# The Father of AI Was a Black Scientist 🤯

An episode of [Earn Your Leisure](https://invisiblenetwork.ai/podcast/1450211392), 27 Feb 2026, 20 min.

Audio: https://podtrac.com/pts/redirect.mp3/traffic.omny.fm/d/clips/e73c998e-6e60-432f-8610-ae210140c5b1/8dbc4f54-a337-4481-9ef2-b355012b0a3d/8ac00838-e0ec-4ee2-832e-b3df0140ceca/audio.mp3?utm_source=Podcast&in_playlist=eac4c628-29cb-469a-b5c8-b355012b0a48

Artificial Intelligence didn’t start in Silicon Valley—and it didn’t start recently. Long before today’s AI boom, a Black scientist laid critical groundwork that modern AI systems still rely on. In this video, we uncover the overlooked history behind AI and why the title “Father of AI” deserves a deeper, more honest conversation. We break down the legacy of David Blackwell, a pioneering mathematician and statistician whose work in probability theory, game theory, and decision-making under uncertainty directly influences how machines learn, optimize, and make decisions today. From Markov decision processes to statistical inference, Blackwell’s contributions shaped the mathematical foundation of artificial intelligence—yet his name is rarely mentioned. This is the history many were never taught. #ArtificialIntelligence #DavidBlackwell #BlackHistory #HiddenHistory #AIOrigins #STEM #BlackExcellence #TechHistory #EarnYourLeisure #MarketMondays See omnystudio.com/listener for privacy information.

## Transcript

[0:01] Speaker 1: This episode is brought to you by P and C Bank.
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[0:43] Speaker 2: This is a very important segment. So can we bring
[0:47] Speaker 2: our guests up?
[0:51] Speaker 3: Hey, hey, how are you now?
[0:58] Speaker 4: We are good?
[0:59] Speaker 5: How you feel it?
[1:01] Speaker 6: I'm feeling great. I'm just a pleasure to be here
[1:04] Speaker 6: and so much fun to listen to you guys. This
[1:07] Speaker 6: is great. Not only is it good stuff, it's interesting
[1:11] Speaker 6: and fun. I love the way you present it and
[1:14] Speaker 6: I'm like, yes, okay, I'm right, I'm taking notes right here,
[1:18] Speaker 6: thank you.
[1:18] Speaker 7: Thank you.
[1:19] Speaker 2: So this is finally important. So okay, Lisa Blackwell. So,
[1:22] Speaker 2: all right, some backstory. If you following video, you know
[1:26] Speaker 2: that they every year they come out with a new
[1:28] Speaker 2: chip and they named the chip after a historical figure,
[1:33] Speaker 2: like one of the top scientists in the world, somebody
[1:35] Speaker 2: that has contributed to artificial intelligence, somebody that you know,
[1:38] Speaker 2: like a pioneer in the space. Last year chip was
[1:43] Speaker 2: named Blackwell. So Blackwell before Ruben is this year. Ruben
[1:48] Speaker 2: hasn't come out yet, So currently Blackwell is the most
[1:51] Speaker 2: advanced chip EVE ever created. Now, the interesting thing is
[1:57] Speaker 2: that Blackwell was named after David Blackwell. David Blackwell is
[2:03] Speaker 2: Lisa's grandfather. Correct, this is a very interesting story, and
[2:10] Speaker 2: we're gonna play a vision. We're gonna play a visual
[2:13] Speaker 2: to talk about it in that week. But before we
[2:14] Speaker 2: played a visual, can you just queue up? Can you
[2:17] Speaker 2: cute this up for us?
[2:20] Speaker 6: Sure? So you're about to see ten minutes of what
[2:24] Speaker 6: is a concept reel for the documentary that we're creating
[2:28] Speaker 6: about my grandfather's story. And it really has a little
[2:35] Speaker 6: bit of the sort of lynch pin that everything turned
[2:38] Speaker 6: around on, like when I start digging into the story
[2:41] Speaker 6: and what I discovered and you guys are getting ready
[2:43] Speaker 6: to see sort of what that looks like. And again
[2:47] Speaker 6: this is the concept reel for the documentary.
[2:51] Speaker 2: Let's play it? Shall We?
[2:53] Speaker 8: Thanks?
[2:53] Speaker 5: Do it?
[2:54] Speaker 3: Okay?
[2:55] Speaker 4: National Medal of Science too. David Blackwell, University of California, Berkeley.
[3:00] Speaker 5: I would like to introduce you to a very very
[3:03] Speaker 5: big GPU named after David Blackwell.
[3:09] Speaker 4: For fundamental contributions to probability theory, mathematical statistics, information theory,
[3:15] Speaker 4: mathematical logic, and Blackwell games.
[3:18] Speaker 8: David Blackwell was it a great amongst greats. He was
[3:22] Speaker 8: the great, great, great mathematician among great mathematicians.
[3:26] Speaker 9: Blackwell was a pioneer who was ahead of its time.
[3:40] Speaker 7: I thought, I knew my grandfather Eggs had done. My
[3:44] Speaker 7: team is at dusk in a five percent dividend man
[3:47] Speaker 7: all the way. Years later, Nvidia named their platform Blackwell.
[3:53] Speaker 7: That's when I started digging and discovered my grandfather. Professor Blackwell,
[3:59] Speaker 7: architect of the mathematics behind artificial intelligence.
[4:15] Speaker 9: A lot of his ideas really cause people to rethink
[4:19] Speaker 9: how do we interpret data?
[4:23] Speaker 8: There are many many standard tools that people use all
[4:27] Speaker 8: the time that are named after David. You know Blackwell
[4:30] Speaker 8: spaces and the raw Blackwell theorem.
[4:33] Speaker 9: Blackwell nowadays is known for what's called the Blackwell rawl theorem,
[4:38] Speaker 9: sort of like saying, if something happens frequently enough, you
[4:42] Speaker 9: should be able to kind of predict what's going to
[4:44] Speaker 9: happen next. However, there might be some bias in some
[4:49] Speaker 9: of that data. That's essentially what the Blackwell Rowl theorem
[4:53] Speaker 9: tells you is that there's a way you can kind
[4:55] Speaker 9: of estimate what should happen, but then minimize the bias
[4:59] Speaker 9: that you would have there in the data. And this
[5:01] Speaker 9: is an amazing approach to doing statistics. If black men
[5:06] Speaker 9: were alive today, he would certainly be the one to
[5:09] Speaker 9: raise up his hand and say, you know, look, there's
[5:11] Speaker 9: bias in AI, there's bias in the training data that
[5:14] Speaker 9: we're using, and we really need to think about minimizing
[5:17] Speaker 9: these as more and more people use these models.
[5:22] Speaker 10: I was very clear that I was going to be
[5:25] Speaker 10: a school teacher. My father had a friend who was
[5:29] Speaker 10: on the school board, and before I finished high school,
[5:33] Speaker 10: he already told my father that if I went to
[5:36] Speaker 10: college and got a degree, he would get me a
[5:39] Speaker 10: job teaching. And this was in the depression, and it
[5:42] Speaker 10: was a great relief to me and everybody else when
[5:46] Speaker 10: it was clear what my future was going to be.
[5:50] Speaker 10: After I got my bachelor's degree in three years, I
[5:55] Speaker 10: decided to spend my fourth year getting a master's degree.
[6:00] Speaker 10: But then at the end of my fourth year I
[6:01] Speaker 10: was encouraged to apply for a fellowship to go on
[6:05] Speaker 10: for a PhD. And I did, and then of course
[6:07] Speaker 10: my objective changed. There were perhaps twenty five awards, twenty
[6:15] Speaker 10: two of them required teaching assistant responsibilities. Three of them
[6:21] Speaker 10: were pure fellowships, and everybody applied for both things, and
[6:29] Speaker 10: the lucky three got the fellowships. And one of my
[6:33] Speaker 10: colleagues who also applied, told me that I was going
[6:37] Speaker 10: to get one of the fellowships, and I said, how
[6:42] Speaker 10: do you know? And he said, well, they're good enough
[6:45] Speaker 10: to be supported, and they're not going to put you
[6:48] Speaker 10: in front of a classroom.
[6:52] Speaker 9: He was right, they were not going to put you
[6:56] Speaker 9: in front of a classroom because because I'm black.
[7:16] Speaker 8: David, you know the I he he was s he
[7:22] Speaker 8: was a black mathematician. And there are no BA black
[7:24] Speaker 8: mathematicians that w would that it were, but I but
[7:27] Speaker 8: they they, they they are very few. Anyway, what was
[7:30] Speaker 8: it like to be David Blackwell? I never could get
[7:32] Speaker 8: him to talk about that, uh, anything about what his
[7:36] Speaker 8: experiences were in Berkeley. He had the problems of not
[7:41] Speaker 8: being hired in the nineteen fifties because the wife of
[7:45] Speaker 8: the chairman of the Berkeley Math Department said, well, I
[7:48] Speaker 8: wouldn't wanna h see us hire somebody that I couldn't
[7:51] Speaker 8: invite to my home yet Jersey name and realized that
[7:56] Speaker 8: David Blackwell was David Blackwell, and did hire 'em these
[8:01] Speaker 8: awful people's dead bodies. But to try to get David
[8:05] Speaker 8: to tell any story of that sort, he just wasn't
[8:08] Speaker 8: a negative person.
[8:21] Speaker 6: My grandfather came to UC Berkeley in nineteen fifty four.
[8:26] Speaker 6: That was the same year that the Brown versus the
[8:29] Speaker 6: Board of Education came down, nineteen fifty four, and my
[8:35] Speaker 6: grandparents are driving across the country with their seven kids
[8:38] Speaker 6: with the Green Book. There was this book that they
[8:40] Speaker 6: had to use to get across the country, so they
[8:44] Speaker 6: knew where they could sleep, safe places that they could sleep.
[8:50] Speaker 6: Then when he got here, he wasn't offered the customary hospitality,
[8:55] Speaker 6: and so he went and they didn't have housing. They
[8:58] Speaker 6: slept in park for two months well and he would
[9:02] Speaker 6: go commute and teach at the school. Seven children.
[9:08] Speaker 11: When we traveled, and we did travel a lot in
[9:11] Speaker 11: the car, in the station wagon. When we would travel,
[9:15] Speaker 11: he would have a map and he would give each
[9:16] Speaker 11: of us a map, and he would have gasoline estimates,
[9:20] Speaker 11: time estimates for how long I was going to take us,
[9:23] Speaker 11: estimates for how long we go to the bathroom, estimates
[9:26] Speaker 11: for what the traffic was going to be. But along
[9:30] Speaker 11: the way he kept us all engaged at our own level.
[9:34] Speaker 12: And it was.
[9:35] Speaker 11: Remarkable to have children ten years apart, one is very young,
[9:39] Speaker 11: the other one is much more mature, and still keep
[9:43] Speaker 11: them all engaged. They somehow felt equal to the challenge.
[9:48] Speaker 11: It was just reflective of his considerate manner of teaching.
[9:55] Speaker 7: Your grandfather was the most delightful, friendly, warmest person.
[10:01] Speaker 4: I just remember him with a smile in his face.
[10:10] Speaker 9: All the years I had heard people talk about David Blackwell,
[10:15] Speaker 9: they never talked about him being angry or bitter. Most importantly,
[10:20] Speaker 9: they never talked about him saying anything negative about anyone else.
[10:25] Speaker 9: And that I think truly is a testament to his character.
[10:28] Speaker 9: That's what I strive to do, is to really say,
[10:32] Speaker 9: maybe things have happened negatively, but let me not try
[10:35] Speaker 9: to dwell on that and let me try to move
[10:37] Speaker 9: forward to say what are positive things that are happening
[10:40] Speaker 9: and what are ways that I can make this world
[10:41] Speaker 9: a better place.
[10:45] Speaker 5: You have arrived at a developer's conference. There will be
[10:51] Speaker 5: a lot of science described algorithms, computer architecture, mathematics.
[11:02] Speaker 12: In March last year, Nvidia unveiled its most ambitious GPU architecture.
[11:08] Speaker 12: We named it Blackwell in honor of doctor Blackwell. Today
[11:14] Speaker 12: we're witnessing the dawn of the AI era, and the
[11:16] Speaker 12: Blackwell architecture is the engine that's powering this new industrial revolution.
[11:22] Speaker 12: We strive each day to honor doctor Blackwell's remarkable legacy
[11:26] Speaker 12: by bringing the promise of AI to industries, developers, and researchers.
[11:30] Speaker 10: Worldwide, specifically through African Americans. I would say, don't consider
[11:39] Speaker 10: your race as a handicap. If you want to go
[11:42] Speaker 10: in a direction, go in that direction. In other words,
[11:47] Speaker 10: make decisions on the same basis as if you were Chinese, right,
[11:52] Speaker 10: or anything else. I don't worry so much about race.
[11:57] Speaker 10: It's going to be a factor. Let other people worry
[12:01] Speaker 10: about it. Don't you worry about it.
[12:06] Speaker 9: David Blackwell was the epitome of excellence. We had a
[12:15] Speaker 9: booth at a math conference, an individual walked by. He
[12:19] Speaker 9: wasn't a black mathematician. He pauses at the table, looks
[12:23] Speaker 9: at the picture of Blackwell and is very confused and
[12:27] Speaker 9: then says, you know, I'm a statistician, but that picture
[12:30] Speaker 9: can't be right. David Blackwell wasn't black. So I asked him, so,
[12:35] Speaker 9: how are you convinced that he wasn't black? And he said, well,
[12:39] Speaker 9: there's this Blackwell Ralph theorem, and it's an amazing theorem.
[12:44] Speaker 9: It just never crossed my mind that Blackwell could be black.
[12:52] Speaker 6: So imagine if David Blackwell didn't have to be hidden
[12:55] Speaker 6: fifty years ago, if he wasn't hidden fifty years ago,
[12:59] Speaker 6: what would stim look like today? What's it going to
[13:02] Speaker 6: look like tomorrow? We don't uphold his face and those.
[13:06] Speaker 3: Like him, Yes, Wow, there, you're wow.
[13:29] Speaker 1: Amazing is incredible watching it, Talking to you, getting to
[13:35] Speaker 1: know you over the past few months has just been incredible.
[13:39] Speaker 1: H The chat is going crazy. You know, we don't
[13:41] Speaker 1: need a month, so we don't need a day to
[13:43] Speaker 1: celebrate our history. We make history every day. And I'm
[13:46] Speaker 1: so happy that you've put this peeple together.
[13:49] Speaker 2: And just for full context for people like, you know,
[13:52] Speaker 2: it's interesting because we talked about AI so much and
[13:54] Speaker 2: who really knew that one of the forefathers of artificial
[13:58] Speaker 2: intelligence was black and held in such high regard in
[14:04] Speaker 2: the world of science that the largest company in the
[14:07] Speaker 2: history of the world, which is in Vidia, named their
[14:12] Speaker 2: most advanced piece of software ever after a black man.
[14:18] Speaker 2: And you know, once again, it just goes back to
[14:20] Speaker 2: I think you said this had in video, like if
[14:22] Speaker 2: he was well known, would what would that do to
[14:25] Speaker 2: stem in our community? Because we aspire to be things
[14:28] Speaker 2: that we see success in. So we aspire to be
[14:31] Speaker 2: athletes and entertainments because we see success in that. It's
[14:34] Speaker 2: not just because we're talented in athletics and entertainment. We are,
[14:38] Speaker 2: but we're also talented in math and science. But we
[14:40] Speaker 2: don't see we don't. We haven't we haven't been exposed
[14:44] Speaker 2: to that. So that's not something that we aspire to be.
[14:47] Speaker 2: But what if what if his story was so well known?
[14:50] Speaker 2: How would that potentially change the trajectory of young people
[14:53] Speaker 2: wanting knowing that artificial intelligence was practically started by somebody
[14:59] Speaker 2: that was black.
[15:01] Speaker 1: Yeah, Lisa, it you know, we had this call and
[15:05] Speaker 1: just I mean, when we talked about relationships earlier in
[15:07] Speaker 1: the show. This is just one of these relationships that
[15:09] Speaker 1: was kind of just like God right, Like I remember
[15:11] Speaker 1: we had a call and it got emotional for a
[15:14] Speaker 1: sec because unbeknownst to you, we are already going to
[15:18] Speaker 1: in Vidio. Shout out to our brother too, and I
[15:20] Speaker 1: know Noel's on the check in. They were like, Hey, Troy,
[15:22] Speaker 1: this this person that you guys should meet. I think
[15:24] Speaker 1: should be incredible. I'm like, who is this person? I
[15:27] Speaker 1: saw the deck, I'm like, oh, this is this is
[15:28] Speaker 1: a great story. But when we connected, it was fresh
[15:32] Speaker 1: off in invest fast and I was like, there was
[15:34] Speaker 1: this message that I got from my brother Marcus Rose
[15:37] Speaker 1: about you know, being who you're going to be so
[15:39] Speaker 1: somebody else can be who they're going to be. And
[15:41] Speaker 1: when I relayed that message to you, I said, yes.
[15:44] Speaker 1: Jensen and Chris, the co founders of Nvidio named the
[15:48] Speaker 1: chip Blackwell, they did their part. They may not have
[15:51] Speaker 1: told his story, but they did their part so that
[15:54] Speaker 1: we could now do our part. I want to know
[15:57] Speaker 1: what this moment feels like for you. I've see being
[16:00] Speaker 1: on the campus, being there meeting the co founder. What
[16:04] Speaker 1: was this moment like for you.
[16:10] Speaker 6: You know, I want to say that this moment right
[16:13] Speaker 6: now is bigger to me than that moment. This moment
[16:18] Speaker 6: to me is bigger because this is my community, this
[16:22] Speaker 6: is what this is who my grandfather cared about, and
[16:27] Speaker 6: these are the people I care about, and so this
[16:29] Speaker 6: is bigger. And to see their excitement about this that
[16:33] Speaker 6: this moves me in a way I cannot express, But
[16:38] Speaker 6: to answer your question directly, it was interesting. It's a
[16:46] Speaker 6: full circle moment in so many ways. Because I just
[16:50] Speaker 6: want to put a finer point on something you said earlier,
[16:53] Speaker 6: where Nvidia named has a history of naming their products
[16:58] Speaker 6: after accomplished scientists and things like that. Well, Vera Ruben,
[17:03] Speaker 6: who's the next one, she's actually an astronomer, and then
[17:07] Speaker 6: another person like they're just different people who are who
[17:11] Speaker 6: have made profound contributions to science. He's the only one
[17:16] Speaker 6: who's really done something in AI specifically, And part of
[17:21] Speaker 6: the reason is there are only a few of them,
[17:24] Speaker 6: and most of them just like Claude Shannon is one
[17:29] Speaker 6: and I think that's what Claude is named after. But
[17:33] Speaker 6: so we came in there and saw what they had,
[17:39] Speaker 6: what they're creating with his work. It's just so powerful.
[17:42] Speaker 6: But it's also something else because nobody knows that he
[17:47] Speaker 6: was there doing it, you know, So it's two things
[17:51] Speaker 6: at once.
[17:52] Speaker 10: Ernest, what's up?
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