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Next, we have another amazing speaker and storyteller and another nonprofit woman leader women in voice, sharing her journey her story on what she has done, how she did it, and why she started Women in Voice. Let me introduce Dr. Joan Palmiter Bajorek is the CEO and founder of Women invoice, the international nonprofit empowering women and gender invoice tech. In three years, women and voice have scaled to 21 chapters in 15 countries with over 100 International ambassadors. And as an official 501 C3 nonprofit partnering with Google and Amazon at events around the world, women, and voice is helping to shape the wise tech field to be more welcoming, inclusive, and intentional as it grows and flourishes. Please welcome Dr. JOANNE Hello. How are you? Well, how are you? I’m doing well. Sorry to keep you waiting. I know you’ve been waiting for a long time. But yeah, that’s how live events are. You’re doing okay on time. Not too behind. So I’ll let you take the stage. Thank you

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For when it’s so grateful to. It’s wonderful to be here Linda and I, I’m going to try to share my screen, and looks like we’ve been having some, or let’s see how this works. There are two monitors. Okay, just a moment here. Give me just a second. Okay. And then if I Ctrl L, I believe, can I get confirmation that you can see my screen?

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Yes, Linda, we can see your screen and your slides. Okay.

1:53  

Awesome. Thank you. Well, it’s wonderful to speak with everybody today. I’m very excited after these other talks, to really delve deeper into the voice field, and conversational AI. And This talk is a dovetailed kind of conversational AI and jobs. So conversational AI jobs today. And in the future, you just heard my intro. So that’s a great place to start. I’ll also just say that I’m a C. Hi, my name is Joan. I’m based here in Seattle. I really have a two-pronged career that’s going on that you’ll certainly hear about today. And this work is presented. I have a Ph.D., I do research in the voice and conversational AI space. I have multiple publications that I’ll be thinking about briefly. But also really, the more I delved into conversational AI, natural language processing, kind of the future of what these tools look like. Also, really importantly, the social impact of this work and the importance of having lots of different people at the table. And so three years ago, I started Women in Voice which is now a global nonprofit and a 501 C three, and been featured at CES and, and worked previously at nuance and Alexa champion amongst many other accolades that are great. But today, I really want to talk to you about three topics, voice and conversational AI, jobs in the sector of which it is proliferating really fast, if you are thinking about pivoting, really consider my field, please. And also a lot about women in voice and the community that we are growing here. So um, you know, some people don’t even know my field exists, but Mark Cuban does. There’s no future that doesn’t have ambient computing or voice activation. None. So when we think about the future, we’re still building what that looks like and how we move forward. But even big, big investors see our space as really a fruitful place to be. So when I talk about voice, what does that actually mean? Is this a field? Hopefully, you have heard or seen, or even use it daily, Siri, okay, Google, Alexa devices are proliferating in the space. And we certainly see this as a hardware play, but also as the software evolves. And hopefully, if you have an iPhone, for example, it seems Syria evolved dramatically in each deployment iteration. So this is what I’m talking about for an end customer experience. But when we really think about conversational AI, we’re often thinking about a voice experience where the input is spoken language, we have some hardware and computing on the back end, that’s cloud, usually, and then the output being spoken language. But this is a really simplified example of what we’re seeing in the ecosystem that both Linda and the speaker before we’re talking about these integrated systems, where we’re seeing inputs that can be speech, they can be biometrics, that can be plenty of different things. The hardware can be you know, VR, there are so many different ways for hardware as well. Like, gestures, etc. Our computing power is getting more and more sophisticated. And what we’re doing on the back end with machine learning, as we saw that cool video and the tech stacks are getting really sophisticated, our outputs could be your cons, they can be switching on and off the lights, we’re really seeing voice and conversationally I expand into many, many domains. So across the stack, a lot of sophisticated things are going on. And when I think also about the kind of trajectory of my fear and kind of think about multimodal, if you give me this little rabbit hole more, my field frequently talks about the term multimodal and leveraging different modalities like I was talking about. So leveraging text, how’s that integrates with touch, audio, computer vision, AR VR gesture voice? In medical contexts, how gesture might be the right approach to not touching things, especially during COVID. We were more sensitive to what we touch, augmented reality, and E-commerce spaces, you know, does this sofa fit well in this context, and really be able to ask and talk to different devices, like Google Assistant in being placed into different IoT. So we call we often call this multimodal the jargon doesn’t quite matter, the concept does. And so I have even more examples of people all around the world using this technology. In different languages, especially potentially, you saw the Ray-Ban and Facebook announcement recently, it’s kinda AR classes that are being built out in that space, as well. But really, I think when we talk about kind of ethics and how it’s being used, there are some really cool applications. My friend in Nigeria is working on kind of how we look at biometrics, and computer imaging, that matches with kind of semantics or kind of pairing like this motion would be explaining, right in the future, we’re tying those things are currently, there’s a really cool company called Affectiva, that was recently acquired by an automotive company looking at lots of different biometrics. And looking at kind of this is one example of a patent they have drivers and using facial and vocal expressions to identify if the driver might be drowsy or intoxicated. And unfortunately, in the United States, 25% of all US traffic-related deaths are related to alcohol impairment. So it’s really the translation of here’s this dataset. Here’s how we’re interpreting this dataset. And what are the kind of ethical or direct

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Legislation potentially even that can be put in place related to these datasets. So it’s really interesting the implications and the importance, but also how we leverage this data as it evolves, and how we can process it. So I have even more slides specifically about natural language processing, which I think a lot of people throw around the term NLP, but you use it, almost everyone is using this more and more. Here’s an example of bill pay. Many of us are our texts are blowing up with bots, and automated material. But on a fundamental level, natural language processing is organizing human language in a sophisticated data-driven computational way. I think we would love to run jargon, but the concept is very concrete. So what that looks like as far as conversational AI, if you use Google Assistant, one of many different systems that were tagging entities, and that your bot, you know, book a flight from Los Angeles to Hawaii, for less than $300. And the system response, you got it, what we’re doing on the back end, to geotag, to look at currencies. This is just a textual-based example. But all the different slots that are going on in these systems behind the scenes. So from that, from the big abstract picture to the more concrete example here, of what conversational AI is doing. So the more I looked into this, the more excited and concerned I was, this is my publication called Voice Recognition still has significant race and gender biases. When we look at the datasets being used, when we look at how this data is being leveraged, and the kind of implications to immigration hiring practices, which were mentioned earlier today. You know, there’s some there are some really problematic and troubling things. Specifically, my research looks at kind of the implications of breakdowns when we see discrepancies, the dramatic changes this makes to people’s experiences. So, you know, a lot of people don’t necessarily want to look at big datasets or, or research this way, but really breaking it down to you know, if Josh White male gets like an A-minus the discrepancies in me reading essentially the same paragraph in a voice AI system as a white female, that I might it might interpret as a c plus of how well it interprets my voice, and for a mixed-race female even worse than that. At a deep plus. So these seemingly small biases and breakdowns and with massive, massive repercussions. And so as I mentioned that these questions, I’ll go back really quickly these questions of race and gender biases and try to understand do I really think that people are, I fundamentally don’t believe that people are trying to make biassed systems. In fact, people have a lot, a lot of incentives to make these systems as good as possible, financially and otherwise. So I really saw an opportunity for us to amplify the work of women. And I think a lot about women who are already killing it in our fields, but also kind of our pipelines, as well as retention of talent. It’s really mostly a retention problem, but most people don’t even know about our field. So we’ll start there. I came up with the idea of women a voice, I’ve launched a call for leadership, a bunch of people signed up, there was a lot of interest right away. And we have scaled really fast since we’re in almost every continent now. Launching in Africa soon, I hope, that really partnering with different organs that share our mission, and see what women a voice can become and how we are working to shape our ecosystem. So our mission as a 501 C three is to amplify Empower, connect, celebrate women and diverse people in the voice tech field via community networking, education events, etc. What I usually say is, you know, our tagline, where the woman who codes for voice tech, if you think about us that way. So we specialize in our vertical in our domain.

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Yes, so as mentioned, we’re all around the world. We’re international by design. In three years, we’ve hosted at least 150 events, come check them out. They’re all online these days, and most of them are free and open to the public. I think there’s just one thing to talk about the numbers. And then it’s another thing to see the faces of ambassadors and events going on all around the world, most of these prepaid Dimmick. But just to really the community, not feeling alone feelings of belonging, and how we support each other is extremely important to retention and opportunities in our field. So, as mentioned, this field is evolving fast, there are so many different pieces and components to it, that it’s hard to imagine one wouldn’t be inspired or interested in participating in some ways. If you’re interested in jobs in this field, my colleague Yara Martino has written up kind of job titles of what’s going on in our field. And kind of the proliferation of what this looks like. So check out jobs titles in conversational AI Addison medium posts, you can also listen to them. But just I’m going to read out the number of jobs in this space on the design and writing side on the AI NLP, machine learning data science side speech scientists, voice actors, researchers, people are hiring like crazy for these jobs. And we’re seeing so many companies hire for Director roles, which typically are hiring for a headcount of four to 10 so there are so many jobs, and we just launched the jobs were in fact, and WWW dot women invoice jobs.org comm check it out so many cool jobs all around the world. And I would be remiss not to mention that women voice we are building out tonnes of programming and events for people to participate in and ways for people to join different initiatives we have so right now I’m running a career accelerator for people to really advance their career and work on that in a dedicated way. We have a membership that has tonnes of really cool perks, freemium to 100 bucks model, comm becomes a member pitch events really supporting female founders and connecting them with investors in our space, as mentioned with Mark Cuban and so forth. That’s sponsored by Amazon Alexa startups. We have two more coming up this year. So you can find all this and more and women invoice.org. And we have a gala. In December, I’m really, really excited about all virtual fear not but really a celebration of the work we’ve done, especially this year, as well as a fundraiser code. So come check that out women voice.org/gala. And our influence, reach and engagement cannot be underestimated. Just people all around the world are finding us across social media platforms come to check us out and whichever ones you participate in, but we are reaching people in Croatia, Nigeria, like the spread of what we’re seeing of people being really interested in our space and coming to join us is extremely exciting. So we’re still early days as far as I’m concerned. Women in voice let’s shape the future of voice together. Thank you so much for listening to this talk and I look forward to connecting with you again. Please learn more at women invoice.org. And if you’re sitting sponsorships admin wouldn’t invoice at work as well. Is there So thank you so much for having me.

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Thank you, Joel. This was awesome. Yes, definitely we need representation in voice tech. So this is awesome that you started this movement. And from the numbers, it seems like you’ve done a fabulous job so far, and it’s only going to continue and grow. And I see that even though it says women and boys, but also it’s open probably to everyone, right?

15:29  

Absolutely. I mean, we are so interesting. As we look at our numbers, we designed for kind of women, and gender minorities in our space, or materials consumed by like a 6040 split. People were tagged as women and men like we especially we want to have allies in the room. Our content, people are paying me like, Can I join where can I sign up? How do I participate? So certainly, we’d love allies, and we’d love that narrative of everyone together, building and learning and growing. So we certainly foster that.

15:58  

Yeah, yeah, absolutely. All right. Thank you, John. Thank you