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Ep 102: Future of Work – What’s Next For Creative Orgs?

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  • 15 Sep, 2023
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Overview

In today’s rapidly evolving business landscape, organizations are constantly looking for innovative ways to stay ahead of the competition and drive growth. One technology that has gained significant attention is generative AI, with its potential to augment and supplement creativity. In a recent episode of the Everyday AI podcast, host Jordan Wilson explored the implications of generative AI for the future of work, particularly in creative organizations. Let’s delve into some key takeaways from the discussion and explore how businesses of all sizes can leverage generative AI to thrive in the evolving digital era.

Understanding Generative AI’s Impact

Generative AI, although not new, is experiencing a surge in popularity as advancements enable its widespread adoption. The podcast highlighted that consumers are at the early stages of experiencing the transformative power of generative AI. It’s essential for business owners and decision-makers to recognize this paradigm shift and proactively explore how it can shape their organizations.

Adopting Generative AI for Competitive Advantage:

To effectively leverage generative AI, businesses must first grasp its potential applications within their industry. It starts with understanding the “why” behind implementing this technology. Companies can deploy generative AI to enhance customer experiences, streamline operations, and drive innovation.

For instance, using generative AI in customer service can automate responses, analyze sentiment, and personalize interactions, leading to more satisfied customers. Similarly, creative organizations can harness generative AI to automate repetitive tasks like content creation, freeing up their creative teams to focus on higher-level strategic activities. This not only increases efficiency but also enables companies to deliver more customized and engaging content to their audience.

Preparing for the Generative AI Revolution:

While giants like Salesforce and Google are heavily investing in generative AI, it is crucial for businesses of all sizes to adapt and prepare for this revolution. Here are a few essential steps:

1. Stay Informed: Regularly keep abreast of the latest developments and trends in generative AI. Subscribe to industry newsletters, follow thought leaders, and participate in webinars or podcasts like Everyday AI to gain insights into its potential impact on your industry.

2. Identify Use Cases: Explore how generative AI can be implemented in different aspects of your business. Start by identifying areas where automation, optimization, or personalization can bring significant benefits. Consider how generative AI can streamline processes, enhance customer interactions, or drive innovation.

3. Collaborate with Experts: Engage with knowledgeable consultants or AI experts who can guide you through the implementation process. Leverage their expertise to understand the specific needs and potential risks associated with generative AI adoption in your organization.

4. Continual Learning and Upskilling: Invest in upskilling your workforce to work effectively with generative AI. This could involve training employees on new tools and technologies, fostering a culture of learning and experimentation, and fostering a strong digital mindset across your organization.

Conclusion:

Generative AI is poised to reshape the future of work, particularly in creative organizations. While it may seem daunting for businesses to keep up with the advancements in this technology, embracing generative AI offers immense opportunities for growth and innovation. By understanding its potential applications and taking proactive steps towards adoption, businesses of all sizes can stay ahead of the curve and reap the benefits of this transformative technology. The future belongs to those who are willing to embrace the power of generative AI to drive their companies forward.

Topics Covered in This Episode

– Introduction to Camilo La Cruz, chief innovation officer for Sparks and Honey
– Overview of Sparks and Honey’s mission and methods
– Integration of generative AI in consumer mindset
– Future of work with AI
– Is AI more creative than humans?
– Considerations for companies looking to adopt generative AI
– Importance of understanding the “why” in integrating AI technology

Podcast Transcript

Jordan Wilson [00:00:17]:

What’s next in the future of work, especially for creative organizations? You know, when we talk about generative AI and how it can really augment and supplement creativity, what does that mean for the rest of us? That’s one of the things that we’re going to be talking about today on Everyday AI. Welcome. My name is Jordan Wilson. I’m your host, and we do this every single weekday, Monday through Friday, bringing you experts and everyday people on the best ways that you can learn AI, but how you can also leverage it to help grow your company and to grow your career.

So if it’s your first time listening, welcome and thank you. If you’re a regular, it’s great to have you back. As a reminder, this is a live stream and a podcast. So if you are joining us live, please get your questions in. What do you want to know about the future of work and creative organizations? We have a great guest who’s going to be joining us here in just a minute.

Daily AI news

But before we do, we always recap what’s going on in the world of AI news. So let’s do that real quick. All right, so is ChatGPT and the GPT for tech going to be dethroned soon? All right, so a recent report says Google is nearing the release of its highly anticipated new AI offering, Gemini. So, Gemini is Google’s next large language model and it is reportedly five times stronger than GPT four. So keep your eyes on that. It was supposed to be released fall, and apparently, it’s the fall already. My brain is still in summer mode. So keep an eye out on Gemini and what that means. And also make sure you go to your Everydayai.com and sign up for the newsletter. We always recap all of these news pieces in the newsletter. 

All right, second piece of news, salesforce is putting its money where its mouth is for generative AI. Wow. So they are planning to hire at least 3300 employees with a heavy focus on generative AI solutions, specifically its own AI model called Einstein Studio. So, Salesforce is also planning to rehire a lot of the former employees that they laid off in January. I think it was around 8000 employees.

All right. And last but not least, there’s even more AI coming for your Amazon shopping carts. So, we reported this a couple of weeks ago when it was announced, but Amazon has started to now officially release some new AI powered features where essentially you can use AI to write your product description. All right, so they’ve announced having AI to help you sort through reviews, a lot of different, even their own kind of ChatGPT that you can better make purchases with. So now helping on the seller side as well. So we have that and a whole lot more in today’s newsletter. So as a reminder, make sure to go to your Everyday.com and sign up for that. All right?

About Camilo La Cruz and sparks & honey

But we’re here to talk the future of work and creative organizations, and I’m excited for it, so please help me. Welcome to the Everyday AI show. Camilo La Cruz. He is the chief innovation officer for Sparks and Honey. Thank you for joining us.

Camilo La Cruz [00:03:29]:

Thank you very much. It’s a pleasure to be here. And happy 100 oh, my God. This week, right? Or was it very recently? Right? Yeah.

Jordan Wilson [00:03:38]:

Thank you. Yeah, we hit 100 episodes, I think, on Wednesday. So, yeah, it’s been wild. And we’ve talked to people from all walks of life. But, Camilla, tell us a little bit about Sparks and Honey and what you all do there.

Camilo La Cruz [00:03:54]:

Yeah, absolutely. We are a strategic foresight and innovation consultancy. We’re still a very young organization, I would say started about 1011 years ago. And really, the mission is to help organizations in both the public and private sector to understand change and really see how the change that we experience in our everyday lives has an impact on the people they serve, right? Whether it’s their employees, the consumers, or customers, citizens. So really help them quantify what’s changing, name it, identify it, and then formulate strategies, whether it’s developing new products or a new marketing campaign or adjusting strategy and messaging or perhaps even imagining the role of their company in the next decade or so. Right. So that’s sort of the mission of the company. When we started, we realized we needed a few ingredients to make this happen, right. One is we need to be connected to a network of super smart people. We built an advisory board. Today, 70 strong are people who are really interdisciplinary thinkers in many, many different areas. We also built a cultural intelligence platform that essentially is aiming to categorize change in culture and quantify it. Right. We call it Q, and it’s been up and running for a while. At some point, we decided to take that platform and turn it into a SaaS business. So the company, if you think about our business model, is half is consultancy and the other half is hands on keyboard access to our platform.

Consumer mindset is changing with AI

Jordan Wilson [00:06:09]:

There’s a lot to digest there. But one thing Camila, I really want to talk about, so even when we think of the future of work and you know, one thing that y’all are trying to do at Sparks and Honey is to quantify what’s changing and to help companies adjust to the strategy and messaging. How does the introduction and I use that term loosely because Generative AI has definitely been around for a very long time, but it seems like it’s really just starting to infiltrate our daily lives. In your experience, how has Generative AI already started to kind of shape and shift consumers mindsets and then what can companies do to kind of prepare for that?

Camilo La Cruz [00:06:56]:

Yeah, absolutely. So, look, I would say that from a consumer standpoint, we’re at the very, very beginnings of what’s going to be massive change. So it’s a gray moment to ask a question. We have advised clients who are releasing or launching new features powered by generative AI. And in the go to market strategy, there’s always the question of what it’s in consumers’minds, right. And if you are in the industry, like, if you’re a professional working in the space and following generative AI, you’re going to see there’s a lot of philosophical dialogue even now in Congress this week, right, about the existential risks of AI and all that. But if you’re a consumer, your views on AI are going to be contextual, right? So they’re context dependent, meaning if you present it in the context of a use case. So I’m going to use, I don’t know, Instacart plugin to be able to more easily sync my shopping list with my lifestyle. Then it’s like, oh, my God. Yes. Give me more. Right? So I think if you’re a CEO, you’re looking at different data points. You’re looking, on one hand, at this very high level, sort of philosophical perspective, and on the other hand, you’re looking at more promising and demand type customer data or consumer data. That I would say is perhaps sort of a good starting point if you want to understand where things are going, which in my view, is accelerating pretty fast.

Using generative AI to connect with customers

Jordan Wilson [00:08:56]:

Yeah, I’d say that is a fair statement. Like, fairly fast. Right? And, hey, as a reminder, everyone joining us. Thank you, Jackie. Wishing everyone good morning. Mike Harvey talking about Gemini, brian saying good morning from the Gulf Coast. As a reminder, if you have a question for Camillo about the future of work in the creative industry or just anything, make sure to get your questions in. You know, speaking of that, speaking of how fast things are changing, because it seems like almost every week there’s something big going on in the world of generative AI. How do you think companies can even keep up trying to use these different AI tools and systems? We talked at the top of the show. Salesforce is really investing heavily in generative AI. Yesterday we talked about EY, major consulting firm building their own large language models. How can companies even prepare for this if they aren’t some of the biggest companies in the world? How can they still take advantage of what generative AI has to offer, but still stay in good contact and in good communication with their consumers or with.

Camilo La Cruz [00:10:14]:

Their yeah, yeah, that’s an excellent question. And very common these days, right? And I would say step one is you have to understand the why, right? I mean, why would you bring generative AI technology? Why would you create generative AI driven features or products and release them out into the wild? Right? And I think in that sense, when you’re thinking about specifically the future of work and what you would do inside your organization, there are a lot of really good answers to why you would do it. I mean, there’s productivity. There’s simply the fact that this is a train that’s already leaving the station. If you don’t jump on that train, it’s going to be really hard for you to catch up to what everybody else is doing. But there’s also, I think, the question that’s a bit more human that relates to how can you enrich the experience of the people you serve, including the people who work in your organization? Right? And that is a question that I think has a lot of different answers when it comes to using generative AI. And there’s a lot of really good examples out there in the world where people are starting to think about, okay, how do I think about this concept of an AI companion or an AI agent and put it in the service of students? Like when you look at, for example, what Kan Academy is doing with Canmigo, for example, if you’re watching and you’re not familiar, there’s a ton of different podcasts that are covering can migo and you can go check it out. I mean, they’re essentially flipping a little bit the equation when it comes to learning, right? They’re saying rather than seeing jazzive AI as a threat, right, I need to catch students who are using ChatGPT. I’m going to use large language models to actually engage in a Socratic discussion with the student. Right. And I think that there’s a lot to learn about what they’re doing that we can apply to the world of.

How smaller companies keep up with AI monetization

Jordan Wilson [00:12:39]:

It’S. It’s it’s very interesting to instead of following up on that I actually want to talk about here. Jackie has a great question or a thought, but I’d like to get your take on this. So she’s saying, I wonder, as generative AI tools monetize, so will the largest corporations have the edge because they’re able to afford all of the tools and the ability to create their own? So what’s your take on that? And then what can all the other companies that not like salesforce, not like EY, if you can’t kind of create your own generative AI tools, maybe, how can you still keep up and even.

Camilo La Cruz [00:13:18]:

Look? That’s a great question, by the way, right? I mean, if you look at history of media and technology, you see that there’s always this dance between decentralization and centralization, right? I mean, radio, you look at some of the first accounts of radio when it was introduced as a technology, they read like the internet in the 90s, right? It’s like, oh, everybody’s going to have the power to communicate and create their own communities. And then it was centralized and a few players sort of reap all the benefits. The Internet was the same thing. It was decentralized and then it became sort of centralized in Wall Gardens. I think we had a lot of discussion about Web Three last year and the decentralization and the power that’s still sort of more in the background when it comes to generative AI, right? Now, this is the moment, if you are a small guy, if you are a small business, to really take advantage of this decentralization stage. Right. I can’t predict how fast it’s going to go back and centralized. There’s a lot of different unicorns that are being minted seemingly every month in the space. So there are really large companies behind all of it and they’re connecting the dots really fast. But if you’re playing with ChatGPT and now you can, through the premium version, get a plugin that connects it to the internet, now you have a really powerful capability at your fingertips, right. So I would say this is the moment where you’re going to try to do everything in your power to create a competitive advantage for yourself using these very powerful tools.

What does the future of work look like?

Jordan Wilson [00:15:04]:

Yeah. And there are so many competitive advantages to be had. And I’m actually glad you even talked about connecting generative AI to the internet, because we did a whole episode on that yesterday. But I do want to talk a little bit and sometimes we look into the future, but what do you think the future of work looks like? You kind of mentioned this thought of AI agents or AI companions. Is that kind of where you see the future of work going? That we’re all going to have a suite of generative AI tools built around kind of our daily role? Or where do you see this going?

Camilo La Cruz [00:15:45]:

I think that’s a fair extrapolation in terms of if you look at where the money is being spent right now, if you look at the last year, Q 2022, q Two 2023, the vast majority of capital going into generative AI is going into AI assistants and AI companions. You combine those two and that’s way more than half of all the dollars. Right. So there’s definitely a lot of appetite from an industry to be able to move fast in that space. We’ve also seen a lot of good indications that these large language models are not just mastering language, which is so already impressive, but they’re even communicating with a level of empathy that becomes really interesting. There’s a paper that came out a few months ago that was comparing the responses of ChatGPT four. It was a blind study versus responses from a reddit medical community. And the responses of Cha GPT Four were ranked by the participants in that study as higher in empathy and and many other directions, which is very counterintuitive. Right. But I think that when you look at the power of a personalized experience that stays with you, whether it’s education or work, I feel like that is definitely a space where I think we all need to pay a lot of attention right now. There’s also I don’t know if you’ve seen Kaifu’s AI 2047 book. I’m sure if you have your geeking out on it, it’s Kaifu and Stan Lee, who’s a very well known writer in science fiction writing in China. And they’re looking at different scenarios of AI in 2047, so out in the future. And one of them is based on education, and it’s in this idea of agents, right. I said AI. 2040 says 2041. This was published in 2021.

Jordan Wilson [00:18:10]:

That’s the old one there. Okay.

Camilo La Cruz [00:18:12]:

They were looking at 20 years in the future. The eight chapter is a short story written by the science fiction writer. And then on the back, there’s Kaifu, who’s one of the biggest thinkers in AI. Out in the world, explaining the technology that would make it happen. Right. And this idea of AI companions has been widely explored in that book. I think it makes sense. I mean, when you start a new job, what’s the first thing that happens? Right. You get a bunch of different people putting a bunch of different meetings in your calendar for, like, two or three weeks. You’re not really very productive, and you’re learning. Right. That experience could happen the minute you join the company with a tool that’s also understanding you as a person. Right. Your learning style, your role, who you interact with, what makes other people in your circumstances more successful. So it definitely has a ton of potential.

Can AI be as creative as humans?

Jordan Wilson [00:19:18]:

As we look into the future. Yeah. 2041, I think there’s so many different ways that this can go, but I think one thing that people always look back to, or a common roadblock or obstacle, is they say, okay, generative AI can’t be empathetic. And then, Camilo, you just referenced some different studies that have looked at generative AI’s ability to be empathetic, but there’s also been similar studies on the creative side. So two of the biggest things is people say generative AI can’t be empathetic or creative. So working in the creative space, what’s your thoughts on that? Do you have any hot takes? Can generative AI be as creative as humans?

Camilo La Cruz [00:20:07]:

Well, I would look at an example in chess, right. And there’s, I think, a crop of writers and thinkers that are investigating this idea of intelligence, right. So the eye in AI. Right. Which I think it’s very important for us to sort of think deeply in this world where now we’re creating a type of intelligence. James Brittle is one of them. He wrote a book called Ways of Being Recommended to Everyone, and then he wrote a piece and an article on the We Transfer magazine that was looking at the example of center chess. Are you familiar with center chess?

Jordan Wilson [00:20:58]:

Oh, no, I haven’t seen that.

Camilo La Cruz [00:21:01]:

AI today can beat, like, Go players, which it was thought to be impossible. Right. Because it requires intuition. So it can do that. It can easily beat any human on chess. Right. Pretty easily, right? But a human and an AI partnering can beat any AI playing chess, right? And so there’s this sort of very geeky, sort of centaur league of chess, if you will, right? And it’s people who play alongside AIS against each other, right. Chess is strategic and creative, and I think that it’s a good analogy, know? Yes, absolutely. I mean, AI can be created. There’s some experiments. Adobe with DreamCraft catcher, like five, six years ago, started experimenting with generative design. There’s a couple of Ted Talks that are if you watch them today, you get goosebumps because this is something that’s been going on for a while, right. And designers are sort of confronting this AI and saying the only way for the AI to actually do its job is if I put my ego in check and if I sort of take a step back, right, and think about my role as differently than what it is. Right. Definitely can be creative. But can it be more creative than a system that seamlessly gives a role to the human in that context? Right? And I think that the answer to that remains to be seen, but I would dare to say no.

How organizations can combine humans with AI

Jordan Wilson [00:22:42]:

That’s a great example that you brought up on because, yeah, we’ve had the AI systems beating the best humans in chess for decades. But when you combine the human and the AI, that is the best, right. There’s no other combination that can win in a game of chess, because this conversation, we’ve gone all over the place, but I want to kind of end on next steps. So they’re hearing you talking. They’re hearing even what you all are working on at Sparks and Honey. So how can they create that combination of humans working with AI? How can organizations start to do that?

Camilo La Cruz [00:23:26]:

Because.

Jordan Wilson [00:23:28]:

It seems like there’s a divide. There’s the companies that got it, and they got it right away. Then there’s companies that are really just struggling. So how can they start to create that unbeatable pairing, that augmented relationship of the brightest humans working with these very powerful generative AI tools?

Camilo La Cruz [00:23:47]:

Yeah, absolutely. So, number one, think about it as a system, right? And you have to design a little bit of the system so the human has a role and the AI has a role. You have to sort of write a job description for the AI and then rewrite the job description for the human. Look at your frameworks, the things that you put out, whether it’s a product or service or whatever it is, and make sure that you understand what inputs are coming from which side and when. You create opportunities to seamlessly sort of collaborate, if you will. So, for example, if you’re creating a type of art direction document and you’re going to give a generative design an opportunity to create, you need to figure out what is that brief. So the prompt, right? And beyond the prompt, like, where is the data. Right? Are you going to use what’s available out there? Are you going to create your own data rooms? Right. We’re using vector databases to create dedicated data rooms, and it tends to outperform just a normal sort of standard large language model. I can talk a little bit about that if that’s important, but I would say know the data, know the inputs, know what each is going to contribute, and create an environment, a sandbox. Right. It could be as easy as a document that’s editable, that has sort of the output of the AI, where the human can go and interact with it. Right. So I think design with intention, think about it as a system and then audit all the different components of the system. Easier said than done, I know, but I know we don’t have a lot of time.

Jordan Wilson [00:25:40]:

No, that’s great because you actually laid it out step by step right there. And I love hey, yeah, maybe it’s because I’m a dork, but I love when people say, start with data. You’ve got to get your data, right?

Using data with Large Language Models

Camilo La Cruz [00:25:52]:

Yeah. Oh, absolutely. Look, I mean, these large language models are very impressive in terms of their abilities, but they have limitation when you go into specific domains. Right. And that’s why if you’re a large corporation, if you’re a small business, you want to definitely connect your ChatGPT to the Internet because the data becomes richer, et cetera. But if you’re a large corporation or a bigger business, you have the opportunity you have the opportunity to use vector databases, for example, to dedicate expert sort of data spaces. Right. And then you have the opportunity to sort of train the responses via the work that you have done over the years, for example. Right. So we at Sparks and Honey, we’ve been doing consulting work for ten years. We can show our own models how a great insight looks like, right? What a prediction, what a forecast looks like. So when we pre engineer a prompt that’s about a forecast, we get an answer that’s strain on our own thing, on our thinking. Right. And that gives you at least a starting point that feels more competitive than if you go with the standard outputs.

Jordan Wilson [00:27:14]:

Yeah. Wow. We took in so much everything from vector databases to creating the best kind of AI human augmented relationship. Talking about the future of created work. Camilo, thank you so much for walking us through this journey. Really appreciate it.

Camilo La Cruz [00:27:33]:

My pleasure. Thank you for the invitation. And here’s to the next 100.

Jordan Wilson [00:27:37]:

Hey. Absolutely. And hey, we talked about a lot, but if you couldn’t keep up, don’t worry, we’re going to be sharing a lot more, a little bit about Sparks and Honey and just going over everything in depth in the newsletter. So even if you’re listening on the podcast and you’re like, this sounded good, I want to know more. Okay, well, make sure to go to youreverydayai.com every single day. We recap the live, stream the podcast in the newsletter. I think it’s fantastic. A lot more in there keeping up with everything that’s going on in the AI world, so make sure you do that. And I have to say this, we have a huge giveaway going today. If you’re struggling to integrate Generative AI into your workplace, you’re going to want to sign up for the newsletter. We’re doing a huge giveaway and it lasts for three days only, helping companies actually put Generative AI to you, so you’re not going to want to miss that. But thank you again, Camilo, and I hope to see everyone back for another episode of Everyday AI. Thanks, y’all.

Camilo La Cruz [00:28:36]:

Thank you very much.

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