Who's In This Podcast
Helen Todd is co-founder and CEO of Sociality Squared and the human behind Creativity Squared.
Katie Trauth Taylor is a growth-focused entrepreneur executive boasting over 10 years of experience inspiring teams to design and deliver magnetic products, memorable experiences, and groundbreaking impacts
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Ep36. Narrative Science & Innovation: Discover the Power of Story in the Era of GenAI with Katie Trauth Taylor, CEO of Narratize, an OpenAI Developer Ambassador
There’s no doubt about it: Generative A.I. (GenAI) had a breakout year in 2023 — and enterprises that have successfully harnessed its potential now stand to gain immense market advantage.
Yet, for all its promise, GenAI adoption lags among the product teams that arguably need it most: those building the complex technologies upon which society increasingly relies.
In this episode of Creativity Squared, Katie Trauth Taylor contends that narrative science offers the missing ingredient for GenAI to fulfill its destiny as an engine fueling scientific innovation.
As CEO of Narratize, Katie leads an all-woman team of narrative scientists leveraging their expertise into an A.I. platform designed specifically for technical teams struggling to communicate ideas effectively. While other vendors focus solely on productive volume, Narratize builds on OpenAI’s and other large language models to provide the accuracy and strategic storytelling capability that technology innovators need to drive internal buy-in and external marketplace success.
Throughout her spirited discussion with host Helen Todd, Katie discusses Narratize’s unique position in tackling GenAI and diversity, equity, inclusion, and access (DEIA) imperatives, the need to fund female founders, the role of IP and consent regarding date, the potential of Generative A.I. as a democratizer for creativity and storytelling, and more.
To be inspired and fascinated by narrative science and algorithms in the era of GenAI, continue reading below!
Narrative Science Sets the Stage for Innovation
“93% of companies are buying Generative A.I. solutions, but only 13% of product and research and development teams are regularly using it.”
Katie Trauth Taylor
With her PhD in narrative science, Katie is a serial entrepreneur who leads the design and implementation of evidence-based methods that enable people to harness the power of stories for accelerated innovation.
From her history implementing groundbreaking systems to support VA hospitals to her present leadership of an OpenAI Developer Ambassador startup, Katie lives at the intersection of exponential technology and effective communication.
In this conversation, she argues that when innovators fail to contextualize the importance of their work through a compelling narrative, the consequences can be severe, even lethal, with cases of scientists contracting ulcers to verify their disputed research.
That’s where Narratize comes in.
Narratize is one of OpenAI’s 8 original developer ambassadors and recently secured a $2M seed funding round, earning recognition as one of Cincy Inno’s 24 startups to watch in 2024.
As a Generative A.I. platform designed for scientific, medical, and technical clients — from NASA and Boeing aerospace engineers to the World Food Forum and United Nations teams — Narrative aims to help users leverage GenAI to more effectively communicate their complex innovations, so their ideas don’t get shelved.
Narratize embeds the ingredients for resonant, evidence-based storytelling directly into the technical communication workflow. If adopted at scale by those designing cutting-edge innovations, she see how GenAI rapidly accelerates solutions to pressing issues like food insecurity. More broadly, it also can sow understanding about complex technologies to heal societal divides and restore trust in expertise.
Narratize’s Co-Founders: Kara Uchtman (Chief Product Officer), Katie Trauth Taylor (CEO), and Catherine O’Shea (COO)
The Power of Narrative Algorithms
Early in her PhD studies, Katie recognized how rarely technical experts receive training to convey their ideas in a compelling way beyond niche groups of specialists. She suggests that missed connections due to poor communication cut off oxygen to promising innovations before they ever escape labs or pass through the perilous gauntlet of internal approvals.
Katie argues that accelerating innovation requires applying principles of both art and science in strategic storytelling. At Narratize, she leads a team of narrative scientists discovering patterns of effective messaging and packaging them into easily referenced narrative toolkits. By mapping elements into “constellations” of ideas — like grouping stars against night skies into familiar shapes — Katie says the abstractions help technologists intuitively arrange complex details into resonant narratives.
“We recognized and started identifying narrative algorithms within innovation management, within research and development, and all the way through to marketing and communications.”
Katie Trauth Taylor
Presenting persuasive evidence lies at the core. One such narrative constellation that frequently appears, Katie explains, is the ABT pattern, referencing how most technical pitches describe a status quo, introduce current shortcomings, and conclude by presenting an improved solution or technology. Katie suggests that formulaic conventions dominate for good reason — they work if executed artfully. Yet cookie-cutter communication fails to inspire action or market success.
Artful execution remains key — as well as being the area where human creativity shines. Like stars comprising unique constellations, the limitless combinations of innovation variables allow for boundless ingenuity in linking ideas into compelling mosaic patterns. This fusion of defined narrative architecture with wide creative latitude for executing messaging distinguishes great technical storytelling, Katie says.
She believes that when executed well, strategically framed communication makes audiences feel connected to innovations that improve lives. By contrast, dense data sans narrative context breeds indifference and the message can just not land with the audience. Misunderstandings shrink potential funding, delay solutions addressing global priorities like food insecurity, and erode public regard for indispensable expertise, pushing progress ever upward.
“Generative A.I. is the great equalizer. It is enabling creatives and those with more humanities-related backgrounds to be able to really grow.”
Katie Trauth Taylor
Empowering Technical Storytelling at Scale
Katie’s expert team at Narratize works to identify recurrent patterns and codify narrative toolkits to inject strategic frameworks into automatically generated communications.
These GenAI-powered templates allow non-writers to efficiently outline pitches, reports, articles, and other materials through prompted dialogue. Narratize technology then fuses user ideas with embedded narrative algorithms to produce compelling technical narratives exhibiting the context, surprise, and evidence Katie suggests stories require to captivate audiences while maintaining accuracy.
Early pilot programs found aerospace engineers at Boeing and NASA raving that automatically generated communications finally conveyed the importance of their technical work in terms that resonated with key leaders and stakeholders. By melding the creative spark of human ideas with the untiring capacity of machines, Narratize allows technical teams to harness strategic storytelling sans intensive training or outside consultants.
Katie suggests that in regulated industries especially, the sheer challenge of documenting innovations distracts from effectively framing broader meaning.
She proposes GenAI as a multiplier, allowing experts to strategically broadcast ideas through clear cross-discipline narratives that speak to hearts as well as minds.
The result accelerates research and development cycles to rapidly securitize funding, accelerate production, and spur marketplace success.
“We can bring…narrative science, data science, and this deep foundational understanding of narrative algorithm…to those enterprises to partner with them in the best use of their data.”
Katie Trauth Taylor
Thought leaders increasingly argue that Generative A.I. constitutes the ultimate democratizer of opportunity by exponentially expanding individuals’ creative capacity. If innovating equals creating, then by infusing strategic narrative into technical communications, Narratize expands who gets to innovate within enterprises.
Katie believes that by setting best practices alight, Narratize gives creativity wings for companies struggling to spark innovation and retain competitiveness.
Tackling Generative A.I.’s Biggest Challenges
Despite the proliferation of conversational models like ChatGPT, product teams working in regulated industries remain rightfully wary of blindly trusting information that could be inaccurately hallucinated.
While such hallucinations can sometimes seem obvious to general users, they can pose an outright danger in sectors where lives are on the line.
“In a high-reliability industry like aviation, or agriculture, or healthcare, medicine, and pharmaceuticals…there’s such a little margin for error.”
Katie Trauth Taylor
Katie maintains that Narratize overcomes such pitfalls through an architecture that extracts the most accurate outputs across multiple models. This provides guardrails mitigating hallucinated content through corroborated consensus balanced against known model strengths and weaknesses.
Katie suggests that by maximizing accuracy rooted in evidence, Narratize generates communications that audiences better comprehend and trust. She observes that when scientists fail to effectively contextualize ideas, public regard erodes alongside funding and political will needed to tackle threats that require broad consensus and short-term costs for long-term gain, like climate change.
Generative A.I. also continues working through embedded biases that manifest in ways that alienate marginalized groups.
Katie notes that diversity intrinsically seeds more innovation and that narratives celebrating multiplicity outperform homogeneous content. So Narratize built dedicated DEIA content knowledge to guarantee inclusive viewpoint diversity.
Katie also secured guidance from renowned DEIA thought leader Abro Maldonado, creator of the Afro-Latina A.I. system Clara, to ensure communications highlight diverse voices.
The Critical Role of Women in A.I.
Katie and Helen’s conversation then shifts to focus on trends in A.I. development and adoption, as Katie argues that despite the proven benefits of diversity for innovation, venture capital (VC) funding concentrates overwhelmingly on male founders. This creates homogenous teams, leading to A.I. solutions that fail to serve broad needs.
Recent studies found that while female founders net higher returns, only around 2% of venture capital fuels women-led startups. When it comes to A.I. companies specifically, the number plummets to 0.3%!
In our interview with Cindy Gallop, Cindy explains the need to fund female founders, and that this imbalance is why companies led predominantly by men focus more on addictive technology optimizing profits over solutions targeting inclusivity.
Katie and Helen concur that emphasizing ethical precautions and inclusive development could unleash A.I.’s promise to empower society.
Katie notes that amid excessive hype cycles, women often champion everyday applications to improve the lives of historically underrepresented groups. She highlights OpenAI Developer Ambassador Emad Mostaque’s Fidenz, which helps users manage passwords, representing the sort of “Opportunity A.I.” that focuses on improving lives, not grabbing headlines.
She goes on to assert that women like her guide GenAI’s evolution to uplift society by bypassing barriers and concentrating on both expertise and influence.
Funding female founders constitutes the fastest path toward A.I. equitably serving all groups. Katie’s all-woman founding team manifests the ethos they want to drive humanity’s shared A.I. future.
“I have two female co-founders, and the journey that it took for us to be able to raise capital was not great. And I watched other, male-founded companies that had…far less actual expertise…get funding before us…It’s just not okay.”
Katie Trauth Taylor
Owning Your Story with A.I.
Helen suggests that while some artists justifiably fear A.I. threatening creative careers, others race to grab its full potential.
She asks Katie’s perspective on IP rights, given GenAI’s unprecedented data harvesting from uncredited creators. Katie responds that while attempting technological restraints often proves fruitless, creatives retain power as A.I. democratizes influence allowing more voices impactful reach. But absent proper attribution, creative careers stall.
Helen brings up the recent Content Authenticity Initiative conference, noting impending societal tumult as 40 countries hold pivotal 2024 elections amidst public manipulation threats at an unprecedented scale.
She urges that understanding A.I. and controlling personal data grows increasingly mandatory for creatives. Katie responds by emphasizing A.I. accuracy and truth as guiding stars, suggesting narrative science fosters comprehension and trust to heal societal rifts.
As Helen and Katie’s lively dialogue continues, Katie offers her belief that funded female founders will bend the trajectory of A.I. toward inclusive innovation.
She proposes that strategic storytelling is imperative. By embedding narrative architecture into the technical workflow, Katie leads Narratize in working to accelerate expert insights in solving humanity’s pressing problems.
“The right leadership will look for opportunities to use new technologies to innovate better and faster, in a way that operates with good intent for good.”
Katie Trauth Taylor
Katie hopes listeners walk away from this episode recognizing that new technologies like A.I. present opportunities to accelerate innovation when guided by thoughtful leadership. She hopes audiences are excited by A.I.’s potential to elevate human capabilities and solve pressing societal problems when applied conscientiously.
Katie relays the story of an innovation leader who transformed a company into a top patent producer by implementing systems recognizing employees’ ideas, enabling them to see themselves as innovators through sharing stories.
She goes on to suggest that communicating unlocks individuals’ potential. By putting scalable technology supporting strategic storytelling into more hands, she argues A.I. can spread innovation capabilities across organizations to fuel impactful progress in addressing humanity’s needs.
Together, Katie concludes, we construct the narratives that co-author our A.I. future — one she hopes manifests A.I.’s immense potential for human empowerment when guided by ethical intentions.
Links Mentioned in this Podcast
- How Bold Get Told — Narratize
- Untold Announces Launch Of Narratize
- Diversity, Equity and Inclusion
- Narratize Closes $2M Seed Round to Accelerate Innovation Through the Power of Story
- 24 CINCINNATI STARTUPS TO WATCH IN 2024
- Women-founded startups raised 1.9% of all VC funds in 2022 — TechCrunch
- Katie Trauth Taylor’s LinkedIn Post
Continue the Conversation
Thank you, Katie, for being our guests on Creativity Squared.
This show is produced and made possible by the team at PLAY Audio Agency: https://playaudioagency.com.
Creativity Squared is brought to you by Sociality Squared, a social media agency who understands the magic of bringing people together around what they value and love: http://socialitysquared.com.
Because it’s important to support artists, 10% of all revenue Creativity Squared generates will go to ArtsWave, a nationally recognized non-profit that supports over 150 arts organizations, projects, and independent artists.
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TRANSCRIPT
Katie: And those careers and prompting, I think are going to be so rich and really change the creative industry for good and forever. However, AI is not.
Helen: Katie Trauth Taylor is co-founder and CEO of Narratize, an all female founded startup based in Cincinnati, Ohio. With her PhD in narrative science, Katie is a serial entrepreneur who leads the design and implementation of evidence based methods that enable people to harness the power of stories for accelerated innovation.
Helen: Narratize is a generative AI platform designed for scientific, medical, and technical clients from NASA and Boeing aerospace engineers to the World Food Forum and United Nations teams to leverage gen-AI to more effectively communicate their complex innovations so their ideas don’t get shelved. Katie and I first met as panelists on an all female panel discussing AI at Together Digital’s National Conference last year, and I’ve been a fan of her and Narratize ever since.
Helen: Katie is also part of our Cincy AI meetup I co host with Kendra Ramirez, which is the largest AI meetup in the region. Last but not least, Katie and I are members of Cincinnati Catalyst AI, a consortium focused on improving the lives of everyone in the Cincinnati region, which is leading the way with responsible AI.
Helen: In today’s episode, be inspired and fascinated by narrative science and algorithms in the era of Gen AI. You’ll also discover how Narratize is uniquely positioned to tackle gen-AI and DEAI imperatives. We also discuss the need to fund female founders, the role of IP and consent regarding data and the potential of generative AI as a democratizer for creativity and storytelling.
Helen: What’s the story we’re going to collectively co-author together with AI? Listen in for what’s possible. Enjoy.
Helen: Welcome to Creativity Squared, discover how creatives are collaborating with artificial intelligence in your inbox, on YouTube, and on your preferred podcast platform. Hi, I’m Helen Todd, your host, and I’m so excited to have you join the weekly conversations I’m having with amazing pioneers in this space.
Helen: The intention of these conversations is to ignite our collective imagination at the intersection of AI and creativity, to envision a world where artists thrive.
Helen: Well, today we have Katie Trouth Taylor. Welcome to Creativity Squared. It is so good to have you on the show, Katie.
Katie: It’s amazing to see you again, Helen. Thanks for having me today.
Helen: Well, it’s a long time coming. I feel like we’ve rescheduled this interview so many times. I first met Katie through the Together Digital National Conference.
Helen: We were together on a panel, an all female panel on AI, which was really exciting. And we’ll go through some of the questions. I’ve seen Katie speak at Startup Week Cincinnati. We’re both part of the Cincy AI Meetup where she’s a great community member and also has spoken. So It’s so good to finally have you on the show and share all of your amazing insights with the Creativity Squared community.
Katie: We don’t often get like one on one time together, Helen. This is exciting!
Helen: Yes. Well, hopefully we’ll have it over drinks too and just not recorded for the podcast.
Katie: That sounds great. That sounds great. But yeah it’s amazing to be on panels together and in public spaces, but to actually get the time, one on one, to dive deeper into the topics we care so much about together. I’m so excited for this.
Helen: Yeah, likewise. And Katie’s a listener. So it’s always great to have listeners on the show too. Well, Katie, let’s dive in. For those who are meeting you for the first time, can you tell us who you are, what you do and your origin story?
Katie: Yes, so I’m Katie Trauth Taylor, CEO and co founder of Narratize. And my origin story is I decided early on in college, I wanted to be a professor, a research professor, and I wanted to really study the way that words make meaning. So I ended up doing my master’s degree in that. And then I went to Purdue university to get my PhD in narrative science.
Katie: And for those of you who are familiar with Purdue, it’s known as an engineering school. So I was sort of the lone you know, humanities, English minded rhetoric, rhetorician, I guess, surrounded by this really incredible set of engineers and engineering experts. And I began recognizing very early on how painfully hard it can be for someone with a scientific, technical, or medical knowledge base in their head to communicate effectively.
Katie: It’s just not typically part of how they create superpowers for themselves, and it’s not really part of their training. So, as I continued down the path and vision of becoming a research professor, I just, I saw that problem and started my first company at that time, and it was called Untold Content and its mission was to accelerate innovation through the power of story.
Katie: After finishing my PhD, I got my dream job as a tenure track research professor. I was at an R1 university. I was teaching students the art and science of rhetoric and scientific and technical communications. And my startup kept growing and we kept getting more and more unique and fascinating opportunities.
Katie: At one point as I was trying to decide whether to lean in full time to my startup and go grow it or stay in what I thought was going to be my dream career, I was in the basement of a veteran affairs hospital, a VHA hospital, and my company was charged with telling the story of how systems engineers were completely transforming VA hospitals to get veterans off the waitlist.
Katie: And this came at a time where the VA was in crisis. They were getting terrible press for true stories of veterans dying on the waitlist because the system was so broken. And I was in the basement of the VA hospital talking with the people who were literally washing linens, and they were coming up with new lean process improvements through the support of systems engineers to completely transform how rooms got turned over.
Katie: And sitting there in that environment, seeing that they work in windowless spaces, and they’re innovating, they’re down there trying to think through how can we turn an operating room and a hospital room over faster, just by the way that we care about the sheets and the blankets that go up those elevators.
Katie: It was such a powerful moment, I think, to just recognize the power of story and creating culture change and helping. Even everyday professionals understand the importance of systems engineering, the importance of something that’s so deeply technical, but in its application holds so much power and really without our support and storytelling and communicating about those efforts, I genuinely believe that those systems engineers would have been siloed into one tiny part of the VA and would not have been able to create the kind of culture transformation that did lead to a change in the system that got veterans off the waitlist and into their doctors in time. And it was just that moment for me where I said, “I can’t stay in academia anymore.”
Katie: I need to go lean into this and be this entrepreneur that I did not have an MBA for. But I thought I’m gonna figure it out. And so that was really a key piece of my journey and I resigned from that dream job. I leaned in and spent the last decade working with incredible enterprises from Hershey to Boeing to NASA and public sector agencies as well, helping them tell strategic narratives about their innovative work and specifically try to help the most innovative ones get message market fit internally as well as externally. It’s such a difficult challenge for innovators to tell their stories clearly and effectively in a way that actually helps sustain the momentum for their incredible expertise.
Helen: That’s amazing. I’ve never heard that story before. And I have grandparents that were in the VA.
Helen: So that, that means even more that you helped shift not only the story, but really made such a positive impact on the VA system. Well, for those who don’t know Narratize, cause you help translate stories in Narratize. Can you kind of share with our listeners and viewers what Narratized does?
Katie: Yes, definitely. So after about a decade of operating my first startup and scaling it, I started listening to our customers and recognizing there is a huge opportunity to move the solution that we’re sharing. So with a passion to solve that problem, right, to help innovators tell their stories. We at Untold [Content] began a research initiative.
Katie: We started with the vision to interview 100 chief innovation officers and chief technology officers about storytelling, because in all of the research on innovation management and all of the amazing conferences we were attending, listening to incredible fortune 1000 leaders share what they’re doing for innovation management.
Katie: They were all talking about story, but there were no clear roadmaps. There were no clear toolkits. There were no methodologies. There were no evidence based practices. And we recognized that and said, we have to change this. And so, two years ago, we started this study where we interviewed 100 chief innovation officers, CTOs, and we asked them to tell us more about the relationship between storytelling and innovation, and we came up with this incredible evidence base.
Katie: We recognized and started identifying narrative algorithms within innovation management within research and development and all the way through to marketing and communications, how do you get traction for an idea? And story is so critical from the moment that a researcher or an innovator has the idea or sees the observation or makes that discovery, all the way through to getting internal buy in to get people rallied behind that and all the way through to production and then finally trying to get it into the marketplace and having markets respond the way you hope they will.
Katie: And we began sort of mapping out all of the narrative algorithms that show up across that process and publishing on it. At the exact same time, because half of our staff have PhDs in narrative science, we became one of seven developer ambassadors into Open AI at a time where Chat GPT was not heard of yet.
Katie: This was not launched yet. This was two years ago in 2020. And. What that essentially meant was we were doing this incredible customer discovery, and at the same time we were sitting in on weekly meetings at OAI and hearing and understanding what these foundational models could do. We were helping contribute to and understand how we can create and identify narrative algorithms as part of that foundational model training.
Katie: And we started building Narratize and Stealth. Over that period of time, we started looking for and seeking venture capital to support our journey. And by March of 2023, we were in enterprise pilots with NASA and Boeing for the technology, and they went so beautifully well. We had aerospace engineers say things like, “This is blowing me away, this is how I need to talk when I’m in front of leaders, this is helping me communicate past just the technical specs and the tech details of my idea, but to communicate the impact of it and the business case behind it,” and we knew we had something, we knew we had solved a pain that was so important.
Katie: And we knew that we were generating a new type of usability with generative AI and a new kind of accuracy, a new level of accuracy. So that next month in April, we launched publicly. We raised our first round of venture capital in May. And I’m excited to share. We just closed our second round of venture capital in November of 2023.
Katie: So, so, so excited to be leaning in and serving some incredible enterprises and to be, you know. I think truly leading the usability and the accuracy claims that are going to make generative AI the highest value possible and the most impactful over the next several years.
Helen: Congratulations, first and foremost for your second round.
Katie: Thank you.
Helen: That’s amazing. And, you know, we always hear the power of story that’s used so much and it’s so true. But I love that you actually know the science behind the power of story and what Narratize is really doing is making sure that important innovations and discoveries aren’t shelved because the story, you know, if people don’t understand the story or the envelope in which the importance of the innovation [comes from], then often it doesn’t get out.
Helen: And I know you’ve shared a story before, like one of your favorites at Narratize that you like to share, if a story, if a great innovation doesn’t have a great story, what can happen? Something about someone ingesting something. Can you share that one?
Katie: Oh, yeah, definitely. There’s so many incredible stories that our team has collected over the years.
Katie: I mean, one of the first is, yeah. So Barry Marshall. Barry, if you’re listening, I’m sorry, but I’m going to tease you a little bit. I think you’ve already felt this personally. Barry Marshall is the physician who discovered that H. pylori bacteria causes stomach ulcers. So he found the reason behind stomach ulcers, but it took him years to convince the gastroenterology community to believe him and to get behind that discovery.
Katie: And it was because he wasn’t the best writer and he wasn’t the most effective communicator. So he ended up ingesting the bacteria himself and getting an ulcer in order to prove it. And, so yeah, they’re just these like very visceral stories of the way that storytelling goes wrong in innovation and discovery.
Katie: And they’re good reminders. And that’s not the only one. There’s another story, the virologist, who discovered that HIV causes AIDS, went through the exact same experience, and so, these have world changing stakes, life saving stakes, when we get [a] story wrong, and it takes time. If it takes too long to get the right solutions to global challenges, everything slows down and the world is not a better place.
Katie: And so that’s really what wakes us up every morning at Narratize, on fire, to build what we’re building and solve the technical challenges that we’re solving alongside our enterprise partners. It’s really all about making sure that you don’t have to ingest bacteria to prove that the science is true.
Helen: I love that story. Well, and since I first met you, I think it was over Zoom in preparation for our panel together for Together Digital, but I thought it was so cool that you studied narrative science and I had never heard of that before as a degree or something that you could get a degree in.
Helen: And I was wondering if you could kind of do a deeper dive and what that means, cause it’s so applicable to everything gen-AI and what you’re doing at Narratize. So I’d love for anyone else who has never heard of narrative science, like get ready cause it’s very cool.
Katie: Yeah. So at Narratize, we define narrative science as the study of the way that words make meaning.
Katie: Sometimes that discipline is also called rhetoric and composition, the way that we create and identify patterns of language, narrative algorithms, that essentially have proven to create certain effects, whether that’s to inform someone or persuade them or inspire them or create narrative persuasion.
Katie: Narrative persuasion is when you’re so wrapped up in a story that you have lost the sense of where you actually are. So Pixar does this every time, right? We’ve all had that experience of sitting in a movie or reading a book and sort of being outside of ourselves. That’s called narrative persuasion.
Katie: There are certain conditions that have to be met for [a] story to do that to us. Impact has to be clear. There has to be engagement and surprise. There has to be, if it’s working to convince us of something, there needs to be some type of evidence that aligns with our ways of viewing the world and it and there has to be alignment with what the priorities in our lives are.
Katie: So there are these drivers, these conditions that have to be met for [a] story to be effective. And when you’re a narrative scientist, you respect storytelling as an art, and we can get into all of the aspects of creativity that go along with storytelling as an art form that really truly can’t be boiled down or completely predicted, but there is also a science to it.
Katie: And I want to kind of, when I explain narrative science, I’d like to put on the hat of the people who we serve at Narratize. So think of, if you’re a scientist in a laboratory, you’re a chemist, you’re doing formulations work. If you are a researcher inside of a pharmaceutical company, and you’re working to identify the next breakthrough in cancer therapeutics, for example or if you’re literally an aviation specialist at NASA and you’re trying to project out how we’re going to get to the moon again, which is happening right now, it’s very exciting. All of those different folks, right? They’re not typically trained the way that a narrative scientist is trained, to see the world through story, and to hear and piece together the algorithms that make up how we communicate as humans.
Katie: They’re trained in mathematical and technical details that are a completely different set of superpowers. And so by seeing and helping them recognize that story is not just an art form, it’s not just meant for the amazingly creative artists of the world, it’s also formulaic. To a huge extent and to help them see the formulas that can help them be effective and getting traction and getting understanding for their work.
Katie: There’s a huge societal implication of our scientists and experts getting their stories right. And so, that’s really a huge passion of ours is empowering those who have technical scientific and medical knowledge and expertise, giving them the tools and the methods and the strategies to help them effectively communicate in every case, because if they can’t, then the growing distrust of expertise will only get worse, right?
Katie: We saw this during the pandemic. It really escalated at that time. And there’s a lot of data to show that there is a growing distrust of expertise. There’s a growing distrust and misunderstanding of science. We can’t seem to get whole cultures on the same page, whole communities, whole societies on the same page about what is scientific truth and so by helping scientists by helping those who are inside of enterprises and research and development teams and product teams and innovation teams, helping to give them the ability to recognize narrative algorithms that are going to help them be more clear, convincing, and compelling to the audiences that they need in order to get their research funded and pushed to the next stage and get their innovations out into the world.
Katie: That’s what we at Narratize do with narrative science. If you step out more broadly, people with this background also are recognizing and training AI systems from the narrative perspective. And some of that work happens in the foundational model training, but it also happens in the way that you prompt a large language model.
Katie: And so those with a narrative science degree who already sort of have that understanding of how to identify narrative algorithm, they are able to gain an expertise and prompt engineering and prompt architecting, which I would say Helen, is only the last five years or less of narrative science, like narrative science actually goes way back to Aristotle.
Katie: Like when you study this, you go way back to ancient Greece and even into indigenous cultures. And you look at language patterns and discourse communities and how they changed over the years. And so, there’s tons of history to this discipline, but the last five years it’s become more. It’s definitely merged with computer science, data science, and narrative science.
Katie: We think of those as a triangle, and when we’re building Narratize, those are the three core elements of our product team that are going to shape the future of how AI supports and fulfills the mission that we’re trying to accomplish with it.
Helen: I love that. And, you know, I heard somewhere that all stories boil down to like five or six different core themes.
Helen: But also when you hear formulaic, I also think of Netflix and we all see the data scientists coming in, setting up the formula for films that are so predictable ’cause they follow, you know, the very exact story arc. But you mentioned the constellations and the algorithms and the difference between, where the creativity comes in ’cause I think all creativity to a certain extent needs constraints to really flourish. But I’m curious, one, I love how you kind of translate your algorithms into constellations as a mechanism with your clients. How many different constellations have you identified and maybe walk us through an example of what that means for our listeners who hasn’t seen one of your presentations and also, the balance of the algorithm and where the creativity comes in so that all of your clients don’t have the Netflix formula, overly predictable outcome of the story that can also happen to you.
Katie: Absolutely. No, I love that question. Yeah. So at Narratize, the way that we kind of bring our narrative science to life is we, when we identify a narrative algorithm, we actually map it out like, like a constellation in the night sky. And I’ll map one out for you to give an example. Here’s a really common one that is used in scientific communications. It’s called the ABT. It stands for, and, but, therefore, and it goes like this.
Katie: Imagine like each time I make a ping sound, that’s a star in the night sky. So there’s an ordinary world, “ping,” and there’s something at stake, “ping,” but there’s some kind of challenge “ping.” And therefore, we need this solution. “Ping.”
Katie: So there are four key elements to the ABT and that narrative. Now that you know it, now that you can practice it, you probably will hear it everywhere. You hear it in every pitch for every innovation idea. We call those big story frameworks. Then there are more unique and nuanced ones that we map to different contexts.
Katie: So for innovation, we’ve mapped at this point over 300 narrative algorithms to different parts of the innovation process. And so, one of them would be the accidental discovery. And so, that’s not just a big framework that can go into multiple types of narrative and be used to create multiple types of deliverables, but it’s actually very nuanced to sharing a narrative about something that was discovered by accident, that the researcher didn’t set out to find this or the innovator or leader didn’t mean for this to happen, but they discovered it by accident.
Katie: And now we need to decide, are we going to move forward with pursuing this or not, and for what reasons? And so that’s a good example where you’re showcasing certain key stars in that constellation. You’re starting with, you know, this is what we set out to do, but this is what actually happened and here’s where it aligns with the roadmap or here’s where it doesn’t.
Katie: And therefore, depending on that choose your own adventure, the constellation shapes from there. And so, really what Narratize does is, it empowers research and development, product innovation, and marketing and communications teams to create content in a way that infuses it with those narrative algorithms and helps them communicate complex ideas, especially for science, tech and medics, medical use cases.
Katie: And so R&D teams and our platform can create whole research reports. They can create pitches, product teams can track user stories, marketing teams can create not just thought leadership level articles, but white papers. So it is a content deliverable. It’s a co-author platform. But the types of stories and the types of narratives that it builds are some of the most robust possible with large language models.
Katie: And I’m so proud of some of the technical challenges our teams overcome to help do that for our customers.
Helen: I love hearing about all the constellations. I know I’ve gone down a YouTube rabbit hole before. I love listening to speeches, but I also love the analysis of them. Like the Martin Luther King “I have a dream.”
Helen: It’s like, this is what I want. Here’s where we are. You know, I think that’s the pings that you’re kind of talking about. Here’s a dream. Here’s where we are and how we get to it. So I find that structure super, super fascinating and that you’re really mapping that out. You mentioned the technical challenges.
Helen: So I want to dive into this a little bit because you know, everyone who’s been exposed to AI knows that they hallucinate and you’re telling stories about very technical, scientific, life saving things. So how do you work with Narratize on that and then also, I think one thing that’s super important to us both is the bias and addressing that.
Helen: And I know that’s something that you’ve worked really hard on with Narratize too. So, can we dive into a little bit of the technicalities behind the tech and the storytelling?
Katie: Yeah, definitely. Let’s talk about the accuracy pieces first, because large language models are definitely known to hallucinate.
Katie: They’ve created some distrust already. In fact, an incredible report from McKinsey came out earlier, probably just a few months ago. And it was called “Generative AI’s Breakout Year, the State of AI.” And they found that 93 percent of companies are buying generative AI solutions, but only 13 percent of product and research and development teams are regularly using it.
Katie: Those who are already seeing not just productivity gains, but revenue gains, and yet the number one concern among executive leaders is inaccuracy. If you are prompting a large language model and what it gives back to you is inaccurate and you are in a high reliability industry like aviation or agriculture or healthcare and medicine, pharmaceuticals, that is unacceptable.
Katie: There’s such little margin for error. So inaccuracy is a huge problem. And for those reasons too, those use cases haven’t been tackled as effectively as other use cases, like creating great marketing materials There’s so much happening with generative AI for branding and for marketing and advertising. Lower reliability, lower stakes use cases.
Katie: So, really what that report found was the number one concern among leaders is inaccuracy. And for those reasons too, there’s a lack of usability, especially in science, tech, and medicine. So those industries are deeply underserved and most people have little to no idea how to leverage tools like Chat GPT or large language models, because they don’t even really know what the use case could be, especially if they’ve only tried chat GPT and they’ve gotten a hallucination like.
Katie: It’s inaccurately attributing a quote or coming up with the wrong reference that, you know, trust is what earned in drops and lost in buckets. And I think it’s been a very tough year for those who have tried the technology from those industries to really find the right solution. That’s been the core technical challenge that we have worked to overcome at Narratize and is really our North Star.
Katie: We set out to say, we’re going to have three big brand promises. It’s going to be speed, accuracy, and magic. And accuracy has to be our North Star. It has to be infused into everything we do. So here are some of the ways that we’ve really tackled this. One, we created a methodology that’s large language model agnostic.
Katie: So although we had this incredible partnership with O pen AI from the beginning and a lot of familiarity with those models and working with them, we committed early on to essentially calling from one LLM into another, into another within a single workflow. That was a huge technical challenge to overcome and we had to bring some of the world’s best experts in generative AI onto our team very early on to overcome it.
Katie: And that also meant investing in partnerships with each foundational model and also becoming, really pursuing partnerships with universities too, and so we use APIs not just into OpenAI’s GPT models, but also into, of course, Anthropx models, into Mermaid, into Meta, Stanford’s, and we went through a rigorous process of becoming an MIT computer science and artificial intelligence laboratory startup.
Katie: It’s a long word. It’s called CSAIL. And they’re just, and they’re doing some of the most groundbreaking work in AI around the globe. And so really working closely with their faculty and their PhD students to see what their research is able to lend to this, but ultimately taking an LLM agnostic approach meant that we could extract the best from each model.
Katie: They all are just designed with their own nuance, their own bias and their own potentials. And so that was key in helping to reduce hallucinations and to increase the likelihood that it would be accurate. But really the biggest, the most important piece of it is really our data architecture, the way that we create knowledge bases at Narratize, those serve as the guard rails behind what is extracted from LLMs.
Katie: So, you know, if you take an LLM agnostic approach, you’re more likely to have a better output because you understand each model and therefore you can extract from each model, what is best. And then the next phase for us is really guard railing what those LLMs output. So that looks like creating knowledge bases around industries and sub industry knowledge and best practices, as well as topical areas that we think are critical for our customers to have success.
Katie: And so one of those knowledge base topical areas, for example, is DE&I. So. What is extracted from LLMs can often be bias. They’re historically, as you’ve already kind of mentioned, right? Historically, those foundational models were trained by a very select group of people who looked very similar, all from a similar type of language, similar discourse, community, similar race, ethnicity, gender.
Katie: And because of that, LLMs have been historically criticized for having quite a bit of bias. So one of the ways we tackle that and increase accuracy is by creating topical knowledge base in DE& I. And we are so lucky because early on, we partnered with just some of the world’s experts in this: Abran Maldonado.
Katie: He’s been a tech advisor to us for the last two years. He actually created the world’s first Afro Latina artificial intelligence. Her name is Claira C-L-A-I-R-A and Claira is trained on DEI best practices and she now can go to a conference and her avatar can be pulled up. I know you’re going to love this, Helen, because you have your avatar.
Katie: It’s amazing. And Claira will come on the big screen at a conference and you can ask her questions and she will answer with a knowledge base of DE&I best practices. So you can ask her about HR policies. You can ask her about the statistics around women and executive leadership roles and how can we create better policies internally to change that?
Katie: And she’ll answer accurately. It’s so beautiful. I’ve been so lucky to have Abran’s leadership and those types of spaces. To really tackle new ways of thinking about, not just accuracy in the evidence base, which we tackle through those industry and sub industry best practices, but also through topical areas that we think are really going to be game changers for enterprises who care about that and who understand that if you have diversity, you’re more likely to be innovative and to keep and maintain your competitiveness in the marketplace.
Katie: So I think ultimately, you know, these factors are all leading to the reasons why our users are rating Narritize’s outputs as being so much more accurate. One of my favorite moments, we partnered this year with the World Food Forum and they hold global innovation challenges and teams all around the world can submit to those challenges and pitch.
Katie: And so they used Narritize’s pitch builder and wove it into their application process. And of the 500 innovation teams globally, who are literally, by the way, trying to solve world hunger and food insecurity, half of them chose to use Narratize to create their pitch. And some of the feedback that they shared was so powerful.
Katie: Obviously they were saying things like, “we made it 60 times faster than we could have on our own,” but so cool, great productivity gain, but they said, “it helped me show the impact of my research. It helped me pull the right storyline for the pitch in a way that helped make that ‘aha’ moment go off for the audience.”
Katie: And so, when we sort of got into our data around it, they said that Narratize’s outputs were 76 percent more accurate than any other generative AI solution that they had used. And that is so exciting to just see the ways in which we’re embedding evidence into the tech stack at Narratize is actually making a difference in the ability for someone with insane expertise to be able to say, “wow, it actually accurately expanded on a technical topic I was talking about and it did it accurately.”
Katie: And then there’s like one final layer, Helen, and I answered this in a ridiculously long way, but for those who really geek out about this, we’re also building in research citation features into the platform. So, pretty soon in the next probably by the time that you’re listening to this, Narratize will launch its research hub. In that, we’re training the AI to recognize the topic that you’re writing about, the industry that you’re in, your context, and it will then recommend peer reviewed citations.
Katie: We’re starting with peer reviewed only at first, and then we’ll move into grey literature and go from there, but it recommends peer reviewed publications that would be relevant to what you’re writing about. And pretty soon it will even begin a conversation with you around, “Did you know that your voice is rather unique in this space?”
Katie: Or, “I’m not sure that this stat you’re sharing is evidence based, or it agrees with the majority of voice in the peer reviewed publications that have discussed this before. Consider where your voice falls into that conversation and cite this source, or maybe read this set of references.”
Katie: Those are some of the capabilities that we’re building and to give that power to the user. So, I’m really excited for some of the product roadmap features that are coming out that are going to even amplify accuracy more.
Helen: I love that. Thank you for sharing. And I love your partnership with the World Food Forum that’s actually solving world hunger.
Helen: And when I heard that, it made me think of AI for good and literally solving world hunger and how AI can find efficiencies, but also, you know, in Narratize’s angle, helping tell the stories that will help solve world hunger to make it possible. It’s so, so important.
Helen: And we hear AI for good so much, and it’s clearly, near and dear to your heart. When you hear that word what does that mean? ‘Cause there’s a lot of other implications. I’d love for you to kind of expand what AI for good means to you.
Katie: Yeah, absolutely. So I’ll speak kind of about my place in the world I guess.
Katie: I personally am headquartered in Cincinnati, though Narratize team members are all over the nation, and we have offices in New York, but in Cincinnati there’s a movement to really embrace responsible AI and to create leadership, global leadership in that space. And I really love the way we’re defining responsible AI and to me, it really embodies AI for good.
Katie: So I’m going to share the definition of the working groups that we’re forming here in Cincinnati, and I hope that it resonates. So we define responsible AI as, “the practice of designing, developing and deploying AI with good intention to empower employees and businesses and fairly impact customers and society, allowing companies to engender trust and scale AI with confidence.”
Katie: So first I’ll say that’s a working definition, but we have some incredible leaders like Pete Blackshaw of Cintrifuse, Kelly Cohen, who I know has been on the podcast before, from the University of Cincinnati, who has just been an expert in explainable AI for almost 30 years now. And we’re working together to say, this is how we’re defining it and I think where there is good intent to empower.
Katie: That’s, I think, my favorite phrase of the way that we’re defining it. So at Narratize, of course, when we think about what wakes us up in the morning, what sets us on fire, we have good intent to support scientific communications, good intent to help innovators.
Katie: Innovators get their ideas off the shelves and to be heard. Good intent to help businesses thrive and to be as innovative as possible and fulfill their missions. So where that intent changes or where our practices don’t align with that intent. I think that’s where we could see the dark side of AI and we have to keep that intent and then actually put policies, [00:41:14] practices and commitments behind it.
Helen: Yeah. And a big shout out to Dr. Kelly Cohen. He’s been a big supporter of our Cincy AI meetup and has literally been doing research on explainable AI, which is really important for responsible AI and AI for good for 20, 30 years. I love the community here in Cincinnati. In one thing, as you were reading that working definition, of the task force or committee that’s really working on this in the region.
Katie: So we’re calling ourselves the Cincinnati AI Catalyst and it has leadership from a lot of the large corporations in Cincinnati. So anyway, hopefully more soon from us, probably by the time you’re listening, we’ll have some actual case studies to be sharing around the work that we’re doing together, but I’m very excited about the future of it.
Helen: Well, and one thing that kind of came through as you were sharing the working definition is it’s all human centric. It’s augmenting humans, it’s having human touch be part of it. It’s the intentionality behind it. And I think that’s so, so important when we’re talking about responsible AI, ethical AI, that it’s amplifying humans and not replacing them. So that was really great to hear.
Katie: Yeah. Early on when we were coming up with our core values, we really zeroed in on human led everything, human led AI, human led culture inside of our company, human led cultures of innovation, storytelling for the enterprises we sell into. And so it’s funny, we didn’t, I didn’t touch on this when we were talking about accuracy and reduction of hallucinations, but one of the other secret ways that’s happening inside of Narratize is because we designed the user experience to really focus on…
Katie: Really, we’ve created Narratize as a coauthor, not a replacement. Some of our competitors have really led their methodologies with, “I’m going to write this for you and you just sit back and do nothing.”
Katie: [With] Narratize we very intentionally designed every step of the user experience to say, your ideas matter, your knowledge matters and your creativity and your voice matters. And Narratize will prompt you in the same way that it feels to sit down with an amazing interviewer and be asked the right questions to help you think more deeply about the topic that you’re trying to communicate and to help you think through parts of it that maybe you didn’t know you needed to communicate.
Katie: And that’s another, ironically perhaps, Narratize is more accurate, is because it starts with the user and it represents their voice. Then there are other implications to that too from an ethical standpoint, that means that you maintain copyright over what is generated. And then we’re building another features like digital signing to help promote that.
Katie: But those are some of the ways that making sure that it’s human led appears in every touch point in the platform. And I think that is unique. And I think if we’re going to have the intention to do more innovation and to help enterprises be more innovative, then that’s not a replacement of a person that is an elevation of their capabilities.
Katie: And that’s so key. I think if you have that intention, then you’re actually creating the methods that are going to support it.
Helen: I love the intentionality behind it because I think that’s key to most things in life, but especially, you know, the intentionality behind the tech, how we’re using it. So, I love hearing that.
Helen: And something that you shared before we started recording is the scene of venture capital. And I’m so proud of you for getting your second round of funding and that you’re pushing these great ideas and leaders like you need to be funded. But can you share the statistic that has a lot of potential to be improved about who’s getting funding and AI right now?
Katie: Yeah. Yeah, so we’ve talked a bit already about the historical bias and AI model training. I don’t even think we touched on this yet, but the AI Now Institute of New York University found that 80 percent of AI professors are men, less than 25 percent of PhDs go to women and minorities.
Katie: And then all of that bias is held to an even worse extreme or kind of escalates to a worse extreme when it comes to venture capital. There’s a lot of understanding I think that’s growing about the problem in venture capital for female founders. Two percent of venture capital goes to female founders, 2%.
Katie: And I think it almost got to three percent a couple of years ago and then it just went back down to 2%. The Alan Turing Institute recently did a study, their women in data science and AI team did a study and found that only 0.3% of the venture capital that goes to AI companies goes to female founded companies.
Katie: So not only am I working in a space where only 2% of venture goes to women, but 0. 3% of AI venture goes to women. I have two female co founders and the journey that it took for us to be able to raise capital was not great. And I think I watched other male founded companies that had far less traction, had far less actual expertise in the space who were using fake mockups, honestly, and didn’t even have real products when we already had products, get funding before us.
Katie: And it’s okay, right? It’s okay, and it’s not okay. It’s okay. To me, personally, it builds resilience, it builds grit. It’s not okay.
Helen: It’s absolutely not okay. It is not okay.
Katie: It’s not, okay? I guess, like, I, like, my personal… it’s just not okay. If you’re listening, right, I think we can all agree that is abysmal. It’s pitiful.
Helen: We’re laughing because it’s like you laugh or cry.
Katie: Exactly. Well, I say, it’s okay, right, because I’ve just learned to live in that world, and I’ve learned to not let it get me so upset that I freeze. That’s why I’m saying, I say to myself “It’s okay.” And we are changing it every day, every minute that we work as hard as we are, we’re changing it.
Katie: And we’re about to blow that statistic out of the water. That’s my hope and my dream and my goal that, generative AI and the understanding of the way narrative scientists plays with data science and computer science actually is a brand new access barrier break, right? That we’re shattering some glass ceilings here.
Katie: And we’ve heard a lot of news and amazing thought leaders say generative AI is the great equalizer. It is enabling creatives and those with more humanities related backgrounds to be able to really grow and become good at things like prompt engineering, prompt architecture and speaking to large language models in a way that infuses their creativity into it.
Katie: So I’m excited for all of those things. I think all of this has to change in every single way. There’s great momentum right now for changing at the policy level, the definition of an accredited investor, for example today, that definition really limits who can become an accredited investor and it excludes investors who are interested in investing in technology, but who don’t necessarily meet certain wealth criteria. And by changing that, we can make investors more diverse and therefore what they do more inclusive and who they fund more inclusive and the whole space more inclusive.
Katie: I think through this whole process. It’s certainly eye opening to me. This is my first experience raising venture capital. My first startup was completely bootstrapped and it grew on its own. It didn’t need as much upfront investment as building an AI company obviously requires and it’s been an eye opening experience to recognize how abysmal these statistics are for women and especially for minorities.
Katie: And it’s, you know, we do what feels familiar. And unfortunately, and fortunately these revelations and AI are changing and breaking that old model. And I hope that venture capital breaks along with it. And I’m so grateful to have some incredible investors like HowWomenInvest, Hurst Lab, Kubera Capital, North Coast Ventures and Cintrifuge Capital and Keyhorse Capital behind us and paving that way and saying, yes, we believe that these three female founders are domain experts and are here to change the game.
Katie: And they might not look like 99.7% of venture funded AI companies. But that is a good thing. And let’s go change it together.
Helen: I love that. That you’re helping pave the way and hopefully any of our listeners or viewers listening to this opened your mind to supporting more women in the AI space as well.
Helen: And the best way to support, we appreciate mentorship, but funding fund women in AI.
Katie: Show us the money!
Helen: Well, you know, one thing I wanted to ask you about too, is… We’ve said many times on the podcast that gen-AI specifically is a great democratization of creativity. And you just mentioned that it can be a great leveler, but I’ve also heard the flip side that because everything is data driven these days, the big companies that have the most data actually have an advantage because they just have so much data that they can leverage versus smaller players in the game. So I’d love to kind of hear [00:51:44] your thoughts on that.
Helen: And then one thing that I love that you mentioned on the panel that we did is also how you think about data, ‘cause when I usually think about data, I always think about the numbers, the crunching, Excel spreadsheets, the new models. Yeah, change the game of how we think about data too. So I know that’s two questions, but I’d love for you to speak to both.
Katie: Yeah, that’s a great question. So when I’m saying that generative AI’s advancements can be a great equalizer, I’m really thinking about the talent and the professional career opportunities that are opening up to those who have storytelling backgrounds, who have branding, marketing, technical communications or writing backgrounds, those are opening up and we can start at the college level, at the university level now helping students understand new ways of working with AI not just on the deepest foundational model training, but on the ways that we communicate with large language models and get them to do what we want them to do and those careers and prompting, I think, are going to be so rich and really change the creative industry for good and forever.
Katie: However, AI is not the great equalizer when it comes to who owns data, who has the biggest dollars invested in these foundational models. That is certainly, at a societal level, absolutely true, that those who hold the most data hold the most cards and have the most potential to create the most nuanced outputs and outcomes from AI.
Katie: Naturally AI is trained to predict based on data that helps it understand context. And the more context it’s given, the better it can predict and the more impressive its outputs will be. So that’s very true. And it is concerning.
Helen: I think, you know, even if you don’t have a ton of data in the sense of competing against some of these bigger entities. I pose the question because I’ve heard both sides.
Helen: And it’s just something that we all think about and exploring right now. But I also think it underscores the importance of Your own IP and protecting your own IP, because you might not have all the data possible, but your IP and what makes your data unique, especially from a creative lens is even that much more important.
Helen: So maybe it’s not the, you know, we’ll answer every question or chatbot question, but the importance of IP. I think this issue highlights even more maybe.
Katie: Yeah, that’s an excellent point. The importance of IP and I think too, having a robust understanding of what kind of data model training requires. So I think people hear the word data and they think of statistics, they think of numbers and massive amounts of sort of big data.
Katie: So most enterprises over the last year have gone from, “Oh, there’s this unique and fascinating thing called Chat GPT” to, “Oh, my shareholders are demanding that the C suite have a strategic plan for generative AI.” And it’s now a top down imperative. Now, most enterprises are forming committees on their use of generative AI.
Katie: They’re vetting vendors through those committees. They’re setting up, thank God, policies on responsible ethical use and making plans for how they’re going to implement it. And all of them are having to decide where to build and where to buy. And most of those enterprises are the ones who have incredible data.
Katie: And of course, every enterprise is deciding what to build themselves with their own data science teams and what to buy and where to partner and which vendors to partner with. And while those enterprises themselves hold incredible and proprietary data, they have a lot of opportunity gain when it comes to choosing vendors who understand large language models.
Katie: And how they’re trained and how to extract value from them. So I think that’s really the beautiful middle ground between whether this is an equalizer for certain groups or not. Where we can bring those with narrative science, data science, and this deep foundational understanding of narrative algorithm and how models work to those enterprises to partner with them in the best use of their data.
Katie: That’s the beautiful thing. I was in a conversation with a global aviation company earlier this week, and they said, “well, we could go feel in the dark for two years, trying to come up with narrative algorithms, but that’s not our expertise. So let’s speed that up through this partnership and integrate Narratize as part of the tech stack and help us understand and make use of our data by understanding and making use of what’s possible with each large language model.”
Helen: Yeah, I appreciate that. And I think, too, in the way that democratizing creativity has come up on the show many times is also just having people access to tools that they wouldn’t otherwise have access to, be able to create things that they might not otherwise be able to.
Helen: So, the tools in and of themselves, foster that type of creativity and new voices to tell new stories, maybe even new constellations might arise from this. But yeah, the big data versus IP… I think as we’re all kind of co-creating the future that we want to live in and the intentionality of how that looks, that we just need to keep in mind the big data versus you know, the landscape that we’re all playing in that regard.
Katie: On the panels that I’ve had the honor to be on with you too, you do such a beautiful job of supporting artists, creatives, writers, illustrators with recognizing where they can maintain their I. P. And hold on to it. And in light of this space that has often felt threatening. So anyway, I’m prompting you now to share a little more about that. That’s a critical piece of, I think, a more bright future with this.
Helen: Yeah, I agree. Some artists are in a really tricky place right now. I know open AI has introduced plugins that you can add to your website or code that you can add to your website that’s like, “do not scrape my data to train your models.”
Helen: I think I got this off of the Hard Fork podcast that it’s kind of like a thief stealing everything in your house. And then afterwards, like, “here’s the security camera, so you catch me next time,” but all of the content has already, you know, been stolen. So it’s a little too late. And there was one very interesting proposition of these models should clear out all their data and start over again with data that’s been consented to train them, which, you know, never came out to play, but it was a more interesting solution to that.
Helen: So in that regard, the genie’s out of the bottle with these tools. A lot of artists. have had their works, train their tools without consent or compensation, which is in a really hard place. I know some more in the content creator influencer space is like, well, being online, this is just a consequence of existing online that you’re going to be training and that’s okay.
Helen: And then you see creators on the flip side that are totally embracing AI and not worrying about all of this. And just like, Running forward, producing as much content. We have a lot of guests on the show who have done this too, of just getting in the front and embracing it for all the right reasons. So it’s definitely a spectrum, but.
Helen: I think one thing that’s just stood out to me this past year is the importance of IP. And for those who weren’t watching, this is my first episode where I’m recording outside of my home studio. I’m in San Francisco and just got back from a conference from the Content Authenticity Initiative Symposium.
Helen: And Katie mentioned earlier that they’re adding digital signatures to their product. And one thing that… This will be played in 2024. It’s going to be- 2024 is a pivotal year. Some stats that they shared the other day is that 40 countries will be voting. About 2 billion of the world’s population will be voting in 2024.
Helen: That’s a massive amount of people going to the polls and potentially challenging our democracy, changing our leadership and direction of where the world is going. And at the crux of this also, or, you know, what’s happening is misinformation, disinformation, which has always been at play, but now AI can make it at scale and easier to manipulate and, you know, have election fraud and all this stuff.
Helen: So going back to digital signatures and understanding what’s real, what’s not, who the author is, who is not, do I believe this, do I not? It’s all so, so critically important. And one reason for the podcast is to become aware and educate. If you’re an artist, and this is all scary, I get it.
Helen: But putting your head in the sand isn’t going to help with the, you know, understanding it because the genie’s out of the bottle it’s here. So whether you embrace AI, or want to protect your content from being touched by these models, you know, there’s tools, but the best thing you can do is learn about it.
Helen: Cause it’s the next internet. It’s the next, you know, phone or whatever. So that’s kind of, that was a very long ranting answer, but protecting your IP is so important in my mind.
Katie: Yeah, couldn’t agree more.
Helen: Well, I feel like we could go on and on and we’ll definitely probably have to have you back on the show too.
Katie: We will.
Helen: And for anyone in the Cincinnati area or region, definitely come to our Cincy AI meetups. We’ve got [01:02:01] actually the task force, I forget the name of it already, on responsible AI as part of our Cincy AI community and we’ll be getting updates. We get research updates from the students and all the amazing work that the University of Cincinnati is doing in explainable AI and fuzzy logic AI, which we don’t have time to go into.
Helen: But one thing I’d like to ask all of my guests is if you want viewers and listeners to remember one thing from today’s conversation, what do you want that one thing to be?
Katie: The right leadership will look for opportunities to use new technologies to innovate better and faster in a way that operates with good intent for good.
Katie: And I think if you took one thing away from our conversation today, I hope it was that, I hope it was hope that there are new approaches to the way we use these technologies to support some real problems that exist in innovation and storytelling related to it and I hope that you walk away inspired by that and excited to try tools that are going to help you, everyone listening to this podcast is likely an innovator or thinks of themselves in that way, I would hope and, you know, knowing that there are tools that are being designed in a way to elevate you and your ways of thinking and the superpowers that you’ve cultivated over your career. That’s what I hope that people take, listeners take from this conversation. And those of you who are on the frontier at the edge of designing systems with AI, I hope you also take away that there is so much.
Katie: It’s so important for us to all aim towards accuracy and to Helen’s point around misinformation and its growth. It’s so critical for us all to care about that, for us all to have a shared understanding of what evidence based means, what peer review means, why it’s critical and how to make sure that it lies at the foundation of everything that we do.
Helen: I love that. That’s so beautifully stated. And I would say, I usually don’t do this, but one of my takeaways too from just knowing you and every conversation that I get to have, I’m always inspired by the power of story, I say this often in little sign-offs, like we’re co creating the future and we are co-authoring the story of how we write AI, the intentionality behind it, how we’re supporting different people in this space.
Helen: So I think as we think about the constellations, the algorithms, like what’s our own story that we tell ourselves about AI and what’s the story that we want to tell and how we can co-author that together. So I’m excited and hopeful about the possibilities in that too.
Katie: I love that so much, Helen.
Katie: It reminded me, gosh, and here I go with one last story, I promise. One last thing.
Helen: All good. I love more stories and tangents.
Katie: I promise this will be the last one, but I interviewed as part of that discovery that they talked about at the beginning of our conversation today, I interviewed Kate Maxwell.
Katie: She’s now at Google running all kinds of amazing things. But when I interviewed her, she was one of the innovation leaders at Raytheon, which is an aviation company. They do a lot of defense innovation. And when she was there, innovation was siloed into about a 10 person team and generally, employees, tens of thousands of employees in the company didn’t necessarily have voice in the direction of innovation and the company and neither did they have a system in place to help support them.
Katie: And so Kate wanted to change that and she started with a really small pilot a few thousand dollars and she started building systems to collect innovation ideas and stories across different teams and it was so successful that they ended up scaling it into a multi million dollar global initiative that was building systems around innovation storytelling, training people in the art and science of innovation storytelling and ultimately it elevated them to becoming one of the top patent producers in the world.
Katie: And I love, I just love that because Kate’s leadership and her vision and her understanding of the evidence base for innovation storytelling, it really sparked this complete culture change and it enabled teams to all see themselves as innovators. So just like getting back to that, if you take something away from this conversation, remember that people washing linens in the basement of the VA hospital, remember the teams who suddenly were able to see themselves as storytellers and innovators, excuse me, because they were given a mechanism for sharing their innovation ideas.
Katie: If we don’t communicate, then it doesn’t form who we are. It doesn’t become part of our identity and it limits our potential. And then it slows the whole company, down the whole organization down. And I think that’s why I get so excited about the opportunity that storytelling creates in our lives. And of course, the way all of these new technologies can put that at scale, put it at our fingertips and not just with a small set of consultants who are going to come in and train you on it.
Katie: It’s about living and breathing it and really doing good in the world from that.
Helen: I got chills listening to you saying that. So, so beautifully said. Well, Katie, it has been an absolute pleasure getting to know you this year in Cincinnati and having you on the show and sharing all of your amazing insights.
Helen: And I can’t wait to continue the conversations both on creativity squared Cincy AI and all the responsible AI and hopefully over drinks before long too.
Katie: Exactly. Yes. Thank you so much for having me, Helen. And for those listening, please connect with me on linked in. I’m Katie Trauth Taylor of Narratize.
Katie: If you want to talk with our team, we would love to hear your vision, your strategies, your questions about generative AI for the use of innovation. And Helen, you are incredible. Your leadership and helping to really create the future of what creativity is going to look like with AI. It gets me so excited every week to listen to the next episode of your podcast.
Katie: So thank you for your leadership. Can’t wait to see you soon!
Helen: Thank you for spending some time with us today. We’re just getting started and would love your support. Subscribe to Creativity Squared on your preferred podcast platform and leave a review. It really helps and I’d love to hear your feedback.
Helen: What topics are you thinking about and want to dive into more? I invite you to visit creativitysquared.com to let me know. And while you’re there, be sure to sign up for our free weekly newsletter. So you can easily stay on top of all the latest news at the intersection of AI and creativity because it’s so important to support artists, 10 percent of all revenue Creativity Squared generates will go to Arts Wave, a nationally recognized nonprofit that supports over 100 arts organizations. Become a premium newsletter subscriber or leave a tip on the website to support this project and Arts Wave and premium newsletter subscribers will receive NFTs of episode cover art and more extras to say thank you for helping bring my dream to life.
Helen: And a big, big thank you to everyone who’s offered their time, energy, and encouragement and support so far. I really appreciate it from the bottom of my heart. This show is produced and made possible by the team at Play Audio Agency. Until next week, keep creating.