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Navigating the AI Buzz: Understanding the Evolving Audience

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Chapter 1: The Current AI Landscape

Recently, several high-profile launches in generative artificial intelligence, particularly GPT-4 and Bard, ignited a frenzy on social media. Each day seems to introduce new AI products, giving the impression that "AI has finally arrived." It’s easy to believe that humanity has transitioned from science fiction to tangible reality in just a few weeks. However, AI has quietly integrated itself into our digital experiences for years.

AI's subtle integration into everyday technology

AI-generated image created with Midjourney by the author.

Nonetheless, this time feels distinct. A significant technological revolution appears to be underway. To understand what differentiates today's advancements from past AI iterations, let’s reflect on the past decade: 2013–2023.

AI has been a part of our lives for a considerable time, though it often goes unnoticed unless you know where to look. If you’ve used a Google service, for instance, you’ve interacted with AI without realizing it.

The unseen role of AI in popular services

The AI of the previous decade was a subtle enhancement to user experience, contrasting sharply with today’s more prominent AI presence. The user experience (UX) philosophy of traditional enterprise-level AI focused on invisibility—keeping AI components hidden from users. Nowadays, there’s a noticeable shift in product philosophy, encouraging users to engage directly with AI features crafted for practical utility rather than seamless integration. (For further insights, read my detailed article on the transformative shift in AI user experience and expectations.)

Section 1.1: The Hidden Audience

For the last decade, the UX design approach for AI emphasized smooth, dependable solutions that required little to no user intervention. If designers preferred that users remain unaware of the AI components they interacted with, why was there such extensive marketing and chatter about AI? Who was the target audience for all this hype?

The answer lies with the creators of machine learning (ML) and AI systems—the engineers, product managers, data scientists, tech leaders, students, and investors who fund these technologies. This audience is not the general users; instead, they are the builders and financiers of AI. If users caught wind of AI developments, it was often through a lens of science fiction.

As time progresses, the responsibility for ethical AI usage is gradually shifting from developers to the users themselves.

Subsection 1.1.1: A Personal Reflection

Having been recognized as a LinkedIn Top Voice for three consecutive years with a community of half a million followers, I can attest that most of my audience consists of current or aspiring builders in ML/AI/data science. My previous talks have primarily targeted this demographic, often overlooking the end users.

Now, I am committed to addressing the AI-savvy product users directly. As the landscape evolves, so too must our conversations about the responsible and ethical use of AI.

Section 1.2: Looking Backward

As we continue this exploration, let’s delve deeper into AI's history and consider its development over the previous decades.

Chapter 2: The Impact of AI Hype

The first video titled "Don't Believe The AI Hype! Do This Instead..." discusses the misconceptions surrounding AI hype and offers practical alternatives for users to consider.

The second video titled "It's Here: The 2024 Gartner AI Hype Cycle™" provides an overview of the current trends in AI and their implications for various industries.

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