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Guess Who’s Getting a New Career? How Generative AI Is Reshaping the Workforce
42 Plays1 month ago
In this episode, we explore the evolving impact of generative artificial intelligence (GAI) on the workforce, with a focus on how GAI can affect Asian American professionals. Drawing from recent research, we highlight how tasks requiring human agency—such as interpersonal communication and organizing—are gaining value, while roles centered on data processing and analysis face increasing automation. Tune in for strategies on up-skilling and re-skilling, plus a few alter ego career pivots as we imagine our lives beyond AI.
Link to article about GAI.
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Transcript
Introduction to Generative AI in the Workplace
00:00:09
Speaker
Welcome back to another episode of Hidden in Plain, flat your podcast for all things Asian in the workplace. This is Jenny. I'm Echo. And I'm Jo. So today's topic is going to be on Gen AI or a Generative AI. I think a lot of people probably are familiar with the topic. You've either talked about it at the workplace or heard people talk about it.
00:00:29
Speaker
But before we dive in, we're going to give a little bit of background on the article that we're basing today's discussion on. um
AI's Impact on Jobs and Current Roles
00:00:36
Speaker
So this article came across to me, or I came across this article, because my ah team started to look into some of the impact of AI on our current job, so we can make...
00:00:49
Speaker
appropriate shift to our own workforce. So it's very relevant as a topic as we all thinking about, oh, now everyone using AI, now everyone trying to make the great use of AI.
00:01:03
Speaker
What does it do to us from the job perspective? If you notice the author for this article They were more like a computer scientists. They're not even like social scientists or like or psychologists.
00:01:17
Speaker
However, if you're looking at some of the content or the study they did, they were using like O-Net and they were using a lot of interviews. They were using a lot of focus groups. This is in the way that SIO would do job analysis.
00:01:32
Speaker
And I was like, why we couldn't do this? Anyway, non-story short, i think this is ah some of the interesting topic that we have been talking about for a while in the workplace. What's some of the takeaways we will be talking about in today's session? I think
Preferences for Work Automation and Collaboration
00:01:49
Speaker
that's going to be very much individual, up to individual interpretation.
00:01:53
Speaker
So I welcome that. Yeah. And maybe I can try to attempt to give a brief summary of this. ah Caveat, this is a long, complex study. So we'll link the article to to this in this podcast.
00:02:08
Speaker
ah But, and Echo and Jenny, feel free to chime in as go down this path of it ah but trying to attempt to summarize it. ah
Tasks Requiring Human Agency vs. AI Capabilities
00:02:17
Speaker
For me, what I got from this was this article was trying to get and understanding of the preference of work that needed to be automated, where um regular workers and experts in AI, where they see where AI can help, ah where they can collaborate and where humans can still do some of the work, most of the work, or mostly all the work, depending on what AI can help with.
00:02:44
Speaker
And then I think they were trying to also get a sense of like a demand. So maybe that demand is at the right word, but got a sense of like where the partnership is. And I think they actually created a little scale on that between AI and human agency collaboration.
00:03:01
Speaker
Yeah, thanks for that summary. So one of the things that stood out to me from this study, it's a very, very dense study, and we're not going to go into too much of the details. One of the things that stood out to me was what task is ranked high and what task is ranked low um on human agency.
00:03:19
Speaker
So one of the things that they found was tasks that are more like interpersonal, like teaching and teaching others and organizing, planning and prioritizing work. those were ranked high on the human agency scale, meaning it needs more human touch.
00:03:35
Speaker
But then if you look all the way on the bottom, establishing and maintaining relationships, that's ranked all the way up ah on the bottom. so And i was like, how do I reconcile this? Because I thought establishing and maintaining relationships, that's very interpersonal and that's that would require high touch from humans. What's your take
Interpreting Study on AI and Human Relationships
00:03:53
Speaker
on that? My initial interpretation with that is, i think this is talking about how the human interact with the agents.
00:04:01
Speaker
So in the future, my assumption without like seeing the details of their questionnaire, i think this is probably more describing how they were, what's the need for them to maintain the relationship between the human and the agent in himself.
00:04:19
Speaker
So my takeaway is that's more referring to that relationship building front because as we were all talking to like AI tools, like I rarely care about what the AI thinks about this relationship. I don't care. like i'm not um I know some people even like having like a cyber girlfriend, boyfriend, but I think they care less about how to maintain that relationship versus like a human beings. You care about the others. like You have to make efforts to make that make that work. That's my takeaway.
00:04:51
Speaker
Hmm. Interesting. I was thinking like, you know, in like maintaining relationships, there's like prompts that we we have, like calling each other or saying a message.
00:05:02
Speaker
or sending an email, and maybe it's with an agent, there could be less of that, or the the prompt is assisted by the AI agent itself, but not so much the, maybe the the interpersonal stuff. That's my kind of spin on it when I see it that low. i I'm with you, Jenny, in that I can't see an AI agent just doing that completely all by itself.
00:05:29
Speaker
And now
Shrinking Demand for Data Skills and Job Security
00:05:30
Speaker
I'm looking at their exhibit six, which and they have more of a description of that task itself. It didn't specify like what do they mean by like maintaining the relationship with whom. It just says developing constructive and cooperative working relationships with others and the maintaining them over time.
00:05:52
Speaker
So I could also interpret that's also maintaining a relationship with another person. Yeah. So I guess there's a lot of room for interpretation here.
00:06:03
Speaker
um And I'm curious to get your take on something slightly different, which is one of the three things that they found from the study was that there is a shrinking demand for information processing skills and greater emphasis on interpersonal skills.
00:06:20
Speaker
and high agency skills. And I know, I think these span a lot of different areas, but I wanted to go back to the first one, which is the shrinking demand for information processing skills.
00:06:31
Speaker
You know, when it comes to like data analysis, data interpretation, ah you know, data processing, it's it's an area that a lot of Asian American professionals tend to occupy.
00:06:43
Speaker
You know, we do a lot of data interpretation, analysis, data crunching. And I'm wondering what this means for us, you know, and a lot of people working in STEM who handle a lot of data, you know are our job safe?
00:06:56
Speaker
Parts
AI's Growing Role in Data and Teaching
00:06:57
Speaker
of it? That's a positive take on it. Maybe we can, you know, the parts where we actually analyze data and input data. I mean, i' I'm sure I know that, as you recall, when we did, remember when we did the qualitative study and we actually had to transcribe the the data?
00:07:14
Speaker
I think there's software out there in the last few years that actually does all that. And I think it does all that stuff in real time now, even on a regular call. So hopefully it assists a lot of us who actually know how to use the how to use it but i'm with you in that yeah it takes it it'll take that time away but maybe it allows us to allocate time to do other things within that function but maybe that job doesn't fully go away it's just certain aspects of it is there's less of it less of the data analysis running of the data and maybe interpreting it and more so explaining it and teaching it to others like you mentioned with interpersonal skills
00:07:54
Speaker
I have a slightly different spin on that. um Yeah. ah yeah My prediction with this one is I do think the demand is still there. like As we're using a lot more agents, as we build more AI tools, the desire and the convenience of leveraging those tools to analyze data is going to be even bigger so that you need this many people to build this for you. Like I was thinking, even thinking about like our own process and how to build those agents.
00:08:26
Speaker
You still need people to build those agents so you can repeat that process. So we can get rid of some repeatable tasks in a past and red reduce some of human neighbors there.
00:08:38
Speaker
But before you get there, you'll probably need to employ even more people to do this. But on the in the long run, though, i do think as all those tasks being automated, obviously, like you don't need this many people to do this work anymore.
00:08:54
Speaker
So I do think in the long run, it's going to make some neighbors redundant or or like an unnecessary. So you don't need to employ them.
00:09:06
Speaker
So that's the implication. for us to think about. but I don't think it's going to happen within like a year or two years. How many years ago? I would say
Diversifying Skills in the Age of AI
00:09:16
Speaker
three years.
00:09:23
Speaker
You're saying that the demand for people with AI capabilities, that's going up for sure. But if you're like a data analyst, let's say, or a data scientist whose main job is to just process data, you're not working with AI, you're just processing data, analyzing data, visualizing data, then they're most likely to be at risk.
00:09:41
Speaker
So what's the takeaway for our listeners? Is it to then I'm hearing to not be segmented or pigeonholed into a certain area, but to be more well-rounded in many different areas? Is that what we're taking away?
00:09:55
Speaker
pivot and become an AI specialist. But but realistically, I think, Doug, what you said early on, kind of like i'm I'm resonating with that because you said it's about letting go of some of the the redundant data analysis tasks and maybe stepping into more of a like teaching role or training role and like and helping people interpret that, like understand that.
00:10:15
Speaker
And I think that's where that's so applicable. to us because typically we're not seen as the instructors or the coaches. We're the ones who do the analysis and pass it on to the other folks who do it in front and they get all the credit.
00:10:30
Speaker
So, you know, as as an Asian woman, like i'm I'm thinking like, well, what's the takeaway message for our listeners, for us? Like, how do we make sure that when the AI revolution, I mean, I think it's happening right now, but when it happens, like Asians are not left in the dust. Do
AI's Rapid Impact Compared to Industrial Revolution
00:10:47
Speaker
you really need this many people teach you or some people just go to the AI tool? Hey, can you teach me something? I nearly like saw someone who built a curriculum out of the AI tool and they can nearly teach themselves.
00:11:00
Speaker
Yeah. So isn't that safe then because the AI can do the analysis and then teach it. Echo, why are you so cynical?
00:11:12
Speaker
I'm cynical is because I've seen what's happening right now. And that's, you that's almost like, I can see a future like in three years, if I keep doing what I'm doing now, i might be out out of that. That's what I'm seeing.
00:11:29
Speaker
and So probably also because the firm I'm working with even like Microsoft, some around they're more aggressive in terms of what they want to achieve. yeah But I think this change going to be slower in some of our industry?
00:11:43
Speaker
No, I've read some headlines with, I think, like, organization with the Mag7s actually not hiring um more engineers. Actually, if anything, they're actually letting go of certain engineers because of AI agents being able to do a lot of coding already.
00:11:59
Speaker
So i think I think you're right in that some of this stuff is already here. The question is, where will it be as you know this exponential growth continues to happen with it, where will jobs be in the next few years? And I think for us, like you know there's certain revolutions, the industrial revolution took a while to take place.
00:12:22
Speaker
It feels like the AI revolution is only taking like about four or five years to like uproot certain jobs and responsibilities. And in a way it is, it is kind of scary, but there's a part of me that's also optimistic about what it could actually take away from us. But
AI's Potential Impact on Specialized Fields
00:12:40
Speaker
I go totally hear where you're coming from is that in that, you know, it could replace a lot of the work that we do.
00:12:48
Speaker
I was actually looking into this because I wanted to know like what what percentage of you know STEM is actually Asian or what percentage of like the tech industry. looks like around 36% of computer engineers are or engineering roles are occupied by Asians. So you know we are going to be one of the most affected demographic groups when companies start to um cut down on roles and replace humans with AI.
00:13:14
Speaker
And I'm sort of with you on Echo. i would like to be optimistic, but knowing that everything is monetized and everything is about ROI, I feel like companies are going to be less about, oh, how do we augment and reduce the redundant stuff that you have to do How do we get rid of you? I think that's what most organizations are going to try and do.
00:13:34
Speaker
And that that has me worried because you know that affects my job too. I'm wondering in five years, are they going to need me to do to write grants to data analysis? You do more than data analysis, Jenny. I do think research is one area, which I was surprised that it's not showing on this list. I guess it's probably like a specialized profession or occupation itself. by itself But i was as as was reflecting upon, like during the research, that requires you to organize and planning the work, that requires you to process information, that requires you
Skepticism Towards OpenAI's Profit-Driven Shift
00:14:10
Speaker
to do all those tasks that somehow is not reflected on this list. Then you also see the article saying, hey, the agent actually write this paper and nobody actually be able to recognize it's AI written and it actually got published. I was like, okay, hold on minute. Yeah. what What are we really doing here? So I'll share this with you because and I would love to get your take on this. So Pew Research Center just released something.
00:14:36
Speaker
Actually, it wasn't it's not that recent. It was from two years ago. And it's about like which U.S. workers are more more exposed to AI on their jobs. And guess which demographic group has the highest exposure?
00:14:49
Speaker
oh Oh, is it us? it's us It's us. 24% of Asian jobs are exposed to ai And basically what that could potentially mean is what we're talking about. Like we're the ones who might have our jobs automated away.
00:15:06
Speaker
Hmm. I'm trying not to think about this on a scary Sunday where kind of, if we do this, we do this recording again and, and kind of slowly get back to work as well too. I think there's, I think in my role in my current workplace right now, I definitely use AI like almost every day to help with like,
00:15:25
Speaker
pulling certain things out, like proofreading, of course, is always a thing, but also like getting a sentiment. I think there's things that like Copilot and its integration to like Cell is actually helping out with a lot with like sentiment and analysis.
00:15:39
Speaker
Usually that takes actually ah quite a long time to do by hand, but the fact that it can do it for it like thousands of ah ah lines so quickly. It'll enable me, but I wonder if it will actually take it away from me because I still need to you know derive certain implications from this from this information to other people.
00:16:02
Speaker
The question is, I think, and I'm tying Echo's thoughts into this, is how long will that last with the current speed and the capability of the AI agent right now And where will it be in three years?
00:16:17
Speaker
One second, I'm going to show you this book. Jenny's getting up and getting a ah physical book.
00:16:26
Speaker
Okay, sorry about the interruption. So this book is called The Empire of AI. oh yeah. um And it's written by Karen Howe, who is a journalist who did a profile on OpenAI and Sam Altman, you know, during the early days of OpenAI. And she writes about her experience.
00:16:42
Speaker
And I'm about maybe 25% into the book. And based on what I'm reading, i feel very skeptical about where AI is headed. And so just to give you a little bit of background, OpenAI was supposed to be you know open and transparent, and AI developed by the people for the people for the betterment of society.
00:17:01
Speaker
But gradually it shifted its mission to um to focus on profit and monetization. And so the development of AI has become this race to the top or you know the bottom, depending on how you look at it.
00:17:13
Speaker
And it's completely deviated from its original mission, which was to improve um human capabilities. yeah It's less about augmenting your job and it's more about automating your job.
00:17:24
Speaker
So I'm worried. Didn't Sam
Trust in AI Leaders and Their Visions
00:17:26
Speaker
Altman said he one of the mistakes he regrets now is actually making it open source when I think DeepSeek took open AI's, some of their framework and applied it and made it much more efficient?
00:17:37
Speaker
Yeah, I remember hearing about that. And it's ironic because that's what it was supposed to be. I'm spending a lot more time thinking about like, how do I make myself more relevant in my job? oh Okay, so here's not even relevant to our today's topic, but since you brought up Sam Ottoman, between Sam Ottoman and Elon Musk, who do you trust?
00:17:58
Speaker
I mean, you have to pick one. Oh, come on, Echo. That's tough. Because there was a war between them and each other were blaming that they were liars, they were not being honest with the audience.
00:18:10
Speaker
Who would you pick to trust that can meet this war? Based on this book so far, Elon Musk. What? Say more. Say more, Jenny. Why why Elon over Sam Altman ah based on Karen Howe's ah ah info?
00:18:27
Speaker
Well, because based on the information she shared, she said that Elon was all about sharing it, like keeping it open, keeping it a nonprofit, making sure that there was involvement either from the industry, the government to control the creation of AI.
00:18:42
Speaker
thought, you know, he's kind of crazy. He's out there and he's gotten a lot of bad publicity. But I didn't realize that he was one of the the voices of reason. And I say that in quotation marks. I mean, Echo, you're the one who brought this up. what are What's your take on that?
00:18:56
Speaker
I would actually say it the same with you, Jenny. If I were looking back, regardless of Yenon's personality, regardless of all those bad comments, and regardless of his personal life as a mess, like all his bets that he has made ah over the years have proven to be right.
00:19:16
Speaker
So that's a track record versus like Sam Ogdenman. Like just based on what I have gathered, I feel like, you know, has a more record that can put my trust in versus the other.
00:19:31
Speaker
um I'm going to cop out because I just downloaded the audio, audible book because Jenny just told me, told me she was reading it. I want to know more about it too.
00:19:42
Speaker
So I'm going to read up on it and learn more about it. I want to go back to Jenny's earlier point. all this All this, I think, is in pursuit of monetization, regardless of what people say. i feel like when people say it, it's it's marketing. Like when leaders come up and say, I want to do this for good.
00:20:00
Speaker
Yeah, but good, but lines my pocket is what I hear. ah So for me, there's this skepticism of like, what's in it for them? How is it going to benefit them?
00:20:12
Speaker
Why are they fighting over these things and why it should be a certain way? You know, is it really for the the know sake of humanity? I've heard some AI tech leaders always talk about, I want to do good. I want to do good and make the world a better place. Yeah. BS, buddy. Yeah. And before doing it. Yeah. Good luck. I don't think so.
00:20:32
Speaker
So what is it and that's in for them? And I think I'm with you, Jenny, in that I want to, um want to know if I can have a stable job in three years it's based on what Echo hinting at.
00:20:55
Speaker
And Echo, you wrote,
Exploring Resilient Careers Against AI
00:20:56
Speaker
if I had to trust anyone, that person would be Jeffrey Hinton. Who's Jack? He is the godfather of AI. So he is the one that he joined Google 10, 12 years ago. And he's the one that behind all the greatest minds. Like the, um I think the one of the founders for OpenAI was his student. Like he was literally like his entire student was,
00:21:21
Speaker
what made this generation of AI possible. And he was the one that also warned everyone, like, AI will will actually replace your job.
00:21:32
Speaker
And he's the one that asked the government, asked everyone to put more of a safeguard behind this thing, because he sees the future. If anyone that I should trust, it's him. Like, he's the creator of all this. And he was the one actually saying, like,
00:21:48
Speaker
The biggest fear or some weather like a regret is like he actually created this by himself. And now feels like it's a monster that he was letting out and a human being doesn't have control over.
00:22:00
Speaker
Kind of like in a similar way. And he was the one that trying to con convince me I need to get a plumbing work a climbing work and instead of just a computer work.
00:22:12
Speaker
What type of work? Like a plumbing. Plumbing work? Oh, blue collar work? So I just Googled him. um He's a professor. he also won the he also won a Nobel Prize last year.
00:22:23
Speaker
Okay, so he's an academic. I feel like I trust, I would put more trust in academics than I would in industry folks, simply because feel like academics do it for a slightly different reason. It's more about the integrity and the research. ah He did actually bend in himself a little bit because his song has, ah it's like a learning some issue, like it's like a mental health issue issue or something, like he couldn't work. So he feel like he needs to save enough money so his son is not ended up on the street.
00:22:53
Speaker
So that's the reason why he joined Google. And then at Google, Google actually gave him enough of autonomy to do whatever the research he wanted to do. That's where like all the neural network, the the the best paper on the transformer. like So all the all the AI now is based on the transformer.
00:23:12
Speaker
And that's the work from his lab. um But then I think he quitted his job after he felt like he made enough money. So now he's like and behind behind the scenes trying to advocate, hey, everyone, we need to be warned by this, need to be like,
00:23:28
Speaker
put a lot of guardrail. He's a person I admire, but I know like even for him, like he banned it for money for a little bit. If you have your your golden, you know, golden eggs, your your nest for yourself and your future generation, but what about the vast majority of people who still have to work until they're like 65?
00:23:46
Speaker
That, I'm kind of worried. So is it going to AI, do work, make enough money, then come back and be like the ones like, you know, shouting out, let's safeguard it and make things safe?
00:23:59
Speaker
It's already too late. The thing is already out. You know, I already have my dream job lined up for me. yeah I wanted to learn an acupuncture. Oh, yeah?
00:24:10
Speaker
Acupuncture? But couldn't a robot do that? I think that requires like a very precise touch on the human body yeah so as well as like the experience. The more experience you have, I don't think this is something easily that robotics can re replace.
00:24:25
Speaker
And it's like in my lifetime.
00:24:29
Speaker
No, I seriously, because I do feel like I myself benefit from it so much because I told you guys like my shoulder got unlocated. It has been like always like a buzzer for me even while I was traveling. After I came back, I only did like two sessions. I almost like, I felt like it healed. I mean, obviously me it has been a while, but...
00:24:48
Speaker
I know if it's not because of my acupuncture, it could be longer for me to recover. So with all those things, I know like my personally will benefit from it. And secondly, I do feel like it's a certain level of of manual work that can't really easily replace the biorebotics right now.
00:25:05
Speaker
Or maybe AI can help me to be a better acupuncture therapist. But yeah, no, I seriously, I got super into it. This is also like a traditional Chinese medicine.
00:25:15
Speaker
Doug, what about you? What would your second career be? o Gosh. So I've been toying with the idea of actually opening a coffee shop and just serving like slow drip espresso, Vietnamese espresso, and maybe croissant.
00:25:30
Speaker
And then I just chill. I like that idea. Shop owner. Yeah, yeah. And then people can come and read and do whatever, maybe meet up, play chess, something to relax. I don't know, like congregate and just talk about life.
00:25:43
Speaker
i AI can't do that, i don't think. Not yet. Would you allow people to stay there all day if they buy one drink? You know, like the people who bring their laptops in the safer hours.
00:25:54
Speaker
Yeah, yeah. would allow that. Buy at least one thing, you know, if they're contributing to it. i mean, actually them being there, ah you know, I think show showcases that people want to be there.
00:26:05
Speaker
i would actually want people to do that, actually. I've thought about this. actually, I want to actually make enough money where if I open up a coffee shop, it where it doesn't need to be profitable. And when I get to that point, I feel like I would be successful.
00:26:18
Speaker
We would have talks, talks like this. I would highlight Dr. Kim and Dr. Yu and they would come and give talks and people would come and listen and learn and discuss. And that
Advising on Skill Diversification for AI Future
00:26:29
Speaker
would be my ideal coffee house.
00:26:31
Speaker
Oh, so a coffee house with an open mind. Yeah, for for for researchers, academics. Jetty, how about you? What would you do as your ideal job? Sorry, Echo.
00:26:42
Speaker
I don't know. i got to think about it because i don't think I would do plumbing. I think I would just vomit when I see poop. Electrician, electricity scares me and I'm scared of heights. yeah Welding kind of scares me too.
00:26:54
Speaker
I think this is something that I might seriously consider and just like develop that skill just in case my job becomes... yeah' I'll get back to you I can't see you with a jackhammer either because the jackhammer probably weighs just as much as you do. It'll just take you around with it. Like robot-assisted jackhammer.
00:27:13
Speaker
Very remote jackhammer. Oh, gosh. Yeah, get ah get back to us on what you would do. um Maybe we could have another ah you know a segment where we actually talk about our dream job should everything fall apart.
00:27:29
Speaker
that That'll be the title of it. So what's the main takeaway for our audience today? You know, just be mindful of what's coming, but perhaps if you are able to maybe start planning for secondary skill sets that could become your primary skill set. So something that's a bit more labor intensive.
00:27:45
Speaker
Yeah, absolutely. And I think like, You know, people have done this before where they had to reskill and relearn or learn new things. And I think as human beings, I think it you know it's natural for us to you know want to be comfortable and be in a spot where you know we have this consistency. But I think you know, the change is something that's going to continuously happen. And we have to, we too have to adapt and change.
00:28:09
Speaker
We can't evolve. I don't like that word, ah but we can definitely adapt to, you know, what's going on. But I'm with
Closing Remarks on Preparing for AI's Impact
00:28:16
Speaker
you, Jenny, that if there's a secondary skillset that's really relevant to your job that ties in with teaching, training, organizing, planning, and, you know, ah that ties in that interpersonal skills.
00:28:28
Speaker
I would say our listeners, please lean into that and see how you can continuously hone that to be one step above the AI.
00:28:39
Speaker
And as usual, I will end up with a chat GPT written haiku for this plan. Are we are we there yet? So the prompt I gave is just ask them to write a haiku for start prepping for AI that come to for your job.
00:28:56
Speaker
And this is what chat GPT comes back. Still mind at the gate. Algorithms sharpen their teeth. I oil my old tools. Oil my old tools. But what if I didn't have those tools to begin with I have to buy tools and oil them.
00:29:14
Speaker
At this point, it's so not it's not just all other old tools. It's almost like you have to find a new tool. Yeah, that's probably right. I gave it some thought. And you know what? I think I would be some sort of repair woman because um I usually like building my own furniture. um i like repairing my own stuff.
00:29:32
Speaker
um In my previous apartment, I painted wall damage instead of hiring someone to do it. So yeah, some sort of like repair person. exactly um right dry Drywall Jenny is is here.
00:29:48
Speaker
yeah and that's going to be my name, Drywall Jenny. I love it. Well, it sounds like we have our secondary jobs thought about, and um now it's about maybe going on O-Net and finding out what skills those are.
00:30:03
Speaker
I'm going to get an acupuncturist. I'm going to get another doctorate degree. Because one degree is not enough.
00:30:11
Speaker
For acupuncture this time. No, I'm kidding. Oh yeah? If you have an Asian face, you can just get away by without a license. It gives you sweet cred. I guess I've never asked my acupuncturist with the license or... Okay.
00:30:26
Speaker
just know it works. Okay. so future acupuncturist, coffee shop owner, and handywoman. There we go. <unk> We're set for the ah for at least five years.
00:30:39
Speaker
Okay, well, thank you for tuning in to another episode of Hidden in Plain Sight. We'll catch you on our next episode. bye Thank you, everyone. Bye, everyone.