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Am I Becoming an AI-Sceptic?

We’re being told that AI will change everything. Opinions vary on whether that will be for better or for worse, but some of the claims are really quite bold. In this article, and follow up pieces, I will explore to what extent the claims about dramatic changes in society due to AI are hype, whether there is truth to them, or, perhaps more likely, somewhere in between.

As an example of why I am asking myself this question, I tried asking ChatGPT and Gemini to give me some quotations from leading figures on the potential of AI, and they responded with some really great and relevant quotations. But… they were all fiction, pure 100% hallucination. Generative AI has its uses, but it seems that its connection with facts can be a little thin. Here’s a video that illustrates the point nicely: YouTube – Catieosaurus | Don’t trust Chat GPT

But let’s start at the beginning. What is a sceptic?

What is a Sceptic?

I know, this is a blog about AI, but we need to discuss the definitions of words here because there are commentators out there condemning AI sceptics, almost as if they are blasphemers, daring to question the great and glorious future that AI has to offer us.

Let’s start with the dictionaries. Dictionary definitions of scepticism vary from the mild to the quite bold:

Already we are on a scale somewhere between doubt and a disposition to incredulity, that’s quite a range. Merriam-Webster is a US dictionary, so that might say something about how the word is used on different sides of the Atlantic.

There is a common theme though – doubt. Let’s look at the meaning of that:

  • (a feeling of) not being certain about something, especially about how good or true it is DOUBT | Cambridge Dictionary
  • If you have doubt or doubts about something, you feel uncertain about it and do not know whether it is true or possible. If you say you have no doubt about it, you mean that you are certain it is true. DOUBT | Collins English Dictionary
  • 1: to call into question the truth of, to be uncertain or in doubt about, 2a: to lack confidence in, distrust, 2b: to consider unlikely DOUBT – Merriam-Webster

The US Merriam Webster dictionary is again pushing the envelope towards negativity there, which suggests we may have some cultural differences around the usage of this word. But we have a general theme of uncertainty and doubt.

Have a read of the definition of scepticism from the Skeptics Society, who probably ought to know what they are talking about:

Some people believe that skepticism is the rejection of new ideas, or worse, they confuse ‘skeptic’ with ‘cynic’ and think that skeptics are a bunch of grumpy curmudgeons unwilling to accept any claim that challenges the status quo. This is wrong. Skepticism is a provisional approach to claims. It is the application of reason to any and all ideas—no sacred cows allowed. In other words, skepticism is a method, not a position. Ideally, skeptics do not go into an investigation closed to the possibility that a phenomenon might be real or that a claim might be true. When we say we are ‘skeptical,’ we mean that we must see compelling evidence before we believe.

The Skeptics Society – Wikipedia

That sounds wholly reasonable to me. But what is the opposite of scepticism?

  • confidence, assurance, trust, certainty – Cambridge Dictionary
  • faith – Collins English Dictionary
  • belief, confidence, conviction, trust, certainty, assurance – Merriam-Webster

Ok, so the question here is – do I have faith, confidence, trust, and certainty about the wilder claims being made about AI? That’ll be a no. Do I want to question, challenge, and find out the truth? Absolutely.

Sceptic it is then. How about you?

For what it’s worth, I am both optimistic and pessimistic about AI. It has the potential to do great good, and also to do great harm, both in and of itself and at the hands of those who use it. This is why I am writing this blog, to try to figure this all out so I can take advantage of the good stuff and be prepared for the bad.

Future Articles

I started researching AI hype with the intention of writing a single post about it, but very quickly I realised this is a much, much bigger subject. The claims of AI disruption, good and bad, span every job sector, every part of society and modern life. Which is a bit worrying really.

So, my intention is to add this list of articles to my backlog and post about them as my research progresses. Here is what I have so far, in various levels of progress.

  • The Impact of AI on Creative Professions
  • Will AI Cause Mass White Collar Unemployment?
  • Will AI Replace Doctors?
  • Will AI Replace Teachers?
  • Will AI Replace Lawyers and Even Judges?
  • Will Vibe Coding Replace Experienced Software Developers?
  • An AI Revolution in Sales and Marketing
  • Will AI Finally Deliver Self-Driving Trains, Planes, and Automobiles?
  • How Close Are We to True Artificial General Intelligence (AGI)?
  • Will AI End Disease, Stop Climate Change, and Eradicate Poverty?
  • Will AI Weaponry Start World War III?
  • Will AI Finally Organize Our Personal Lives?
  • Does Size (of Your Business) Matter?

What I do want to share now though, is a list of reasons why there is hype, and why people may benefit from making extravagant claims and doing their best to scare us silly. We can’t just look at what people say, we should be looking at why they are saying it and, perhaps, what they stand to gain from saying it.

The Drivers of Hype

One thing is clear – the main driver of the hype is money. There is a LOT of money on the line. Millions have been replaced by billions, even hundreds of billions, and unsurprisingly, everyone wants a piece of the action: individuals, start-ups, corporations, investors, and governments. Some of the factors feeding the hype factory are:

Venture Capital

The AI sector attracts tens of billions in venture capital funding each quarter in the US alone (Major AI deal lifts Q1 2025 VC investment | EY – US), with a good portion funnelled into generative AI start-ups. This massive capital inflow is driven more by perceived future potential than proven business models, so start-ups are incentivized to inflate their AI credentials to attract funding and lucrative buyout offers before they have even delivered anything substantial.

The market becomes saturated with overpromising players, pushing forward technologies that may not be mature or even viable, relying on a constant stream of publicity and announcements to keep the hype going until payday.

The Stock Market

The stock market has appeared disconnected from actual company performance for quite some time already, with stock prices rising and falling based on confidence, personalities, rumour, and speculation as much as financial fundamentals. When one company in a sector has a good or bad day, other companies in that sector often experience a similar move in share prices.

Firms that align themselves with AI often see a surge in share price, and in some cases, all it takes is a press release, picked up and recycled by automated news feeds and blog sites. In the current volatile financial climate, any signals at all that might be perceived as positive or negative are picked up and amplified. AI is increasingly used to determine what precise wording should be used in press releases and announcements to gain maximum effect, inevitably leading to an exaggerated tone, which could be viewed as hype.

AI-Driven Investing

AI models are increasingly used by hedge funds, financial institutions, and individual investors for trading stocks and, particularly, cryptocurrencies. This automation can amplify swings in prices, causing major shifts with little or no real-world justification. Automated models may follow each other like falling dominoes: once one issues a sell signal, others may be triggered and follow suit. Meme stocks and organised purchasing and selling of stocks or crypto, amplified by automated trading, can make or lose fortunes in very short periods of time.

Fake news can be as powerful in generating a profit as real news. These AI models may base decisions on mathematical trends or, increasingly, analyse sentiment and content from online sources and social media to predict financial market movements. (Forbes: The Disruption Of AI In Stock Markets: A New Era Of Investment Decisions And Automation) Those sources themselves can be driven by AI in response to those same market movements, raising questions as to whether there are humans in the loop at all.

Fear of Missing Out (FOMO)

Corporations, investors, and even public institutions worry about being left behind when their competitors make announcements that they are adopting AI and predict great things in the future.

Politicians also jump on this bandwagon, promising efficiencies and cost savings with little understanding of what is required to deliver them. Such announcements are amplified by the media, creating a sense of urgency and a cycle of further announcements, rushed AI adoptions and exaggerated claims of success.

AI Washing

Many companies now label ordinary automation or data analysis features as “AI-powered” to ride on the waves of hype. This practice, termed ‘AI washing’, has become so pervasive that regulatory bodies like the U.S. Securities and Exchange Commission (SEC) are now investigating and penalizing misleading claims.

Public and investor trust are eroded when the marketed AI capabilities underdeliver. Over time, AI washing can lead to a backlash where genuine AI innovations are viewed with undue scepticism due to the noise created by opportunistic branding.

The Rise of Clickbait

The proliferation of clickbait, where even respected media outlets use sensationalist headlines to drive engagement and advertising revenue, further fuels the cycle of AI hype. AI is just another topic for clickbait, exaggerating impacts to people’s lives, spreading fear and concern in the name of viral content. The result is a misinformed public with a conflicting mix of unrealistic expectations and extreme pessimism, even fear, which inevitably spills over into politics and public discourse.

The Blogosphere and Influencers

Bloggers, vloggers, and other online influencers rely on likes, subscribes, and viral content for their revenue. While some undoubtedly have high standards and provide quality content, others are little more than clickbait with little original material.

AI is being used to scrape content from rival channels and to automate the production of scripts, or even fully AI-generated blogs and videos, recycling the content without adding any additional value. Other vloggers produce explanatory videos on how to do this, spreading the practice even further.

As social media algorithms reward emotionally charged or sensational content and the interaction it generates, influencers are incentivized to go to further and further extremes to compete. Sadly, this is then picked up by more mainstream media and investor communities, and the cycle of hype begins again.

What’s Next?

People who know me probably won’t be surprised that I’m falling on the sceptical side of things. But now AI is a thing, and I have a platform, I’m going to see how deep I can go in the research and writing as I figure it all out.

Whatever your views, it is clear that AI is going to have major impacts on us all. Maybe not the AI we have today, but given the speed with which it is developing, tomorrow’s AI could be good, bad, or outright terrifying.

I will post new articles over the next few weeks. If this sort of topic interests you, please do subscribe to be notified when I post new content.

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