EP. 13 - Pros and Cons of AI: When to Embrace It and When to Be Cautious

Speaker 1:
Everyone. Welcome to our deep dive today. You know, AI is everywhere these days, so we're gonna try to get a clearer picture of where it really shines and where it could, you know, lead us astray.

Speaker 2:
Yeah. It's all over the place, isn't it?

Speaker 1:
We're focusing on this article from MeasureOne. Have you seen it?

Speaker 2:
Yeah. Pros and cons of AI, when to embrace it, and when to be cautious.

Speaker 1:
Right. It just came out on November 4, 2024.

Speaker 2:
Catchy title.

Speaker 1:
It is. And they get right to the heart of it.

Speaker 2:
Mhmm. You know, everyone's talking about AI's potential, and it it's pretty compelling. Like, simplifying complex processes, boosting efficiency, uncovering data insights way faster than we could on our own. Like, in customer service or compliance.

Speaker 1:
Yeah. AI could really streamline tasks, you know, reduce human errors, free up employees to focus on strategy instead of just, like, you know, busy work.

Speaker 2:
Imagine what they could do for insurance paperwork.

Speaker 1:
Oh, yeah. Which I think we've all had our struggles with.

Speaker 2:
Absolutely. But that's just one side of the coin, right? The article also talks about the potential downsides.

Speaker 1:
Right. It basically says that if AI isn't implemented carefully, it could really backfire.

Speaker 2:
Yeah. It's like handing someone a powerful tool without any instructions. You really need to know what you're doing.

Speaker 1:
So true. One major risk is the potential damage to a company's reputation, you know, and to data privacy if things like transparency and ethics aren't prioritized from the get-go.

Speaker 2:
Yeah. So it's not just about efficiency. It's about trust too.

Speaker 1:
Absolutely. And we've seen real-world examples where things haven't gone as planned. Like, the article mentions AI-driven lending platforms that unintentionally ended up discriminating against certain groups.

Speaker 2:
Really?

Speaker 1:
Yeah. Leading to legal issues, and it's a reminder that AI isn't inherently neutral. We need to be really vigilant.

Speaker 2:
Okay. So it's complex. On one hand, there's huge potential, and on the other, there are real risks if we're not careful.

Speaker 1:
Exactly. And this leads to a really interesting example in the article about the 2016 election.

Speaker 2:
Oh, yeah. And the role AI played.

Speaker 1:
With those algorithms on social media, how they might have contributed to spreading misinformation and amplifying divisive content? I think this is where it gets really interesting for everyone listening.

Speaker 2:
You know? We've all seen how algorithms shape our online experiences on social media, even just the news articles that pop up in our feeds.

Speaker 1:
Yeah. It's very personalized, but it's also being curated by AI. How much influence does that actually have on us, on our perceptions and our decisions, especially with the 2024 election coming up?

Speaker 2:
Yeah. It's something to think about. The article suggests that in 2016, those algorithms might have inadvertently swayed public opinion and eroded trust in the electoral process.

Speaker 1:
Yeah. You know, by feeding people information that just confirmed their existing biases.

Speaker 2:
That's a bit unsettling.

Speaker 1:
Yeah. It makes you wonder how we can make sure AI is used responsibly, especially in contexts that have such a big impact on society.

Speaker 2:
So where do we go from here?

Speaker 1:
That's the question, isn't it? What are the solutions?

Speaker 2:
Well, the article talks about choosing AI tools with strong safeguards, what they call guardrails.

Speaker 1:
Guardrails?

Speaker 2:
Yeah. Basically, building in transparency, error checks, data protection, and clear boundaries for what AI is allowed to do.

Speaker 1:
Okay. So it's not about rejecting AI altogether. It's about being strategic and, you know, setting those boundaries and guidelines.

Speaker 2:
Exactly. Asking the tough questions up front. Like, where could this go wrong?

Speaker 1:
What biases do we need to watch out for? How can we ensure human oversight and accountability?

Speaker 2:
And the article highlights MeasureOne's approach to document processing as a positive example.

Speaker 1:
Yeah. They seem to be doing things the right way.

Speaker 2:
Right. MeasureOne combines AI assistance with a strict set of rules. It's not just letting the algorithms run wild.

Speaker 1:
They're using AI's power, but within a framework that ensures accuracy and control.

Speaker 2:
So they're using AI to optimize, but maintaining human oversight and control.

Speaker 1:
Precisely. And they've applied this specifically to auto insurance verification where precision is key.

Speaker 2:
You don't want errors there?

Speaker 1:
No. You don't. It's about peace of mind – AI working with you, not potentially against you.

Speaker 2:
Find that balance between AI's capabilities and, you know, human control and ethical considerations.

Speaker 1:
Exactly. Okay. So we've covered a lot.

Speaker 2:
We've seen the potential of AI, the risks, and the importance of safeguards. Where do we go from here? What are your thoughts?

Speaker 1:
Well, the article doesn't have all the answers, but it does emphasize that the future of AI is in our hands. It's about the choices we make, how we develop and integrate this technology.

Speaker 2:
I like that. It's not just about watching this evolution happen. We're active participants in shaping it.

Speaker 1:
Exactly. But how do we do that?

Speaker 2:
Yeah. AI can feel pretty complex and intimidating, especially for someone like me who's not a tech expert.

Speaker 1:
You bring up a good point. Understanding doesn't require you to be a programmer. It's about developing that critical awareness of how AI is being used and asking the right questions.

Speaker 2:
Like, when you see an AI-powered tool or service, think about what data is it using. How are the algorithms making decisions? Are there potential biases?

Speaker 1:
So being informed consumers, not just of products, but of the tech itself, we need to understand how it works at least on a basic level, so we can make choices about how we engage with it.

Speaker 2:
Right. And that awareness extends to the companies developing these technologies. Are they transparent? Are they considering the societal impact?

Speaker 1:
These are questions we should be asking. So holding these companies accountable, pushing for AI that aligns with our values.

Speaker 2:
Exactly. And the article gives an example of a company that's trying to do just that. Remember MeasureOne?

Speaker 1:
Yeah. The document processing done.

Speaker 2:
Right?

Speaker 1:
Right. They go into their approach, which they call deterministic document processing.

Speaker 2:
Okay. I have to admit that sounds a little technical. What does that even mean?

Speaker 1:
Think of it this way. Most AI systems learn from data and use that learning to make predictions or decisions, but those predictions can be unpredictable. With deterministic document processing, MeasureOne combines AI with strict predefined rules. So instead of letting the algorithm make all the calls, there's human control and logic built in.

Speaker 2:
So it's like the AI is doing the work, but with a human supervisor checking to make sure it's accurate and follows the rules.

Speaker 1:
That's a great way to put it. It's like having a super-efficient assistant who always double-checks their work and never goes off script, and they use this for tasks like auto insurance verification where accuracy is crucial.

Speaker 2:
Right. You don't want any surprises there.

Speaker 1:
Definitely not. No insurance headaches because of an algorithm's mistake. That's what's interesting about their approach.

Speaker 2:
They're finding that sweet spot between using AI's power to streamline things and maintaining human oversight to make sure it's accurate and to minimize risk.

Speaker 1:
It sounds like a promising model. They seem to be walking the walk when it comes to responsible AI.

Speaker 2:
It's certainly worth paying attention to, and they're not alone. There are other companies and organizations working on ethical frameworks and guidelines for AI.

Speaker 1:
That's encouraging. It sounds like there's a growing awareness of the need to approach this technology cautiously and with foresight.

Speaker 2:
Definitely. And that's where the article leaves us with a sense of both the potential and the responsibility we have as we navigate this new AI era.

Speaker 1:
Okay. So if we zoom out and look at the big picture, what's the key takeaway for our listeners?

Speaker 2:
I'd say it's this: AI is powerful with incredible potential to change things, but it's not magic and it comes with real risks.

Speaker 1:
The future of AI depends on the choices we make today. It's about being informed, asking critical questions, and demanding that AI be developed and used responsibly.

Speaker 2:
We can't just sit back and let technology dictate our future. We need to be involved in shaping it.

Speaker 1:
So what can our listeners do to be part of that conversation?

Speaker 2:
Well, I'd encourage everyone to go beyond this deep dive and keep exploring AI.

Speaker 1:
Okay. So you're saying this is just the starting point?

Speaker 2:
Yeah. What are some resources or actions people can take?

Speaker 1:
Absolutely. There are tons of great resources out there like the AI Now Institute or the Partnership on AI. They're doing great work on the societal impacts of AI and advocating for responsible development.

Speaker 2:
That's like a good starting point.

Speaker 1:
Yep.

Speaker 2:
What about on a personal level? What can people do in their everyday lives?

Speaker 1:
Be mindful of the AI you're interacting with. Ask questions about the products and services you use. Are they transparent about how their AI works?

Speaker 2:
Do they have policies to address bias or potential harm?

Speaker 1:
You can even contact companies directly and share your concerns or support for responsible AI.

Speaker 2:
So it's about being an informed and engaged consumer, voting with our wallets and our voices.

Speaker 1:
Exactly. And don't underestimate the power of conversation.

Speaker 2:
Talk to your friends, family, colleagues. The more we raise awareness and have thoughtful discussions about AI, the better equipped we'll be to shape its development in a way that benefits everyone.

Speaker 1:
We can all play a role in making sure AI is used for good. And remember, this isn't about fearing AI or rejecting it. It's about understanding its potential and its limitations and working together to ensure it's used ethically and responsibly.

Speaker 2:
That's a great point. AI is a powerful tool, but it's up to us to guide its development and make sure it's used ethically and responsibly.

Speaker 1:
Well said. And if you're interested in a company that's putting these principles into practice, check out MeasureOne. They're a great example of how AI can be used to improve efficiency while keeping human oversight and control.

Speaker 2:
Great reminder. Thanks for joining us today for this deep dive into AI. I hope you're walking away feeling informed, empowered, and ready to engage in the conversation about the future of this incredible technology.

Speaker 1:
It's been a pleasure. Until next time.