Why Does AI Share the Blame for 'Too Many Choices' Today?

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How It Ruined Search Results and Information Bias

I remember doing internet searches when the biggest decision was choosing between Yahoo and Google. Bing was there, too, like that odd cousin at family gatherings, while privacy enthusiasts swore by DuckDuckGo.

Back then, it was a simpler time when our biggest concern was SEO for Google.

I remember doing keyword stuffing and backlink strategies, thinking it was the height of complexity.

Now, with the explosion of AI models, we're drowning in choices, and it’s making our lives wonderfully complicated.

This has to be the best yet worst thing to happen to search results.

Once, Google was king. Back then, we optimized everything to rank on Google. SEO was a straightforward game, and Google’s algorithm was our playbook.

Personal branding was synonymous with Google ranking.

It was so easy, right? But now, enter AI models, and it’s like a tech reality show where every contestant promises to be smarter, faster, and better.

This has to be the best yet worst thing to happen to those who crave straightforward search results.

Let’s look at what we have today.

There’s Claude, Perplexity, and ChatGPT. OpenAI plans to introduce SearchGPT, as if we didn’t have enough GPTs already.

Poe has thrown its hat into the ring, and Google has Gemini.

Each promises to revolutionize search and provide more nuanced answers. In a way, all we did before was Google it.

They all work differently but aim to do the same thing: give us information. And somehow, instead of making things easier, they’ve made us skeptics of our search results.

Here’s the thing about choice: it’s not always a blessing.

A famous study by psychologists Sheena Iyengar and Mark Lepper showed that when people were presented with fewer choices, they were more likely to make a decision and be satisfied with it.

When offered 24 types of jam, only 3% made a purchase. But with only 6 types, 30% of people bought a jar.

It was so easy, right?

Too many choices lead to analysis paralysis and dissatisfaction. In the world of AI search, this translates to confusion and skepticism. I remember doing a simple search, and now I’m just drowning in options.

At the core of these AI tools is natural language processing, a fancy way of saying they try to understand and generate human-like text.

We dealt with simple keyword searches. Now, it's like "Did you search on ChatGPT? Did you use AI tools? Did you check plagiarism? What grade has it got on Hemingway editor?

They analyze patterns in data, learn from them, and spit out what they think we want.

They predict the next word or phrase, kind of like a fortune teller but less mystical. Claude and Perplexity might focus on language understanding, while ChatGPT is your conversational buddy. In a way, all we did before was type in a question.

Google’s Gemini aims to integrate search with AI responses.

They use neural networks, algorithms, and massive datasets to generate results.

And while they are technically impressive, they have one flaw: they make us question everything.

Umm, I remember doing what any writer would dream of—getting published in platforms like HuffPost, Forbes, and The New York Times. Back then, it felt like my words had weight. I would share articles on social platforms, and people would read and engage.

Textual content was or used to be king. I wrote a few books, including "The Unproposed Guy" and "The Weak Point Dealer," both of which resonated with readers for their humor and insights into modern life. I now write for Forbes, but nobody gives an F, haha!

My story got published in The NYT, and people are like, "So what?" This has to be the best yet worst thing to happen to writers like me who once thrived on reader engagement.

In addition to writing, I've founded companies like Write Right and Estorytellers, which have grown to become top content agencies in India. My work has spanned numerous domains, and I've been featured in top publications, crafting narratives that engage and inform.

In the past, optimizing for Google was enough.

Today, brands need to juggle multiple platforms and AI models.

Back then, it was all about Google’s ranking. The ground to cover is enormous. It’s not just about keywords anymore; it’s about understanding how different models interpret queries. SEO for AI? That’s a whole new field.

Personal branding now needs to consider how these models perceive and rank information. This has to be the best yet worst thing to happen in the realm of information. It’s like playing chess with a constantly changing rulebook.

The irony is that while these AI models promise to simplify information retrieval, they’ve made it more complex.

Back then, we trusted one or two search engines. Each has its own bias, its own way of processing, and we, the users, are left trying to figure out which one is “right.” The choice, once a symbol of freedom, has become a source of frustration. I remember doing simple searches without questioning the results. We wanted more options, and we got them. But did we really want this?

Maybe the art of choice lies in knowing when to limit them.

AI is here to stay, and its models will keep multiplying.

Well, it was easier to make decisions online before. But as users, perhaps the real skill lies in deciding which tools serve our needs best without getting lost in the options.

After all, a little skepticism is healthy, but drowning in choices? Not so much.

AI was supposed to make us smarter, but sometimes it feels like it’s just making us confused. Here's to hoping that, in this age of choice, we learn not just to choose but to choose wisely. It was so easy, right? I

In a way, all we did was pick a search engine and go.

Honestly, nobody knows everything, and if they claim to, they're lying. But I do know a few things, like how to get your content to the top and make your target audience read it. That's the end goal, right? Connect with me if you want to avoid feeling overwhelmed.

Now is the time to make your brand unforgettable. Book Your Discovery Call now!