A 30-minute intro call turned into 2 hours. The reason? Shared trauma at the same company.
Melynna and I worked for the same company, Company A, but at different times. Technically, we’re coworkers. We just never crossed paths there
One day, her LinkedIn post about AI safety landed on my feed, and it deeply resonated with me
Before sending a connection request, I checked her profile and found out she had worked at Company A too
So I quickly drafted a personalized note about her post and our Company A connection
She accepted, and we scheduled a quick 30-minute intro call
And guess what? It went on for 2 hours
No, it wasn’t because we’re “chirpy girls.” 😄
We started with our current work and our views on what’s happening in AI safety
Then, at some point, Company A came up. Oh boy, there was no looking back
One of us mentioned what a traumatic experience it was, and the other instantly related. For both of us, it was one of the most difficult times of our lives
The difference? As an American, she had the luxury of walking away from that job. As an Indian on a visa in a brutal job market, I had the “luxury” of getting laid off or staying in the trauma
That’s how we bonded: over shared trauma
From that day on, we became each other’s work supporters
So when I asked her to come on the podcast to talk about the “future of work and the future of AI”, she instantly said YES
Easily the fastest idea-to-podcast-recording story I’ve ever had
In the episode, we talk about why she’s pursuing a Master’s in Foresight at the
University of Houston, and what a degree even means in the age of AI
Some highlights from the episode:
📺 An ad that looked a lot like Jennifer Connelly telling us “Don’t hire humans, hire AI”. Did she ever agree to it?
📺 When a startup shuts down, your Discord servers, Slack channels and emails can become a gold mine for someone else
📺 In the future, will human labor disappear completely, or become a luxury?
📺 What gives a foresight professional hope “in a vast world of darkness”?
The episode is out; watch on YouTube; listen on Apple Podcasts or Spotify.
Episode Summary:
Aashka interviews Melynna Garcia, who is pursuing a master's in foresight and brings experience across technology and other industries, about how foresight can help organizations think beyond a single predicted future. They examine AI's effects on workers, consent and ownership of human data, labor protections, competing visions of human-machine work, and the challenge of deciding what counts as truth. Aashka Patel speaks with foresight practitioner Melynna Garcia about who should shape AI’s future, how to respond to potential job displacement and concentrated power, and what strategic foresight careers look like. Garcia outlines her Human Manifesto, including a proposed 70/30 human-AI workforce, and describes local concerns around data centers in Texas.
Timestamps:
00:00 AIR Bites (Precap)
01:55 Why she left AI, then came back
07:01 Foresight vs forecasting: many futures, one number
09:59 Weak signals: IP and your workplace data
12:32 Headcams in Bangladesh, metaglasses in India
18:12 Licence your skills, don't give them away
22:07 They own your likeness forever
28:10 Can foresight outrun AI misinformation?
33:07 Human labour becomes a luxury good
35:20 Machine-only: hire agents, not people
36:55 The hybrid future we actually live in
41:48 Would you watch robot pickleball?
45:21 "It's not AI doing this to us"
47:56 Your vote and your wallet are AI policy
51:55 The AI race fear and the data center boom
55:49 Careers in strategic foresight
59:16 How to learn foresight for free
01:03:12 The Human Manifesto and the 70/30 workforce
01:11:13 A Bitcoin mine became my town's data center
01:14:29 End Credits
Transcript:
Aashka (00:49)
hello and welcome to On AIR with Aashka Thank you so much for joining us, Melynna today. It’s a pleasure to have you finally on the podcast.
yeah, let’s dive right into the questions. in this era of AI, a lot of people are asking what’s even the point of degree anymore, right? And yet here you are pursuing a master’s in foresight. So what’s the actual foresight you had?
That led you to pursue a master’s in foresight.
Melynna Garcia (01:17)
Yeah, that’s a great question. So yeah, there’s a a short answer, but I’m going to opt in for the long answer. So after I graduated, I was thinking about the future of AI. So I graduated with a bachelor’s in anthropology and I was really interested in social technical impacts of AI and aging populations and
As a result of that, I was starting to look at different programs and I came across Foresight. I had spoken to the dean right after graduation, but it just wasn’t a program that I was interested to work on at the time. I instead I opted to try to do a master’s in data analytics because I thought that was more in line with AI at the time. but eventually I I circled back around and I think that there’s something in Foresight called like signal scanning.
I call it vibes. I’m very much a vibe person. And I think that somewhere along 2022, I made the concerted effort to pivot into AI. I was decided
to go back into AI after having worked in tech and in space and oil and gas. I was like, I really need to make my way back into working in AI. And I think that.
working at different AI organizations, talking to different leaders and seeing how they were thinking about how to deal with the upcoming future made me realize that there was no foresight. When people say nobody knows what they’re doing, they really mean it. And work yeah. And working at
Aashka (02:49)
Yeah. Mean it.
Melynna Garcia (02:53)
different organizations across like sales, marketing, strategy, and then operations, you start to realize, man, there’s really a big problem there. And so
Yeah, I think that was like the overall vibe for me is like seeing the problems internally at organizations that were preparing to integrate AI and preparing to help other organizations integrate AI widely across infrastructure really like raised a concern for me and I was like, I should really start thinking about AI futures. And so I got in touch with the dean at the Foresight program, Andy Hines, and decided that now is the the right time to dive back in.
Aashka (03:32)
Yeah.
Melynna Garcia (03:31)
Yeah, that was a really long answer.
Aashka (03:34)
Yeah, yeah. That completely makes sense. So i it was around twenty two th that you decided to pursue, okay. Yeah, i it was all almost around the Chat GPT moment right?
Melynna Garcia (03:45)
Yeah,
so there there were a couple of things that were happening around that time too. So when I graduated
from college, I had done a couple of papers and different studies looking at AI. At that time, like I knew
about the singularity, but I was convinced that this would not happen in my lifetime. But I still had that interest
in AI. And so right after graduating from college, I was volunteering slash interning at this startup.
That was working doing different like AI stuff. And that really like kept me thinking about AI. So as I started my career in tech,
I always had AI in the back of my mind. It was the one thing I would I would always talk to people. especially as like machine learning came to gain popularity, I would always talk about AI. And then in 2020, when the pandemic happened, that’s when I started my master’s in data analytics.
and concurrently
also an associates in AI. So the
Aashka (04:44)
nice.
Melynna Garcia (04:44)
the pandemic really like pushed me forward to start thinking and taking seriously a future where I could work in AI.
Aashka (04:50)
Okay. Yeah, makes sense. so can you explain or double click more on what’s your masters all about? Like what what are you studying and how does it equip you to ma plan for futures and scenario planning and stuff?
Melynna Garcia (05:06)
Yeah, so the program I’m in is one of the oldest programs in the world. And specifically why I’m in this program is because while I think that I’ve always been a foresight thinker, I didn’t really possess the correct like language or tools or methodologies. And I think this program is really helping me strengthen those skills.
Aashka (05:29)
Yeah, makes sense. Makes sense. So there’s a big difference between foresight and forecasting. So can you break it down for people who are unfamiliar with that?
Melynna Garcia (05:38)
Yeah. So the way that I think about it, I usually tell people about it, it’s I think of foresight being more like the social science, like in the sense that it’s like super qualitative and forecasting
being super quantitative. So the difference between
both are that they both have some common ground. And what I mean by that is that they’re both leaning on like some signal scanning, some horizon scanning, and even scenario planning. However, the the major difference is that foresight is looking at
Multiple alternative futures while forecasting is betting on a specific future. So foresight
does not predict the future, but
forecasting does. So this is why often
Aashka (06:15)
Okay. Okay.
Melynna Garcia (06:19)
you’ll see that when there are forecasting competitions and that sort of thing, people are specifically looking to see what future is more most likely to happen. And they use a lot of quantitative tools, it’s very math-heavy.
And foresight is not in that same realm. however, like I said, they do have some crossovers. I yeah.
Aashka (06:40)
Yeah. can you expand on the crossovers that you mentioned?
Melynna Garcia (06:44)
Yeah. So for example,
there is a lot of signal scanning in both realms, but I think that the
the approach to it might differ a little bit depending on how they were trained. So for example, there are some foresight practitioners that have more of an academic background, and so they have like a very specific methodology in how to do this. Whereas like a lot of forecasters might come from like very heavy maths programs.
Aashka (07:11)
yeah.
Melynna Garcia (07:10)
And so the way that they
approach this process is very different because they’re not specifically being trained in forecasting. It’s something that they just kind of like evolve into. So the crossovers
like I would say is like signal scanning, horizon mapping, and scenario planning. So
both of us do the same thing. We just approach it a little bit differently. And so you you can see the differences when you get both peoples in the same room.
but
I will say that something that I’ve been starting to see more of is I’ve been seeing more forecasters taking an interest in like foresight methodology and then vice versa, like foresight practitioners finding the value in forecasting and seeing how they can apply it to their work, specifically as AI continues to like take over the world. so yeah, I I think those are the main cruxes, the main crossovers.
Aashka (08:04)
Yeah, yeah. so you mentioned a lot about signal signal mapping and stuff. So what are some of the weak signals you are watching right now that most people aren’t paying attention to when it comes to work and AI? as you mentioned, AI is here to take over the world. So what are the weak signals from your foresight lens?
Melynna Garcia (08:27)
Yeah, so I I think I have to preface this by saying that I’m very biased in this regard because I have my own thoughts and opinions
Aashka (08:36)
Yeah.
Melynna Garcia (08:36)
on AI. So my stance on this is not neutral whatsoever. So I
Aashka (08:41)
Ha ha.
Melynna Garcia (08:41)
think that some of the signals that I’m particularly looking at right now are like the future of IP and what
that would look like and how that will impact the future of work. I think that there
Are a lot of signals that are going on right now. So for example, the state of Colorado recently introduced artist corporations, and I think that’s a very interesting way to think about how to protect artist’s IP by
creating
a different corporate structure that will protect that, right? I’m also
looking at the lawsuits that OpenAI and Anthropic have in terms of copyright. I’m looking at like different
lobbying efforts that they’re looking at in DC and how they’re moving things
Aashka (09:25)
He
Melynna Garcia (09:26)
in that regard. but in general I’m also looking at how factories are implementing AI and data training across the board. So I would say for me that that is one of the weak signals that for me is like quite strong right now because it’s no longer it’s no longer a
I would say that a weak signal is usually something where like you and I are in conversation and we say something and I’m like, that’s funny you said that. And then
I would go on Twitter and see that somebody else also shares that same belief. And then maybe two or three months later I see an article and I’m like, wait a minute. I have now heard from three different people about this. Something’s going on. I
Aashka (10:03)
this is what Yeah.
Melynna Garcia (10:07)
would say those are more weak signals, right? And for
Aashka (10:10)
yeah.
Melynna Garcia (10:11)
me
IP is a stronger signal because there’s a lot of work.
However, I haven’t seen a lot of connected effort to measure what is going on. It is something that’s
in conversation in terms of like the future of work and where AI is going.
but I don’t think it’s been mapped out the way that it should be. So in my head, I’m like, it’s a weak signal for a lot of people that are not thinking about it, but for me, it is
a very strong signal that there is something happening here.
Aashka (10:37)
Yeah, yeah. Makes sense, makes sense. So during our pre podcast chat, you mentioned something about Bangladesh garment workers. So can you walk us through that story and how does it like what does it have to do with AI and the future of work?
Melynna Garcia (10:53)
Yep, so this is this is a signal. So I came across
Aashka (10:56)
Yeah.
Melynna Garcia (10:57)
a video on TikTok where factory workers
in Bangladesh were wearing headcams. And
I was wondering what that was, so I tried to find more context to the video and I couldn’t find much. CNN did a short
coverage on it, and essentially what it led to was that factories in Bangladesh were
in agreement with some data training companies.
And they were now putting these headcams, had this headgear on their employees so that the cameras could record their dexterity and how they went about doing different things. And the one thing
about Bangladesh is that their second largest economic sector is the garment industry. So this is why we see like made in Bangladesh on a lot of her clothes, because a lot of our clothes get made there.
And so to me, that was like a really strong signal when I was thinking about the future of IP, because to me, it is very suspicious that a company would be interested in documenting a human dexterity as it pertains to an industrial sector, because we’ve
already seen what industrialization
can look like across factories. We’ve already lived through
that. But for a country where the second biggest industry
Is the gar the garment industry, it makes you like pause and go, my god, these companies are trying to figure out how these humans are going about creating clothes, how they’re sewing, how their movement is going, so that they can then
go and train robotics to be able to replace them on the garment line. And that to me is like a
Aashka (12:32)
Yeah.
Melynna Garcia (12:35)
huge signal of what the future of work could look like because we are already hearing a lot of talk.
Of economic disempowerment and
job replacement. And
Aashka (12:46)
Yeah.
Melynna Garcia (12:46)
if this is already happening now, we can only think and imagine what will happen in the next five to twelve years and what
the future of millions of people across a country like Bangladesh could look like going from
having some economic via viability to having no other way to survive because
Aashka (13:05)
Yeah.
Melynna Garcia (13:05)
their skills have now been learned.
by a system that they didn’t consent giving rights to.
Aashka (13:11)
Yeah, yeah, yeah. So did you get any insight on like are these workers getting incentives to put those cameras on their head, right now? Or like a an extra hourly wage or something like that? or they are just
Melynna Garcia (13:27)
So I
Aashka (13:27)
doing it, yeah.
Melynna Garcia (13:28)
so I found different discourses online, and it’s hard to tell what is true because of course there
are a lot of regulations when it comes to factory production.
a lot of countries, for example, let’s say Australia. Australia has a very strong anti-slavery policy. And so in
countries where they produce
A lot of like garments or shoes, and where children might be involved and whatnot.
They have to upkeep certain regulations in order for businesses in Australia to conduct businesses with those companies. So I found
different things on the internet, and it’s hard to tell what is reliable because, of course,
you can’t tell what’s going on unless you’re actually a person working on the factory line. So you can see reports of
Yeah, there are some incentives being paid out to to employees, but there’s also mixed
reports where people are putting on forums, and of course I’m using Google Translate to determine what is true and what isn’t. They’re saying that
Aashka (14:28)
Yeah yeah.
Melynna Garcia (14:30)
this is not true, that they’re not receiving any incentives, and that they’re being forced to continue overworking
because not only do the cameras detect their movements, they also detect
a drop in efficiency.
So it’s it’s a very tricky thing to police, but I have seen
Aashka (14:49)
Yeah.
Melynna Garcia (14:50)
reports that in India there there’s also now reported
Aashka (14:53)
Yes.
Melynna Garcia (14:54)
cases where women are wearing metaglasses in factory floors. And so
Aashka (14:59)
Yes, yes.
That’s why I asked you about the incentives thing because like in the Indian context also I read similar stuff. like factory workers or labours in general having those cameras on their head and recording every piece of their work. but like as you mentioned, like it’s a mixed thing that we read online, like what’s happening on the ground. I actually reached out to
one of those data gathering companies, the founder of that company, because sometimes in this organizational structure the sufferers turn out to be the labors like even if the data gathering company is giving some incentives for now let’s say but the company with whom the labors are employed with they are not giving it to the labors. That also might happen.
So yeah, we really need to dig down. I I’ll let you know like if I get more insights on that thing. But yeah, similar thing is happening in
Melynna Garcia (15:56)
Yeah.
Aashka (15:56)
India too. so so currently the labour laws today tie work product ownership to the company. These laws were written for a human workforce. so how badly do current labour laws fit the AI reality, like with AI agents and stuff, and what would need to change?
Melynna Garcia (16:17)
Right, so in this specific example where we’re talking about the Bangladeshi garment workers, I’m not entirely sure what protections of any exist in the country to protect our economic viability as AI continues to to push forward. currently, as I understand it though, there are a lot of red flags going on, there are a lot of alarms going off.
Aashka (16:39)
Yes.
Melynna Garcia (16:40)
In terms of labor law protections. And so, at least in the United States, we have seen that, for example, SAGAFTRA made very concerted efforts into ensuring that their actors would be protected from digital twins and that
they could have like some type of payment and royalty, right? But we’re not seeing
the same thing happen for employees who are not getting consent when it comes to their data.
being used to train agents to emulate their specific skills.
So for example, we were talking about factory workers, but there’s a whole other side where we’re looking at data annotation workers, where we’re looking at professionals like you and myself. So let’s
say that we worked at a company and that company is a startup and it’s like looking like there’s a lot of like potential and all of a sudden that potential just like flops.
And the company shuts
down. What we’re seeing now is that there are sunsetting companies that are coming in and that are helping these companies sell their data. And so we’re
seeing
that there’s like a gold mine there where you can now sell your Discord servers, your Slack channels, your emails. And that becomes problematic because, say, like a person like me, where I’m currently working as an operator, the way that I problem solve.
is documented
in my Slack channel. It’s documented in
Aashka (18:04)
Yeah.
Melynna Garcia (18:05)
my in my Google workspace. And so for a
company to come in and train on that data without me having consent, without me getting some type of economic remuneration for it, it becomes problematic
because somewhere out in the universe there will be an Melynna agent that can do and think
Aashka (18:21)
Hehehehe
Melynna Garcia (18:23)
the way that I can based on that short amount of data. And I won’t have any say over that. And so I
think that
That there’s no current labor protections to protect us towards walking towards that future. And that is something that we should be thinking about, not just in a US, but in a global scale. If we’re going to integrate AI widely and we don’t yet have a a plan to ensure that people are able to survive in an economy where job displacement is a mass.
Then we need to be able to give people a way to survive in that world. And I think labor laws are probably the first step. So yeah, there’s a lot of work that’s being done by unions in different
realms. Like, for example, port workers are now I’ve seen like they have taken a stand in the last two years because now there
are like docks that are completely automated, and
there are issues that like one or two people will have to deal with.
that should that you would usually be dealt by a hundred people. And so that also becomes a problem because now you’re putting a lot of stress on one or two people, where it used to be a problem
Aashka (19:28)
Yeah. People.
Melynna Garcia (19:31)
that a lot of people held together. So yeah, there’s
there’s a lot of issues with labor laws and and a lot of work that needs to be done there to to ensure that
we have a way to survive. And I think that
the core of this is if n labor is no longer needed, then
What do humans do? Because labor
Aashka (19:50)
Yeah.
Melynna Garcia (19:51)
is the only way that we can survive, you know?
Aashka (19:53)
Yeah.
Yeah. Yeah. Yeah. So in our previous chat you mentioned about the idea of workers licensing their data rather than having it consumed for free. So what would that actually look like and i is there a model that exists anywhere in the world for this today?
Melynna Garcia (20:12)
Yeah, so there are similar models, but there’s not a specific one out yet, at least not that I’m aware of. So when I’m thinking
Aashka (20:19)
Okay.
Melynna Garcia (20:19)
about similar models, I think about actors, for example. Actors do receive royalties when their work continues to
be aired on TV decades later, when it’s being streamed on TV, musicians get the same thing for streaming their music and whatnot. So there are models
there on how to ensure that people are being paid for their work.
However, when it comes to humans and labor and our work being duplicated by agentic AIs, we don’t have that yet. But I do think that there
will be a future where we have that, where we have agencies
where we can license our likeness, whether it is for media where we want to license our image, or whether
it is that we want to license our skills or expertise or experience, because those do provide a lot of value. And we know they do because companies
like the big labs like openai, like anthropic, X, Meta, they’re paying millions, if not billions of dollars to get their hands on original data that can help expand the capabilities of their AI systems. So there’s value there. We just need to be able to
Aashka (21:22)
Yeah. Yeah.
Melynna Garcia (21:27)
like get over that hump. And I think it will only happen when somebody opens up an agency. I will add this there’s
a TikToker Kavi Lame. I’m
Sure, I’m mispronouncing his name, but
he sold his company for like $900 million. And as part of that deal, he also sold his likeness. And so I
think that is the first case that I’ve heard where someone has sold their likeness in that regard.
and that has been intentional. However, there on the other side of things, this was a very intentional action where he will profit. But on the other hand of it, people are.
Selling their likeness without being aware of it. And so, for example,
Aashka (22:08)
Yes.
Melynna Garcia (22:09)
I should have mentioned this in one of the weak signals, but I think that terms and conditions will become very popular. Like people will start talking about terms and conditions. But for example,
Aashka (22:15)
Yeah.
Melynna Garcia (22:19)
on my LinkedIn, I get a lot of ads for
AI-generated headshots. And when you
look at these companies and you look at their terms and conditions, a lot of them
will say
something like, Hey, you will pay me 1999 and in in exchange,
we will produce 60 images and you can choose the best one and use them on the internet. But the caveat
Aashka (22:39)
Yeah.
Melynna Garcia (22:40)
is that they will own your likeness for perpetuity. And
so if they own that likeness, all of the images that you have uploaded, it means that these
companies can then go and use your likeness anywhere else. And that becomes a problem.
Because now you
Aashka (22:56)
Yeah.
Melynna Garcia (22:57)
have people that are unintentionally, unconsciously selling their likeness, and it’s gonna be used
Aashka (23:01)
Yeah.
Melynna Garcia (23:03)
somewhere somehow in any corner of the world. So, like,
imagine if you were traveling and say you go to Malaysia and you’re traveling, and all
of a sudden you see a commercial with your face, and you’re like, what is
going on? That is me, that’s my face. And you’re not being paid.
Aashka (23:19)
God and you are not being paid for that.
Melynna Garcia (23:24)
And what if the commercial is promoting something that is unethical or that violates your own values and alignments? So these are
Aashka (23:30)
yeah, yeah.
Melynna Garcia (23:32)
things that like we really need to be aware of. So when we think about like maybe licensing our likeness or our skills, I think we
need to be in charge of it. We need to be able to protect our own intelligence and be able to
have a way to profit over it and decide where and when we use it.
Aashka (23:51)
Hm. Yeah, yeah, makes sense. Because in India a lot of celebrities have contested against like having those personality rights. they had cases or battles f fought for personality rights and they have won. So like for celebrities of course paying the hefty lawyer fees and everything is worth pursuing and of course they are dependent on them on those like
likeness or personality rights. but for us like we think like, Okay, who am I? Okay. So yeah, that
Melynna Garcia (24:25)
Exactly. And there’s like
there’s examples of this happening in the US. So for example, I’m
sure you’ve seen this on on the internet, but there’s a startup
in San Francisco that put up ads in San Francisco, New York City, and it was like, Don’t
hire humans, hire AI. And the image that they were using looked a lot
like Jennifer Connolly, the actress. And a lot of Redditors like picked up
on this and they’re like, Did Jennifer Connolly agree to this? Did she give away her likeness?
To this company, and as a result, they had to take down those ads, and now
Aashka (24:54)
Huh Of course not. Huh Huh
Melynna Garcia (25:01)
they have a different person. And I look at the new person that they have, and I’m like, this looks like a model. And I’m pretty sure
that somewhere a photographer might have sold images of this model, and
Aashka (25:10)
Yeah. S yeah.
Melynna Garcia (25:14)
now they’ve trained these advertisements, and now you will walk around
and you will see yourself telling people.
Don’t hire humans, hire an AI. And so it’s like it’s a crazy world because you’re right. Someone like Jennifer Connolly would have the resources to sue these companies and ensure that her likeness isn’t be an abuse, but common people like us don’t have the same opportunities or resources, and so
we are essentially being attached to things without us having consent. And so
Aashka (25:43)
Yeah.
Melynna Garcia (25:44)
it becomes really tricky, and this is why I’m advocating for
You know, us having control over likeness and thinking about
digital twins as something that we control.
Aashka (25:55)
Mm hmm. Yeah, yeah, makes sense. So a while ago you mentioned about like in the case of Bang Bangladesh, we are not able to understand what’s happening on the ground or what’s the truth behind those workers and the camera thing. So here’s
Like the argument from forethought research, like AI-driven epistemics could push our relationship with truth in one of two opposite directions. Either it makes truth cheap and easy to verify for everyone, or it traps us all in personalized bubbles so deep that even the people shaping the narrative can no longer see clearly. And foresight is fundamentally an epistemic.
practice. so it’s about helping people make sense of a rapidly changing world before they have to act in it. So here’s the question like if AI degrades our collective ability to track what’s true, does foresight as a discipline become more important or less? And are foresight practitioners actually equipped to operate in that second world?
Melynna Garcia (27:01)
So that’s a tricky question. And
I will answer the the last question. I would
say probably not, because I’ve looked at the numbers of how many Foresight practitioners are in the world, and I’ve seen
different numbers from anywhere from ten thousand to a hundred thousand. So when you
think about those numbers, it’s like can a hundred thousand people really figure out what’s best for eight billion people?
that that becomes a problem in itself, but
I don’t know, actually. one
Aashka (27:29)
Yeah.
Melynna Garcia (27:29)
of the things that I was thinking about is
that while I agree with what Forethought is saying, I also disagree because I I also think that there is something about net neutrality and who decides
what is good and what is bad. And so
Aashka (27:45)
Yeah.
Melynna Garcia (27:46)
until we can determine who’s in the room and why they’re in the room and how they’re thinking
about what is true and what isn’t true, it
like becomes a complicated thing.
Aashka (27:58)
Yeah.
Melynna Garcia (27:58)
Yeah, and like I’ve personally seen what these rooms look like and when they start to put out this perception of the world that is very singular, that is very insulated, while
I might agree with it because I’m on the same wavelength, I also like have to sit back and think like, hey, maybe there’s a problem here because the people that are in the room already think and agree with this train of thought, and maybe we should get people from the outside to challenge those those thoughts. So
Aashka (28:25)
Yeah, yeah.
Melynna Garcia (28:26)
Yeah, I
don’t know I don’t I don’t know what the answer is here.
Aashka (28:27)
Yeah yeah I
Melynna Garcia (28:31)
there there’s there’s really no way to be neutral on this take because
whoever including myself, whoever has an opinion on this already has implicit bias.
Aashka (28:42)
Hmm. Yeah, yeah, makes sense. And a lot of efforts from the big players, like Elon Musk has tried chasing truth seeking AI, in the first place and then it turned out to be the same Chat GPT Claude and stuff.
And yeah. Yeah. Yeah.
Melynna Garcia (28:59)
Yeah. And and that’s that becomes a problem because what truth is it? Right? Is it
the truth for one person? Is it the truth for one country? Is like who’s benefiting from this truth? And that’s that’s where I mean like this becomes
this becomes really tricky because
Aashka (29:17)
Tricky, yeah, yeah.
Melynna Garcia (29:18)
safety for one is not safety for all.
Aashka (29:21)
Yeah. Yeah. Makes sense. Yeah. That’s a great quote. Safety.
Melynna Garcia (29:25)
Yeah.
Aashka (29:28)
Yeah, yeah. L like it’s okay to not have an answer at the moment. Like a lot of leaders also say that we don’t know about the future, so it’s fine, to not have an answer. Yeah. Mm-hmm. Mm-hmm.
Melynna Garcia (29:39)
Yeah. Like i with my own like implicit biases
and my model of the world to me
And to me, when I think about what is more important and what should be prioritized and what will cause existential risk, I’m thinking
about two different models. So one, like the the model that is like right here in front of us, of course, involves misuse.
And I I have a model of like human on AI sabotage, right? And the risk that that will
Risk that that will create in the future as humans are initially misusing these tools and they’re sabotaging these systems intentionally. And then when I think long term about
the t the capabilities that these tools are already showing now and how these capabilities
will expand in the future, I
think, yeah, there’s a lot of risk there, and that risk is both present now, will be present in the future, but it’s like it’s hard for me to tell and determine which
one has more urgency and which one we should focus on first.
And which one will determine the fate of the world? I honestly I think at the end of the day, this will be determined by the economic leverage that we pursue as individuals and
the futures that the leaders at these organizations are are walking us towards. So I guess that
was like my very long answer to like still insist that I don’t really have an answer to this question.
Aashka (31:10)
E
it’s totally fine. It’s totally
Melynna Garcia (31:13)
Yeah.
Aashka (31:14)
fine. let’s move on to the next one. so Philip Tremell, an economist, makes an uncomfortable argument. even if people genuinely prefer human work, a live performance, a human therapist, a handcrafted object, it may not save
The labor share because as AI alternatives become vastly better, the opportunity cost of choosing the human option rises until it’s just not worth it. In that future, human labor doesn’t disappear, it becomes a luxury good, something the wealthy pay a premium for. So from a foresight lens,
What does that mean for the kids being told to stay human, to lean into creativity, empathy, craft? And are we training a generation to compete for a s very small pool of premium human jobs that only a few will ever access? Like it’s basically proposing what the Italians are in the current world, like having just a small piece of the bigger pie. So wha what’s your take on that?
Melynna Garcia (32:17)
So yeah, the I love this question. This is a great question because I both agree and disagree with this. So, first off, when I
Aashka (32:22)
Okay, yeah, perfect.
Melynna Garcia (32:24)
think about human labor in the future, it depends what world we’re in. So if if we’re
in a world where machines can do everything and
there is very little contribution that humans can do, I can see how human outputs would become luxuries. But I also kind of think that in that same world,
look human labor could also become something that is favored. And the reason
I say that is because my main work that I’m working on as part as hopefully my thesis is thinking about the the futures that we have in front of us and what that will look like. And so it these futures are not very distant from what we already live in. So for example, we exist in a world where
We can interact with only humans and only do human things. And while we might have access to technology like a pen, this isn’t
technology that’s going to like really like make a great change in my life. Whereas it would have maybe two or three hundred years ago, right?
and so when I think about this, I’m like, there are only three futures, and we already know them because we’re living in them. And these three
Aashka (33:30)
Yeah.
Melynna Garcia (33:31)
can coexist, right?
So we will have like, for example.
we’ll have communities that are human only. And in these communities,
maybe all labor will only be performed by humans. And in this sense, people that buy this labor can either treat it as a luxury or as favorable labor. Because the same way that we have an option to go into the store and buy organic or unorganic products is the same way that we might treat human versus non-human labor. The second model is like machine only labor. So for example
Companies that are thinking about optimization and efficiency might prefer
to hire a bunch of agents than hire humans. And so in this way, work would only be performed by agents or machines, right? And we already see this. There are factories
that build things only using machines, and humans might only show up to make sure things are okay or just to make sure that the building was built safe and that they’re following protocols for like OSHA, whatnot.
And then the
last scenario is a scenario that you and I coexist and most people are living in. And that is a hybrid scenario where we are living
with technology, but we are deciding how much technology we integrate into our life. So for example, you might choose to turn on Siri on your phone. You might choose
to have an Alexa in your household. You might choose to use Claude or X or Grok rather or Chat GPT, right? These are three different features.
And they’re all coexisting in the same world.
And so when I think about human labor being treated as a luxury, I can see how that would be true for a certain subset, but
I can also see that for another subset, human labor would be treated as something that is favored and something that they prefer. And
so it’s like it’s like this very weird thing. So for example, like when you look at designer bags, right?
Hand designer bags are usually created in a studio and they’re created by hand. And that is how they can justify like a great price tag of like $10,000 because they go through all this process, they use up all of these hours, hundreds of hours of labor, and then you can sell like a Birken bag for like 10 grand. I can
justify it because I see that it’s human-made, right? But at
the same way, you might go on Shein and find a bag that looks kind of similar for
$30 or $35 and it’s made by a machine. They’re
both bags, but which one do you prefer? And how are
you using your economic leverage
to decide who you want to support? So
yeah, I think there’s like these three coexisting futures. And now when I think about that world, and
Aashka (36:11)
Mm. Futures. Huh. Hmm.
Melynna Garcia (36:17)
I think about how do we tell kids to continue being human.
It gets a little bit interesting because I
think that we should continue being human. I do not think that we should outsource, yeah. I don’t think that we
Aashka (36:25)
Yeah. Becoming human
Melynna Garcia (36:30)
should outsource or offload our cognitive capabilities because every human on earth is an individual. We’re differently unique. Everyone has different capabilities. There
might be someone that has a very similar profile to me who might be a great piano player.
And I
am only a beginner piano player. In fact, I probably
play as well as a five or seven-year-old because
that’s as far as my capabilities went, that’s as far as my efforts went. But there might be somebody with natural talent that’s just amazing
at it. Why would I then tell that kid to not play the piano and go adopt AI technologies? Like I
think this has to be a very individualistic approach.
where we decide like what works
for for people and what being human means.
But I do think that there is a a very specific future where we
are starting to look into crafts and and pushing more adults, not just children, into these life paths. So for example,
A couple months ago I did a presentation for one of my classes. And I very ignorantly said at that time that we were losing culture. And I think it was because at that point of at that point in time, I was in a very insulated perception of the world and I wasn’t having a lot of touch points with different communities and what different people were doing. And now
that I’m out and about and exploring different things, I am seeing that
There is a resurgence for craft making. There are communities that are specifically tracking crafts that are on the verge of extinction and are trying to train people to become proficient at them. So, for example, something like tailoring. It is very hard now to find a tailor or a cobbler. And there
are people that are specifically trying to build fellowships to train the next generation to go into these crafts and trades. And so when I think
Aashka (38:24)
Yeah.
Melynna Garcia (38:27)
about
how do we compete in the future?
I think it just depends on what world you want to live in. If you want to live in a very human world, then you will
go and adopt skills that will help you become a cobbler. If you don’t want to do that, then you will go and learn how to work with an agent. Exactly. So it’s I think
Aashka (38:40)
Hmm. Hm. Hm. Train any I Yeah.
Melynna Garcia (38:48)
it’s it has to be a very individualistic approach. And
I reject any idea or notion
Of a world where AI agents
completely take over and do everything. I think we still need to keep some of our humanity because that’s what makes humanity great. Like, are we just
going to press end to the human renaissance and
Aashka (39:08)
Ha ha ha.
Melynna Garcia (39:09)
let whatever is coming up next just take over? and
I I say that because we have to remember that AI systems are being trained and developed based on human data, right?
Aashka (39:21)
yes.
Melynna Garcia (39:22)
But their perceptions of the world are being controlled to benefit
very specific outputs. And
so even though they’re being trained on human data, if their outputs
are being chained or locked to have a very specific perception or output of the world, then
we lose everything that we have been building for thousands of years as a human race. So
Aashka (39:48)
Yeah,
yeah.
Melynna Garcia (39:48)
Yeah, I I
would say kids need to stay human, but we do too. Adults need to stay human.
Aashka (39:52)
Yeah,
yeah, yeah. Makes sense. So I had a personal question on this, since you mentioned about pickleball. let’s say twenty thir twenty forty let’s say, would you rather pay for a pickleball match where two humans are playing or two humanoid robots are playing, where would you pay?
Which match would you like to watch? like a paid match. Yeah. Yeah.
Melynna Garcia (40:18)
Well it depends. It depends on my mood because
what if the rules and regulations for both games are a little bit different? I think I might be interested in seeing some
humanoids play pickleball. but
what if the people that are playing pickleball are my friends? Maybe I would want to go see them just because they’re my friends and I wanna go support. So I think it it depends and
I’ll put it like this. I was recently in San Francisco. I had a sister trip out there,
and a lot of our trips on day one were all in Waymo’s.
And the reason was that I wanted to
Aashka (40:57)
Yeah.
Melynna Garcia (40:58)
have more quality time with my sister. I wanted to be able to have
conversations with her without like an Uber driver listening in on them. And so for that
Aashka (41:03)
Listening. Yeah.
Melynna Garcia (41:07)
day, it was important that we were in a Waymo because we were bonding. But on day two,
When we were very much in a rush and we needed recommendations on things to do, it was more
convenient for us to ride in an Uber where we can have touch points with a human and we can get recommendations
on where to go for the best burritos or where
Aashka (41:26)
Yeah.
Melynna Garcia (41:26)
the the nearest pharmacy would be that would actually be open past midnight.
And so I just think it it it’s gonna depend on your needs and wants in that future. So I would say both. I would be open
to going to see both matches.
Aashka (41:40)
Yeah, yeah. So my answer would be also both because I ha while I was working with Amazon there was this event called Battle Bots and
initially on reading that name I was like what the hell is happening to the world? Like why are we watching two bots battle just like we would see wrestling matches and stuff.
And it was really interesting. Like I got hooked on to the entire I think forty five minutes was the duration and I was completely hooked. I I I just wanted to see two bots fighting. So yeah,
Melynna Garcia (42:18)
Yeah.
Aashka (42:19)
it was really interesting. Yeah, yeah. So yeah.
Melynna Garcia (42:23)
It’s in
an in a weird way, even though you’re consuming an event where you’re
seeing humanoids fight or play pickleball or whatever it is, you’re also
creating human connection because now you’re talking to the person next to you and being like, Did you see that? What do you think about this? This is crazy. So
it just depends on the future that we want. And I think that the great thing
Aashka (42:47)
Yeah.
Melynna Garcia (42:48)
about thinking about
these futures is that in these versions of these futures, we would elect what future we want. If you very much oppose any type of AI and technology, you don’t have to go through these events. And I think that’s
that’s the future that we should have. We should have an elective future.
Aashka (43:07)
Yeah, yeah, yeah. Makes sense, makes sense. Like whatever we choose to see, we just want a human to be sitting on our side so that we can discuss the basic
Melynna Garcia (43:16)
Yeah.
Aashka (43:17)
human connection need that we have. Yeah, moving on. Yeah. Yeah.
Melynna Garcia (43:21)
Because that that will still that will still be a necessity.
Aashka (43:26)
Be there, yeah. I I wouldn’t want an AI agent or like a robot sitting next to me and commenting on the event that is happening. So yeah. moving on. economists studying post AGI scenarios have argued that once AI becomes a substitute for labor at scale, capital could become the dominant factor in the economy. Is essentially compressing wages and concentrating wealth further. Like that’s a
important fear and research that is happening currently, like concentration of wealth, concentration of power. So does that match with what you see in your foresight work and what actually can be done about it?
Melynna Garcia (44:08)
Absolutely. And does match with what I’m seeing. But again, I
think this comes back to what do we want to do about it? Because we’re not without options, right? We still have
a lot of I won’t say a lot, because that would be a lie. We still have a lifeline to make a change.
The way that I see it is I live in a world where I can support anthropic and buy their monthly subscription and
maybe by my monthly usage that will help
train an AGI in the future. And in that
world I am contributing to a future that might displace me economically, right?
I think we have a choice here to make.
Do we want to participate in that displacement? If we don’t, then we probably wouldn’t we shouldn’t be supporting these companies to begin with. And so
I think that becomes a problem. Like we for some reason have given up and we’ve given
up accountability as well. We’ve given
Aashka (45:09)
Yeah.
Melynna Garcia (45:09)
up accountability in how we approach this whole thing. Like we know something is happening. We see this storm. We’ve gotten the forecast, and still we’re just
standing then going like I think it’s gonna rain and we have no umbrella it’s like we’re just we’re just asking to be wet and
Aashka (45:26)
That’s a great analogy, yeah.
Melynna Garcia (45:28)
so it yeah it it’s it’s this weird place to be
Yeah.
Aashka (45:33)
Yeah. Okay.
Melynna Garcia (45:34)
I I think
that one of the things that I am seeing
and one of the things that I think that can be done specifically in the United States, right? Because I only have a a good idea of what’s going on here is two things, like I I was mentioning, being more intentional about how we’re using our economic leverage to impact the futures that we want to live in, and two
vote responsibly because while AI policy right now is
just starting to trickle in into the political floors,
this will become a huge thing in two years. And I think more people need to be aware of what what’s happening. Because we’re not
just talking about disenfranchisement. We’re not talking about loss like loss of control. We’re talking about a great deal of issues that will impact all of us.
And if currently we’re seeing that capabilities are already showing some not great things, then we should
probably make sure that our representatives, our legislators are aware of what’s going on, they actually understand it, and they do not have a bought-in mentality to supporting these companies because they have profit to make. So I think
what we really need to do is take some accountability as humans.
And make
sure that we’re using our money wisely and that we’re electing
people that will actually represent
us and what is best for us.
and I’ll add a last one actually.
I think we need to change the narrative of AI
is bad, AI is doing this to us, because at the end of the
Aashka (47:10)
Yeah.
Melynna Garcia (47:10)
day, the AI isn’t doing this to us. We’re doing it to ourselves. And
Aashka (47:15)
Yeah yeah.
Melynna Garcia (47:16)
the companies only benefit from this narrative because they get to walk away from it.
But the damage is being done by us. It’s it’s a very masochistic approach. And so sometimes
I think like, Man, I should really write a paper on like in defense of AI. Because it’s not AI that’s doing this to us. It’s us buying into the damage. Yeah.
Aashka (47:30)
Yeah. Yeah. Yeah. Into it. Yeah. Yeah.
Yeah. Yeah. Yeah.
Yeah, so moving on to the next question. So a paper from Forethought Research again.
Argues that the most important lever for existential safety right now isn’t slowing dangerous AI, it’s actively accelerating specific tools. AI forecasting systems, coordination infrastructure, collective fact-checking, automated negotiation. They call it differential AI development, and they say even a few months of lead time for the right tool could flip the outcome.
Do you agree and also which tools to prioritise and who decides that, do we actually have the institutional capacity to make those calls wisely before the window closes?
Melynna Garcia (48:23)
my question here
Aashka (48:23)
Okay.
Melynna Garcia (48:24)
in terms of who decides this, it’s again,
who are the people in the room and why are they in the room, right? Because largely if you’re already in the room, it’s probably because
you designed the room, right? And the people that design
the room are probably gonna invite people that also fit in the room.
And I think
what needs to happen here is people need to get a little bit more uncomfortable and they need to introduce people that probably don’t belong in the room, that don’t understand why the room was built, and we need to
get different perspectives in. Like I like to think about
it as kind of like jury duty. We need to have
a representation of our peers judging and making these decisions. And so
when I think about this th
Aashka (49:11)
Yeah. So basically
just to give more context on this, like let’s say for example the AI race is happening, right? And people keep saying like the companies and the leaders keep saying that the race is already happening. If we don’t do it first, then other company or the country would do it first. And we are eventually gonna be in that kind of scenario or the future that we don’t want.
So with those narratives like let’s say the negotiation thing, the tools for negotiation, effective negotiations, like that can actually prevent the race from happening by negotiating the terms, like n and not having that kind of fear like if we don’t do it, someone else is eventually gonna do it. So like those kind of tools, that’s the question
Melynna Garcia (50:00)
Yeah. I I think that a lot of that fear was also invented though. And it has a purpose
Aashka (50:04)
Yeah.
Melynna Garcia (50:05)
and a benefit. And I think that’s where I have a problem with this because well for one, we should have coordination. Absolutely. We should all be sitting down on the table and figuring out how we’re gonna do this correctly. And it should not just be world leaders. It should also be the
people developing this technology and the people that are trying to look out for the protection of humanity as a whole, right?
Aashka (50:25)
Yeah.
Melynna Garcia (50:26)
And secondly, I think what happens here is
This idea that if if we don’t build it, someone else will. I
think that this is more marketing and PR to ensure that it does get built. And by creating all of this fear and all of this tension in the market, there’s a lot of money to be made. This is why we saw an explosion of data centers being built all across the world, including
Aashka (50:49)
Yeah.
Melynna Garcia (50:51)
here in my backyard. Like
They’re they’re building another data center, and we don’t really
have a specific idea of why. Why are we building these data centers? And I think
the core of it is like we don’t even understand or know
why we’re using AI or what the
the goal or purpose for AI is.
Most people will say it’s like, we’ll cure all disease, we’ll get rid of climate change. Where are the plans? There are no plans. It is very loose policy, it is very optimistic.
But essentially
the only thing that we’re seeing is that we are creating narratives where we’re seeing people push each other and they’re like, well, if if the US doesn’t build it, then China will build it. And we don’t
want China to build it because they’re an adversary. We don’t want them to have more power. And if they build it, then they will use it against us. And then we will have
no more economic power in the world stage.
But
Aashka (51:42)
Yeah, yeah.
Melynna Garcia (51:43)
what we’re seeing as like completely
Different. I of course there
are things that are happening behind governmental doors, and I’m sure that they have
their own strategy and their own way that they’re approaching it. But what I’m seeing is that the United States is creating models that can
create deep fakes that can make that can take people’s clothes off with image generation. And I’m
seeing, for example, in China where like they’re using AI to be able to automate the shopping process, right? You go into a store.
And you know that all of the product approach that’s in front of you isn’t expired. It’s in good quality. It hasn’t gotten rotten. So it’s like
it’s hard to tell what
Aashka (52:22)
Yeah.
Melynna Garcia (52:23)
is going on here because the terms and the definitions have already been determined, and they’ve been determined by the people that are making the most profit. so yeah, I I
don’t agree. I don’t know what to prioritize here. I do know
that the people that make these decisions.
should not be the people at the top of these labs. It should be humans, right? Because
if you gave me the option to build two data centers in my backyard and those data centers were specifically being used to ensure that we could train AI systems to eradicate disease, then I think that is a good use of these data centers. But if we’re using
those data centers so that it can
help me write an email.
I think we’ve lost the plot.
Aashka (53:11)
yeah.
Melynna Garcia (53:11)
And I think that’s what
that’s where we really need to determine what the risk is. We need to determine
what the use is, what the intentions are. It’s PR,
man.
Aashka (53:22)
Yeah, yeah, yeah.
Melynna Garcia (53:24)
And I s
I say this as a person who like finds himself in like this really weird spot because my
origin and introduction into AI was AI ethics, right? And I’m currently
Aashka (53:35)
yeah.
Melynna Garcia (53:36)
sitting in AI safety. And AI ethics and AI safety want the same thing, but they don’t like each other.
And I am like in between. I’m like I like both of y’all, y’all both have good points. But we should talk to each other to solve this problem. So yeah.
Aashka (53:50)
Yeah. Yeah, yeah.
Makes sense, makes sense. So moving on to the careers part,
So
you are studying foresight, so what careers can you actually build with that? And can you describe some of the roles that foresight trained people end up in? And like are these people ending up working at these frontier labs or anything of that sort to make actually powerful decisions?
Melynna Garcia (54:19)
Yeah, so a lot of my peers in the program and a lot of the foresight practitioners that I’ve come across are people that have a lot of industry experience. These are people that have
10 plus years of experience in their career. And so a lot of time when they come into foresight, they’re coming into foresight to be able to help build the future of that career. So for example, I have a classmate who was a nurse.
And she is now working with like different nursing organizations to determine what the future of nursing will look like. And that is amazing because she has a lot of value to provide, and she’s now using
these different tools and methodologies to really help expand what the next iteration will look like. some of my peers are working at big Fortune 500 companies, and when they graduate the program or while they’re in the program, they are moving
into
different roles. So these would be like a futurist in residence, innovation and strategy. Some of them are
going more into the design sector. So they’re looking into
creative strategy. Just general strategy roles or consulting. I
would say a lot of them end up in consulting.
at the moment there aren’t a lot of foresight roles available in either labs. About a year ago,
Anthropic had an insight an internal role for strategic foresight. And it was very
interesting to me because somebody sent it to me from Anthropic and they’re like, hey, what do you think about this role? And it was interesting
to me because they were looking for someone with foresight capabilities, but they were
not looking for someone with a foresight degree. And so the way that they are thinking about it’s a little bit different. the
Aashka (55:56)
Interesting.
Melynna Garcia (55:57)
way that both OpenAI and Anthropic are recruiting for foresight roles.
Are
people that come from technical backgrounds that have a very strong understanding of the future that they want to build? So these are mostly product-facing
people that they they have a very strong idea of what
tools they want to build and how these tools will help people and how they will use them. They’re not
people specifically coming from an academic background of foresight. So the way that
it’s being used in the in the labs is very different. I do see a future there.
But I don’t see a future right now. I think that maybe in a year or two, when it’s a little bit too late, these organizations
might start hiring for foresight practitioners to start looking into different things. yeah.
Aashka (56:42)
Yeah, yeah.
Yeah. I it it’s interesting that you mentioned about like the labs wanting foresight people but not wanting it from like a having a degree background So what is one resource, a book, a community or whatever that you think more young people should know about when it comes to AI and the future and f specifically for someone who is
Who
feels like, okay, I do have some foresight abilities and I would want to showcase that, like but what would be the starting point that would equip them well to do that professionally?
Melynna Garcia (57:20)
So I actually
yeah, so I actually thought about this question a lot and I actually couldn’t sleep because I was like, what do I recommend? I’m like, what do I recommend? There’s so many things that have
Aashka (57:27)
sorry about that Yeah.
Melynna Garcia (57:32)
helped me get to where I’m at that have changed the way
that I I think and see the world from like watching
Aashka (57:37)
Hmm.
Melynna Garcia (57:38)
different sci-fi movies as a kid and sci-fi series, reading sci-fi books. all of
that has impacted the way that I think about the world.
And I think that when I was like putting a lot of thought about it, I was like, I think foresight is something that’s just worn naturally. Like I
think that based on your own life experience, you have a specific perception of the
world. And I think it would be a mistake for me to say, go read this book or go read this, because
it ignores the natural signals that are naturally coming to you.
And I think what more people, especially more youth,
Aashka (58:12)
Yeah.
Melynna Garcia (58:14)
should do is that they should trust the signals that they are seeing in their environments. They should,
you know, like people say they usually have a gut feeling when they know something’s gonna happen. And
Aashka (58:23)
Uh-huh, yeah. Yeah.
Melynna Garcia (58:26)
I think that most foresight practitioners have that. For me, like I said before, I call it vibes. For other people, they’re like signals. I found a signal of this. And so I think
that really what I recommend is for people to trust what they’re seeing.
and reading it clearly and accurately because I think
a lot of times we see what’s going on and we decide to ignore it thinking, it will get better or someone will fix it. And so
yeah, I I don’t have a specific resource. I think we should we should trust ourselves there. in terms of like how to maybe
Aashka (58:54)
Yeah.
Melynna Garcia (59:00)
professionalize your foresight perception, I would say
there is a book. People can choose to read it or not, but
it’s the book that we are trained on at the University of Houston. It is written by Andy Hines and Peter Bishop.
And actually, I I’m blanking on the name, so I’m Googling it now. It’s
Aashka (59:21)
Not a problem.
Melynna Garcia (59:22)
it’s called Thinking About the Future Guidelines for Strategic Foresight. So,
Aashka (59:28)
Okay.
Melynna Garcia (59:29)
and this book essentially goes through the different like tools and methodologies that we’re being taught at the program.
And helps them think about
foresight more strategically. But yeah, I think in in this case, I think we should really be seeing what’s out there. We should really be going out. I
while I was in that trip with my sister in San Francisco, I was telling her the importance of travel. It was like you
go out into the world and you’re scanning, and
we think that we know it all, we think we’ve seen it all.
Aashka (1:00:00)
Yeah.
Melynna Garcia (1:00:01)
But in
reality, when you think about it, the the amount of scanning that we’ve done in the world is very minuscule in comparison to everything that is going on. So yeah,
I would say that people should
Aashka (1:00:14)
Yeah.
Melynna Garcia (1:00:15)
find their own resources, find their own signals, find things out.
Aashka (1:00:18)
Or maybe create
their own resources. Like if they are having these kind of
Melynna Garcia (1:00:21)
Absolutely.
Aashka (1:00:22)
gut feelings, they should write a blog post and so is there a community that is there around Foresight People that people can join and share their gut feeling in intuitions and then maybe build on top of that?
Melynna Garcia (1:00:36)
Yes. so there’s the Association of Professional Futurists. they
have a circle community and you can join it, and there’s
a lot of resources that are being shared there. There’s also a lot of work that’s being shared. So for example, the Association of Professional Futurists puts out a magazine called Compass, where different foresight practitioners across the world are writing different articles on specific themes and things that they’re seeing. I think
that
that is something that some people could enjoy. But I I
think I would second what you say. I I would say like create your own resources because
in creating your own resources, you’re creating signals for other people.
Aashka (1:01:17)
Yeah, yeah, yeah. So, we have talked about a lot of things that are not happening good or that are maybe sad or not so happy. So let’s talk about what gives you hope as a foresight professional.
Melynna Garcia (1:01:33)
I think what is currently giving me hope in a
Aashka (1:01:35)
Ha ha.
Melynna Garcia (1:01:36)
vast world of darkness is my
idea of the world model that I shared with you. So I
could I call this a human manifesto and it is a project that I’m working on. that idea
of that world, that possibility is what gives me hope. Because
it makes me feel like things will be okay, that we will
land on our feet and that we will figure things out.
That’s what keeps me going at work. That’s what keeps
me going at school. That’s what keeps me going in my personal life. But
outside of that, it can be kind of hard because I
Aashka (1:02:11)
Yeah.
Melynna Garcia (1:02:14)
am constantly online. I am
in front of my two monitors every day. And so it’s hard to ignore everything else that’s going on in the world because
it’s being broadcasted constantly on my screen. So I think that.
Aashka (1:02:27)
Yeah, yeah.
Melynna Garcia (1:02:29)
Coming up with your own t model of the world,
it’s is like significantly important because
it it allows you to think about what worlds could exist that could
benefit all of humanity and not just a few. yeah.
Aashka (1:02:48)
Yeah. can you double click on the human manifesto thing
Melynna Garcia (1:02:53)
so the human manifesto is something that I’ve been thinking about for a while. So I am an avid notes writer, and
over the last three years I’ve been thinking about what economic leverage we have in a post-AGI world and how we can make sure that that leverage is built before
AGI happens.
And in this case,
we’re talking about an AGI that can replace us, that can cost job displacement. And so
the Human Manifesto is a call to action. It outlines
the three different worlds that I mentioned one where it’s
all humans, one where it’s a hybrid model, and one where it’s machines only.
And the call to action is that people should be more involved and more conscious about how they’re using their money while they have it, because
If
we walk into a future five years from now where job displacement is amass because AGI has completely replaced the economic model as we know it, then we have no leverage. And so
while we still have leverage, we should use that power. it also touches on civic duty and being, of course, a responsible voter and voting
for people that will represent our needs now and not represent the needs of lobbyists.
Because what we’re seeing at large is that we have representatives that are showing up in Congress, but they’re not there working for us. They’re there working for the lobbyist. And that
becomes problematic. And so, yeah, the the manifesto is it’s it’s that. It’s it’s a call to action, hoping to
awaken people up to see the possibilities of this world where we could thrive and where we could live with
AI. And in it, I pitch a 70-30 model. And that model is essentially
where 70% of the workforce continues to be human and 30% of the workforce is AI. And the reason
Aashka (1:04:46)
Yeah.
Melynna Garcia (1:04:46)
why is because I think that 30% of an AI workforce would produce enough financial outputs where we could provide
UBI for people, where we could have a model
Aashka (1:04:55)
Yeah. Interesting.
Melynna Garcia (1:04:57)
where people could survive. And let’s be honest, not everyone desires to work. There are some people that are intrinsically
ambitious and they want to work and they want to create things and there are other people that don’t want to do that. And so in this model, we’re looking at people that do want to work. That we’re looking at people
Aashka (1:05:08)
Yeah.
Melynna Garcia (1:05:15)
that want to create, we’re looking at people that want to be in control of their life. And they can
do so by having economic viability by selling their labor.
Aashka (1:05:24)
Mm-hmm.
Melynna Garcia (1:05:26)
Yeah, the the hope with this is that
Maybe it will create some impact that maybe one
or two people will read it and go, like, hey, maybe there’s something here that we can develop an AI policy around that could benefit us. we’ll see what happens. I have shared
it and presented it before. I presented it while I was at the Responsible AI Institute, and I got
a really good feedback from my coworkers there. And it is something
Aashka (1:05:49)
Yeah.
Melynna Garcia (1:05:50)
that I’ve shared within the program, and I’m trying
to get more.
grounding on to ensure that this is something that makes sense to people. But there are a couple
Aashka (1:06:00)
Yeah.
Melynna Garcia (1:06:00)
of different things that I’m exploring in there. So for example, AI free zones, I’m exploring
the idea of licensing likeness and approaching digital twins in a different manner. So a lot of the work that I’m doing all comes back to this manifesto and taking action
Aashka (1:06:14)
Yeah.
Melynna Garcia (1:06:15)
and accountability for our future.
Aashka (1:06:17)
Mm. Yeah, that’s super interesting. Like I and in that seventy thirty scenario, hopefully we can get a four day work week
Melynna Garcia (1:06:30)
Yeah.
Aashka (1:06:30)
and a three day weekend. Yeah.
Melynna Garcia (1:06:33)
And I mean that that’s that’s essentially what
could happen here because what we’re thinking about is that that a human-only labor force is going to work
as long as they want to. This is optional. They’re they’re buying into it. But a labor force
Aashka (1:06:43)
Yeah, yeah,
Melynna Garcia (1:06:48)
that is hybrid, where you are going
and working out working for an employer, your
necessities at work aren’t going to diminish because you’re going to be working side to side with AI agents that can take
over a lot of the work.
Right. And so
Aashka (1:07:03)
Yeah.
Melynna Garcia (1:07:04)
the need for us to be at work will obviously decrease, but there will still be a need for us to be there. And so
that’s that’s where I was approaching. And I think that there is a very positive, almost utopian future out there that exists. We just need to make sure it gets built. And it won’t get built
if we’re buying and supporting organizations that are trying to get rid of us. And
it won’t get built if we’re buying and
if we’re voting and supporting candidates that don’t care about us. So yeah, the the other thing that I will add to this is that there are already
a lot of signals for this work and this thought process. And
I see them in AI labels. So for example, earlier in the conversation I said something about how close have tags that say like made in Bangladesh. In the future we’re gonna have tags that say made by humans.
And that is
going to psychologically affect how we decide to waste our money. And I think that that is something that is really cool
that we’re now seeing artists do when they’re putting their art out there. They’re saying, Hey, I didn’t use any art. The type of disclosure
that’s being now that we’re starting to see in
outputs is greater than supporting this thesis that maybe we want
to know.
we’re using our money. Maybe we want to know how we’re using our energy. And
maybe corporations will need to start releasing their constitutions to see how it is that they tend to support humanity as it continues to evolve. Because as it stands right now, the constitutions,
Aashka (1:08:35)
Yeah.
Melynna Garcia (1:08:38)
even though they’re not written down, they do not support human flourishment. So
Aashka (1:08:42)
Mhm. Yeah, yeah. And maybe we as humans feel feel good about paying for something that is human made. Like right now like for artisans whose craft is in revival mode right now
We would like to support those kind of artisans and we would like if it is costing us a little more than a normal made garment or anything, if we can help them survive. that’s a human nature that we have to support more humans and their work.
I had
Melynna Garcia (1:09:17)
Slowly.
Aashka (1:09:18)
one last question. how does it feel to l
live in Texas right now. I was living in Texas until twenty twenty four and you as you mentioned the data centers thing and the Stargate project happening and stuff. So how does it feel and like on a granular level, like I are the utility bills actually going up? What is happening on the ground?
Melynna Garcia (1:09:41)
So it’s kind of weird right now. And I’ll say this. So I live in a college town. I live in a college town that
had originally built a Bitcoin mining facility that recently
changed and evolved into a data center. Now we’re building a second data center, and
Stargate is only like an hour and a half away from where I live. And
Aashka (1:10:03)
okay.
Melynna Garcia (1:10:04)
so I have recently started to see that there are
More community meetings and gatherings
that I’m seeing on Meetup.com and an Eventbrite where people are saying, Hey,
we need to go talk to City Council. Why are they approving this? Why wasn’t the community informed? I think
that all throughout Texas I’m seeing this. I’ve also lived
down in the border in Brownsville and I’m also seeing that people down there are organizing to ensure that these data centers are not coming in and like polluting the environments and whatnot.
as far as utility costs goes, I have not seen an impact yet. However, I know that people an hour and a half are seeing those impacts. And they’re not just seeing it in the utility costs, they’re also seeing it in the quality of water. And
that becomes a huge issue because the areas where these data centers are being built are right now leaning more toward rural areas. And that has a great impact because these rural areas
rural areas are
usually areas where there are a lot there’s not a lot of like economic opportunities, there’s not a lot of resources, and if there are, the resources that are there are farming, agriculture, right? And so what
impact does that do if you build a data center next to a ranch and the
rancher is the one that’s supplying all of the beef to a certain area? How does that
impact the food that we’re consuming? And so there are a vast amount
of impacts that we’re already seeing
That are being ignored, but I am seeing that within the last two months, this has become a greater issue. And I can say this confidently because
when the Senate primaries were happening here in Texas,
I was going out with my partner to hear these candidates speak. And when the topic of AI came up.
They would
only breach the topic to focus on deepfakes, generate
AI-generated content that was creating child pornography, but they weren’t really
breaching the topic on capabilities, loss of control, economic disenfranchisement, and specifically what these data centers
would do in terms of environmental impacts. And now that has become a subject that more people are speaking on.
And that more people
have an interest on and a subject that I would say is convincing more people to go out and protest, whether it’s with their vote or showing up at city
council to ensure that their life isn’t being breached upon by a company with diverse intentions. So yeah, it’s it’s a little bit tricky. I say that there are more people being involved, but not enough.
Aashka (1:12:55)
Hmm, yeah, yeah. Makes sense. Yeah, that’s a good note to end this episode on and thank you so much for your time and thank you so so so much for your insightful responses. And I know it wasn’t like easy to talk about certain stuff, but still you managed to put your thoughts in the best possible way. So thank you so much and yeah, let me stop the recording.
Melynna Garcia (1:13:21)
Thank you, Aashka
