Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
Now on Colorado's Morning News. Colorado lawmakers again further delaying
the implementation of the states first in the nation artificial
intelligence law is after it became clear that negotiations between Democrats,
the tech industry, consumer advocacy groups, and unions wouldn't yield
to any results. The AI law, which is meant to
prevent the technology from being used as a tool of discrimination,
(00:22):
have led to shouting matches.
Speaker 2 (00:24):
Is there actually any law or regulation that can do
what the state legislation is attempting to do regarding AI?
What does good AI regulation and oversight look like? Well?
I had the opportunity to discuss these issues and more
with JR. Garcia. He's an AI machine learning engineer and
expert focused on AI governance, and he's the director of
Solutions Engineering with A and m IT and consulting Colorado legislature.
Speaker 3 (00:47):
They kicked the AI bill down the road here they
were trying to find a way to write a bill
to make AI non biased. Is that even possible and
feasible from your expertise with AI?
Speaker 4 (00:58):
Not that I've seen. So. The problem is that all
data is generated by humans, and humans by default have biases,
So anything that's generated by humans. You get a large
enough data set, there's going to be bias in that data.
It's almost impossible to get around it.
Speaker 3 (01:13):
What is good from your vantage point, good or smart
legislation or oversight when it comes to AI, I think transparency.
Speaker 4 (01:20):
So transparency is probably the biggest thing. So if your
data is being used to train AI models, if companies
are using your data to make decisions, there should be
use policies. You should have to accept to that in
order for them to use that data to make decisions.
So I would say transparency is the biggest thing.
Speaker 3 (01:42):
When you see these big AI groups, whether it's Elon
Musk or some of the competitors, do you have concerns
about who's overseeing AI? And simply in this may be
a jingoistic question, would you rather have the US be
the leader in AI or some other country or does
that matter because of the human bias?
Speaker 4 (01:56):
So I do think that the US should be the
leaders in AI because of countries like China that are
spending tons and tons of money tons of research around AI,
and if they get to some of these technologies before
we do, it could be a problem. We want the
US to be leaders in the space that being said,
there still should be some regulation by the US government
(02:17):
because you can't have guys like Elon and all these big,
large companies, you know, doing things like the Wild Wild
West doing everything that they want, grabbing everybody's data, doing
all this stuff. There should be some regulation, but I
don't think it should slow us down enough to where
we take a step behind China.
Speaker 3 (02:34):
What concerns you about AI, at least in its current state.
Speaker 4 (02:38):
So bias is a big thing, because AI will amplify
if there's anything bias, racist, anything like that in the
data set, AI will find it and amplify it. So
I think that's part of it. The other part of
it is the amount of data that we're giving up
to these organizations and how these data sets are being trained,
(03:00):
things like artists, creative type things that are being used
to train these data sets can be a problem because
people are able to use that and kind of generate
their own things, and the people that generate the content
don't get any compensation for it.
Speaker 3 (03:14):
Are you still positive about the good side and the
good things you see with AI?
Speaker 4 (03:18):
Yeah, one hundred percent. I think the good outweighs the bad.
But I think it's a balance between innovation and risk.
So I think we all need to be innovative, so
not only us as individuals, but also companies. We need
to start using these tools because it makes us more
efficient and better at our jobs. But there's risk associated
with that, right. The more data we give these models,
(03:40):
the more data we give these companies, the more risk
there is that some of our personal information might get
leaked out, We could get hacked. Hackers are using this
data so that they can build bad things. So it's
a balancing.
Speaker 3 (03:53):
Aunt is there. I know all industries will probably have
some sort of AI component or can benefit or to
a detriment to AI, But is there one industry that
you look at right now that says AI could totally
reform or transform this industry?
Speaker 4 (04:07):
I think healthcare. Healthcare is probably the biggest thing. Why
is there, Well, there's a lot of correlations that an
AI model can make that a human can. So there's
a lot of examples that people have been sharing around
putting their symptoms and things that they're seeing into an
AI model. In those AI models being able to predict
(04:28):
or tell those individuals what could be wrong with them,
and it's very difficult for a doctor or specific specialist
to look at things that they might not know a
whole lot about, whereas an AI model can correlate those
large amounts of data and give you something it's a
little bit more tangible.
Speaker 3 (04:47):
Sometimes, well, I would assume in an expert's hand, because
then when I hear it from you, I think, well,
isn't that just web MD? And some people are hyper
chondriacal and will look up their symptoms and think they
have something. Right.
Speaker 4 (04:56):
Yeah, it's part of that balancing act, right, So that's
it's definitely a concern, So you do want to have
somebody validate things. But I think AI can definitely transform
to the healthcare industries, probably one of the one of
the bigger industries that could be transformed by the technologies
that are coming out right.
Speaker 3 (05:13):
Now, what do we see or what do you see
with AI in the next one, five, ten years.
Speaker 4 (05:18):
It's so hard to say. It's hard to say what
happens in the next six months because everything's moving so quickly.
But we kind of started with generitive AI. The next
kind of phase of AI is going to be agentic AI,
which means agents that are going to be doing things
on your behalf. What happens beyond that is really hard
to say, but that's really what's going to be happening
in the next I would say six months to eighteen months.
Speaker 3 (05:40):
And then just to follow up and kind of bring
this full circle talking about the oversight of AI. If
I hear you right, the best way to do that
is transparency and openness. How do you regulate or oversee
or have some sort of legislation that promotes that.
Speaker 4 (05:53):
I think if a company is gathering user data or
employee data to make decisions with AI, they need to
tell you about it. So you need to be able
to opt in or opt out of those companies using
your data. So I think that's the first thing. Companies
are not going to do that by themselves. They have
to be regulated to do that. I think the US government,
are you going to have to pass laws in order
(06:14):
to require companies to have that transparency because today that
isn't the case in all states.
Speaker 2 (06:20):
JR. Garcia, AI machine learning engineer and expert focused on
AI governance and tis the director of Solutions Engineering with
A and M IT and Consulting
Now on Colorado's Morning News. Colorado lawmakers again further delaying
the implementation of the states first in the nation artificial
intelligence law is after it became clear that negotiations between Democrats,
the tech industry, consumer advocacy groups, and unions wouldn't yield
to any results. The AI law, which is meant to
prevent the technology from being used as a tool of discrimination,
(00:22):
have led to shouting matches.
Speaker 2 (00:24):
Is there actually any law or regulation that can do
what the state legislation is attempting to do regarding AI?
What does good AI regulation and oversight look like? Well?
I had the opportunity to discuss these issues and more
with JR. Garcia. He's an AI machine learning engineer and
expert focused on AI governance, and he's the director of
Solutions Engineering with A and m IT and consulting Colorado legislature.
Speaker 3 (00:47):
They kicked the AI bill down the road here they
were trying to find a way to write a bill
to make AI non biased. Is that even possible and
feasible from your expertise with AI?
Speaker 4 (00:58):
Not that I've seen. So. The problem is that all
data is generated by humans, and humans by default have biases,
So anything that's generated by humans. You get a large
enough data set, there's going to be bias in that data.
It's almost impossible to get around it.
Speaker 3 (01:13):
What is good from your vantage point, good or smart
legislation or oversight when it comes to AI, I think transparency.
Speaker 4 (01:20):
So transparency is probably the biggest thing. So if your
data is being used to train AI models, if companies
are using your data to make decisions, there should be
use policies. You should have to accept to that in
order for them to use that data to make decisions.
So I would say transparency is the biggest thing.
Speaker 3 (01:42):
When you see these big AI groups, whether it's Elon
Musk or some of the competitors, do you have concerns
about who's overseeing AI? And simply in this may be
a jingoistic question, would you rather have the US be
the leader in AI or some other country or does
that matter because of the human bias?
Speaker 4 (01:56):
So I do think that the US should be the
leaders in AI because of countries like China that are
spending tons and tons of money tons of research around AI,
and if they get to some of these technologies before
we do, it could be a problem. We want the
US to be leaders in the space that being said,
there still should be some regulation by the US government
(02:17):
because you can't have guys like Elon and all these big,
large companies, you know, doing things like the Wild Wild
West doing everything that they want, grabbing everybody's data, doing
all this stuff. There should be some regulation, but I
don't think it should slow us down enough to where
we take a step behind China.
Speaker 3 (02:34):
What concerns you about AI, at least in its current state.
Speaker 4 (02:38):
So bias is a big thing, because AI will amplify
if there's anything bias, racist, anything like that in the
data set, AI will find it and amplify it. So
I think that's part of it. The other part of
it is the amount of data that we're giving up
to these organizations and how these data sets are being trained,
(03:00):
things like artists, creative type things that are being used
to train these data sets can be a problem because
people are able to use that and kind of generate
their own things, and the people that generate the content
don't get any compensation for it.
Speaker 3 (03:14):
Are you still positive about the good side and the
good things you see with AI?
Speaker 4 (03:18):
Yeah, one hundred percent. I think the good outweighs the bad.
But I think it's a balance between innovation and risk.
So I think we all need to be innovative, so
not only us as individuals, but also companies. We need
to start using these tools because it makes us more
efficient and better at our jobs. But there's risk associated
with that, right. The more data we give these models,
(03:40):
the more data we give these companies, the more risk
there is that some of our personal information might get
leaked out, We could get hacked. Hackers are using this
data so that they can build bad things. So it's
a balancing.
Speaker 3 (03:53):
Aunt is there. I know all industries will probably have
some sort of AI component or can benefit or to
a detriment to AI, But is there one industry that
you look at right now that says AI could totally
reform or transform this industry?
Speaker 4 (04:07):
I think healthcare. Healthcare is probably the biggest thing. Why
is there, Well, there's a lot of correlations that an
AI model can make that a human can. So there's
a lot of examples that people have been sharing around
putting their symptoms and things that they're seeing into an
AI model. In those AI models being able to predict
(04:28):
or tell those individuals what could be wrong with them,
and it's very difficult for a doctor or specific specialist
to look at things that they might not know a
whole lot about, whereas an AI model can correlate those
large amounts of data and give you something it's a
little bit more tangible.
Speaker 3 (04:47):
Sometimes, well, I would assume in an expert's hand, because
then when I hear it from you, I think, well,
isn't that just web MD? And some people are hyper
chondriacal and will look up their symptoms and think they
have something. Right.
Speaker 4 (04:56):
Yeah, it's part of that balancing act, right, So that's
it's definitely a concern, So you do want to have
somebody validate things. But I think AI can definitely transform
to the healthcare industries, probably one of the one of
the bigger industries that could be transformed by the technologies
that are coming out right.
Speaker 3 (05:13):
Now, what do we see or what do you see
with AI in the next one, five, ten years.
Speaker 4 (05:18):
It's so hard to say. It's hard to say what
happens in the next six months because everything's moving so quickly.
But we kind of started with generitive AI. The next
kind of phase of AI is going to be agentic AI,
which means agents that are going to be doing things
on your behalf. What happens beyond that is really hard
to say, but that's really what's going to be happening
in the next I would say six months to eighteen months.
Speaker 3 (05:40):
And then just to follow up and kind of bring
this full circle talking about the oversight of AI. If
I hear you right, the best way to do that
is transparency and openness. How do you regulate or oversee
or have some sort of legislation that promotes that.
Speaker 4 (05:53):
I think if a company is gathering user data or
employee data to make decisions with AI, they need to
tell you about it. So you need to be able
to opt in or opt out of those companies using
your data. So I think that's the first thing. Companies
are not going to do that by themselves. They have
to be regulated to do that. I think the US government,
are you going to have to pass laws in order
(06:14):
to require companies to have that transparency because today that
isn't the case in all states.
Speaker 2 (06:20):
JR. Garcia, AI machine learning engineer and expert focused on
AI governance and tis the director of Solutions Engineering with
A and M IT and Consulting
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