Robotic ramblings and Smarty® solutions

In an age where we treat digital devices like freshly-grown appendages, our obsession with Generative AI is only natural. With minimal prompting, GenAI can write songs, novels, poetry, and more. Some GenAI creations turn out pretty okay, and some turn out less okay (look at this bear/fish hybrid we made), but that’s part of the fun. 

As GenAI becomes more prominent in our personal and work lives, so too do concerns about its effects. Artists, writers, marketers, and developers alike are becoming nervous that robots will replace them in their careers. The dystopian future isn’t so near, though, as we can easily recognize robots from humans…or can we?

While the capabilities of AI and all the things it can do may seem daunting, we should also recognize how freakin’ cool it is! We may even be able to channel its awesomeness for good.

At the end of this blog, we’ll provide tips on optimizing your AI outcomes because businesses are currently jumping on the GenAI wagon, hoping to save on labor costs and increase efficiency. However, does it really do everything they hope it does?

​​GenAI is ineffective and problematic when businesses use it without ensuring their initial data is clean and then rely solely on the gibberish it spits out, taking it as fact. 

If you’re working with images or video, it’s easy to spot the often hilarious errors AI art is known for. (How many fingers are on a human hand, again?) When employing AI for data analysis, errors can be much harder to identify. You could be sinking time and money into GenAI and using those results to make strategic decisions without realizing your data is inaccurate.

How, then, as puny humans, can we become allies with our new robot overlords and use the power of AI for good?  Our short answer is to steer the technology with more precise, better inputs. In short, to make your AI projects subject to human judgment. Remember, you’re smarter than GenAI. 

An algorithm can’t be creative or use critical thinking. It doesn’t have the emotional intelligence or the ability to solve complex problems without the proper guidance. It simply spits out what you tell it to. Ai is terrific at performing monotonous and repetitive tasks. You get the most out of AI when you use it as a guide for improving processes while understanding its limitations and taking the proper steps to combat those shortcomings. 

For a more in-depth answer, keep reading!

The problem: AI amplifies your bad data

This robot is limited by what you, the user, feed it as much as by the company incorporating GenAI results. If you were to type in “Create an image of an intergalactic space battle” to a GenAI tool, you could probably get some pretty fascinating results. 

But anyone who has toyed with AI-generated art understands that the second you involve human subjects, combine disparate ideas, or fail to flesh out your prompt, the results are pure nightmare fuel. 

The same principles apply when looping GenAI into business critical, data rich projects. Proper input data structuring is essential when getting the correct result from a bot. Many businesses and organizations use GenAI to draft reports, analyze datasets, model projections, compare and contrast locales through address data points, and more. It’s not enough to just highlight a section of data and copy/paste it into the bot. Your prompt needs to be structured, detailed, and specific. 

Contrary to popular belief, GenAI can’t read your mind or magically repair bad input data.  If you mistype a house number or misspell a street name, the AI machine won’t know how to correct this information before calculating the output. It assumes you’re the expert, and what you enter into it is 100% accurate. Thinking AI is an all-knowing power and automatic corrector leads to incredibly unreliable outcomes, even with the strictest parameters.

Smarty’s solution: Only accurate data

Your business is probably using address data daily to mail packages, streamline the checkout experience, speed up form-fills, or create accurate risk assessments, to name a few. The best way to make sure that the address data you want to analyze is being entered correctly is to ensure it’s verified, standardized, and geocoded to perfection. 

That’s why Smarty® offers solutions for the broadest of address intelligence use cases, such as International Address Autocomplete, down to the most specific, minute pieces of an address, like US Secondary Address Data. Your data will always be clean and accurate while using these products. YAY!

Operating on bad data will result in bad AI results because, believe it or not, artificial intelligence is… well… artificial and slightly unintelligent. We can all take a deep breath, knowing that it’s not as smart as the human race, but it’s a great tool to get our creative juices flowing and provide outlines and structure to our sometimes mushy, half-baked ideas. 

GenAI has the capability to enhance our datasets, as long as we’re cautious to double-check the information it spits back out to us. 

As much as we focus on the input parameters, we should also focus on our own “user error” potential. Running the address information we wish AI to analyze for us through a verification process or *cough* a fantastic set of APIs in a fabulous address intelligence suite will be a great way to get started.

Conclusion

It’s great to use AI capabilities to enhance what we’ve already got going on, but first, we need to put some things into check. Before you unleash the powers of GenAI, ask yourself the following questions: 

1. Is the data I want AI to work its magic on standardized, validated, and clean?
2. Is the GenAI tool I’m using capable of providing the results I’m looking for?
3. Is the prompt I’m using clear enough that a 5-year-old would know what to do with it?

After getting the results from the AI search, ask yourself these questions:

1. How reliable is the information I received? Is it verifiable in any other source?
2. Did I ask GenAI to provide sources or explanations defending it’s analysis, and were those explanations and sources viable?
3. Are the results returned useful to me and my organization?

By asking and answering each question, you’re ready to prove you’re smarter than a robot. Let those analyses fly and reap the rewards of using AI to build on your already great organizations.