The Future of Work: AI-Embrace With a Level of Skepticism, Part 2

UC Berkeley Extension
18 min readJul 24, 2023

Welcome to the Future of Work podcast with UC Berkeley Extension and the EDGE in Tech Initiative at the University of California, focused on expanding diversity and gender equity in tech. EDGE in Tech is part of CITRUS, the center for IT research in the interest of society and the Banatao Institute. UC Berkeley Extension is the continuing education arm of the University of California at Berkeley.

In this episode, we’re taking a look at artificial intelligence and how it is changing the future of work. Last time, we explored how AI was changing education. Now we want to take a look at how AI might change your job and create wholly new jobs. ChatGPT, a generative AI chat bot from OpenAI, and Bard from Google are changing how we see AI’s role in how we do our jobs. From drafting speeches to writing and debugging code, AI can remove some of the grunt work. But as Sam Altman from OpenAI CEO said to Congress, AI is a tool. It’s not a creature. And that AI can help with tasks, but not jobs. So if AI could replace many tasks but could also lead to much better jobs, how should we be thinking about AI in our own careers? What do we need to be wary of? And what should we embrace to leverage the power of AI? To learn more, we turn once again to Ittai Shiu.

Ittai is an instructor at UC Berkeley Extension’s Entrepreneurship program, teaching marketing research, concepts and techniques. He has a background in digital marketing and advertising technology, with 20 years of experience working with interactive agencies and global brands. He is the founder of LaunchPoint, a California-based nonprofit focused on creating paid professional learning opportunities for students from underrepresented communities. Welcome, Ittai.

Ittai Shiu: Hi, Jill. Good to be back.

Jill Finlayson: I want to start off with talking a little bit about LaunchPoint. We touched on it last time just ever so briefly, but I wanted to learn more about how you came to start this nonprofit and what your goals are there.

Ittai Shiu: Yeah, absolutely. So the motivation to start LaunchPoint was the notion that not everyone starts off on equal footing upon graduation. So getting into and graduating a four-year college, it’s a huge accomplishment. But it’s also this inflection point where careers start. Unfortunately, despite talent and hard work and grit, you’ve got these socioeconomic and demographic circumstances that create inequalities that can limit segments of the population.

So internships, in my mind, they’re critical precareer component. Yet, almost 50 percent of internships are unpaid and some students just don’t have the option to work for free. Working for free is kind of a privilege. So we see is a gap starting to open up between students from privileged and marginalized backgrounds. So we’re talking about students with limited to no supplemental income, relying heavily on financial aid, and working where money is the priority, it’s a necessity, and typically, working a job that does not necessarily develop career related skills.

So studies show that these variables have a negative impact on academic performance. So what LaunchPoint does is we identify these students. We provide them with the support and the training, and then match them up with a host company that we’ve worked with to establish a professionally relevant, comprehensive, professional experience that will build out their professional network, that will build out their professional skills, and will set them up with to be on equal footing when they start their careers.

Jill Finlayson: These kind of applied learning experiences are so critical today. And our topic is going to be around how AI is changing the workplace. How do you see your work as transitioning people from what may be a technical education to a professional job, and the expectations of the workplace?

Ittai Shiu: Yeah, it’s interesting because when we vet internship candidates, and this is all relatively new within the past couple months, we will ask, well, what AI tools have they used? Because, one, I’m still learning. I’d like to learn new tips. But two, we’re curious how those who have access to fewer traditional resources are able to innovate and use AI resources, because that’s a fascinating and very practical skill that they can take to any workplace.

Jill Finlayson: So how are they discovering AI tools?

Ittai Shiu: The combination of everything that it can do, from having a comprehensive research assistant, to being able to have an idea and have an instant sounding board so that they can develop that concept, to decoding some complicated figures to forecast an answer based off of incomplete data. These are all things that encourage students to be more ambitious about their visions and potentially some of their own entrepreneurial aspirations.

Jill Finlayson: Yeah. So how do these socioeconomic differences play out in terms of access to AI, or even thinking about AI as a skill they should be acquiring?

Ittai Shiu: This is where I think AI is an equalizer, because as long as you have an internet connection, you have access to these AI tools, and for free or for very cheap, everyone, regardless of circumstance, has access to the same technology, the same knowledge, answers, resources, and the ability to execute on their vision. So a lack of these things is no longer a barrier to them being creative with what they want to achieve.

Jill Finlayson: What kind of on ramps do we need to create? And are you seeing, I would say, generational differences in who’s willing to try and use AI or who’s adopting it?

Ittai Shiu: Not really. Well, I don’t want to say that. I think there’s anxiety on both sides. I think it’s easy to see the scary side of AI. It seems the initial reaction to this realization that businesses can do more with less immediately means that jobs are going away. And these sentiments are certainly amplified in news and social media. I think there was a Pew Research study that found that the majority of news articles about AI had a negative tone. And let’s face it, every movie or TV show featuring AI that I’ve seen always results in bad things happening to humans.

But in trying to stay optimistic here, let’s consider that statement of doing more with less with a more optimistic lens. And in my interaction with students in my research, I found that college students are very optimistic about what AI means. I mean, there’s certainly acknowledgment that AI represents a fundamental shift in the future of work. But in my research, less than 10% of students have very strong concerns about its negative impact on job opportunities. 47% believe AI is actually the key to pursuing their own career objectives. So I thought that was really interesting and optimistic of that generation to come back with.

Now, with regards to students transitioning from academics to career, AI has the potential to play this amazing pivotal role that changes everything. It’s a force multiplier. And you brought up earlier, an equalizer. In terms of the different generations, I can’t talk about young professionals without talking about me being a young professional.

I started my career in digital marketing, crunching numbers, just working with Excel and pivot tables, and hacking and cursing my way through SQL. And basically, what I was doing, I was pulling data from multiple platforms and campaigns and bringing it together, so that I could report on it and I could analyze it. And there were days where it was 80% of my job. But it was a great way to understand how all the data works together and how to find and extract insights. And from there, I developed the ability to see a story in the data, to tell a story in the data, to make optimizations that improve my results, to propose new things, new tactics, new strategies, and most importantly to grow partnership with my clients, to grow the business through strategic recommendations.

Now, as those skills grew, what was expected of me also increased. I’d eventually start to manage a team of my own. I needed to scale up that team’s, my team’s output, as long as I could see the bigger picture, as long as I could articulate a vision, as long as I could effectively manage my team towards that vision and adapt to changes in the environment.

I think we’re all familiar with that now infamous use case about that Wharton professor, who gave AI 30 minutes to come up with an entire advertising campaign. And the results were astounding. And I think they described it as superhuman. It ended up creating copy, video scripts, images, an entire email marketing campaign. I heard on another podcast an agency executive ballparking the effort as costing like upwards of $8,000 to $10,000 in human resource. First thing I thought was, well, that just invalidated my 20s. That’s all I used to do. But staying optimistic here, for those younger professionals, I mean, it’s an exciting time, because you now have access, again, for free or for very cheap, this force multiplying technology. And that’s going to empower you to accomplish a lot of work. And you no longer need to prove yourself by doing the grunt work or showcasing on your resume, hey, I know Excel. I have the foundation to do the grunt work. You can take your ideas, your vision, your approach, your perspective, your youthful energy, and you can focus it to see the bigger picture and to articulate a vision, like I did with my team, effectively manage resources towards that vision and adapt to changes in the environment.

What you’re doing now is you’re no longer someone to prove that you can do grunt work. You’re no longer someone that achieves through grunt work. What you need to do, what you’re doing now is proving yourself by showcasing that you have the potential to create something big and solve interesting and complicated problems. So that makes this a really exciting time for young professionals. And as we’ve all seen in classrooms and with professionals entering the workforce, they’re most certainly embracing AI. They’re realistic about AI. And they’re being creative about its application.

Jill Finlayson: So what do you mean by force multiplier? What does that mean when it refers to AI?

Ittai Shiu: That’s a term that just kind of stuck with me. I have a volunteer who’s a Marine veteran, who’s retired and is now going back to school. And he’s helping me with some operational projects. And he drops a lot of military terms on me and that one stuck. So force multiplier is a military term. And it’s a factor or multiple factors that enhance, or that multiplies your effort. A force multiplier reduces the amount of effort required to do work or to achieve a goal. And I mean, if as the example with the Wharton professor example, I mean, the goal was to create an advertising campaign-force multipliers, all of these AI tools-that allowed him to create in 30 minutes. Force multiplying capability is now accessible to anyone-anyone in any industry, any walk of life, any community, any economic circumstance, and that’s exciting.

Jill Finlayson: So you had to learn the hard way. You had to churn the numbers. You had to go through the grunt work, as you described. But that gave you a comprehensive understanding of how things worked. If you shortcut that, what are you missing out on? Or are we just skipping over, like you said, the grunt work and allowing people to leverage creativity and solve bigger problems?

Ittai Shiu: Yeah. So, I mean, I definitely see where you’re going with this because I take pride in all of the hard lessons that I learned, getting up to where I am now. And are younger professionals getting off easy by not having to do this? Is AI creating a disservice by not allowing them to travel the same path? And again, staying optimistic here, OK, well, just basically told junior professionals to think big, and to be visionary, and to be adaptive, and a great manager.

But where are they going to learn this? Where are they going to learn these lessons? That’s why I think it’s also a really great opportunity for senior professionals. I mean, the uncertainty around AI isn’t just with the young. There’s plenty of senior professionals who have the same anxiety about jobs going away. But senior professionals like me, like us, we’ve got plenty of experience. We’ve got stories. We’ve got perspective. And we’ve got the wisdom that comes from both accomplishments and failures.

And it doesn’t matter how technical any of us are. AI, unlike any other big technology shift, the learning curve isn’t a barrier. Now, I can’t begin to explain how it works. But it’s easy to teach. It’s easy to play with. It’s an easy concept to understand. You add parameters, you add parameters, guide it, ask questions, get output.

So it means that senior professionals, as long as they’re willing to embrace it and experiment with it, they can be as innovative as anyone else. They can be a value added contributor. They can be their own visionary. And that also gives you something that AI and young professionals can, and that’s the opportunity to be a really valuable mentor. There’s a whole generation of incoming professionals who are going to need you as much as you need them, which means this mentorship and collaboration between generations is more important than ever.

So junior professionals who want to have an impact, they’re going to need to learn how to stay focused, how to manage resources, how to prioritize, how to lead and inspire and make unique mistakes. And you’re going to be able to do that by looking to senior professionals.

Jill Finlayson: It’s interesting. There was an article in The New York Times called “In the Age of AI-Major in Being Human.” And it talks about, how are you creative? How do you create a personal voice? How do you engage with people, create productive meetings? But I liked, in particular, how can you be unpredictable? Because that’s something that AI at this moment is not good at doing. And so as we think about this as a senior manager, there are some skills that they can pass along to junior employees.

But what are their obligations to explore and adopt AI? How do they get their first taste of this? And how do they see the business application? So I’m really putting on my senior exec leader, going, I know this exists out there. Where do they get started in exploring and figuring out its applications?

Ittai Shiu: I came across an interesting term. And she coined the term, I don’t know if she coined the term, but it was called, find a “reverse mentor.” And I thought it was very innovative. Basically, like how do you find a young, like-minded Gen Z professional who could provide you with input and feedback on how you could see your business from the eyes of somebody who was younger? I think that looking to that younger generation to figure out what are some interesting applications is one really great approach.

I also think, don’t discount you as an entrepreneur, as somebody who’s creative, that understands the nuances of the industry that you’re in, and diving in and experimenting with what AI has to offer, tuning into podcasts, listen to talks, and really think about how all of these tools that are coming up everywhere can be a force multiplier for you, and how does that change the direction or the velocity of your business.

Jill Finlayson: I love the focus on experimentation. And really, there’s nothing like getting hands on, and trying things, and seeing what can happen, because by doing that, you can start to ask the bigger questions: How might we use this to increase efficiencies? How might we use this to improve our customer experience? And so until you try it, it just is this foreign object that’s sitting out there and something, perhaps, to be concerned about, but you’re not thinking about it in terms of the advantages.

So if we think about the advantages, there’s a much bigger picture here. There’s sort of the individual company. But there’s also the US as a whole. How do we think AI can help the US become more competitive?

Ittai Shiu: Well, so first off, I think globally there’s going to be a surge in entrepreneurship. Previous point we went over was about how access to knowledge and expertise is no longer a barrier to entry. And a successful venture will come down to creativity, vision, or resourcefulness, force of will, the ability to effectively leverage AI tools. And this applies to anyone with an internet connection. So that’s really exciting for the global economy, for folks from underserved communities.

But as this applies to the US, the US remains the most entrepreneurial country in the world. I mean, that’s our competitive advantage, our ability to take risks in the face of failure, to find innovation in the face of new technologies, and positive effect AI is going to have on global entrepreneurship, entrepreneurship in underserved communities, that is going to be amplified in terms of the competitiveness of the United States.

Jill Finlayson: I’m a huge fan of entrepreneurship. I think it just teaches great problem-solving skills, full stop, whether you go on to be an entrepreneur or not. But I do have to put the glass half empty question out there, which is, Silicon Valley is known for moving fast and breaking things. And if we move fast and break things with AI, we’re going to cause damage at immense scale. So what is our job then as a country to put some guardrails in place? What do you think needs to happen to ensure that AI is used for good and not for evil?

Ittai Shiu: I think I did make that point earlier about unique mistakes, making sure that we have learned from our past lessons and mistakes, and making sure that we keep those in focus. I also think that wherever in the US the innovation comes from, is that we innovate and we learn fast, and we’re not afraid to fail and learn and really create the standard by which AI can be used for good. I think there’s healthy discussion around the concerns of AI, everything from biases and inaccuracies. I think that that is being discussed nice and early on. We talked all about this in the last segment with education and academics. I do appreciate the conversation is out there in the open.

So it’s not a surprise when bias inaccuracy is a concern when it comes to how it’s applied in business. Also, the generation of false and misleading information, I think we’re unfortunately very used to that and have a, I don’t know if there is a healthy level of skepticism, but there is enough skepticism for us to ensure that we’re not taking everything at face value, and that we are practicing just through the content that we see on the news and social media. Kind of do our own fact checking, whether it’s on social media or it’s something generated from AI, or it’s an entrepreneur that’s blazing ahead.

So I think we’re starting to see, the fact that there are these conversations early on means that guardrails around ethics, and responsibility, and accuracy means that we’re starting to lead the way in what is acceptable usage of AI. And I think because this conversation is out in the open, continue to talk about it. And it’s not going to disappear as we get so enamored by all of the things that AI can do.

Jill Finlayson: So as we bring this back to the folks who are listening to this podcast, and they’re thinking about ChatGPT. How might they use this in their daily jobs? Are there certain jobs that are finding more uses for this?

Ittai Shiu: Any repetitive job should be under the microscope. Anything that requires you to do things multiple times, even the feeling that something is inefficient is already like a red flag that we should take a look at how AI can automate that. I do think that any type of job that requires a lot of data and analytics in order to support a decision, I think that will be enhanced simply because AI’s ability to forecast, collect data, collate data from different sources, and extract insights become more commonplace. So I would like to believe in a world where decisions-smart decisions, smart, educated decisions-are made faster, which increases the velocity of business.

I’ve always had a problem with automated chat customer support. And I’m excited that that experience is going to be more human-friendly, and even problem-solving, maybe even like therapeutic, who knows? But the list can go on. I mean, anything that requires predictive maintenance or risk management. All of these early warning signs can be brought to light through the collection of multiple data sources, timing, I mean, all these other variables through AI.

So basically, I don’t think there’s any job that AI will not touch. I do know that it’s a slippery slope between, will it make the job better or will it take the job over, leaving a human out of a job? I mean, that’s a very real concern. But it’s all towards the goal of improving the experience for the customer. I mean, it certainly does mean increased profitability. But hopefully, that also means reinvestment into other activities that enhance communities and creates other jobs, so that we try and focus on the value creation and the job creation that AI makes possible.

Jill Finlayson: You talk about it takes a human to interpret results. You get data, but then somebody has to act upon it. What is really the role of humans as AI takes more of the redundant work out?

Ittai Shiu: Yeah, I mean, there’s always going to need to be some human element, whether it is a matter of empathy of required to make the right decision or engage with another human in a certain way, whether a response has the right context to be appropriate. I think, actually, we ended our planning session with that conversation around whether or not AI could do this podcast. My takeaway from that-actually I thought it was a great question because, absolutely, right now, AI can plenty of things to produce the podcast. Eventually, it can synthesize your voice, Jill, so that you could be replaced. But the goal of this podcast is to create something that is compelling, that’s interesting, that your audience will resonate with.

Now, while AI can produce all of those components, and in the future spit out a fully baked podcast. But if it’s able to accomplish that goal, I think it’s because it was lucky. I think in order to do that, considering current events and what’s going on with people, and to do that with intention, that’s only something that, Jill, you and your human team can do.

Jill Finalyson: Having a vision, a goal, an objective. Increasingly, we will see AI, but somebody has to direct the machine, right. Somebody has to give it insights to guide the direction that it’s going. It’s sad to hear that I might be going away, but always good to hear that technology is growing, right, that its capability is growing and allowing us to be better, more thoughtful. And I myself have used ChatGPT to ask queries, just to broaden how I think about ideas, and to get other perspectives, and to think about things in a more thoughtful and robust way.

So as you’re thinking about people who are mid-career, or soon to graduate as they’re going out into the world, what are your last words of advice for both education and work now, on thinking about how AI could fit into their career journey?

Ittai Shiu: Yeah. It is to continue to think big. It is to, it sounds cliche, to follow your dreams. And that may sound a little bit cheesy, but you know what, take some time. What is your goal? What is your vision? What do you want out of life, in your career? Is it to start a business? Is it to start a nonprofit? Is it to develop your skills so that you become an expert at something?

Whatever it is, the one takeaway that I want to make sure listeners take away from my thoughts is that AI is not the silver bullet. It won’t solve, like I mean, global warming. But it will remove barriers. It will remove barriers so that anyone, all walks of life, are able to learn, ask questions, plan, execute, and really empower themselves to go for and achieve their vision.

I myself actually had always wanted to start a nonprofit, and life got in the way. I was busy. And interestingly enough, I leaned on AI for everything from writing assistance to finance and accounting. And it really removed a lot of those barriers so that it actually became a lot easier than I thought to kick off and launch a nonprofit that seems to be doing pretty well right now.

Jill Finlayson: I love that. So AI as a tool to unleash potential, to allow people to lead and follow their curiosity. And, at the end of the day, find out that these things that they want to do are actually easier and demystified and possible. And so using AI to open those doors is a hugely exciting path. And as long as we’re taking care as we do it, I’m very excited about the future. Thank you, Ittai.

Ittai Shiu: Yeah, my pleasure. Thanks so much, Jill.

Jill Finlayson: And with that, I hope you enjoyed this latest in a long series of podcasts that we’ll be sending your way every month. Please share with friends and colleagues who may be interested in taking this future of work journey with us. And make sure to check out extension.berkeley.edu to find a variety of courses to help you thrive in this new working landscape. And to see what’s coming up at EDGE in Tech, go ahead and visit edge.berkeley.edu.

Thanks so much for listening, and I’ll be back next month to continue our discussion on the future of work. Until next time.

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UC Berkeley Extension

UC Berkeley Extension is the continuing education branch of the University of California, Berkeley. We empower learners to meet educational and career goals.