INBOX INSIGHTS, October 2, 2024: Getting Lost in AI, Economic Indicators Part 1 - Trust Insights Marketing Analytics Consulting

INBOX INSIGHTS: Getting Lost in AI, Economic Indicators Part 1 (10/2) :: View in browser

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What Happens When You Get Lost in Generative AI?

I hate everything I’m writing today. I know I’m not alone. You probably hate it too. Ha!

But in all seriousness, I (and likely you) read Ann Handley’s newsletter over the weekend, where she begged and pleaded with us not to use AI to write the first draft.

I will admit, I am guilty of doing just this. And as a result, I am seeing the results that Ann warned us all about.

“The first draft is the thinking draft. That’s where you need to be fully present. On board. Just you and your glorious ideas.

Otherwise, you undermine yourself. You shortchange your growth and creativity. You put the ROBOTs first. You put yourself second.”

I have been putting myself second. I thought it was okay, that it was still me, still human. I was using tools that I had built to represent me, so what was the hard?

Well, here I am – perhaps one or two months later, and I feel like I’ve lost the ability to write the first draft on my own. I have shortchanged my growth and creativity.

Insert deep sigh here.

Ann will tell you that I do that a lot. Sigh deeply. My brain is constantly spinning and working through scenarios. When it comes to a solution or realization, I sigh. Apparently, I come to solutions in my brain often enough that my deep sighs are noticeable.

Let me clarify; while I’ve been using tools like KatieGPT, which is 100% trained on my writing and tone, I am the one editing. My edits usually alter the content so much that it’s no longer what AI generated. But I still let AI do the deep thinking for me.

Here I am, writing about how I’ve shortchanged myself because I became reliant on AI. So, what went wrong today?

I had an idea to summarize a couple of articles that had come out recently about women in the workplace and their use of AI. Gemini did a good enough job of summarizing the article into some main points. I then gave those points to KatieGPT and asked her to write a reaction post. She did. It was subpar. I gave that post to our Ideal Customer Profile that scores content. It scored about a 70 and gave some feedback. I took that feedback and gave it to KatieGPT to rewrite. She did; I re-scored the content and it was now a 90/100. This meant that it resonated with our ICP.

I hated it. I hated every single word of it. I tried to rewrite it, and I hated it even more. It had become so overthought, so convoluted that the real Katie got lost.

This is what happens with generative AI. Or rather, this is what can happen if you let it. Generative AI can do a lot of things. Great things. Amazing things. But it shouldn’t replace you, the human. It shouldn’t replace your ideas, your creativity, your ugly drafts.

This is why having a thoughtful AI integration plan is so critical. When I spoke about this at MAICON a few weeks ago, I emphasized that you need to put people first.

I didn’t follow my own advice. It happens. And I’m willing to admit it.

We get so caught up in the day-to-day that we forget to do things the “right” way instead of the “easy” way. In my case, it wasn’t even the easy way. It was lazy, and I can admit that. I always want this part of the newsletter to resonate. I want it to be authentic. And in my mind, I still had that, even if I was using a synthetic version of me.

Well, lesson learned. I commit to you (and myself) not to let generative AI create my first draft. It’s not doing me or you any good. I’m shortchanging myself, and ultimately you, the reader. If I don’t love what I’m writing, why should you?

Ok, enough groveling. You get it. I get it. To be clear, none of this was written using generative AI.

Until next week! In the meantime, I’ll be over here writing super hideous first drafts!

Is generative AI stifling your creativity like it did mine? Reach out and tell me, or come join the conversation in our free Slack Group, Analytics for Marketers.

– Katie Robbert, CEO

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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris tackle the important topic of speaker selection at events, specifically focusing on inclusivity and representation. Discover the challenges and considerations when selecting speakers for events, particularly when catering to a specific audience, like women in a particular industry. Learn valuable strategies for creating a more inclusive and diverse speaker lineup at your events, ensuring all voices are heard and represented. Gain insights from Katie and Chris’s open and honest conversation about their experiences and perspectives on this crucial issue, and find inspiration for positive change in your event planning.

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In this week’s Data Diaries, let’s do a quick review of economic indicators and what they mean. With as many unprecedented things happening pretty much all the time now – thousand-year floods, Category 4 storms forming in 2 days, labor strikes, wars, etc. – more than ever we need to be keeping our finger on the pulse of what’s going on so we can react quickly and plan accordingly.

Fundamentally, there are two classes of economic indicator – leading and lagging. Leading indicators tend to be used to predict things, and lagging indicators tend to be used to measure outcomes.

Some examples of leading indicators:

Building permits: whatever’s going to be built doesn’t exist yet, but this is a good indicator that something’s probably going to be built.
Hours worked: when people work, they earn wages that get spent. More hours being worked means more compensation, as well as rising activity.
Consumer confidence: when people feel good about the economy, they tend to spend more.

Some examples of lagging indicators:

Consumer price index: how much more or less things cost, which is well after something has been made, shipped, and put up for sale.
Unemployment rate: how many people are looking for work. This lags because it takes time for people to file unemployment.
Inventory levels: how much of something a company has left after people have done their buying.

When I look at economic indicators, I try to look at a mix of leading and lagging, especially for indicators which can be both. Unemployment is a lagging indicator of company demand (you lay off people when you no longer have the revenue or profits to support their work, or their work has been outsourced), but is also a leading indicator of purchasing (unemployed people tend to buy less stuff).

Selecting economic indicators is something you should do with an eye towards your business. If you look at your current customers and your value chain, what companies, industries, and components are critical? If you’re a restaurant, the price of beef or rice or flour is a leading indicator because that’s going to affect what it costs to make your products. The price of gold is probably not as relevant.

If you’re a consulting firm like Trust Insights, hiring demand for marketing jobs is supremely relevant, because the less demand there is, the more people on the job market, and the fewer potential buyers there are of our products and services.

So how do you decide what economic indicators to use? Unsurprisingly, one way to assemble a basket of economic indicators would be to ask an Internet-aware generative AI model like ChatGPT with web search enabled, Perplexity, or Google Gemini (the consumer edition). We specifically want to ask about economic indicators available through a free, public source like the St. Louis Federal Reserve Bank’s FRED.

Here’s an example of the kinds of data FRED provides:

In this example, we’re looking at M2, the amount of money available in the US economy created by the US government. What it tells us is that in 2020, in the early months of the pandemic, the US government created an extra trillion dollars, and then did so again in 2021. This had a massive inflationary effect that is still being felt today. Since 2021, the government has been trying to slowly destroy that extra money to reduce inflation without causing massive economic chaos.

If your business dealt with any kind of financing and lending, this economic indicator would be a strong leading indicator to help you understand how borrowing was likely to go.

In next week’s issue, we’ll look at building a complex prompt to gather up the data, and the week after that, we’ll look at how to start analyzing it. Stay tuned!

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