Where are the Women in AI? – Altitude Accelerator

Theodora Lau recently wrote a Linkedin post called “Where are the Women?”

This was a timely post that responded to the slap in the face to many women, who have made incredible strides to affect substantive change in AI, who saw the NYT article that snubbed the work of prominent women like Fei Fei Li, Timnit Gebru, Kate Crawford, Joy Buolamwini, Meg Mitchell and others too numerous to mention. 

This article came off the week of drama that saw Sam Altman re-installed as the CEO of OpenAI, when 5 days before, he had been fired.

What we’re witnessing is an increasing polarization within the industry where, despite the significant efforts of women engineers, data scientists, policy makers and professionals in AI, there continues to be a lack of recognition and respect for their work and their voices in industry, and in the media.   

This continues to be contentious and women across the AI world are rightfully angered at this perpetual lack of respect for the cumulation of work that has been done by women, and the non-binary community – the perpetual underrepresentation of these critical voices. 

This comes at a time when everyone– researchers and mainstream– are worried about the further development of AI technology and its implications for humanity: jobs, lack of access (knowledge, skills, economic, geography, income), where representation matters as these technologies are built. 

Theodora Lau is the founder of Unconventional Ventures, a public speaker, and an advisor. She is the co-author of The Metaverse Economy (2023) and Beyond Good (2021), and host of One Vision, a podcast on fintech and innovation. Through her work, she explores the intersection of financial services, tech, and humanity.  Theo’s recent blog post had me nodding my head and questioning why this is happening? I reached out for a much-needed conversation.

Hessie Jones

So there was this. Exacting slap in the face to many women who have made incredible strides to affect some substantive change in artificial intelligence, as many of the harms even came to light. So this flap was the recent New York Times article. That snubbed a lot of the work of prominent women like Fei Fei Lee, Timnit Gebru, Kate Crawford, Joy Buolwamini, as well as Meg Mitchell and many, many other women who are too numerous to mention. And it came off the same week of the drama unfolding at OOOOpen AI and Sam Altman, with the help of Microsoft, securing reigns back into the company that had fired him five days before, and it was also the very week where Mia Dan, who is an incredible force in the industry, had just organized a very important gathering of women in AI. Ethics. It was a five year anniversary that not only celebrated the 100 most brilliant women in AI ethics this year, but also tried to address the issue of attempting to bridge the gap in as much of our technology progresses, So what we’re seeing is this increasing polarization in an industry, despite all the work that women, scientists, engineers, policy makers, professionals and AI. Continue to do. There will be this continuous lack of recognition and respect for their work and also their voices within industry and within media. So one week in the one week that Sam Mountain was man of the hour, he drew praise in media. He also came. He also drew a lot of negative scrutiny, but two female board members who are just doing their jobs to challenge the decisions that he was making were effectively ousted from Microsoft. So there’s this contentious debate about women for with respect to women who are. Within the AR world and all of us who are actually looking in. About this continuous lack of respect for the culmination of work that’s been done by women by the non binary community. And this perpetual under representation of these critical voices as, as you know, a lot of this work has progressed so, and it comes at a time when everyone is starting to question whether or not this very technology AGI that’s coming to the floor. It has significant implications on where we are as human beings and and what it can do to us. At the end of the day. So I reached out to a friend of mine and she’s here today. Her name is Theodora Lau. She’s the founder of Unconventional Ventures. It’s a public. She’s also a public speaker and advisor. She just recently co-authored the Metaverse economy, and she also wrote beyond. Good and is also the host of One Vision podcast on Fintech and innovation, and through her work she actually explores the intersection of financial services. Is tech and humanity and she deserves so much praise for for the amount of work that she’s been doing in the industry and I welcome her here today. Hi, Theo.

Theo Lau

Hello, thank you so much for having me here. It’s a pleasure.

Hessie Jones

It’s well, one of the reasons I had you have you on is because of the recent blog post that you wrote on LinkedIn and it was called where are the? And and I want to talk about that today because it it it kind of cuts to the core and I guess anger for all the what’s happening in this world so. So I’m happy to to have you here today. So let let’s dive in. First of all, let let’s not talk about Sam Altman. But let’s talk about the fallout of Sam Altman, because I don’t want to give him any more press. So Tasha McCauley. And Helen Toner were two board members and they, along with Ilyas Killer, who was the chief scientist and Co founder of Open AI, advocated for the removal of Altman afterwards. They had not only asked them, they had installed a little more of a compliant board. With the likelihood, I guess the likelihood of of actually instigating a queue to. A coup that actually happened and that lead to be less likely in the future. So tell me, tell me your thoughts on all of this and what what went through your mind when you saw these events happen?

Theo Lau

Yet again, I think those were the. Literally 2 words that. Came to my mind. I think for a lot of us who have been watching how the tech sector sector has been evolving, not just this year, but even years before this, we’re all very familiar with the tune of ohh. We are not here. We’re not at the table. What makes this hurt more than others is. What it means now, there is no lack of hype that talks about the future belongs to artificial intelligence and how the technology will change everything that we do, how we work, how we earn a. Living, etcetera, etcetera. For something to. Be transformative. That will impact everyone on the planet. You can’t say that this is a shared future, unless. People are represented at the table when decisions are being made. When we are represented. When we think about what the technology will do, who would serve who we might hurt in the process, you need those voices now. When you replace the two women on the board. With others, I believe someone quipped online that that looks more like a devil’s panel than a board. That’s immediately what came to my mind is OK, so this is going to be yet another demonstration of leveraging technology for self-serving and trust. I mean it’s it’s plain simple than that.

Hessie Jones

They had there was this quote from Meredith Whittaker who you know as the the President of signal, the messaging app. And she looked at this open AI debacle and she doubts that even. Even after this, if they do decide to add a single woman or a person of color. That it won’t really affect any meaningful change. And she said, like unless the expanded board is able to actually, genuinely challenge Altman and his allies packing it with people who tick off the these demographic boxes to satisfy a call for diversity. Is nothing more than diversity theater, and she was saying, and this is important for you as well because you live in the. US and she says we’re not going to solve this issue, that AI is in the hands of a concentrated capital at at present by simply hiring more diverse, diverse people to fulfill the incentives of concentrated capital. You’re actually not doing anything more in the US you are considered a capitalist country. You’re not considered. Canada, who is very much a social slash capital capital company country. How do you think can you reconcile the need to to do right by technology that that’s critical to all our futures in a world where where Capitalism reigns supreme?

Theo Lau

It will eventually is not going to be anytime immediate I think. I think it’s time we acknowledge that it as painful as it sounds. Now, when we went through the period of COVID, we thought that was going to be an event that will level set the playing field at least a little bit, right? That everyone is forced behind the screen and. Perhaps perhaps it would have been. A moment of reckoning. That will change how we work, and that was actually when beyond good was written. It was during COVID. Unfortunately, I think we all saw how things have played out in 2023. The entire year funding for women is less than how it was before funding to underrepresented founders is dripping to men and. Against that backdrop, now we have people that are suing companies that said, oh, you should not have such and such DI program because now you’re discriminating against. I guess the rest of the people, never mind that. You know, you’re just writing $10,000 checks here and there is bread crumbs. Literally. So I I think what’s been playing out is people have been and always have been comfortable with with the boys club, with the status quo. Now saying that there’s not enough people who want to change the. Problem is, the mass majority of it do not see the intention to have to change because it has been working. And and and that is one big problem. When we think about AI, because if you look at how a lot of these tools are being developed, who is behind the developing of these tools, who are these tools serving? And what are they based on, right? A lot of these tools are based on the Western culture. Let’s just be honest. The people that these tools will benefit against our people in the Western culture, what about the global S? What about people who do not use English as a predominant language in what they do and how they work? When you start creating this divide and this technology has the ability to even increase the divide. Against that backdrop, you have the same old club. That has benefited from technology and the implosion of capital to few. These technology for years and years and years. I don’t think you need a. Crystal ball to see what’s gonna happen.

Hessie Jones

Well, I think so. When you talk about who does it serve, I mean, like apart from AI like the the system has always benefited those who actually created them. And you know, when it when it comes to, let’s say even trying to get a loan, trying to get a mortgage. Trying to be hired. Those rules are already embedded in the very systems that that have created them. So even if you didn’t have the model, you had decisions that that were part of the processes and baked into the way people sold or sold them or how they actioned it within the company. So, so you know, trying to make change means that you are willing to upend a companies years and years and years of of processes or people willing to do that.

Theo Lau

And data too, right? So think about an easy example, redlining. Which, technically speaking, is not allowed anymore. The problem is the result of that redlining practices. Are manifesting themselves in neighborhoods right that have been disadvantaged people, home owners who had been discriminated against in the past. All of that data set is now being used to fight into AI machines that create lending decisions, right? So yes, even though the from a technical perspective, people are not supposed to discriminate anymore. But when your model is based upon data from the past that is biased, that discriminated against certain population. You know, to go back and find ways to change it to unbias it if you will. And there are companies that do that by the way. One of my favorite is actually headed by two women founders. So unless you actually intentionally go in and. Try to fix it. This will keep going and going and going.

Hessie Jones

Yeah, I agree with that. OK. So let’s let’s turn a little bit to the New York Times, our favorite. Publication, maybe not. They came out with an article like shortly after. It’s probably about a week ago. And so this is their. Year end list and this is the headline. And who the who’s who behind the dawn of modern artificial intelligence. And so their their sub head head fed before chat bots exploded. The popularity of group of AI researchers, tech executives and venture capitalists had worked for more than a decade to fuel AI. And what do we see? All of them for first of all, not one single female on it, and more predominantly a whole slew of white men, predominantly from Silicon Valley. Really carefully curated by the way, and I’m not sure. I’m not sure if the author was actually a white man. Maybe maybe it didn’t matter, but he definitely was a man and it fueled a lot of anger in Twitter from Kara Swisher. I I heard her loud and clear on Twitter. And many women. Who actually saw this less than thought? Why the hell is this happening today? I don’t know why.

Theo Lau

Good question. What? When I saw it, it reminds me a lot of things that we’ve been seeing in Fintech. There is a striking parallel. It’s like deja vu for us all over again and again, again and again, a lot of the who’s who’s list is always. Predominated by by men, I think at least as a whole in the industry lately I’ve been seeing at least one woman on the list. Just like you know, the panels that we always see, we always see a woman moderator.

Hessie Jones

Yeah, exactly.

Theo Lau

Hey, there’s representation. I’ll tell you an interesting story. So recently I’m trying to to do a year end on blog posts. Basically talked about the industry in 2023 so I had tried to experiment with one of the Gen. AI tools because everyone is saying oh, you know, see you have to try. You have to try. OK, fine. So I actually tried it. And this is the prompt that I use Fintech founders talking over predictions for the new year. I use that prompt. Guess what did the picture look like? One guess it’s just men and I’m happy to share it later. I generated 4 pictures using the meta I all four pictures are men with beautiful hair. Rolled up shirts, sleeves, suits. Talking of drinks and a beautiful wooden table like. All right, maybe it’s just meta. Let me try a different tool. I tried Bing AI which is powered by open by ChatGPT in the back end. Same thing beautiful pictures of men with beautiful. Hair young man. Not one single woman. In both of those tools that I use. One would say, well, you know the tools biased, the tools, not biased, the tool does what data is being fed tool, the tool itself, and then you go back and question what about the data and then? You go back and. Think about, well, how often do you see mentions of female founders? Intact AI, Fintech and what have you. How often are they acknowledged? How often are they quoted? It’s been quite a few years now. I started reading through headlines of newspapers. I’m like one of those old school people that still read newspapers. If you pay attention, you will see that often times when they talk about businesses news, you will see the name of male CEO’s on the headlines. And most often you will see a female bank. A female leader and their names are normally not there and so I started this was when Twitter was still working functioning. I started a hashtag that says, you know, what’s her name? She has a name, hashtag. She has a name. And and I. All of these little things right infuse the whole. Space that we are in that. Oftentimes, men are the ones who found companies. Men are the ones who head up companies, and their names are there, they’re quoted. People go ask them for things they are recognized, and I would have people come and tell me. Well, you know, but that person is not known. That’s why we don’t use her name. I’m sorry. Excuse me? She. Is a bank CEO. What makes her less prominent than this other bank CEO that you’re quoting that the man?

Hessie Jones

I know. So I I I’ll give you one experience that I had on mid journey and I my prompt was imagine I guess that that’s the the prompt imagine an hour what what is the average person look like in the city of? So in Canada we have I I tried. Pickering, where I’m from, tried Waterloo, which is, you know, Waterloo has Waterloo University. It’s a it’s a. It’s pretty much a university town. And then I tried Brampton. Brampton has so much diversity in it. That’s where. That’s where Altitude Accelerator is. So it brought up 4 pictures. In Brampton, of one young Brown in. Men and three older brown Indian men Brampton, Brampton, Brampton, which has over from my understanding, over 202 hundred diverse ethnicities, Waterloo, one White. University person and then 3 old white men Pickering. Same thing. Not one woman, not one woman in any of them, but yes, definitely. Ethnic bias in an area that is one of the most diverse in Canada so. So it’s it’s not even the people that are famous. It it it’s. Almost like this redlining effect that you had that you talked about, where if more than X number of people live here, there is a generalization that’s made about that postal code or zip code. And so they tend to use that as a proxy. For credit or income

Theo Lau

It’s as if we don’t exist, right?

Hessie Jones

I don’t understand, but here’s here’s the thing though, like and so we’re talking: women in AI there is based on stats that there is a lack of female representation and artificial intelligence wired in 2018 said that there were 1212% of leading machine learning. Researchers were women. 2020 World Economic Foreman Forum found that 26% of data and AI positions in the workforce were also held by women. I saw a quote from Sasha Lucioni of hugging face and she said AI is a very is very imbalanced in terms of gender. It’s a not. It’s not a very welcoming field for women. So I don’t know what do you think.

Theo Lau

It’s not welcoming because it’s very dominant by certain. Demographics of the population. I think Ellen Turing Institute had similar stats. Unfortunately, that in the UK, for example, only 22% of data and AI professionals in the UK are women. The scary part was in the 22%, the scarier part is only 8% of research. Researches that contribute to machine learning conferences are women. 8%. Again, goes back to. If this is a space that is going to impact all of us, why are we not bringing more people on board? And I reject the fact that there are not enough women in the pipeline. We’ve used that excuse to now we have used that excuse too often. In our education system that there’s just not enough women. I think if we are willing to look beyond the little black book, there are a lot of amazing women. I was just working with one of my favorite conferences earlier this week on their AI track. And I’ve always been a fierce advocate of bringing more women on the panels overlook them. I don’t want just one woman, two women. I want the majority of my panels to be women. I’ve gotten complaints from people before that I’m discriminating against the other agenda. But you know what? They’re thousands of other panels out there that you can choose from. I will gladly take all men. It’s not going. To be anyone of mine that I’ll be working on, there are a lot of women everywhere. If we are willing to look beyond certain artificially created. Criteria, if you will. I’ve had pushback from people that says, well, you know what we won’t take. People, women, speakers, unless they’re a CEO of. A company? Why? I won’t take this unless there are acts, but thereby you’re creating artificial barriers for people that you know, it’s almost like a chicken and egg, isn’t it? Because if. They don’t have the exposure. To be out there, to be quoted, to be speaking in conferences, they won’t get the opportunity to keep going up that. Doesn’t mean they’re that lesser. Then you know their peers It just means that they’re not given the right opportunities. So why aren’t we doing better? And it goes back to the word that you just used diversity theater, right? We are doing nothing more than a diversity theater. So if we are intentional, we can change it. Carnegie Mellon, for example, is a brilliant university that has created a lot of amazing minds cultivated a lot of amazing people in AI. They had intentionally done a lot of work to bring more women in the space in engineering just so. That it helps. Level the playing field. Now. I wish my alma mater would have done that because when I was there was like 3 one of three women in my class. And I don’t think. That that ratio has changed much. I think there’s still 70% men. But it goes to show. If you want to, you can bring more women in engineering and. Cloud and AI.

Hessie Jones

Absolutely. But I mean to your point about, there’s not enough women coming in, but that that also speaks to the criteria of all the different schools that are using some level of, I don’t know, their model to to pick some of the the top people to actually. Entered the university and how many of the how much of that criterion is biased against women, or bias? Exactly. And I think the other part of it is also women in STEM. Why has there been so much. Efforts to to bring you know. Science and math to much younger, you know kids so that they could they themselves could look at a future and data science or or or math etcetera because because there has been a stigma against women and their ability to even comprehend these. Complicated subjects. And so when you think about the pipeline, the pipeline has been disadvantaged from the time that that we were young. And it’s the it’s the education system. It’s it’s even the bias of our parents potentially that have been pushing us to look like a girl to wear pink, to wear blue, to go and do a thing that’s good for you as a girl versus you as a boy. It’s been part. Of our lives.

Theo Lau

It’s all future, isn’t it? Right. And and I can resonate with that so much. I love Legos. Case you can’t tell is is very much a part of our family’s life. And I recall. I have a I have a son and a daughter, and, and we’re fortunate to live close enough to a lot of the museums that you know, that’s one of the. House times that we do. And when my daughter was little. She was a toddler. Think she was like about two years old? I took her and my son at that time he was 5/2 an Air and Space museum is one of my favorite. I love that we walked in there and you know they always have the gift shop at the end of you know. Before you leave the museum. Hey, bring a piece of memory with you. Guess what was on eye level? Of my daughter shows that she can reach things that she can see. Hello Kitty pink Hello Kitty and a little space helmet. That’s it. All the other books. Everything else. Well for boys.

Right. And so it speaks to exactly what you were talking about has it’s part of our culture too and how we’re bringing up children. We condition them to a certain route as well, and I remember my friends. They would bring me like pink Legos for my daughter. I’m like what? What is this pink Lego thing? First of all, I don’t like pink, but more so I did not grow up with pink Legos. I grew up with space Legos. The the space Lego set, the Moon Base station. All of those, that was my favorite toy. That was for both boys and girls and whatever. Gender that you know you want. Is not gender specific, so why are we doing this now? It shouldn’t have to it it. It shouldn’t have to be like, you know, girls play with dolls and Lego that look like dolls and then boys play with everything else. No, because then you are conditioning them as you say, to a certain point.

Hessie Jones

Exactly. I want to throw out a stat there be start stack here, because when you’re talking about earlier about you know, who gets to speak? Who gets invited to panels there? There was an actual online news database study that actually brought out some interesting stats and that said that this year’s men have been quoted 3.7 times. More frequently than women in the news about AI and English speaking nations. When we talk about news that focus on stories on science, technology, funding, discoveries and developments that are centered around women, 4%, only 4% of those news stories and in Britain and the US. 18 and 23% respectively, of the news editors are men. And men are between 3:00 to five times more likely than women to decide what constitutes a technology story. So there’s this full going foregone conclusion that unless you are the subject, if you, unless you’re a man that. A subject of what we call pervasive interest. More than likely you may not be part. Of the story. I don’t know.

Theo Lau

And I I have a lot of comments, but none of them say for work refrain I it’s …. It’s the same old as the net. In a sad way. If you look at the stats. Every year that look at, you know, gender gap, that looks, you know, World Economic Forum. Every year they publish it, a gender gap report. That number has barely moved, be it, you know, economic disparity, be it, you know, political disparity or just plain. Opportunity gaps. It’s always been hovering about 130 something years. That hasn’t changed. I I think. There is an illusion of change, but until you can have equal representation at the top. We won’t be able to change, at least not in a meaningful manner.

Hessie Jones

 The thing is, there’s so many systems that need to change that they need the practices need to change and like the one, one of the things that I was speaking to you about before we entered this call was was about Wikipedia. And the reason I’m bringing this up is because, you know, in the age of large language models and where AGI is going. The at some point you know be pervasive and all our all our lives. Wikipedia is one of the the most great sites to be used in large language models and right now let me see where did I find this stat. OK, 4.5 billion. Unique global visitors just in the month of April this year, right? One thing that a lot of people may know or may not know, let’s let’s just see is that 90% of the editors in Wikipedia are white male, and they live in North America, which means that most of the information on Wikipedia has one very particular. Narrow worldview. And the all the 10% remaining editors, 9% of women and 1% consider themselves non binary. So you know from that. Perspective that there’s. A. A colleague of mine, Volha living, it’s decided to edit Wikipedia to add more. Female names and underrepresented names into the list, and we started with the women in AI ethics. And let me tell. You it was a bit of a. Blog because not only were we outdone by the number of men here, but all these rules that have been created, we were we didn’t conform to like the definition of notable was very interesting. You had to be caught, your name had to show up in certain magazines. You had to be a Google Scholar in order to be considered notable, and if they didn’t know who the person was, but they were. This person was notable in other city. Polls. They basically rejected them, so there was a whole slew of stuff that was happening. And the reason I bring up Wikipedia is that because it becomes an influential database when it comes to AGI, and I think for for the amount of bias that’s already in there in editing. And creating content in the space if it continues to to be that influential, influential in in the creation of large language models, and we’re all screw.

Theo Lau

We are and and. First of all. Kudos to what you’re doing and you need to give yourself a lot of credit, firstly for for pushing the space and almost like rolling. Up a large. Stone uphill that goes back down every once in a while and squish all of. Us and and it takes a village. It makes me really sad because there are a lot of amazing minds everywhere doing a lot of amazing work. The system is stacked up against many of them, not to mention that typically women do bear most of the caregiving task, and that’s the one thing that I’ve always said is inequality is a policy choice if policy. Is created in such a way with the needs of underrepresented demographics in mind. We would have had a much better caregiving infrastructure. Women would have less time that they’ll have to spend doing a lot of things, literally like mental gymnastics, just to try to figure out how to get the day through. Caregiving is so expensive it’s hard to find a lot of employees. They’re not really, you know, flexible, etcetera, etcetera. I remember a couple of years ago, I think Melinda Gates in one of. Her books, she said. Women, on average, spend an extra six years in their lifetime just doing caregiving stuff at home six years. Imagine what we could have accomplished if we were all given extra 6. Years you can have a second degree, perhaps 2 Masters degree a year. Go on vacation, do more work, etcetera, etcetera. So so it’s it’s every single corner and direction that you look, there is something that is pushing back. And it’s it’s no wonder we are where we are.

Hessie Jones

I know. I was listening to this podcast about COVID and about the the amount of time that women were actually spending because there was no. Caregiving during that time, everybody had to stay home. They were they were actually doing twice the work. Yes. Look at that. And so the other stats is that if you’re looking at the the number of researchers men have published twice as much as women during COVID because they were at home. They had more to do. Women, on the other hand, who had to resort to actually also playing mom during the day. While they’re working.

Theo Lau

And teacher.

Ohh there go teacher did not publish A published public. Half of what they normally did during a normal school year, so it does. It does talk about how policy, how things are not changing in favor of making it easier for women to actually become productive and contribute to the workforce. 

Theo Lau

I mean, the US is the only developed country without a paid family leave. So there there goes that right. If you as a woman. And I was lucky I had three months off, but most people don’t, you know. So you have to take off without pay. Well, who can afford that? Especially with this economic climate, right. And so then you have to figure out. OK then. What do I? Do with my career choices. And yesterday my son. Actually he asked me an interesting question. He’s working on a project in school in his middle school and he said his teacher wanted him to come ask me what the biggest sacrifice I’ve made for them and you know the last however many years. And I told him, is that you? Know I think the one single biggest sacrifice and I’ll I’ll say it’s not just, it’s a change was that I quit my job. I quit my job when my son was born because he had a lot of health issues and I decided that I was just going to quit and stayed home. I stayed home for a year and a half. And he asked me, why did she do that? I’m like, well, because you are the most important thing, right as a family. And this is what we do as a family. It hurts. It hurts me professionally. It hurts me and pay. But it was worth it. Right. So when you look at a woman’s life and what they do, the breaks that they take when they have children. And then later on in life, when they have to take time off to take care of their parents, the aging loved ones, grandparents and what have you, because majority of family caregivers are women. So they’re again another break. And then throughout their lives, most likely a lot of them will resort to work that gives them more flexibility because, again, mental gymnastics of things you need to do. And we wonder. What can we do to change it? And there is policy policy change.

Hessie Jones

So outside of policy and I mean, is there something that you and I? I could do to make some substantive change

Theo Lau

We both write, we both speak right? We both have an opinion.

Hessie Jones

We both have, but there’s also only two of us, right? So, like, what are your thoughts in terms of how maybe women collectively can do things to, to actually change the status quo.

Theo Lau

And men to, right, it cannot be just upon half of the world’s population to change the status quo. It needs to be everyone because it impacts everyone so. I’ll give you an example. In the last five years, the podcast has been running. For this year. I made a huge change. I brought in two. Co-host one is Barb. She’s from Canada and the other one is Stephanie. And she’s based in Atlanta. And between the three of us, if you look at the cover picture of our podcast, you have white Canadian. You have me and then you have Stephanie, who’s black and she’s. From the islands. And that change was made intentionally because we all have our own bias. We all have our own little black book. And I recognize that. And I want to change that and to change that we need to bring in different voices who have different communities who have access to different resources, who have different opinions. Who have friends? Who might be from different places, who have different backgrounds? Again diversity, but intentional diversity, and that’s how we’re able to bring in a lot of different guests. Across health, tech, even people that I wouldn’t have known had it not been because of Barb and Stephanie. And so that’s one small change that I believe that people who have a platform can do. If you’re running a podcast, I don’t care if you’re a. Men, women or. Binary. However, whatever it is that you. Think you belong? You can contribute. That’s the one small thing that you can do. If you’re event organizer, bringing more people from different places, from different sectors, even. Right. Just because you’re running an AI conference doesn’t mean that you know you can only bring in people that are just, I don’t know, have a master PhD degree in AI you can bring in different fields because that’s the beauty of technology. It’s not just about the people who know how to code, but people who use the technology, people that will be impacted by it. There’s so many different. Verticals that you can think of that I think. That’s the beautiful thing that we can do together as a community.

Hessie Jones

Yeah, I think the other thing that I would add is that we have to uplift the lesser known voices. There’s still a lot of women who who are, let’s say the go to influencers. It’s just like celebrities, right, we have to start intentionally building the. Plans of people who are doing amazing things but may not necessarily have the confidence or the foresight to be able to deliver their voice in in a meaningful way in. Like and if we can encourage that, I think we’d have so many voices to choose from like it’s it’s going to be a lot more, I guess, challenging for media to say, well, there there’s not enough, there’s not enough people who of this, you know, subject matter expert. Expertise to be able to choose from and, but we have to create that we have to create that and we have to be intentional about giving back to others who have helped us elevate our own voices. So and as you told me earlier, Twitter is not going to be the space to help us do that. And so we have to move on to the next available. Social network could it be blue sky?

Theo Lau

I don’t know, I’ve I’ve tried. Almost all of them, but I will. I will say this one thing and I reflected on it recently too. I did a book signing in, in, in the fintech event in Vegas. A lot of people came who showed up and. I was very, very grateful. For I was talking to a friend of mine and she. Was asking me like, who are these people? One of them was someone who gave me a first shot and published my article without knowing me. Nobody knew me at that time. This was like 6-7 years ago when I just randomly started writing. Cause God forbid I have an opinion and I’m a woman, so I wrote. I started writing articles in LinkedIn and he spotted one of them. He’s like I would love to publish it in the Fintech newsletter and he did. And then there’s another woman. Penny love her to pieces. She’s the editor of American banker, and again, she reached out to me years ago. And said I would. Love to bring you on the podcast. She didn’t know me. And then there’s, you know, Victor is a conference organizer and and at that time, he gave me the first opportunity to speak on stage, even though at that time my boss told me that I would never put you on. Stage because you don’t know how to speak. That’s a whole different story, right? So when you think about the trajectory that we ended up on, the path that we are in right now. Is built upon the shoulders of all of these people who gave us a first shot. The person who put you on stage the first time, the person who published your article the first time, the publisher who didn’t know me, who reached out, and. Say I want. To publish a. Book with you. Like why? I don’t really. What? Me. No. Right. So so is that so is. Exactly. To your point, giving back, we are all in a position that we can give back, give someone else the first chance. Bring them on.

Hessie Jones

Thank you. I love that. And you know that is the that is the last word that I think is going to be meaningful for this podcast. And I thank you so much for talking with me through this really, I guess important and difficult topic because as you know we look for change… hopefully when I retire, things will change, but my that’s like less than 10 years and I don’t know whether humanity is going to have the gumption to actually make substantive change within a decade, So, we’ll see, right? Anyway, Theo, thank you for coming.

Theo Lau

Thank you, Hessie.

Hessie Jones

That’s it for me today and I think that’s all we have time for. If you have our audience, if you have any important topics that you’d like us to cover, please don’t hesitate to contact us at [email protected]. This is going to be our last podcast for the holidays, so I wish everyone as safe and happy New Year and you too, Theo please have an amazing holiday. And we’ll see everyone else in the new year!  Take care. Have fun and be safe.