BlastPoint Deep Dive Podcast

Thought Leadership Blog_Alison
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Tom: [00:00:00] Welcome to, uh, the Blast Point, deep Dive. I'm Tom and uh

Anna: oh, Anna.

Tom: And we're kicking off something kind of new today, so we're really excited about it. It's called blast points thought leadership series. And uh, yeah, it's basically, um, well every quarter we're gonna be bringing you these short but really focused looks at what's happening with AI data and strategy and to kind of get the ball rolling.

You know, for this first one we're diving into the perspective of BLA point's own CEO and co-founder.

Mm-hmm.

Tom: Allison Alvarez and specifically how she thinks businesses can and should integrate AI effectively.

Anna: That's right. Allison has been sharing a ton of her expertise on this in her latest blog posts.

So yeah, what we wanna do today is just break down some of her main ideas, give everyone listening, a really solid understanding of what to think about when you're looking to, you know, use AI in your own business. And we're really gonna be drawing on Allison's experience here. So it's kind of straight from the source in a way.

Tom: Absolutely. So why don't we just jump right in. Allison, right off the bat [00:01:00] kind of emphasizes this idea that, you know, we gotta get real. About what AI is, it's a tool. Mm-hmm. It is not, you know, magic. It's not something that you can just plug in and you know, all your problems just vanish.

Anna: Absolutely.

She really emphasizes that, you know, AI can be super powerful. It can be amazing for certain tasks. Um, you know, things like automating processes that are repetitive or Right. You know, looking at massive amounts of data. Yeah. Trying to find those patterns that would take us forever to spot as humans, you know?

Yeah. But it's not, at least not yet at a point where it can just replace us making decisions.

Tom: Right.

Anna: You know, replace that human judgment.

Tom: She uses this really interesting analogy in the blog post. She says, we should think of [00:02:00] AI like that coworker.

Anna: Oh yeah. That's a good one. Who

Tom: can be super capable, even brilliant sometimes,

Anna: right?

Right.

Tom: But also prone to just

Anna: making mistakes. Yeah.

Tom: Making those, yeah. Those strange mistakes.

Anna: And I think that's really interesting because what she's getting at there is that just like with that coworker,

yeah.

Anna: You need to have checks and balances. You need to have systems in place. Yeah. Where you're not just blindly trusting what they say.

You know? She even has some real world examples where, you know, people relied too much on AI and. Things went wrong. Right. You know, they didn't have that human oversight and it caused problems. Like remember those? Uh

Yeah,

Anna: those AI powered legal tools. Oh,

Tom: yeah. Yeah.

Anna: That were making up case citations, like

Tom: Yeah.

Can you imagine just

Anna: a complete mess legally if you were relying on that?

Tom: And it's not just the legal field, right? Right. I mean, she talks about that airline chatbot. Yeah. That was like in Invent and Discounts.

Oh, right. And

Tom: that's not just, you know, little whoopsie that's, yeah, he's, [00:03:00] it's, yeah. That could be a big financial problem for the company, maybe even legal issues.

Right?

Anna: Absolutely. And I think those examples really drive home what Allison's saying. Yeah. Even if the AI seems to be giving you the right answer, you gotta verify. Especially if you're gonna use it in some way that could affect your business, your customers, or your reputation. It's about being thoughtful, you know, being smart about these technologies.

It

Tom: is, it is. So, another thing that Allison really delves into, and it's, you know, it's pretty important to understand about ai.

Mm-hmm.

Tom: How it actually learns, and it all comes down to something called training data.

Mm-hmm.

Tom: And she makes it clear the AI models. They learn from this data and if the data isn't perfect,

Anna: right, the AI

Tom: won't be either.

Yeah. Right.

Anna: So think of training data as just this huge mountain of information. Yeah. It could be text, images, code, you name it. And it's basically fed to the AI system so they can learn to see patterns and Yeah. Make predictions. But the thing is, if that data itself. Already has biases or [00:04:00] problems. Like say if you're looking at data about successful employees and certain demographics just aren't represented well.

Right. An AI tool that's trained on that data could end up even unintentionally kind of repeating. Mm-hmm. Those biases in its decisions.

Tom: Yeah. So basically you can't just plug in the AI. Hmm. Assume it's objective and let it run wild.

Anna: No, no. You

Tom: really gotta look closely at what it's learning from.

Anna: Yeah. And Allison says it's not enough to just look at the data before you also have to really test, right.

The outputs, the results the AI is giving you. Yeah. Make sure it's accurate and fair across the board for all different kinds of situations and groups. And that's really what responsible AI is all about.

Tom: Yeah. And you know, that brings up another point that Allison makes that's really interesting. That how we use ai, how we interact with it, can actually feed back into its training.

Anna: Yeah. It's almost like a loop, right? Yeah. Yeah. And, and it has some implications for our data and, you know, our privacy.

Yeah.

Anna: So think about it, when you use, you know, those. Free [00:05:00] AI tools or the really cheap ones, the providers, they're often using the data from your interactions to keep training their models to make 'em better, right?

So it's something to keep in mind, especially if you're sharing, you know, any sensitive information. Allison's really strong about this. She says businesses need to really read. Those terms of service. Mm-hmm. Read those license agreements before they start integrating AI tools.

Tom: Makes sense. We all kind of just click through those.

But with AI it sounds like it's really worth taking the time.

Anna: Yeah, totally. Especially when you're talking about protecting your business' information. Right. Or the data of your customers, you know, that's really key.

Tom: Absolutely. Absolutely. And you know, Allison also looks ahead a bit and talks about all this stuff happening with AI regulation.

Yeah. Governments all over the world are starting to pay attention. So it's definitely on our radar as businesses.

Anna: Yeah. She brings up the possibility that in the future we might have to be more upfront about when we're using ai, like, you know, if you're using it to write marketing content. Yeah. Or maybe to [00:06:00] help out with customer service, you know?

Mm-hmm. And as those data privacy laws keep changing, they're probably gonna have an impact on how we're allowed to use AI too.

Tom: Makes sense. So basically what she's saying is that being transparent right now.

Anna: Mm.

Tom: Even going above and beyond.

Anna: Mm-hmm.

Tom: Being ethical in how we use AI could be a really good move in the long run.

Anna: Absolutely.

Tom: Even something as simple as just letting customers know when they're talking to ai Right. Could help build trust.

Anna: Yeah, absolutely.

Tom: So. I mean, it sounds like Alison has given us a lot to be cautious about, but she's saying we should just avoid AI altogether.

Anna: Oh, definitely not. I mean, she's all about being careful and thinking critically, but she also points out a bunch of areas where AI can really help businesses when it's used correctly.

Of course. Right. For example, you know all those AI powered text generation tools that are out there? Yeah, yeah. Chat, GPT, Jasper, Claude, all those. Allison says they can be super useful for. Brainstorming ideas for cleaning up your [00:07:00] writing for summarizing information. Yeah. But the key here is that you still gotta have a human look it over before you hit publish.

Tom: Right. So it's at a partnership. Right. AI is boosting what we can do, but not replacing us. We still gotta think critically.

Anna: Exactly.

Tom: Makes total sense. I know she mentions those note taking AI tools too.

Anna: Oh yeah. Things like Otter do AI and gong.io. Mm-hmm. Those can be amazing time savers, especially for teams.

Tom: Right? 'cause they can take all that transcription that's summarized and work Yeah. Off our plates.

Anna: Exactly. And you know, for software developers, there's tools like GitHub copilot that can really speed up code, and especially when you're working on really complicated stuff.

Oh yeah.

Anna: And then there's all those AI image generation platforms like Mid Journey DLE, right.

You know, the possibilities for Creon visuals are just incredible with those.

They are, yeah.

Anna: But Allison reminds us that there are, you know, some ethical questions we gotta think about there. Yeah. Especially when it comes to intellectual property and how it affects artists.

Tom: Right. So as we're wrapping up here, I'm [00:08:00] curious, what do you think of the key takeaways from Allison's perspective?

Anna: Well, her main point, I think, is that AI is just becoming more and more woven into how our businesses work. Even how we live our daily lives. Right.

Right.

Anna: And that puts a big responsibility on leaders, you know, to think carefully about how we adopt it.

Tom: Yeah. To

Anna: make sure we're doing it ethically and being open about it.

Tom: Yeah. She really keeps coming back to that idea, right. That AI is a tool.

Anna: Mm-hmm.

Tom: And it can make us better, but it doesn't replace us. You

Anna: still

Tom: gotta be in charge, make the decisions, and be a little skeptical of what it spits out.

Anna: Absolutely. And I think it's important to point out that blast point itself.

You know, we're all about providing AI solutions that help businesses understand their markets, but we do it responsibly, which is really at the heart of what Allison's talking about. And her final thought is a powerful one. You gotta approach AI integration like you would any other big decision for your business.

Tom: Mm-hmm.

Anna: Weigh the good and the bad. Really think it through.

Tom: That's solid advice. Mm-hmm. [00:09:00] Gives you a lot to chew on as you think about, you know, how AI fits into your own company, your own work. Definitely.

Anna: Thinking about all the examples we talked about, it's like what are the things you do in your work that AI could actually help with, you know, but always remembering that human element needs to be there too.

Tom: Absolutely. Absolutely. And of course, if you enjoyed this deep dive into data and ai, make sure to subscribe to the Blast Point Deep Dive podcast for more amazing stories from the cutting edge of technology. We'll be back soon with another episode exploring how data and AI are shaping the world around us.

Anna: Until then, keep exploring, keep learning, and keep pushing the boundaries of what's possible. We'll be here to guide you every step of the way.

Tom: Thanks for joining us.