Podcast by InnovatorsBox®

Dear Workplace: Season 3

Sensemaking AI – 1: Where to Start

Dear Workplace – a Podcast by InnovatorsBox®. Hosted by Monica H. Kang.

Reimagine how you thrive at work through conversations that matter. Hosted by workplace creativity expert Monica H. Kang, we’ll study the latest trends, changes, and challenges to untangle workplace people problems. We’ll talk with executives, innovators, and experts and visit different industries around the world so that you get first dibs into the changing workforce. 

Guest: ANNE T. GRIFFIN

Founder & Principal Product Lead at Griffin Product and Growth

Anne is an emerging tech product leader and coach, and subject matter expert in AI, blockchain, tech ethics, and inclusivity, with a decade of experience in customer-focused product management for tech startups and giants like Priceline. She has collaborated with Microsoft, Comcast, and Mercedes-Benz. Anne offers "products for emerging tech" including coaching and lectures at top North American universities, including Columbia and West Point. She excels in linking technology with human experiences to forge innovative products. Outside work, Anne enjoys learning, traveling, beach time, fitness, and cooking exceptional ribs.

Guest: andrew ngui

Senior Advisor, City of Kansas City

Andrew Ngui is a strategic systems builder focused on enhancing collaboration and inclusivity among individuals and organizations. Renowned as an innovation catalyst, he has successfully fostered human-centered movements that drive innovation and bridge divides within complex ecosystems. Andrew's work spans government, startups, academia, and industry, contributing to the prosperity of cities and regions globally. His approach centers on simplifying complexity through effective systems and processes, leading to significant, worldwide program successes.

In this episode, we kick off our series with two special guests: Anne T. Griffin from New York and Andrew Ngui from Kansas City. Together, they share insights on how AI is shaping our world and discuss strategies for navigating its complexities. 

This episode covers a discussion about AI, its implications, and how to navigate the rapidly changing landscape. It includes insights from both experts on the importance of understanding AI as a tool, managing data privacy concerns, up-skilling for leaders, and being curious in exploring AI applications. The conversation also touches on common misconceptions about AI’s abilities versus human intelligence, legal issues surrounding copyright, and data use by AI platforms. 

Whether you’re a seasoned AI expert or just starting to explore the field, this episode is for you.

Join us as we uncover the latest trends, debunk misconceptions, and learn how AI is transforming industries and communities. 

Sensemaking AI: Where to Start

2 Videos

Episode Shownotes

1. Episode Title: Sensemaking AI – 1: Where to Start

 
2. Host: Monica H. Kang, Founder and CEO of InnovatorsBox
 

3. Episode Description: AI is everywhere, but how much do you know? I’ll be honest. I’m still making sense of it, and today’s guests are here to say it’s ok! For the next few weeks, as we make sense of AI and the changes in AI, we will be speaking with leaders who are building careers and companies in AI. And today’s guests are a special start as we kick off the series. Meet Anne T. Griffin in New York and Andrew Ngui in Kansas City, who are on a mission to democratize AI and technology. So whether you’ve been doing AI for a long time or just getting started, you’re at the right place. Welcome to Dear Workplace.


4. Guests:

      Anne T. Griffin, Founder & Principal Product Lead at Griffin Product and Growth

      Andrew Ngui, Senior Advisor, City of Kansas City

5. Key Topics Covered:

  1. Introduction to AI: Exploring the basics of artificial intelligence and its widespread applications.
  2. Misconceptions about AI: Addressing common misunderstandings about the capabilities of AI, including its ability to think like humans.
  3. Data Privacy and Copyright Concerns: Discussing the implications of AI on data privacy, copyright issues, and protecting original creative work.
  4. AI as a Tool vs. Master: Understanding the balance between leveraging AI as a tool for efficiency and being cautious of its potential risks and limitations.
  5. Skills for the AI Age: Highlighting the importance of developing critical thinking, sense-making, and data literacy skills in the context of AI.
  6. Optimism about AI: Expressing optimism about the future of AI while advocating for awareness and informed decision-making.
  7. Continuous Learning and Exploration: Encouraging curiosity and ongoing exploration of AI opportunities and advancements.
  8.  

6. Highlights

  • Anne T. Griffin shared insights into the transformative potential of AI in various industries, emphasizing the importance of leveraging AI for social good.
  • Andrew Ngui discussed the practical applications of AI in transforming cities and improving public services, highlighting the role of AI as a tool for efficiency and collaboration.
  • Both guests addressed misconceptions about AI, emphasizing the distinction between AI’s computational modeling capabilities and human thought processes.
  • Concerns about data privacy and copyright issues were raised, prompting discussions on the need for proactive measures to protect personal information and original creative content.
  • The conversation underscored the importance of viewing AI as a tool rather than a master, advocating for informed decision-making and awareness of potential risks.
  • Skills such as sense-making, critical thinking, and data literacy were identified as essential for navigating the complexities of AI and its implications.
  • Despite challenges, optimism about the future of AI was expressed, with an emphasis on embracing AI as an experimental playground for innovation and learning.

7. Quotes from the guests:

     Anne T. Griffin:

    1. “AI is really about putting humanity into a better state.”
    2. “There’s a bit of a misconception that AI is some sort of magic wand that you can wave and fix everything.”
    3. “When we talk about the future of AI, it’s really about collective good. It’s about how can we use this tool to help everyone.”

     Andrew Ngui:

    1. “AI is a good tool to an extent, but depending on how you use it or depending on the permissions that you allow, it could be a very bad master.”
    2. “Everyone needs to be curious…start with your areas of passion, your areas of interest, areas of focus.”
    3. “In the age of AI, the response that AI generates is, for the most part, black and white. There’s very little gray area.”

8. Resources Mentioned:

  • Various AI platforms and technologies discussed by Andrew Ngui, including OpenAI’s GPT, Anthropics’ Claude, Google’s BARD, and others.
  • The concept of AI poisoning was mentioned as a potential solution to protect digital content from AI-generated replicas.
  • Monica H. Kang encouraged listeners to explore AI opportunities and advancements with an open mind, emphasizing the importance of curiosity and continuous learning

9. Contact Information:


10. Closing Thoughts by Monica Kang:

Monica Kang emphasized feeling more prepared and less overwhelmed after hearing from Anne and Andrew. She highlighted the importance of starting from where one is currently in their understanding of AI and remaining curious and inquisitive about its developments in the future.


11. Episode Length and Release Date:

Episode Length: Approximately 54 minutes
Release Date: March 7, 2024


00:00

Monica H. Kang
AI, artificial intelligence, machine learning. I feel like we’ve heard these three words and more from all different industries all year and all this time, but what does that really mean and how do we prepare ourselves for it? So for the next few weeks, I’m excited to explore what is really going on in AI. What are the beneath in AI, and what can we do if we are not so really sure how to grow or upskill ourselves in AI? We don’t want to be losing track. So I’m excited to welcome you to how we’re going to sense, make, and understand AI for the next few weeks. You’re listening to dear workplace by innovators box. I’m your host, Monica Kang, and I’m excited to have you here today. As we kickstart, I wanted to invite two friends to talk about this to get started. 


00:56

Monica H. Kang
First, my friend Anne, who’s going to share what it means to really make sense of AI. She’s the right person because Anna is a product manager with twelve plus years of experience helping startups and Fortune 500 companies rethink AI, blockchain and tech ethics. As a daughter of a chemist and an electrical engineer, she grew up immersed in sciences. Her passion for products and people led her to tech. As a product leader, she built her career in Microsoft, Comcast, Mercedes Benz and Priceland. In her dedication to democratize AI learning, she stakes frequently on AI and blockchain and teaches the AI week of blockchain, cryptocurrency and more at pre college programs at Columbia University in New York City and in many other places. 


01:52

Monica H. Kang
So all in all, if we want to make sense of product management, AI, blockchain, or tech ethics, she is the right person to ask. So I invited Anne to share a little more how do we make sense of AI and where to even start? How to learn. 


02:11

Monica H. Kang
Welcome to dear workplace. I’m so excited to have my friend anti Griffin back in the show. She was our guest previously in season one, season two, and ready to dive into deeper conversation on all about AI. You’ve been very busy since we last caught up. You’ve been now continuing to really make AI, blockchain and all of that more accessible, relatable. So I guess before we dive in, take us a step back. How do we even make sense of this AI? It’s just been everywhere suddenly and feels like it’s going really fast. 


02:46

Anne T. Griffin
I would say it is going really fast, but I think it’s one of those things where we’re just at a moment where the technology can now support a lot of the things that we’re really interested in, and that’s one of the things about emerging technologies, is that they seem like they’re so far off for so long. For example, AI was something where it’s kind of gone through its own winters. It had gone through cycles where people didn’t want to fund it. And part of the things were, hey, this is really cool, but I can’t really use this to help tag my friends on a social media site. I can’t really use it to help me write articles for my newsletter. 


03:23

Anne T. Griffin
And now we’re at this place where the technology can support things like large language models, which is, that’s specifically the type of model that is Chachi PT is based on. And people are so impressed. And I think what has really changed is that we now have AI that people can anthropomorphize in a large word a lot more. Because even when it doesn’t write maybe as well as you would if you were writing an article, because you know exactly kind of what you want to write, what you want to say, it’s still very impressive that if you didn’t really know better and you weren’t really paying attention, you’re like, hey, if I got this response or someone handed this in, I’d be like, okay, yeah, like a human wrote this. 


04:05

Anne T. Griffin
And I think that’s the impressive part because before a lot of this was, hey, I’m going to recommend you this Amazon shoe that’s going to follow you around for the rest of your life. And now it’s, oh, wow, wait. It can actually make recommendations, it can write requirements documents and it makes people really excited. 


04:23

Monica H. Kang
Those are really great examples and very resonating thinking about how many of our relationship with AI has changed in the past few years on the macro scale, tell me, what are the things that you are most worried about and most excited about where AI trend is heading? 


04:38

Anne T. Griffin
Yeah, I think where I am concerned about is people using AI in ways where I would say you could do this, but there are a lot of privacy concerns because there’s a lot of things, especially with these type of gpts like these large language models, where, because it seems so human, you have this ability for people to maybe trust them. One of the things that is coming up now, and not all these are even based on large language models are these ais that are kind of like dating AI companions. And I actually talked about this with Rolling Stone back in May where people trust these AI companions to say things to it because they are pretending to be in a relationship with this virtual companion that they maybe wouldn’t tell anybody else. 


05:29

Anne T. Griffin
And what happens when all of that information gets put in one place and you realize how bad the dating apps are with selling data? What happens when your AI companion sells your deepest secrets, where you might tell them, oh, I’m going out for surgery for this, or I’m that, and who was able to buy or sell that data? So things like that where I’m concerned about the privacy and you’re even seeing in Chat GPT, sometimes people actually having their resume with their email phone number found via very simple prompting. So if you know what you’re doing, you’re able to do that. And obviously over time, there will be some of these privacy concerns that are addressed that are kind of more of a bug than a feature. 


06:13

Anne T. Griffin
But in terms of data is just as valuable as ever, especially as these language models do need a ton of data to train on. So it does raise the question of the buying and selling of data. That’s still going to be a thing. And as these machines become more integrated into things that we trust, what happens there. And so those are the things that keep me up at night about where AI is going, but there’s also so much to be excited about as well. 


06:41

Monica H. Kang
Tell me a little bit more of the things you are excited about as well. 


06:45

Anne T. Griffin
One of the things I’m most excited about where things are right now is where it’s giving me the freedom to focus more on the things that are like high leverage and really matter. As a product professional, one of the big things about my job is strategy, but there’s a lot of other tasks that need to happen, like we need to write requirements, documents. We need to be able to maybe say like, hey, we’re going to work with engineering to improve a process, and those are all very important things. But if we aren’t really doing a lot of the work on the strategy, then that’s going to be an issue. You always want to make sure that you have a strategy behind what you’re going to build, what you’re going to invest resources in, what you’re going to invest time in. 


07:26

Anne T. Griffin
And I think leveraging AI in the right ways can help you, whether it’s like helping you figure out how do I best decide what is the research path to help me build my strategy. Can I do an outline for the strategy document? Not like figuring out what the strategy is going to be, but save me time in terms of how do I effectively communicate my strategy and then other things. But it’s always like this balance again of making sure you don’t put proprietary information into, like, a GPT. But I like the ways in which it does free up time, especially if when I was running a coaching business a couple of years ago, one of the things is they were like, okay, a really important part of marketing is your newsletter. 


08:06

Anne T. Griffin
And sometimes at the end of the day, I would be exhausted and I would get to writing my newsletter and I would just be like, my brain is completely blank because I used all my brain cells for my day job for everything else. And I think, oh, wow, now I could use Chachi PT and say like, hey, give me ideas, give me inspiration. I wouldn’t necessarily trust it to write a full article. There’s still a lot that I would probably end up editing with how I am. But those are the kind of things where it’s like, how do you have it help you with your creativity, and how do you also take your time back in more meaningful ways? 


08:39

Monica H. Kang
I love that. Such a powerful example that using it really as a tool to ignite you, but being careful of not necessarily just doing that copy and paste and submitting that wherever it’s heading. Tell me also, what are some common misconceptions you’re seeing about AI from the public that you are also worried about? 


08:56

Anne T. Griffin
One of the things that some people don’t really understand is they think that where we are now is that we have some sort of general artificial intelligence. That is not the case. We’re not to that point. So sometimes people overestimate everything that AI can do, and we’ve seen that especially a lot with copywriters. Yes, there’s things where I’m like, maybe I’d be like, I’m tired. At the end of the day, I don’t really want to hire a copywriter for my side business. So maybe some of those people are going to have maybe less work. But in terms of like, hey, this person has a day job. In the beginning, when Chachi Bt first started getting popular, some of my copywriter friends said like, hey, I’m having people at work saying like, oh, we don’t need this person to write this. 


09:40

Anne T. Griffin
We can have Chachi Bt write it. And for how specific their industry was and their specific industry knowledge and understanding the audience, it was just something where it’s like a chachi Bt might get you so far, but for the type of business that you are in, I would be very reluctant to just say, yes, Chat GPT can just feel free to go do it. And the other thing that concerns me about it is a lot of people are actually not very good writers and don’t read a lot. To really also have the discernment of what good writing is and what bad writing is. And so you can have someone who’s like, great, I don’t need that copywriter in my business. I’m going to use Chachi PT. 


10:20

Anne T. Griffin
And then it’s like, okay, how is that working out in terms of your conversion rates, your open rates? What is that really doing to your funnel? Whether it’s your marketing funnel, your ecommerce funnel, and those are all things where you can refine them. But at the end of the day, we’re really not at a place where those are 100% replaceable. But people have that misconception and then sometimes try to. And then there have been scenarios where people actually were hired back because they realize, oh, wait, even with Chetchy BT, I have no idea what I’m doing. 


10:51

Monica H. Kang
It makes me think of the scene how, as you pointed out, we thought were losing some of these jobs. But actually, no, we need them even more because they actually know and can vet the information from chat GBD because they actually know what they’re doing. But you raised also a really big macro question, which is ethics and trust and copyrights. We’ve kind of already seen a swing of different conversations. New York Times suing OpenAI authors and creatives, saying that’s not fair. There’s like publishing and copyrights all over the place. So are there new questions and trends we should be on the lookout for? Because I feel like we’re just opening the Pandora box now. 


11:27

Anne T. Griffin
Absolutely. And this has been discussion. You mentioned the New York Times article where I think Chachipt or OpenAI offered as low as like $1 million for a copyright license, which is in the scale of money today. I mean, I wish I had a million dollars, but I just mean the scale of corporation money, that’s like a $20 bill for a corporation. Right? And so that’s a thing where I think this year especially, we’re going to be seeing a lot more conversations around copyright and where that specifically goes. And I think this is ultimately going to be a bit of a battle ultimately with the different parties, like the different organizations and Capitol Hill. And it’s going to be kind of who can out lobby who, because we really do need independent journalism that is well done, that has human editors. 


12:25

Anne T. Griffin
And we are also seeing this rise of misinformation and disinformation, especially around elections. We’re in an election year and think about like if you just had Chachi Pt as is, be your editor in the middle of an election year, mind you, it’s learned from the Internet. So it’s also learned from all the misinformation and disinformation, but not necessarily in a way that was designed to train it, how to identify it and avoid it. So we really do need that. So it’s like we don’t want this to be another thing that chips away at their business. They’ve been struggling for the last like ten to 20 years. And I think it’s going to be this thing of we’re going to probably see in the next few years what this means for the future of media journalism. 


13:07

Anne T. Griffin
And even thinking about when we get to a place where the technology can support this even for video better. I mean, it does video now, but imagine it can do the whole show pretty accurately. We’re not there yet, but just thinking about this is so important. And also, I want touch on what this means for the actors. Right. They were at this tentative agreement. For those of you who aren’t aware, the actors have been on strike since I think, the spring or summer the writers were on strike. They reached an agreement. But one of the major sticking points in terms of the actors and their union is actually not being scanned to be used as AI in perpetuity. So you can’t just use your image and likeness forever and ever. And that’s been a big sticking point. 


13:52

Anne T. Griffin
And even this tentative deal still has things in there. And it also brings questions like, to the art of acting and what does that really mean? And I think it’s like if some of these professions lose that battle, I don’t think it’s going to go away completely, but you’re going to see a shrinking, and I think this year we’re going to see a lot more of that in the news, in conversation, and a lot more people saying, like, hey, I don’t care if all the actors are fake, but also you’re going to see things of people who are like, no, I feel very strongly about this. 


14:30

Monica H. Kang
Well, I’m sure, especially when that comes to their own jobs, they will not say that answer very much. And speaking of which, I’m curious. We’ve already seen a wave of new jobs, new skills needed as technology has been integrated even more and more throughout our times and works and everything and changing how we work with AI, I’m feeling like there’s going to be even more new jobs and different types of skills that we’re going to need in talents, whether they are directly in AI or any work they do. So I’m curious what you’re seeing and how hence leaders and innovators can upskill themselves or maybe freshen up their resume in a different way because there’s going to be new jobs out in the market. 


15:07

Anne T. Griffin
Yeah. So I think it’s really interesting because there are going to be new jobs, but where they are and what they are might be very different. So it may not be, hey, there’s lots of new jobs in Netflix. I know Netflix for a while very famously went viral on social media for hiring a very well paid, prompt engineer. And I think that was probably them trying to really push the limits of generative AI and what their business is, which, if you understand how Netflix put blockbuster out of business, you really need to think about how that type of company, and it’s a really mature company, it’s not really new anymore. It is in my head. 


15:49

Anne T. Griffin
But I’m like, so much time has actually passed that they really need to figure out how they can disrupt this industry, especially when it is very crowded and the prices for streaming are expensive and people are figuring out who should I cut the cord with or who should I stop streaming with? And so where I’m seeing the types of jobs where people are talking about this is like, self driving cars. Maybe, like, taxi drivers might need less of those. If we have some sort of critical mass of self driving cars on the road, we’re not quite there yet. Obviously, there’s a lot in the news around certain automakers with autopilot for some really bad accidents that have happened. And obviously, we don’t want people getting harmed or hurt. Those are people’s families, loved ones. 


16:32

Anne T. Griffin
But there might be like, hey, who is actually monitoring that? The fleets are doing what they’re saying they’re going to do. It’s great to have all these fail safes in place, but there should really be a human intervention to be able to say, that car seems like it’s doing something funny. I should stop it. So instead of, like, an Uber driver, where you’re like, hey, the uber driver is taking me someplace, it doesn’t seem like it should. What if the self driving car starts taking you someplace? 


16:56

Monica H. Kang
It should. 


16:56

Anne T. Griffin
It’s maybe, like, a different intention, but it’s also still very scary if you’re the one in the car. And I’m like, is the car hacked? Is somebody, let’s think about even, like, very dark, but, like, human trafficking. Could human traffickers start hacking these self driving cars and be like, oh, well, I saw a woman get in. I think I can figure out what vehicle this is by the plate. There’s so many things where we just have to be very thoughtful in terms of things that we don’t have anymore. How do we also have that human intervention? Because even now we have all sorts of AI that’s been used in medical technology for a while to help us better identify tumors, heart problems, those sort of things. But even that is always used in combination with a medical professional. 


17:39

Anne T. Griffin
So it’s not just like, oh, great, the AI said you need open heart surgery. Here we go. It’s really like, okay, great. A medical professional is going to look at as well and be able to say, like, actually, I don’t think that’s anything we’re going to check back in this amount of time. And so I think about that for the future of what are the things where it’s going to look very different. It might not be a job that exists today, but it is something we really need to find. Where are the other places where we’re really going to be thoughtful in terms of the human intervention? 


18:10

Monica H. Kang
And I’m hearing almost because of the scenarios that you shared, we have to be probably even smarter and wiser to distinguish, hey, this information is incorrect versus just taking everything as is. Do you think maybe that could be a good thing? Like, it’s going to push us to say, you need to actually make sure you really cross check all the information and not just rely simply what’s been provided? 


18:32

Anne T. Griffin
I think that is one of the dangers, though, because I think a lot of people don’t read one of my favorite April Fool’s jokes, and I actually don’t care for April Fool’s jokes, but I think this one is really well done. Every year on April Fool’s, NPR posts an article on social media that says less people are reading. That’s the headline. If you open the article, it actually talks about how people actually don’t click into links to read. You just get a bunch of people replying directly under it, talking about how people don’t read books and all this other stuff. And just like, yes, that is also a problem. You maybe have less people reading books, but the article is actually about how social media people don’t vet stuff. 


19:11

Anne T. Griffin
They just read the headline, don’t read the article, and they jump to conclusions and then actually start posting about it. And especially with generative AI other things, we’re going to start seeing how much easier it is for people to create this content that has misinformation disinformation. And it is going to be more important than ever. But even if you look at Twitter today, you see a lot of misinformation and disinformation that is spread around and not really fact checked. You’ll see another article a week later that’s like, hey, there was a lot of misinformation last week about that topic, but you’d be hard pressed to even figure out what was the misinformation disinformation. And did this article get to the people who were spreading it accidentally? 


19:56

Anne T. Griffin
Honestly, I think figuring out what is the truth on the Internet is going to be like a really big battleground, and we’ve already seen that even before this kind of current wave, even with things like QAnon, where you can really get people to believe a lot of very interesting and dangerous things. 


20:17

Monica H. Kang
So how can leaders better prepare themselves to fight and face these situations? I feel like part of the other challenges, there’s just so much information about AI, so many new terms, so many things to keep track of, and I think just even making sense of it feels overwhelming. But to your point, if we are not being cautious and thoughtful, especially as leaders, we’re creating multitude of negative consequences. So what advice do you have for leaders out there? It’s like, okay, and I really want to do a good job. Where is my one one? Where do I start? What am I supposed to do in my routine? 


20:51

Anne T. Griffin
Yeah, I think for leaders, step one is definitely educating yourself, taking classes. It doesn’t even have to be like you specifically. Learn to code if you are more technically inclined. It doesn’t hurt to better understand how these systems are built or what they’re built on, but even just better understanding. What is an LLM? How does Chat GPT work? How does the Amazon recommendation system work? How does Netflix’s recommendation system work? How does a self driving car use all these different types of AI to work? And then I think step two is really, some corporations are already doing this, like Amazon. Amazon has an AI ready program where their goal is actually to train millions of people on AI. And I think people are just like, oh, well, it’s like the Internet. You’re just going to use it. 


21:36

Anne T. Griffin
And then one day, bam, everyone’s going to have used it. But one of the things is people did take computer classes even before the Internet. It was just to learn, how do you type on a computer? How do you use Microsoft Word? And that was like a thing where it’s like putting Microsoft Word used to be a thing you put on your resume. And now it’s like, well, okay, if you’re putting on your resume, I’m kind of questioning, do you not have enough other skills that we need to use this filler content? Right. One of the things about AI, though, is we’re in that early stage where maybe more people have access to it, but a lot of people don’t understand where the privacy risks are. You don’t want somebody putting your corporation in danger by putting proprietary information. 


22:13

Anne T. Griffin
Maybe they don’t understand what proprietary information is or how someone would get a hold of it. Or maybe you could actually ten x certain roles in your organization. How can you actually up the game of all your developers, no matter how good they are, from your best one all the way to the ones that need a bit more growth? Like, are there copilots out there that are a really good fit? So there’s a lot for you, I think, to actually train. And even though it might seem obvious, because we’ve all been using computers, we’ve all been even using AI without even realizing it, even when we just click, yes, that’s me in the Facebook photo. It’s something where there’s just so much going on in the future and it’s developing so quickly. 


22:52

Anne T. Griffin
And I think that’s really where people need to think along the lines of, if I were a futurist, what would I want to prepare this organization for? 


23:07

Monica H. Kang
So important. Tell me a little bit more about diversity and tech as well, because as everything and all of this is happening, that is also becoming a concern of how do we make sure everyone has equal access, because it’s still not true. 


23:21

Anne T. Griffin
Yeah, I think one of the things that is an issue is that since 2020, we’ve obviously seen that technology gap, and I don’t think it’s closed. It was really just more obvious because all of a sudden everyone was on Zoom school, and not everyone had high speed Internet. I live in New York City, and they had a bunch of students who they said just disappeared. They didn’t show up in Zoom classes. They don’t know if they left New York City. They don’t know what exactly happened to them. And maybe they all did return to class when classes resumed in person. Maybe they just moved away. But we also don’t know who kind of actually fell out of the system. And when you think about these people just never showed up online. 


24:06

Anne T. Griffin
And some of that may be other circumstances, but some of it may have been they didn’t have Internet access. And when you think about all of our AI is really dependent on having that Internet access, you realize how big that gap is. And you even think about the students where their parents can afford a GPT subscription or, hey, don’t cheat, but leverage GPT to help you write your outlines. How is that kid doing in school compared to the kid who’s having to do it all on their own, all from scratch, who doesn’t have those type of resources? And so I think we’re going to continue to see that gap widen, and I think it’s going to be really important. 


24:42

Anne T. Griffin
There’s been all these efforts of diversity in tech, and obviously with the economy the way it is, people have been, oh, maybe that’s less important to me and funding it less. But I really think now more than ever, the organizations who are committed to it, whether they’re nonprofits or like corporations themselves, even within the government, AI is already at this tipping point. What other technologies are out there? Again, thinking more like, I think this is going to be my thing for this year, is like thinking like a futurist. What other technologies are out there that people are like, oh, I’m not really worried about it. That seems so far away that we really need to make sure that there are diverse voices and learners and leaders in that space. 


25:25

Anne T. Griffin
And I think one of the people I’ve seen do really amazing work, actually no relation, Janae Griffin. She’s been doing a lot to actually try to help increase diversity in space tech. And I’m like, I don’t know a lot about space tech. I think it’s really fascinating. But we’re starting to see more and more companies get into space tech. And you even see Jeff Bezos. He built Amazon and then what does he do? He starts a space tech company, even with some of these other billionaires. And so how do we think about this? Even AI today? Yes, we need to help people catch up there, but how do we get ahead of what else is going on in the future? 


26:03

Anne T. Griffin
So you don’t have these people where they’re still struggling just with getting on the Internet, and you have entire communities who are still stuck there versus people where it’s like you can get that high paying job in AI or space tech and your world is just a drastically different place. 


26:21

Monica H. Kang
So, so important on all the multitudes. Taking a step back, if you think about AI, would you say you’re optimistic about the future ahead or pessimistic? 


26:34

Anne T. Griffin
I would say I am balanced. There are things that I think are honestly terrifying and keep me up at night. I also think there are things where, oh, that’ll be really nice. I would say it’s like, oh, it’s trade offs, but not necessarily because some of those other things in, like, I think one of the things that one of the headlines from last year was the Department of Defense considering do we use AI that can make decisions on whether or not it can kill? And that’s one of those things where that opens a lot of questions and that is really scary. And I think people could say, well, okay, well, if other countries are doing that, do you want to be the country that doesn’t have it? 


27:18

Anne T. Griffin
There’s a lot there, but that’s the thing where that type of thing doesn’t make me sleep better at night. But there’s also so many things where if we can use it to, again, free up our time, be able to spend more time with what matters. And in a way that also, there’s a lot, I think, economically we have to assume, right? Or it’s like assuming there are still many well paying jobs, then I’m like, I think that’s really nice where it’s like being able to say, hey, I have bandwidth to actually spend it on what really matters in this life. 


27:53

Monica H. Kang
Very true. We covered a lot of different grounds. Anything that we haven’t covered that you want to leave a last wisdom to our audience about AI and how they learn about AI. 


28:04

Anne T. Griffin
Yeah, I would say you want to learn about AI. I would even just start by watching caveat this, where obviously you want to vet maybe things on the Internet, make sure what you’re reading or watching is legitimate information. But even just starting explain AI to me, like in five videos on YouTube or find articles that are for people who, even if you’re not super technical, find resources that are for people who are maybe less technical. There are some great books out there as well. But I would just say if you’re like, hey, I just want to have a starting point. You don’t have to feel like you have to really understand everything to start. I think the most important thing is that you start from somewhere. 


28:48

Anne T. Griffin
So when you start hearing these things in the media about like, oh, yeah, AI is going to do this, AI is going to do that. You understand what is more realistic and what to question versus what might sound like. People are trying to sell you into this idea because a company wants regulatory support for it. 


29:10

Monica H. Kang
Got to look out for those marketing funnels. That looks very flashy, but maybe not for the right reason. Anne, thank you so much for joining us on today’s show. We absolutely also recommend Anne’s resources. We’ll check base so that way we have those aggregated in the blog that you’ll see later. But Anne, thank you so much for taking moment to join our show and sharing all about AI. 


29:30

Anne T. Griffin
Thank you so much. Thanks for having me. 


29:34

Monica H. Kang
Okay, I’m definitely going to be looking into all the links and resources that Anna shared and so I hope you would too. We’re going to put those in the show notes as I mentioned, so please take a moment to check that out. But in the meantime, you’re probably also wondering, well, geez, I still don’t really necessarily have a job or my work related to AI, so how can I learn how to relate to AI differently? Still as a starting point? It’s a very question that’s been on my mind too, and the reason why it’s great for us to have my next friend, Andrew nuing to speak about this. Andrew is a visionary systems builder and a strategic thinker. 


30:15

Monica H. Kang
As he works in technology, government, community leadership, he has constantly been able to rethink about how we see new ways to bring people and organizations to work better together. As an innovation catalyst, he engineers solutions to champion inclusivity, unity and collaborations across silos and has a proven track record of catalyzing human-centered movements and spur innovation bridge gaps in complex ecosystem. It’s the very reason why I was inspired when I saw his speech in Korea many years ago when were speaking at a leadership conference and hence collaborated often with him throughout the pandemic in how we relate to system thinkings and many different community bridging. No wonder he has worked at MIT before and served different communities now through his city innovation work in Kansas City. 


31:10

Monica H. Kang
So let’s dive in and ask Andrew what he thinks about AI and what we can do as we’re learning about AI. 


31:19

Monica H. Kang
Welcome to dear Workplace by Innovators Box. I’m Monica King and I’m so excited to have my friend Andrew Ngui again on the show. He was a guest in our previous seasons, but today we’re going to dive all in about AI andrew, especially the angle. I’m curious to hear your perspective is because AI is literally everywhere, how do we even make sense of it? You’ve been attending a lot of conferences, and as somebody who’s been always in technology and innovation, what’s honestly been the most fun and effective way to stay in touch with AI and actually learn about AI. 


31:54

Andrew Ngui
Thanks Monica for having me. So everything I shared today is personal and not related to my work. Really the best way to think about it is go according to your areas of interest and then also go according to your areas of focus. 


32:12

Monica H. Kang
That’s so key. So in your areas of interest, what’s on top of mind lately? 


32:17

Andrew Ngui
Yes, there actually is a lot. So in terms of the work that I’m working in transforming cities, there are so many areas that we can start to even think about. The first I would start to think about is all the public facing aspects of work. How can we deliver better services? How can we do a lot of different things to be more efficient? And so that’s really at the start of it. Then we start looking into AI enablement that is not necessarily interacting directly with people. And so then we begin to get into more complex areas. 


32:55

Monica H. Kang
Thank you for breaking that down. I feel like there’s just so much to learn and so many places to start taking a step back. What’s been your relationship with AI in general, and how has these recent events changed or perhaps influenced in how you think about AI differently? 


33:12

Andrew Ngui
Yeah. Thinking back to what I wanted to do when I was sending an MIT short program, I’m actually seeing that come to reality right now. Right. The ability to predict, the ability to tell you about things that you don’t even necessarily have to think about many reminds you in advance. And so I’m living that right now. That’s been, what, ten years ago since I went to that program, but that’s really what I wanted to see happen, and so I’m so excited to be living that. 


33:44

Monica H. Kang
Are there common misconceptions you’re seeing about AI that you are worried about as well? 


33:50

Andrew Ngui
Yeah. And I’ll just touch briefly about the other part. What’s exciting now, generative AI has transformed the landscape of what people think about artificial intelligence. 


34:00

Monica H. Kang
And what does Gen AI mean for you? 


34:03

Andrew Ngui
Absolutely. So let me put it this way, and this was shared with me at an MIT conference a while back, before humans needed to learn how to speak computer. Now computers have learned how to speak human. Right. And so generative AI, you look at the large language models popularized, obviously, by chat, GPT and OpenAI. They’re now able to articulate what is important to us in a language, in a way, in a manner by which we understand and actually even more so derive value from. 


34:48

Monica H. Kang
So what are the misconceptions? You said both things. You implied the exciting things, but also things that you’re worried about. 


34:54

Andrew Ngui
Yeah. So the misconceptions, I would say, are assuming that generative AI knows how to think, but really, it’s not necessarily about thinking, but it’s inference. It’s about computational modeling of what we assume to be learning and what we assume to be intelligence. So I think just because you get something that seems like a response that is somewhat close to a thoughtful or meaningful response by a computer, suddenly we think that, oh, the generative AI model is more human like. 


35:39

Monica H. Kang
Could you share an example? 


35:41

Andrew Ngui
Yeah. So, for example, if I said, and this in my last role, this is what I did, I said, hey, can you GPT, can you generate for me a list of items in terms of how we can improve the startup ecosystem? And it came up with an entire list of all the things that I was actually working on. 


36:02

Monica H. Kang
Wow. 


36:03

Andrew Ngui
Right. And then you suddenly was like, oh. And so then I said, what else? And then it came up with something else. So suddenly there becomes a question of like, well, how is it that a nonliving thing can think about these things, when really the fact of the matter is that the large language model has been trained on so much data that it’s able to infer the most probabilistic response to the question asked. Does that make sense? 


36:42

Monica H. Kang
Yeah. And it kind of brings me to the bigger question on the other side, where we’re now seeing a lot of legal lawsuits on saying, like, okay, we get the big picture that AI relies on big data, but can we aka think about where that starts? Where is this big data coming from? It’s one thing when people are getting excited and putting their information, and of course, a lot of companies are putting regulations and saying, we don’t want to do that. We don’t want to give away our ip in this online black hole that is going to go. Even though it sounds human like, we’ve also seen on the news recently with a lot of both authors and even New York Times suing OpenAI and saying like, hey, you cannot take away our data and information. 


37:22

Monica H. Kang
And so I’m curious what you think of these situations both. Again, the opportunity, but also concerns like, how do we balance that? And I know as a result, the question of what do we really trust? How can we trust AI, and what’s the instinct and how we build that relationship? That’s actually empowering. 


37:39

Andrew Ngui
Yeah. So there are a number of different points that you brought up there. I’ll start with the first one, and the first one is on copyright. So the way I think about this is very simple and perhaps in some way simplistic. If you publish something on the Internet, you should assume that there’s some level of permanence to that. If either a human or a robot can read part of it, you should assume by default that it can and will be used. 


38:12

Andrew Ngui
I’m not going to go into whether all these different lawsuits have merit or not, but at the heart of it is assume that anything you put out on the Internet can and will be used, and it will probably be used in multiple ways, shapes or forms, and in some cases, in ways that we may not necessarily even expect or realize is possible. 


38:37

Monica H. Kang
And I feel that’s scary. There are many components to it, I think, especially for the arts industry, even, like, just how AI generated artwork, illustrators not being paid for their artwork or seeing their art stolen and printed somewhere else, or authors saying that, like, hey, how is the AI able to write about the stories? Because they copy the entire ip of that book. And that feels a little different than simply me writing something on social media that I know it’s going online. 


39:07

Andrew Ngui
Yeah. So you asked the question about intellectual property. How might artists and people in the creative field. Yeah, exactly. So then, actually, that’s an interesting story, because I do have a friend whose work was actually infringed on by another person in a different country, and they did a number of different things to change it, but not necessarily transform that work. And so as a result of that, this friend of mine launched a platform that is dedicated specifically to work that has an original human creator. And of course, we’ve also seen that any sort of AI generated work cannot be copyrighted, at least for now. The other part, just speaking from a creative perspective, has also been the rise of AI poisoning. I don’t know if that’s a term that you’ve actually heard of. 


40:04

Andrew Ngui
So the concept that in an original piece of work, you can actually embed a watermark, a digital watermark that poisons the art piece so that it’s not AI readable. Right? Yeah. Can you do that? 


40:22

Monica H. Kang
That sounds really cool. 


40:23

Andrew Ngui
Absolutely. So you can just look it up. AI poisoning, if that’s the correct term. But actually, I’ve seen that, and I’ve actually shared that with a number of different people to say, hey, these are ways to protect your original content, whether it be a still image, whether it be a video. You know, how in the old days, we would overlay a translucent layer to watermark? So these are all digital watermarks. So if you think about it from that perspective, too, coming back to the point of permanence of information, data, artwork, et cetera, on the Internet, how might we be able to look at the opportunity to protect that? 


41:05

Monica H. Kang
It sounds like there’s going to be now new innovation to think about copyrights and creative rights in a different way. That all being said, I know another component at AI that we had a conversation as people who are learning about AI on the back end and wanting to get more involved is also balancing and remembering that at the end of the day, technology is only as good as the tool and the master. And so tell me a little bit more why that’s on top of your mind and what that means for you. 


41:30

Andrew Ngui
Yeah, absolutely. So let’s start with fire is a good tool, but a very bad master. Fire is a tool you can cook your food, you can keep warm, et cetera. So then I’m going to jump ahead into AI. To the extent that AI is useful as a tool at this time, you want to think about it from that perspective, as a tool that improves, helps you become more efficient in regards to generative AI, as an example, helps you to be more efficient, potentially also be a sounding board in terms of sharing your work in that system and then actually getting feedback in literally seconds. That’s pretty incredible. But at the same time, the flip side to that too is the issue of leveraging your private information as training data. 


42:25

Andrew Ngui
For example, right now, OpenAI’s tool, unless you are accessing it through its API and you’re not in a particular incognito mode, all the information that you share can and will be used for themselves. That’s not necessarily good from your perspective. So that’s what I mean by AI is a good tool to an extent, but depending on how you use it or depending on the permissions that you allow, it could be a very bad master. 


43:01

Monica H. Kang
So how can we manage that? Are there particular settings that we should do? You mentioned about incognito mode. For those who are like listening and learning about this for the first time and realize, wait, all that questions I asked was now available to everyone else, what can we do next time? 


43:18

Andrew Ngui
Yeah, so that’s potentially available or it may be anonymized. We don’t know because it’s beyond our control. And which is really at the heart of the point that I was trying to make. AI being a bad master is because it is outside of your control, because is a black box, because we don’t necessarily understand how it infers the information and comes up with the most probable answer that gives us something that looks like the appropriate answer. Right. And so to your point, and just speaking from the perspective of generative AI for a second, how might we be protecting ourselves? It is to go in with two eyes open and to think about how might I be able to protect my data? 


44:05

Andrew Ngui
So, for example, if you were to sign up with any sort of platform, openais, checkgpt, anthropics, Claude, and even Google’s bard and whatever else out there, or even a combination of all of the above, then we want to be looking at data privacy policies. How is the startup or the business or the platform protecting your data, if at all? And so then you have to weigh the risk, right? Does the value of what you’re trying to do outweigh the risk, the inherent risk of using artificial intelligence? 


44:48

Monica H. Kang
How can leaders then upskill and train themselves? Because of everything that you just talked about for AI world? 


44:56

Andrew Ngui
Yeah, so that’s a great question. So how can leaders, upskill and be in the know? I think the first point I like to make is that everyone needs to be curious. And so this comes back to the first point that I made earlier, which is start with the areas of interest, start with your areas of focus as it relates to the work, to the projects that you’re doing. Can you do it better, faster, quicker? Are there ways and means that technology as a tool, and notice I’m saying technology not necessarily just AI, but is a comprehensive set of tools that can help you in your job, in your work, in your play, in whatever area that you’re focused on. That’s probably the first step. 


45:44

Andrew Ngui
And then you start looking, once you have gained some level of insight, then you start diving deep into the areas that you have found to be useful and helpful, and then look at the components individually, specifically with the data privacy concerns. 


46:03

Monica H. Kang
Thank you so much for breaking that down. As I’m hearing it’s a reminder that there are specific, actionable steps that we can take. We just have to break it down. And I’m curious, like, how do you manage your time and energy? Because another thing is for driven leaders. They’re like, I want to learn everything, but they’re so hard to keep up. So how do you make sense of the patterns but don’t get overwhelmed by the noise? 


46:30

Andrew Ngui
Yeah. So then it’s a question of what is your signal to noise ratio? Right. So do you allow yourself to focus on versus what do you allow yourself to get distracted by? 


46:44

Monica H. Kang
But what if I don’t know? What if I don’t know, because AI feels so foreign and I’m learning about all of this, everything feels like a pattern. How do I figure out? 


46:54

Andrew Ngui
I think really at the heart of it, you have to go back to what are your areas of passion, your areas of interest, areas of focus and to actually be disciplined about it. And so that is probably going to be the hardest part to have to be able to implement self discipline and to practice at self discipline in those areas, because otherwise it could be very broad. 


47:21

Monica H. Kang
Are there also skills that we should be needing more? 


47:25

Andrew Ngui
Oh, yes, absolutely. Skills in the age of artificial intelligence. The core skill that I think you would need in the age of artificial intelligence is sense making. And what does that mean specifically? It means, does this particular thing, or does this particular work make sense? In the age of AI, the response that AI generates is, for the most part, black and white. There’s very little gray area. But then if you look at the work product that humans generate, there is a significantly larger amount of gray area comparative to a generated response, in this case by generative AI. And so that increases a level of subjectivity to interpretation, to some greater level of inference and understanding, and it provides color to a variety of the work that you do and the responses by which you give. 


48:24

Andrew Ngui
And to the further extent, the work product that you create could be a physical or digital product, whatever it is. 


48:34

Monica H. Kang
How has AI saved you time and changed the way how you work currently? 


48:40

Andrew Ngui
I think for me personally, there has been a lot of opportunities to improve upon the level of work that I’ve achieved. Right. You can start at first drafts, but you can also look at getting feedback in the work that you do. For example, just saying generative AI as an example, how might I improve this and make it a world class XYZ, whatever that might be? 


49:14

Monica H. Kang
So, having had this conversation about all the different aspects of AI, would you say you’re an optimist or a pessimist about where AI is heading overall? 


49:23

Andrew Ngui
I think to use a stock market term, I would say I’m very relatively bullish on it. It’s not helpful to close your eyes and pretend that doesn’t exist, right. Even if you’re not using it, you should be aware of it. You should be aware of it because it is all around us. What we call, in so many ways, call artificial intelligence now has existed for a long time. Only now is the term AI becoming more popular. But the stuff that Google is doing and everybody else in the tech world has existed for a very long time. It’s just a rapid increase in the popularity because of the generative AI component that has, I guess, put it in the spotlight. And so I would say, at least be aware of it. 


50:20

Andrew Ngui
At least understand both the pros and cons, understand the concepts behind it, especially for leaders who are concerned. I would say start exploring and then I’ll draw it back to what do children do? The job of a child is to play, because in them playing, they’re learning, they’re failing, they’re growing. And so think about a few years ago, Iot, Internet of things was a big deal. 


50:57

Monica H. Kang
Oh, yes, I remember that. 


50:59

Andrew Ngui
Right. And so then there was a playground of Iot. So now we’re in the age of artificial intelligence. We should think about it as an experimental playground. It’s the same thing. It’s not any different. It’s just a different tool for life for the benefit. And obviously don’t be. 


51:20

Monica H. Kang
That love it. Well, thank you so much, Andrew, for sharing these insights. Any final words of wisdom about AI as leaders are diving into it more? 


51:28

Andrew Ngui
Yeah, final word about artificial intelligence. I’ll just say what Nike says. Just do it. 


51:36

Monica H. Kang
There we go. So folks, just do it. Dive into it. We will continue our conversation with AI. Thank you, Andrew. You’ll get a chance to learn about and how to reach him later in the notes and we’ll see you soon. Again, thank you. 


51:51

Monica H. Kang
Wow. I feel having now heard Anne andrew a little bit more prepared and maybe perhaps not as overwhelmed to know that I can start with where I am today. AI still is maybe perhaps the beginning. And we’re still about to see more and more changes in the next few months and years to come. So it’s probably more important that we remain curious and inquisitive in how we want to show up. Still, you might be wondering, what are the type of jobs and companies people are making with AI? And next week, I’m excited to give you that answer. I’m going to invite a friend who is using AI, perhaps in an industry that you haven’t thought of. Skincare. Tune in next week and you’ll get a chance to learn more what that’s all about. Have a great week and I’ll see you next week. 


52:42

Monica H. Kang
This is your host, Monica Kang at Dear workplace by innovators box. Thanks so much for tuning into today’s episode at Dear workplace, where we untangle your questions about the workplace. I hope you enjoyed today’s conversation. Please send us your questions, feedback suggestions at [email protected] or dearworkplace.com because we want to know how to continue to dive deeper in navigating those questions with you. This show, of course, is possible thanks to the amazing podcast team at InnovatorsBox Studios that I want to do a little shout out. Audio Engineering and producing by Sam Lehmart; Audio Engineering and assistance by Ravi Lad; website and marketing support by Kree Pandey; Graphic Support by Leah Orsini, Christine Aribal; Original Music by InnovatorsBox Studios; and executive producing, directing, writing, researching and hosted by me Monica Kang thank you again for your support. 

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