Sarah Luger, PhD sat down with host Alex Olesen, VP Vertical Strategy & Product Marketing at Persado to share some key ways humans and AI work together and could collaborate in the future. This partnership between humans and AI offers an uplifting perspective. AI automates mundane tasks at scale, leaving humans with more time to complete more complex tasks. But, what does this mean in the short term and in the long term? According to Sarah, right now, ChatGPT and GPT-based technologies are being used a lot in marketing, writing, and creativity-based tasks. Generative AI is great for writer’s block and people can easily figure out how to engineer prompts thanks to decades of using Google. On the enterprise level, the relationship between AI and humans is based on trust. Not just humans trusting AI to complete tasks quickly at scale, but also using AI to add value to the customer experience. Forward-thinking companies use AI to learn customers’ preferences and to provide more personalized experiences and recommendations.
“At Orange, we take our customer engagement extremely seriously. We are customer-centric. Our concern is a great customer experience and we know that we’re sitting on a gold mine of data. Now we have a tool that allows us to personalize and create even better experiences,” said Sarah.
Sarah hopes to see in the future how large language models will transform economic and global engagement, especially when it comes to underserved languages and communities.
Episode Transcript:
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Alex Olesen: Welcome back to the Motivation AI Matters. Today I am really excited to be joined by Sarah Luger.
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Alex Olesen: Sarah, thank you for joining us today.
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sarah: Thank you so much, Alex. It’s a real pleasure. As you know, I’ve been working in the space for some time, but also excited about Persado’s role in this space. So thank you again for having me. My name is Sarah Luger.
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I got my PhD. At the University of Edinburgh many years ago in artificial intelligence, and…
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Sarah: …I’m being quite honest to say that I’m surprised and excited about the developments in this space. In the past, I’ve worked at startups. I’ve worked at IBM building a precursor to the IBM Watson Jeopardy challenge robot.
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Sarah: I’ve also been at Orange in Silicon Valley for five years. We’ve worked on numerous topics, including voice by metrics, chatbots, call center technology…
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…and of course…
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Sarah: …everything that has to do with large language models and Generative AI.
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I’m really excited, especially because, as you may or may not know….
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Sarah: …Orange is a large company with almost a hundred 40,000 employees, and we’re in 27 countries. Many of those are in North and West Africa, and many of our customers speak languages that are low resource, which means they don’t have a lot of training data.
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Sarah: They don’t have an online presence that supports the kind of data and that’s used in conventional translation systems to create high-quality translations. So, I’ve been working a lot in that space. And I do see both potential…
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Sarah: …for large language models to support our customers, but also some peril. And I’m looking forward to chatting more about that today. Thank you.
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Alex Olesen: I think that’s fantastic. And you’ve got a great background. I know you’ve…
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Alex Olesen: …seen this industry evolve through numerous iterations. It’s most recent what is now being referred to as Generative AI.
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Alex Olesen: I know you just touched on a lot of really interesting topics. We’ll dive into it over the course of this episode. But to give the listeners a good baseline…
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Alex Olesen: …in your own words, could you define what this new term Generative AI means, and then talk to me a little bit about who Generative AI is important for?
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Sarah: So, I think…
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Sarah: …for the average person out there. Generally, today…
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Sarah: …AI is where the output resembles human content. It resembles a language that is either…
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…that seems like it’s constructed by a human…
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Sarah: …or technically Generative AI systems are based on algorithms that learn from a vast amount of input data. And the most recent cases that we’ll dig into. That would be all of the digital data that’s on the web as well as some knowledge bases, knowledge bases being things like Wikipedia that give structure and associate terms. And…
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Sarah: …some apparent meaning to this, this vast sea of language data. And so…
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Sarah: …what’s going on under the hood is that there is…
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Sarah: …this vast amount of data is being used to learn the patterns of how we as humans speak…
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Sarah: …and how we write, and with innovations, both from Google’s 217 transformer paper, incredible compute innovations…
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…as well as just ongoing neural networks developments.
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Sarah: There’s the possibility, as many of us have now tried since November 30th, 2022, when Chat GPT was launched…
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Sarah: …to engage with a Generative AI system in a way that most people had not engaged with an AI system, you know. Perhaps in the past, you had AI, a secondary character in a video game, you know, or there’d maybe been some predictive analytics in an enterprise…
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Sarah: …application you were using. But the core of Generative AI is using these patterns of words at a vast scale. That then for us makes it seem like…
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Sarah: …this computer, is…
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Sarah: …almost human-like content that’s being output. And it’s really a powerful difference between…
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Sarah: …systems from even six months ago, right? We had it seven months ago. We’ve had a seat change. And your second question is…
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Sarah: …Who is it most important for?
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Sarah: Right now…
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Sarah: …we’re in the hype cycle, and it’s important for everyone…
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…this is great for everything…
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Sarah: …and I respect the hype as someone who’s in Silicon Valley because I understand the role that it plays and the duality of…
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Sarah: …how we get an investment and how we build prop products and how we have to compete with other hype cycles, most recently in blockchain.
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Sarah: But I think that this is really important for…
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Sarah: …creating customer-centric tools
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Sarah: …that support…
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Sarah: …voice bots textual, you know, marketing text. I think that marketing and customer support are the first areas that are going to see innovations in these really…
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Sarah: …human seeming…
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Sarah: …engagements that can be created for their customers. So…
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…those are the two areas that the people I see that will be most affected. But then I want to also flip that and say…
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Sarah: …I think the Holy Grail of enterprise…
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Sarah: …innovation that isn’t as shiny and sparkly as some of the others, you know, key terms I’ve just mentioned…
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Sarah: …is enterprise intranet search.
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Sarah: So, the ability to search through a company’s resources, to answer questions for employees, or answer questions for employees that are then passed on to customers. I think that that is…
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Sarah: …really key because it will help you and I do our jobs better and reduce mundane tasks…
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Sarah: …it’s something that AI, in general, is, you know, aims to do with any technology. We try to elevate our…
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Sarah: …work tasks up…
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…the difficulty chain. So, we want, as humans, to not do the same thing every day, but to understand patterns…
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Sarah: …and reduce repetition…
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Sarah: …and do more and more challenging tasks, and those more challenging tasks are very hard for computers, so don’t fret. Many of us will still have jobs. On the other hand, those lower-level tasks are…
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Sarah: …really great opportunities for computers to come in, Generative AI systems to come in, and support us.
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Alex Olesen: Yeah, you’ve raised some really interesting points, some of which, you know, we’ve discussed in prior conversations. But I’ll summarize those quickly for the listeners.
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Alex Olesen: You know we’ve talked about. And I love the way that you put it. You know, some hype cycles around the Metaverse around blockchain. I think we’re definitely seeing a surge of a hype cycle around Generative AI…
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Alex Olesen: ..you know, to another one of your points. The barrier to entry for consuming this type of technology in my observation, has been lowered…
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Alex Olesen: ..as of November of last year.
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Alex Olesen: Chat GPT is so readily available for the average consumer. You know, broaching the consumer market…
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Alex Olesen: …and…
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Alex Olesen: …you know, as you’re alluding to breaking into the enterprise space as well.
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Alex Olesen: I think, is going to have…
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Alex Olesen: ….widespread benefit both in terms of the way consumers interact with this type of technology, but also the way large enterprises similar to Orange…
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Alex Olesen: …derive value from this type of technology. But I do want to touch on another point that you’ve made, which is unique to the other conversations that I’ve had in the last couple of months…
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Alex Olesen: …which are the implications around education and career development.
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Alex Olesen: I love what you said because it goes. It goes against the grain, in my opinion…
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Alex Olesen: …of what we have seen in the news around job displacement…
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Alex Olesen: …and the automation of tasks. I think you delineate very well, and artificial intelligence will help eliminate some mundane tasks. But you put a great perspective on the state of the market by saying it will free…
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Alex Olesen: …humans up to do more challenging tasks, and I find that to be a very pragmatic and uplifting perspective…
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Alex Olesen: …if you could expand on that a bit, Sarah.
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Alex Olesen: What…
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Alex Olesen: would you say…
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Alex Olesen: …are some interesting applications of humans and AI working together?
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Alex Olesen: …might be that we haven’t necessarily considered yet….
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sarah: …Great…
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…yeah. And I I appreciate you…
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sarah: …your perspective as well, because I think that we’re at a point where, because of the hype, there are some…
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sarah: …main primary narratives that seem to be…
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…they. They seem to be extremes. They’re either fear- based or or wildly outlandish. And you know that the reality is somewhere in between.
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sarah: I’ve heard that…
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…with new innovations we grossly…
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sarah: …overestimate the near-term change, and then underestimates the long-term change…
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sarah: …and that’s not my quote, but I strongly agree with your point. What are the ways that this hasn’t been used? And it hasn’t been clear and with collaboration between humans and…
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…these tools. What will…
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sarah: …become clear in the near term? So, what is happening now, what do we see now?
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sarah: Right now, Chat GPT and GPT-based technologies are being used in a lot of marketing, writing, and text and ideation and creativity-based tasks.
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sarah: So, they’re really good for this blank page problem. Maybe call it writer’s block…Also, from a prompt perspective. You know, we’ve all grown up to some extent feeling comfortable with Google searches. And so, we can figure out how to engineer prompts that give us an output that we’re looking for…
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…But humans and computers working together has a long-standing history of this. And in artificial intelligence we’ve developed agents
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sarah: …which are some little software
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sarah: …products that help humans complete tasks. And there’s been research in this multimodal, you know, with sensors, what is there. There’s a lot of use in industry. But I think that the next wave of…
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sarah: …this technology will be using the
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sarah: …trust which a lot of users have gained from this first iteration. And you know, later, I want to maybe push back on that trust. But if we think of this as kind of a consumer life cycle..
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sarah: …using the trust that the consumer has from the output of their large language model….
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sarah: …chat interface…
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sarah:… and turning that into a resource…
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sarah: …that maybe takes the place of a Google search. Right? So, I think that chat interfaces are going to transform the way that humans work…
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sarah: …with…
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sarah: …computers in the fact that we may no longer have Google page rank be as an important in terms of Google being the font of all knowledge. Maybe that verb itself. I’m gonna Google. It will…
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sarah: …cease to be as relevant. I think we’re going to have a split in our society where people who have become very…
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sarah: …adept at using chat technology may go to use this as their primary resource for new information, for information discovery.
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I think that that could have profound implications on the Enterprise search and our ecosystems, you know, if we think of trying to make a decision about, say, is…
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sarah: …Siri, or Google Home or Apple home pod. What is the best smart device…
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sarah: …it’s hard to evaluate, which is…
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sarah: …in a way you know, just a discrete test.
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sarah: But maybe, as many consumers do, people make decisions based on their ecosystem. So, I imagine in the future that…
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sarah: …open AI will leverage this…
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sarah: …collaboration with Microsoft to really pivot the enterprise solutions that the average person spends a lot of their time on…
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…and by…
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sarah: …changing that habit…
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sarah: …anytime you use an ecosystem, you’re providing them with a lot of data…
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sarah: …and when you provide an ecosystem with a lot of data, it allows them to personalize and learn your preferences. And this could change the way that we, online…
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sarah: …receive, ask for and receive new information, answer questions. And…
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sarah: …could that pivot reshuffle the companies that we get many of our goods and services from, or at least our initial point of contact for those goods and services, because I do think that…
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sarah: …especially younger consumers, will feel more comfortable using these tools…
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sarah: …as…
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sarah: …a co-author, as a co-pilot…
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Alex Olesen: That’s really interesting. And, Sarah, you’re touching on a topic that actually comes up with a lot of clients that I speak to. You know, we’re in an interesting…
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Alex Olesen: …environment from a macro perspective. At the moment there have been macroeconomic headwinds…
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Alex Olesen: …you know, large mid market startup businesses have to navigate in terms of personnel decisions, R&D investment decisions…
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Alex Olesen: …specifically within tech, there have been a lot of reductions in force…
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Alex Olesen: …So, let me just paint that as the
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Alex Olesen: …personnel backdrop for humans interacting with machines simultaneously…
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Alex Olesen: …this new technology appears seemingly out of nowhere last year…
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Alex Olesen: …to the untrained, it can come across as this, all-seeing oracle that can answer any question. So, if I’m sitting from the perspective of…
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Alex Olesen: …someone in the workforce that spells a threat…
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Alex Olesen: I love the direction that you’re taking your point of view because of the way that you phrased it, and I will have to look up this quote. We…
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Alex Olesen: …overestimate the near-term impact and underestimate the long-term impact…
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Alex Olesen: …and what I’m finding…
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Alex Olesen: …in my personal experience with our clients is…
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Alex Olesen: …these…
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Alex Olesen: content assistance or generation tools, they help alleviate…
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Alex Olesen: …writer’s block. They help get the first notes on the page…
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Alex Olesen: But that human expertise of motivating someone to act…
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Alex Olesen: …of understanding the nuance of…
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Alex Olesen: …what’s being discussed…
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Alex Olesen: …is it from what I’m gathering, from what you’re saying, not quite…
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Alex Olesen: …and maybe this is two points, not quite the capability and not quite the near-term intent of this technology. And I think…
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Alex Olesen: …that is.
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Alex Olesen: …a very good dynamic to exist specifically in the environment that we find ourselves in now.
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sarah: Alex, can I? Let me ask for clarification? So…
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sarah: …are you…
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sarah: …I agree completely with what you said. But this is your question…
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sarah: …I think. Let me just. I kind of started thinking about one word you said with human intent…
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sarah: …and I think one of the challenges with the output of large language model systems…
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…is what we’re calling them…
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sarah: We’re calling that output information…
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sarah: …and I’m not sure if that’s a great word…
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There’s a researcher I spoke with last week…
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sarah: …who would like us to remember how large language models work on the inside
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sarah: …and view the output as synthetic media, because information is constructed by a human…
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sarah: And if…
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sarah: …words are not constructed by a human…
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…Is it information?
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sarah: And this is a very interesting discussion, and I think that this is nothing that we’re going to solve today. But it goes. It touches on another topic in this space, which is anthropomorphizing these systems, as you noted, you know, they’re…
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…impressive. And if you don’t know the inner workings, or if you’re new to this space…
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sarah: Or actually, that’s not fair. If you’re a human. you…
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…automatically…
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sarah: …give intention to text…
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sarah: …you give you meaning out of the kind of bag of words that you get back. And this bag of words is really good. And so, it’s our natural tendency…
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sarah: …to find meaning. I mean, think of conspiracy theories like we try to find meaning in desperate facts. And this goes back to…
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sarah: …our…
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sarah: …core. Human animals…
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sarah: …backgrounds. You know, this is how we probably survived on the African belt. Right? We needed to understand the signal. So…
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sarah: …when I hear the word hallucination…
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sarah: …I also get a little bit concerned that we’re anthropomorphizing these systems.
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sarah: And I think maybe a better word would be error and answer. And in using the word hallucination, we’re about, we’re evoking…
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sarah: …spirituality, creativity…
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sarah: …ideas and words that are very close to human souls. And again, I want to take a step back and say, this is a machine, people.
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…It’s an error.
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sarah: And so, I just kind of went on that tirade because of your mentioning intention. But…
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sarah: …I think, harnessing…
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sarah: …our human intention to complete tasks, to work together with each other. you know, to build companies and…
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…support customers…
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sarah: …we can use these tools to do that. But I want to push back on hallucinations and perhaps information as output…
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sarah: And then…
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sarah: Yeah, sorry, Alex, please. No need to apologize. Quite the contrary, Sarah. I am always looking for a good reason to weave the word anthropomorphize into a conversation, and I’m glad that you took it.
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Alex Olesen: Well, it’s interesting, right? Like it’s really interesting how we do this. And…
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sarah: …it’s not like it’s not a bad thing. It’s a natural thing. And this is why we…
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Sarah: …you know, this is how we relate to our pets. I mean, you know, this is like…
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sarah: …you know. I’ll fight you if you don’t think my cat totally understands…this is a totally human behavior, but…
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sarah : …it’s something that…
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sarah:…has a…
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sarah: …a core part of who we are, and there’s a reason that it’s in the fabric of our humanity. but…
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sarah: …it also…
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sarah: …in this case confers trust…
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…and trust, is something that should be earned…
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sarah: …and I like the fact…
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sarah: …that you know…
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…as you said, a lot of people are saying, Oh, chat with you! Is it bad for education? Chat GPT has gotten a lot of folks who had not previously played with AI playing with AI. It’s lowered the barrier to entry…
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sarah: …in this space.
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…There’s a ton of things that I had to learn in school that are now, you know, solved problems.
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sarah: You know the ensemble learning of the past is completely out the window. It’s great that I understand what’s going on. But if the tools are out there, there’s great documentation. There’s a great open-source community. Then we have a lot of people entering this workspace…
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sarah: …who are going to be because some of these current iterations are so fun, they’re sticky. They’re good products, as you and I in the Bay Area would say.
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sarah: But as you also mentioned, that means…
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sarah: …that’s in conflict with the macroeconomic trend…
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sarah: …of letting people go in a lot of mid-size companies, even the larger companies. And I think that there’s…
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sarah: …an essence of…
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sarah: …a lot of mid-size companies that have AI teams are taking a step back and saying we were going to build this internally. And now we can buy this. And so, we don’t need some of these internal people…
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…and…
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sarah: …I think…
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…that if you look at…
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sarah: …the current strategic ecosystem…
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sarah: …strategically, this is exactly what Open AI and some of these companies want to do…
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sarah: …they’re looking for customers and…
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sarah: …to some degree the price point has been so low for people that it’s really lowered the barrier in that dimension as well. It’s an accessible price point to learn these technologies, and then, when you’re playing with them at home. You bring them into the workspace and say, Hey, I’ve got some great ways that we can automate…
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sarah: …some workflows. But more broadly, if you look at it you know these macroeconomic trends…
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Sarah: ..the open AI lost 54 million dollars, and it has a hundred employees.
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sarah: The…
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sarah: …technologies that we’ve been talking about are extremely extremely compute, intensive, which means…
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sarah: …they’re probably 2 companies who are making money out of LLMs right now. One is Nvidia and the other is whatever power company they were…
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sarah: …accessing to run these scrapes of the web.
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Alex Olesen: Sarah, I want to touch on a theme we have alluded to throughout the episode…
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Alex Olesen: …and that is the theme of trust…
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Alex Olesen: …as these companies…
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Alex Olesen: …be them, large enterprises, start-ups, even providers in this space. As these companies embark on their journey…
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Alex Olesen: to either build LMS or incorporate Generative AI…
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Alex Olesen: …into their go-to market, how can companies earn the trust of their consumer base…
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Alex Olesen: …and use this technology in a way that will not feel invasive or not feel like it is infringing on the privacy or the rights of the consumer?
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Great question. I think that this is going to be…
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sarah: …you know, I do want to give respect to Open AI for creating a great product because…
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sarah: …LLMs have been around vectorized…
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sarah: …data…
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…word embeddings have been around, but they created a front end. That was it.
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sarah: It’s a great experience and…
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sarah: …I think that in general, trust, in a way that they can parlay into building a…
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sarah: …partner and a customer business that will have some really big, impressive names. What does that mean? You know, when the rubber hits the road for everyone else.
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sarah: When you come into…
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sarah: …a situation where you’re trying to win a sale from…
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sarah: …a customer, I think it’s really important to say…
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sarah: How can I define my company? And what do I have that makes my company unique? And in most cases this question, before November 30th, 2022 would be, I have a relationship…
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sarah: …and I am with this customer. I have relationships with customers like this customer, and I have a long standing…
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…data set…
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sarah: …that includes…
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sarah: …well documented metadata of these relationships. Okay? So, maybe that was a computer scientist describing an enterprise customer engagement. But I think that that fundamentally has not changed. If you came into a…
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sarah: …space where you are providing a service, and you have…
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sarah: …a great customer field. And because of that ongoing engagement over years, you have a ton of data that reflects your customers…
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sarah: Then you are going to be in a great situation…
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sarah: …in the large language model realm…
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sarah: Why? Because you’ve already gained the trust, and you’ve already created great results for your customers. And now you’re just laying a technical…
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sarah: …technology on top of that, a technical layer that says we can…
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sarah: …optimize this past data even more, we can surface new insights. We can respond to your questions in a more naturalistic way. And we can have deeper…
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sarah: …information discovery from our pre-existing information. Using some of these, vector-based approaches. Right? So, when you think about trust, I don’t think about someone who’s coming to the market tomorrow with, I can solve X, y, and Z with large language models or Chat GPT, for…
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sarah: …you know, road cleaning, whatever it may be. But I do think that trust is about relationships, and from a technical perspective, it’s about data. And if you can leverage that data…
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sarah: …to create naturalistic experiences for your existing customers, you’re going to make them happy. And you’re going to gain more data is key and data is what…
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sarah: …is really amplified. The large language model scene. So, I think a lot of companies need to understand that their data is gold.
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sarah: At Orange, we take our customer engagement extremely seriously. We are customer-centric. Our concern is great customer experience. And we know that we’re sitting on a gold mine of data. We know past preferences….
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sarah: …and now we have a tool that allows us to personalize and create even better experiences, you know. And that’s why we’re amplifying that trust.
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Alex Olesen: Fantastic. Well, Sarah, I know we’ve covered a lot of ground today, and thank you for all of the insight. I have one final question now that we’re on the topic of Orange and the projects that you’re working on.
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Alex Olesen: What’s on your plate right now or in your pipeline excites you the most that you’re working on?
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sarah: Thank you. Because…
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sarah: …I’ve been talking a lot about generative, and…
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sarah: …I hope this is as articulate as needed. But the thing that excites me the most is working on…
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…low resource language projects. We have a lot of customers…
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sarah: …in our West African. Well…
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sarah: …okay, let me start at the beginning. Hi, my name is Sarah, and I’m really interested in low-resource language projects. This is why I joined Orange five years ago.
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Oranges in a particularly well-suited position to support…
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sarah: …our customers in numerous areas. We have a bank, we have a video game company. We’ve entertainment streaming services. We lay Internet cable. We have satellites, you know. What don’t we do? Well…
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sarah: …we…
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sarah: …are focused on providing great customer experiences to everyone…
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sarah: …and many of our customers are in places that have underserved languages…
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sarah: …So, orange is in French Africa. But a lot of people in these regions no longer speak French, it’s not considered…
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…a necessary language as much as new trends in…
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sarah: …in political and community…
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sarah: …economics spring up, you know, there’s the ability to buy and sell products locally…
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sarah: …and with that local focus, a lot of people have been returning to local languages that are spoken..
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sarah: …or comparatively underserved. And so what does that mean? It means that with the shifting dynamics of these areas as well as other, you know, macroeconomic forces, we have a lot of customers who do not speak French…
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sarah: …or would prefer not to speak French…
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sarah:…now.
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sarah: I describe to the uninitiated low-resource languages as languages where there’s no Reddit, although in the past week that illusion is less powerful. But…
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sarah: …it means that there’s not a lot of data online. So, I am very passionate about selling people products in whatever language they would like, and providing goods and services and whatever language they would like. So recently, I ran a machine translation competition between French and Bombara. That was text-based. We had…
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sarah: …20 participants cash prizes. The winners are from all over the globe, and well…
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sarah: …only a couple of the participants actually spoke Bambara. Almost all of the participants in the competition spoke, or had family members who spoke a different low-resource language. And…
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sarah: …this was a really impressive experience, because it reminded us that no matter how much the large language model hype cycle…
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sarah: …you know, brings us cool, sticky…
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sarah: …products and…
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sarah: …crazy new applications, and really, and you know, the Pope and a puffer coat, whatever it may be. I think it’s really important to remember that…
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sarah: …natural language processing is not a solved domain. And there are a lot of challenges out there for the global population that are not English-centric or not French-centric…
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sarah: …and I’m hoping that you know when we were working on this last iteration of the translation project.
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sarah: Everyone was saying, Okay, large language models have dropped. How relevant are they for this domain? And then our next step is to experiment with that and figure out how can you…
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sarah: … .augment large language models for languages that are basically small language models and you know, have their own orthographic challenges.
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sarah: And at the end of the day, it’s really about customer service and people. So, I think it’s been a really great experience. And I’ve met a lot of really interesting people…
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sarah: …and I trust that that will continue to be a great way to leverage new technologies…
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sarah: …with a global…
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sarah: …economy and global engagement. But I do want to reiterate that…
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sarah: …LLMs have not solved AI. We there’s probably going to be a plateau right now, where…
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sarah: Open AI has not been mentioned. They don’t have plans to release a GPT…
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sarah: …different, than you know the LLMs.
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sarah: Models are out there, and there’s been a lot of optimization around…
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sarah: …how to compute and run these models on smaller and smaller memory devices. And so I would watch to see what Apple is up to because I think they’re going to. They’re going to jump on the scene with a pretty interesting privacy…
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sarah: …oriented solution as is their brand.
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sarah: But I’m really excited about the power of communication and the power of speaking to people in their own language. So, watch the space for more machine translation…
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sarah: …and low resource language innovations…
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Well, thank you, Sarah, and you know this has been a fascinating discussion, one which I think the audience is really going to appreciate, not only for the…
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Alex Olesen: …information and insight that you’ve provided, but I think also a very…
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Alex Olesen: …actionable, optimistic, and pragmatic point of view. Again, for the listeners, this was Sarah Luger.
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Alex Olesen: Sarah, thank you very much for joining. I really enjoyed our conversation and I’m looking forward to the next one.
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sarah: Thank you, Alex. It was a pleasure.
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