INBOX INSIGHTS, November 20, 2024: Setting Boundaries, ChatGPT Turns 2 - Trust Insights Marketing Analytics Consulting

INBOX INSIGHTS: Setting Boundaries, ChatGPT Turns 2 (11/20) :: View in browser

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Keeping the Human Element: Boundaries in an AI World

Recently at #MPB2B, amidst discussions of emerging technologies and innovations, a profound theme emerged that transcended the technical specifications and implementation strategies. The conference revealed an essential truth about our evolving digital landscape: maintaining human connection remains paramount as we navigate the possibilities of generative AI and marketing technology.

I put up a post about my experience here.

This emphasis on human-centric approaches resonated deeply with my professional philosophy and experience. As we explore increasingly sophisticated technological capabilities, the question isn’t just about what technology can do, but about how we preserve authentic human engagement within these advances.

Why Boundaries Matter

I’m that person who leaves parties early to go to bed. Zero guilt about it. I’m also not big on hugging – it’s just not my thing. These might seem like small, personal quirks, but they’re actually boundaries I’ve set that help me function better in social situations. These boundaries keep me sane and safe. They work for me and me alone. You would need to decide what your boundaries are.

The same principle applies to how we handle technology in business. There is no shortage of tech to choose from, and a million different ways it can help you. It’s easy to get lost in the weeds of letting tech take over.

Why is this important? You’re going to get pulled in a lot of directions. Heck, you already are! Being able to set boundaries allows you to better set expectations and say no when you need to. As you move into 2025, consider establishing boundaries with your team.

Setting Tech Boundaries

The “Shiny Object” Boundary
- Not every new tool needs to be implemented
- Just because we can automate something doesn’t mean we should
- Sometimes the old way is the right way
The “Human Touch” Boundary
- Deciding which tasks stay human-driven
- Identifying where personal expertise adds irreplaceable value
- Maintaining authentic connections with clients and team members
The “Automation Line” Boundary
- Defining clear limits on what we automate
- Protecting creative processes that need human insight
- Keeping strategic decisions in human hands

In my own work, I’ve had to set some pretty clear boundaries with technology. Given where Trust Insights is with generative AI, I could easily get swept up in what’s possible. For instance, while AI could probably write some of our content, I choose to keep our core messaging human-generated. Why? Because our expertise and personality are what make our content unique. (And no, the irony of writing about AI boundaries isn’t lost on me.)

So, where do you start? I’ve given some examples of what boundaries you can set, but you need to set ones that make sense for you. Start by asking yourself and your team some questions.

Audit Your Current Tech Use
- Where are you perhaps over-relying on automation?
- Which processes actually benefit from human touch?
- What’s the real cost of removing the human element?
Define Your Non-Negotiables
- Which tasks must stay human-driven?
- What values can’t be compromised?
- Where do you need to maintain direct human connections?
Create Clear Guidelines
- Document your boundaries
- Share them with your team
- Review and adjust as needed

Easier said than done, this may take a few tries to get right. Once you’ve established your boundaries, communication is key. It’s easy to get frustrated when people overstep, but clear communication is crucial. Did we clearly define our limits? Did we effectively communicate those boundaries? Consistent communication is essential, even if it means repeating yourself. After all, we can’t expect others to respect boundaries they don’t know exist.

As technology continues to evolve, our boundaries will become our compass. They’ll help us navigate the delicate balance between leveraging powerful tools and maintaining our human essence.

Remember: It’s okay to embrace technology. It’s also okay to say, “This far, no further.” Your boundaries are valid. They are yours. You decide where the line is.

The future of marketing isn’t about choosing between human and machine – it’s about setting smart boundaries that let both thrive. And honestly? That’s exactly the kind of future I want to help build.

What boundaries are you setting with technology in your work? 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 discuss their key takeaways from the MarketingProfs B2B Forum 2024. You will learn about the surprising reality of AI adoption in marketing. You will discover the challenges of accurately measuring AI usage and the inherent biases in current surveys. You will gain insights into the human element of marketing and how it intersects with AI. You will understand the value of listening in market research and how to extract insights from industry events.

Watch/listen to this episode of In-Ear Insights here »

Last time on So What? The Marketing Analytics and Insights Livestream, we did a Halloween special on AI-powered share of voice. Catch the episode replay here!

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👉 New: Generative AI for Hospitality

In this week’s Data Diaries, let’s celebrate a birthday. We’re a little early since next week is the Thanksgiving holiday here in the US, and there will be no Data Diaries column for the birthday week itself.

On November 30, 2022, just a little less than two years ago, OpenAI released a model named GPT-3.5-turbo, and a web interface to it named ChatGPT. That year is generally accepted as the year the general public became aware of generative AI.

What did people have to say at the time when this new entity came into the world?

“I doubt it will improve exponentially, but it will improve.” – Steven Pinker, Harvard Gazette, February 14, 2023

“The ability to generate human-like written text has prompted suggestions that the technology could replace journalists. However at its current stage, the chatbot lacks the nuance, critical-thinking skills or ethical decision-making ability that are essential for successful journalism.” – Samantha Lock, The Guardian, December 2022

“What ChatGPT cannot yet do — and might never be able to do, many experts think — are tasks that require the many gradations of human judgment applied to a range of problems and other cognitive challenges. Take, for example, a chart or table showing an underperforming company’s metrics. ChatGPT could summarize the data and tell a user what the chart shows. What it can’t do — yet — is explain why the data is meaningful.” – Megan Cerullo, CBS News, January 2023

As we reflect on generative AI for the general population entering its terrible twos, it’s interesting to look back at what people thought during its earliest days. GPT-3.5-Turbo, as a model, had severe constraints at launch:

A working memory (context window) of 16,384 tokens, or about 12,000 words
A maximum output of 4,096 tokens, or about 3,000 words
A parameter set estimated at roughly 12 billion parameters (statistical combinations, more parameters means more capabilities and skills)

Today’s state of the art models by vendors like OpenAI, Google, and Meta, just two years later, look like this:

A working memory (context window) of up to 2,000,000 tokens, or about 1.5 million words, a 121x change
A maximum output of 32,768 tokens, or about 25,000 words, a 7x change
A parameter set in excess of 405 billion parameters, a 32x change

When we look at how fast generative AI models have evolved in just two years’ time, the rate of change is staggering. I can’t think of any other technology that has evolved this much, this quickly.

And on a per-token basis, AI has gotten dramatically cheaper in the last 2 years. At launch, OpenAI’s APIs for developers cost $0.50/1M input tokens and $1.50/1M output tokens. Today, 2 years later, the replacement for that model costs $0.15/1M input tokens and $0.075/1M output tokens – a 70% cost reduction on input and a 95% cost reduction on output.

Name a technology that has gotten 121x better and 95% cheaper in 2 years. There isn’t one.

To put that into context, imagine buying a Toyota Prius 2 years ago that got 50 miles per gallon, with a range of about 500 miles before running out of gas on a 10 gallon tank. If AI were that Prius, today the gas tank would be 1,210 gallons, getting 1,600 miles per gallon, and you could drive it 1.9 million miles before running out of gas. If the world had a highway at the equator, you could drive around the planet 76 times before running out of gas. And the Prius cost $35,000 when you bought it 2 years ago and now costs $1,750 new.

There’s an aphorism that we overestimate the short term and underestimate the long term when it comes to new technologies. In the case of generative AI, many of us underestimated both, because no one expected the technology to move this fast, to advance this much in so short a time.

Today, there are models you can download and run on your computer (assuming it’s a beefy laptop that can play video games at full performance) which have GREATER capabilities than the model ChatGPT launched with on its birthday. What used to take a room full of servers just to operate today can run on your laptop. Devices like Google’s Pixel and Apple’s iPhone 16 can run different AI models in your pocket, a feat that was impossible 2 years ago.

The key takeaway here, echoing Katie’s opening, is that if it feels like things are moving ridiculously fast, it’s because they are. It’s not you, it’s not some deficiency you have. You’re not doing anything wrong. Keeping up with AI is practically a full-time job itself.

So what do you do? The answer is that “we” are always smarter than “me”. Not only should you set boundaries for yourself, you should build a community around yourself that can share the load. Groups like our Analytics for Marketers Slack allow all of us to contribute news, ideas, and technologies collectively that we might miss individually. The companion, the corollary to boundaries is building healthy communities around you so that you don’t miss things AND you don’t have to sacrifice your boundaries to keep up with the massive changes in the world.

Happy birthday, ChatGPT.

Here’s a roundup of who’s hiring, based on positions shared in the Analytics for Marketers Slack group and other communities.

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