FORREST BRAZAEL: Well, hello and welcome
to "AI, the Future of Us," which is a podcast-style video
series that explores the ways in which AI is shaping our future
and how we can prepare for the changes that lie ahead.
I'm your host, Forrest Brazael.
And today, we're joined by Firat Tekiner, who
is a product manager at Google Cloud focused
on data and analytics.
Firat, it's great to have you.
Thanks for being here today.
FIRAT TEKINER: Thank you, Forrest.
Good to see you.
How are you?
FORREST BRAZAEL: I'm doing well, thank you.
But we are going to be talking today
about how AI impacts the future of business analysts,
specifically.
And I think maybe the best place to start
is to talk a little bit about your background in this area.
Firat, so can you tell us a little bit about your expertise
in the field of data and AI?
How did you get into the work that you're doing now?
FIRAT TEKINER: Thank you.
It's interesting.
So I did my PhD many, many years ago in reinforcement
learning in AI, but no one wanted to pay for my skills.
I did my postdocs and became an academic.
And it's interesting that 20 years ago, it was popular,
but it wasn't in the business area at all.
So I moved into data analytics, continuing to do AI as well.
So I worked with world's largest organizations,
helping them to build that data analytics environments
and such, and then came to Google, building
interesting products for our customers.
FORREST BRAZAEL: So you're sort of an undercover AI
expert in the field of data, which
is perfect for the conversation that we're having.
So with that said, what do you find
most fascinating about where we're at in AI right now,
Firat?
Maybe especially with the advances in generative AI
that we've seen over the last few years,
what's exciting right now?
FIRAT TEKINER: I think one of the challenges
throughout the years is difficulty
on getting the environments into the hands of the AI
practitioners.
So it was very expensive.
They were on the very few people can do it.
And realizing the return on investments
for the organizations were very difficult.
So what we are seeing now is increased interest
because tools are becoming such that people
can see the benefits of AI in their day-to-day lives.
And that's what generative AI is giving us.
So using something like Bard, for example,
and writing some questions to them,
getting some ideas or some articles
is really helping us in terms of the productivity.
That will impact everyone.
It is not just going to be the people who
are experts in the area, but we are really broadening it.
And I don't want to use the democratization,
but we are really democratizing the AI to the masses as well.
FORREST BRAZAEL: Yeah, well, I think you're
right on about that, Firat.
And I mean, even more than that, you've
started to dive into what does this mean for specific roles,
for specific people, even beyond just
that narrow subset of, quote unquote, "AI experts?"
And that leads us right back to where we started, which
is with business analysts.
So let's say I'm a business analyst right now.
I've been doing this for a few years.
I've got established existing workflows.
How do you see AI affecting my field in the next few years?
What impact do you think it's going to have on me?
FIRAT TEKINER: I think it is interesting, right?
And I'll start with a dream.
My dream is that, as a business analyst, you come.
And what you have in your mind you just
articulate as nature language.
Give me the top 10 products that we
sold within the past 10 weeks.
It is a typical BI dashboard at the end of the day.
Imagine coming and doing it that way
and accessing to the dashboard straight away.
Or the other part of this is that you don't really
need to go and do the data engineering.
The system will build everything for you,
and you'll be able to start using that.
That doesn't mean that the data analysts will not be there
because someone really needs to still look
into things like the data quality,
whether it is using the right sources,
whether it has the most refreshed data and such as
well.
And someone really needs to bring that context
and bring that know-how from the business side into that
and articulate what those results are.
So the business sides will be there,
but their productivity will be uplifted.
They are not going to spend time on what
are these APIs or the data types that I
need to bring in to be able to massage this data
and show this dashboard?
That will be really--
there'll be a catalyst from the generative AI side of things.
We'll get to the results faster, and we'll
spend more time on activating the business problems
and having more impact to it as well.
FORREST BRAZAEL: Yes, I well-remember
working for a BI company years ago and wrangling
with their custom DSL and trying to figure out
how to get past that to the questions that I wanted to ask.
And bringing that natural language in
is, I think, exciting because of the barriers
it can remove between us and the interesting questions.
What do you think--
I mean, alongside of the productivity increases,
we know there are potentially some ethical considerations
to applying automated intelligence, generative AI,
to some of the things that business analysts do.
So what do you think are some of these pressing ethical
considerations surrounding the integration of AI
with a business analyst's work?
FIRAT TEKINER: And that's a very good question.
And that's one of the things that we'll be seeing a lot.
For example, the robots and I want to call them the robots.
So I've been explaining this to my eight-year-old.
So she comes with-- and Daddy, how can we build--
how can I ask questions and get these results?
Because I've been telling her about everything
around the Bard and ChatGPT, such over the world.
And she was like, how can it get me all of this information?
It's human beings building the algorithms.
It is processing the data and the content
that we have been generating throughout the years
and decades and centuries in a sense, which is what we are
feeding into the models here.
So, naturally, our thinking is changing throughout the years
as well.
Some of the things that we found maybe acceptable, which
we are realizing they are not the right things
and right attitudes anymore, because we are evolving.
Systems, unfortunately, don't see it that way.
We are feeding the information as one go.
They are not separating all the information out there
on the internet.
As a result, they come with biases.
They are trained on data that can be biased.
So we need to be mindful of that.
Also, there's privacy issues as well.
Who owns the data, where the data sources are coming from?
This is an important aspect of it.
And transparency is important, right?
So how did you get to that information?
How could I be sure that it is the correct information as well
that you are displacing?
The one thing about the LLMs is they
are convincing online as well.
The hallucination that the term that
came from Google researchers is really so convincing
when it gives out the results that you believe that that's
the correct information.
How do you know that this is correct information?
Or who decides what is correct or not as well?
So we are going to be seeing challenges around that a lot.
FORREST BRAZAEL: No question.
And of course, we know some of these questions
have been around for a while.
Bias is not a new problem in the data world.
Making sure you have clean, accurate data
has long been a challenge.
But it seems like some of these things
are being-- they're being accelerated.
They're being thrust more to the forefront
by the speed with which we're now
able to produce some of this stuff, which is both exciting
and maybe a little bit terrifying.
So the last thing I want to ask you about
is just really, practically, what
are some key skills that I need as a business analyst to be
able to remain successful to--
I don't want to say AI-proof my career exactly,
but to continue to stay relevant and take
advantage of these things that are coming out?
FIRAT TEKINER: Right.
So one of the things that I would stay
up-to-date with the latest developments.
So try understanding-- it is a rapidly-evolving field.
We'll be seeing a lot more changes.
It is like really trying to catch up a very fast moving
train, if you like.
So try to understand what are the key areas to focus on.
Try to stay up-to-date.
Learn about exactly what you mentioned
about the ethical considerations around surrounding AI
as well because we really want to give the right answers.
And develop skills that will be in demand in the future.
AI is likely to automate some of the jobs, but not everything.
If you have the right background,
if you have the right foundations,
you'll be able to articulate the results that comes out of it.
If you are able to put your understanding
and your viewpoint on it, you'll be really leading this.
And most importantly-- and I remember one of my first
mentors in life telling me this--
be open to change, be bold.
It is not about I know this particular system anymore.
Systems are going to change.
But I know the skills.
I understand how to work with data.
I understand how to get the insights
and articulate the insights from the data.
And be responsible as well.
AI is going to be a really powerful tool.
We need to use that responsibly.
These are the key things.
If you have the right foundations,
I think you'll be succeeding.
That's how I see it.
FORREST BRAZAEL: I think it all comes down
to responsibility, accountability,
and trust, doesn't it?
Always has, it always will.
Thank you so much for joining us today, Firat.
It's been incredibly insightful to hear
your thoughts on the impact and the effective use of AI.
And of course, we all look forward
to seeing how AI will continue to shape the world around us.
And we hope that everybody watching this
will be inspired to embrace its potential
and its opportunities.
So thank you so much, Firat.
Have a great rest of your day.
FIRAT TEKINER: And thanks for having me, Forrest.
Thank you.
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