Our AI Paths Are Different, But We Share The Same Road

Seujan Bertram |
 08/01/23 |
4 min read

Our AI Paths Are Different, But We Share The Same Road

The age of AI is upon us, and we’re all touched by this technology somehow. Its most widely discussed iteration, the “it” tech of the season, is ChatGPT specifically and generative AI in general. And there’s good reason for these capabilities to have entered the spotlight. How are you incorporating it into your workflow and considering its implications? If you aren’t, let’s explore that, as I think you’ll want to reconsider

What is this AI capability that we see everywhere we turn right now? Generative AI “is an artificial intelligence system capable of generating text, images, or other media in response to prompts. Generative AI models learn the patterns and structure [from] their input training data, and then generate new data that has similar characteristics.” And it’s an undervalued bit of technology in many industries right now.

It’s new and exciting and a definite stepping stone in the next stage in our digital evolution—one to which we must all adapt. It’s time to find ways to work with AI, not against it. Our society’s digital transformation is inevitable, and those who do not transform along with it, will be left behind. Christopher Losee describes the potential it presents succinctly:

“AI is the ultimate force multiplier, freeing us from the limitations of human thinking, enabling a new and never before seen level of productivity. Right now, people are paid based on the difficulty of the problems they solve. But with AI, we can solve problems faster and more effectively, making us more valuable to employers. The key is to not try to compete with AI, but to use it to our advantage.”

It’s time to increase our AI literacy as we rethink tasks.

Increasing AI Literacy as We Rethink Tasks

We are seeing early AI adopters pulling out ahead of the rest. These tech-forward folks are learning a lot as they go and are putting AI through its paces. Some are taking on challenges we must work through, while others are running tests that identify bias and showcase the importance of being critical users.

For example, we know how important it is to take care when structuring prompts for AI from these activities. “Small differences in prompts can generate highly biased output. . . . A very slight difference in the prompt has deep ramifications in the generative output. This has the potential to be even more damaging than the egregiously harmful cases we covered in our first series, because, in any given case, it’s tempting to use the document as is. The bias is almost impossible to see without the statistics, and the statistics are almost impossible to see without software that is designed to find them.”

These efforts teach us how to get the best results from AI and drive home the point that we are still in the early days of AI’s potential. And although AI is advancing faster each day, we’re at a crossroads where we can still shape our path with it as it develops. Rather than avoid it, it’s entirely possible to future-proof your career by focusing on elements AI can complement. More companies and people will undoubtedly use it to greater degrees in the coming years, and now is the time to start working with it and evolve your skills in tandem.

As part of this effort, you’ll also want to recenter yourself with the human side of work life. This means making time in our digital, fast-paced world to network person-to-person, whatever form that takes, and capture the pulse of people in every scenario, from colleagues to consumers. Your insight, intuition, and understanding can and should frame and enhance whatever outputs AI offers. Used in tandem, an AI/human communications combo can forge forward without losing its humanity.

And all of this work will be incredibly important as AI reflects its creators. We can all help shape the future of AI and reframe existing narratives.

Shaping the Future of AI

As it exists today, there are algorithmic flaws, of course. It’s to be expected. And we must catch any biased constructions as they’re created and certainly before they’re relied on for predictive modeling. This requires a strong push toward inclusivity at all levels of AI development and in the tech community as a whole. Everything from design and coding to decision-making requires an inclusive approach.

Fortunately, AI quickly reveals its knowledge gaps with a little prodding. And this presents a great opportunity for further improvements on all fronts, and it’s up to us to make those changes. Its potential is exciting and limitless, particularly as it helps us recognize and work with various biases and predispositions.

For example, AI can be directed to offer answers to questions from a female or male perspective, and those answers can then be compared to enhance our understanding of ourselves and the underlying framework that supports AI’s programming. It’s a powerful self-awareness tool and will teach us much about ourselves if we let it!

Wherever you find yourself on this AI path, we’re all seeking to adapt, overcome, and keep pace with this evolving technology. We’ve all embarked on a journey of increasingly sophisticated digital transformation, but some of us haven’t started moving yet, while others are sprinting toward the front. I’ll be watching for you on the road to whatever comes next, and I hope you keep an eye out for me too!

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