
Speaker 1: future that they're being exposed to, And so how do
Speaker 1: we get more people to recognize this opportunity? Like what
Speaker 1: did you see or what called you? Pulled you back
Speaker 1: home and said, you know what I'm doing big in
Speaker 1: Atlanta and wherever else I'm at, but there's still work
Speaker 1: for me to do here in Jackson.
Speaker 2: Yeah. Well, first of all, all my family still in Jackson,
Speaker 2: majority of all my family in Jackson and Mississippi area.
Speaker 2: So never will forget home, never will forget my people,
Speaker 2: my friends, my family. And then also it had so
Speaker 2: much potential. I remember coming back home after being in
Speaker 2: Silicon Valley, in New York City and Atlanta overseas even
Speaker 2: as close as you know, Memphis and New Orleans, and
Speaker 2: you're seeing so much progression happen all around you, But
Speaker 2: in my hometown of Jacksonssissippi, I would see, you know,
Speaker 2: just I didn't see the same rate of change that
Speaker 2: I was seeing in other areas. And so I wanted
Speaker 2: to be a part of that and at least contribute
Speaker 2: in terms of STEM education, exposure and tech because that
Speaker 2: was something I had been successful in. And so I
Speaker 2: knew that I contributed that, you know, started the nonprofit
Speaker 2: being Path and working on the real estate development to
Speaker 2: do a lot more there in Jackson. And so I
Speaker 2: knew that, you know, why not Jackson because it had
Speaker 2: definitely has the most potential probably out of any city
Speaker 2: I've seen this, and I think if we can do
Speaker 2: it there, we can do it anywhere.
Speaker 1: So a big conversation that people who are concerned about
Speaker 1: AI have is where it's getting its data from. And
Speaker 1: you mentioned this earlier, like, you know, it learns from
Speaker 1: historical you know, facts, historical deta sets, et cetera. And
Speaker 1: so I was listening to an episode of some podcasts
Speaker 1: two weeks ago maybe, and it was talking about how,
Speaker 1: you know, particularly like open AI and others have downloaded
Speaker 1: like entire Hollywood movie, you know, libraries and entire music
Speaker 1: catalogs by record labels and entire you know libraries from
Speaker 1: you know, random housing, et cetera, to feed the model.
Speaker 1: Some of that on some of that illegally because those
Speaker 1: are copywritten you know materials and can you So there
Speaker 1: they are deep ethical concerns. The point here and so
Speaker 1: what concerns you when you think about how we're building
Speaker 1: this so that you can work in your own way
Speaker 1: to ensure that we're doing this in a way that's
Speaker 1: still fair to people and creators.
Speaker 2: Even yeah, it we I mean, I can't say it enough.
Speaker 2: But so in the tech industry there's three percent. There's
Speaker 2: a stat that says three percent of the tech industry
Speaker 2: are black females, and that number has been the same
Speaker 2: for I think they said last twenty or thirty years.
Speaker 2: So that is a problem and I said black women,
Speaker 2: but the stats are similar for black men and look
Speaker 2: at any other BIPOD group. I think that until we
Speaker 2: have diversity on the tech development teams, we will continue
Speaker 2: to see a lot of these issues because that's where
Speaker 2: a lot of this is flagged that you know, upper
Speaker 2: level management. I think we're seeing a lot more black
Speaker 2: and BIPOD CEOs of tech companies which is great. I'm
Speaker 2: hoping that they can help steer, you know, more inclusion
Speaker 2: in these emerging technologies. But the person who's actually doing
Speaker 2: the coding, the person who's actually training the model, the
Speaker 2: person who's actually gathering the data and making sure that
Speaker 2: the data is good enough to go into the model.
Speaker 2: That's where we need that extra set of eyes to
Speaker 2: make sure that we're seeing the level of inclusion that
Speaker 2: we want to see and also thinking of the right
Speaker 2: bias testing that we should be adequately thinking about. Also
Speaker 2: a lot of the data. I mean, in this country,
Speaker 2: we have no policies in place. I mean they're a
Speaker 2: lot closer than what we used to be just three
Speaker 2: years ago, twenty nineteen, but we're very inching along in
Speaker 2: terms of you know, what is considered in compliance, what
Speaker 2: is not in compliance, what are how do we hold
Speaker 2: companies accountable? How do we even put some standards in place?
Speaker 2: And it's very difficult. So it's not a trivial thing,
Speaker 2: even if everyone's hearts and minds were in the right place.
Speaker 2: So it is something that we're constantly going to have
Speaker 2: to work at, and it's a what we call a
Speaker 2: shared responsibility model. Everybody has to play a part in this,
Speaker 2: But ultimately, I would say again it boils down to,
Speaker 2: you know, getting more diversity in the tech development roles.
Speaker 1: What skills are going to be most valuable in a
Speaker 1: market that's driven by largely AI models, Like what skills
Speaker 1: when you talked about those kids who were like questioning
Speaker 1: going to college, you know, what skills should they be
Speaker 1: learning to ensure that they can still find a place
Speaker 1: in the market.
Speaker 2: They they should definitely be very hands on, uh and
Speaker 2: at least somewhat tech savvy when it comes to these
Speaker 2: emergent technologies. I again, it's so much information out there,
Speaker 2: it's really no excuse to not learn. I mean, even
Speaker 2: look at social media. We've been exposed. Look at how
Speaker 2: fast something can go viral. Look at how fast a
Speaker 2: trend can catch on across the entire world, or a
Speaker 2: dance on TikTok and take off that in that same
Speaker 2: vein these technical courses on how to learn how to
Speaker 2: use your to AI for marketing, how to learn how
Speaker 2: to use basic programming skills to help you solve problems,
Speaker 2: and using different products on the market that you know,
Speaker 2: learning how to evaluate products. Even like all these skill
Speaker 2: sets are necessary and unfortunately a lot of our youth
Speaker 2: are you know, not engaging with these things, you know,
Speaker 2: at as they should be in order to be prepared.
Speaker 2: I do whole hardly believe that people can be prepared
Speaker 2: for this next wave. And just think about this is
Speaker 2: only the beginning, Like have we barely scratched the surface
Speaker 2: of because the technologies just now get into the hands
Speaker 2: of people. It's just no getting into the hands of
Speaker 2: the black community. So we barely scratched it. Serve there's
Speaker 2: so much potential here and so I just hope that they,
Speaker 2: you know, take the bull by the horns and just
Speaker 2: run with them.
Speaker 1: This is quote on your ex I wont say Twitter,
Speaker 1: but your x account where it's just maybe a couple
Speaker 1: of weeks ago, where you said tech is not black
Speaker 1: or white, it's green as in money. That's why we
Speaker 1: can't risk losing DEI diversity, equality inclusion in tech, furthering
Speaker 1: the financial power gaps in communities, financial empower gaps in
Speaker 1: the communities, from entrepreneurship to big tech. Find a way
Speaker 1: to make tech work for you, your company, or your community.
Speaker 1: So with that what you said there, you know, as
Speaker 1: you and I know, there's only so few nationally, doctor doctor,
Speaker 1: you know, walking around and you know, I'm sure you
Speaker 1: walk into a lot of rooms where nobody looks like
Speaker 1: you or is your gender, you know, especially in the
Speaker 1: work that you do. And so to that last point
Speaker 1: you said, find a way to make it work for you,
Speaker 1: your company or your community. What was the way you
Speaker 1: found to make this work for you where you added value?
Speaker 2: I saw the need to, uh, you know, you know,
Speaker 2: it's the saying, the biblical saying, teach a man how
Speaker 2: to give him a man to fish, You feed him
Speaker 2: for a day, teach him how to fish, feed him
Speaker 2: for a lifetime. So I wanted to help people feed
Speaker 2: themselves for a lifetime. So I started the nonprofit bean
Speaker 2: Path in my hometown of Jackson, Mississippi, which has no
Speaker 2: shortage of challenges. Are you gotta do is watch the
Speaker 2: news or google Jackson, Mississippi to see all the challenges.
Speaker 2: And but I knew that, uh, if you can teach
Speaker 2: these people here, they will go on and teach other people,
Speaker 2: and they will teach other people because that's the cycle.
Speaker 2: And someone even showed me. I remember my eighth grade
Speaker 2: teacher sent me to my first engineering camp when I
Speaker 2: first realized what engineering actually was and if she had
Speaker 2: not done that, I would have majored in music. I
Speaker 2: probably was still really fine. But I think, you know,
Speaker 2: I love music too, but that was a game changer.
Speaker 2: So if I can change the game for somebody else,
Speaker 2: hopefully they keep giving that cycle back and then the
Speaker 2: whole community benefits from that, you know. I think that's
Speaker 2: what did it for me. I mean everything else is
Speaker 2: just kind of you know. I love my role and
Speaker 2: as being a principal scientist and being able to interact
Speaker 2: the cutting edge technology every day. I work with some
Speaker 2: brilliant people from Amazon to startups that I advise to
Speaker 2: other you know, techies, but the real passion comes from
Speaker 2: teaching people how to fish when it comes to technology.
Speaker 1: So I'm kind of position this question a little bit ago,
Speaker 1: but you just brought it back up with you know,
Speaker 1: the teachers that what you would have been in music
Speaker 1: and et cetera. There had to be a conversation or
Speaker 1: a moment or et cetera where somebody pointed out, you know,
Speaker 1: this math and computer science area to you and it's
Speaker 1: like it finally registered, like this is the path of
Speaker 1: me or I don't know what your story is, but
Speaker 1: there's had to be a moment where it just you
Speaker 1: could have went left and you went right. What was that?
Speaker 1: Can you tell more about that conversation that actually made
Speaker 1: the switch flip, because what we're struggling enough already is
Speaker 1: just having math principles in our community to be able
Speaker 1: to take these paths. So can you talk about what
Speaker 1: got your interest to the level where you're like, I'm
Speaker 1: in that's for me.
Speaker 2: Yeah, I knew that, I mean the way this particular.
Speaker 2: So I've done math and science classes. Uh, you know,
Speaker 2: I was I was excelling in math and science as
Speaker 2: a kid. That was just kind of my thing. I
Speaker 2: wasn't really big on on history and all these other subjects,
Speaker 2: but that math and science was my thing. And so
Speaker 2: I remember that eighth that camp after eighth grade, they
Speaker 2: they just showed us, Hey, you type these letters and
Speaker 2: numbers in the computer, you can control things around you.
Speaker 2: And I was just like, oh, what hold on, let
Speaker 2: me try this. And it was so fascinating to me.
Speaker 2: And I was like, wow, I one day I'm gonna
Speaker 2: be able to control the whole world. And that's really
Speaker 2: what it really and so and little did I know
Speaker 2: because this was you know, I mean, I graduated high
Speaker 2: school and like in three and so back then, like
Speaker 2: computers didn't control everything like it does now. Like you know,
Speaker 2: I was, we went through the Y two K together
Speaker 2: and all that, and so we didn't know it was
Speaker 2: gonna be, you know, all this, and so I didn't
Speaker 2: even know that and then let let alone. How I
Speaker 2: ended up getting into A and knowing how that would take,
Speaker 2: I never knew. I just was interested in it. And
Speaker 2: I think for people, we just got to find a
Speaker 2: way to show people in our community the possibilities that's
Speaker 2: out there and how it relates to them according to
Speaker 2: what they're interested in. I got into AI because I
Speaker 2: was interested in the Shazam app and I thought that
Speaker 2: was so cool. Because I was a musician, I was like, well,
Speaker 2: I want to hear this song. I was like, how
Speaker 2: is this thing working? This is so cool? And that
Speaker 2: was the same techniques in AI and music. At the
Speaker 2: time it was even called AI, it was machine learning
Speaker 2: or pattern recognition or digital signal processing, all of that.
Speaker 2: Those are the same techniques were using today in AI
Speaker 2: and national language processing and jeergy of AI. And so
Speaker 2: you know, you never know where things will take. You
Speaker 2: just start with what you're interested in. So we present
Speaker 2: it in a way that you know, shows people. You know, hey,
Speaker 2: you now some people on the street, they've been doing
Speaker 2: math for a long time. They're involved in some legal activities,
Speaker 2: but they know math. You know, we just got to
Speaker 2: make it relate to the things that they're used to,
Speaker 2: the things that you know, excite them.
Speaker 1: You know, you started being path you know, your nonprofit
Speaker 1: to help along this route. And there's a lot of
Speaker 1: nonprofit people, you know, executive directors and community organization folks
Speaker 1: who will listen to this episode to hear you. And
Speaker 1: what role do you see those community organizations and nonprofits
Speaker 1: playing and making sure that we are educated and aware
Speaker 1: of what's happening.
Speaker 2: Yeah, the the organizations and the community, they play a
Speaker 2: huge part in the ecosystem what I call the tech
Speaker 2: ecosystem because I think takings really at the center of
Speaker 2: it all. And people and so whereas you have the
Speaker 2: colleges and universities, you know, they're going to educate the
Speaker 2: people who are going to college. You have government, you
Speaker 2: know they're going to take care of their constituents. You
Speaker 2: have the large corporations, you have the startup companies. But
Speaker 2: what about everybody else, which is the majority of people.
Speaker 2: Those who are not in school, those who don't have
Speaker 2: a startup company are working tech, and those who are
Speaker 2: not in government. That's the majority of people. If we
Speaker 2: touch those people, then we connect the gap in the ecosystem.
Speaker 2: And that's what Being Path focuses on, and that's what
Speaker 2: a lot of other nonprofits that are similar. They try
Speaker 2: to focus on that gap in the community and make
Speaker 2: sure that those people are not forgotten.
Speaker 1: Black Tech Green Money is a production and Blavity afro
Speaker 1: Tech on the Black Effect podcast Networking I Hire Media.
Speaker 1: It's produced by Morgan Debond and me Well Lucas, with
Speaker 1: additional production support by Sarah Ergon and Love Beach. Special
Speaker 1: thank you to Michael Davis and Kate McDonald. Learn more
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Speaker 2: Peace and love,