A definition of hype:
To publicize or promote, especially by extravagant, inflated, or misleading claims
Recently, I talked about the wonders of the world of Web 3.0. But, on reflection — and it’s always a good idea to reflect — did I fall for the classic hype-train trap?
New technologies emerge all the time. Sometimes they go unnoticed by the masses but play significant roles in our lives. For example, who knew flash drives so heavily relied on quantum physics?
Then, for the technologies that headline every single corner of the web, two come to mind. The first was artificial intelligence (AI). Now, it’s web 3.0.
Understanding the Gartner Hype Cycle
The Dunning-Kruger effect, which I discuss further in a previous post, is when an individual who has had little exposure often has overconfidence towards a topic, demonstrated in the graph below:
Interestingly, the Gartner Hype Curve has an identical shape. All we need to do is change and add some labels:
The Dunning-Kruger effect outlines novel subject matter on an individual, while the Gartner hype cycle outlines this phenomenon at a population scale. Thus, we either think we know a lot about the topic at the early stages, or we get excited about the subject and expect it to do amazing things.
How does the Garnet Hype Cycle apply?
Let’s look at the example of AI and machine learning (AI and ML). The origin story dates back to the 1950-60s. The late Arthur Samuels pioneered this work with the checkers board game. Then, decades after the progress of AI stalled — the “AI winter” received less funding and attention.
Again, less than a decade today, AI gained traction mainly due to the availability of large data sets, cloud computing, and more powerful processing power.
The expectations resurfaced. AI will create a utopia, replacing all our tedious and dangerous jobs, servicing in-demand work, and even making better critical decisions for us. The AI rhetorics even sneaks into keywords for job postings, research proposals, and start-up landing pages.
The hype is real, as well as the over-promise.
Coming back to reality, you will know with my sad attempts and building a classifier to detect iris colour; AI has its limits.
Instead of a better world, we got the Newsfeed.
Instead of ending problems, we created new ones: endless doom scrolling, misinformation echo chambers, and amplified bias.
Maybe, AI didn’t meet the expectations. And that’s like with a lot of things: holidays, movies, and title-contending boxing matches.
But to be let down is a good thing because now we are back to reality. Coming out of the trough of disillusionment follows the plateau of productivity. Nothing is exciting, but we consistently and slowly make progress. The world gets value, and we aren’t all hijacked by cleverly marketed trends. Remember, the route is unattractive in the public’s eye. On the other hand, AI interests the individual working on the problem.
So what toppled AI’s from its throne? Web 3.0. I described it as the future of the web. To summarise, web 1.0 and web 2.0 are the era of read and write. Web 1.0 saw the internet’s invention, reducing the barrier to information. Web 2.0 saw the consumer become the creator, with social media platforms like YouTube and TikTok being prime examples. Web 3.0 does away with the centralised platform, becoming decentralised through a blockchain and peer-to-peer networking.
Through web 3.0’s decentralisation, Democratisation is the answer to a world of industrialisation, monopolisation, and self-satisfaction. The majority, who would otherwise be weak alone, are strengthened by being brought together on web 3.0, taking power away from the very rich and powerful.
We are seeing this with the world of finance — distributed finance in the form of cryptocurrency.
A faceless identity created Bitcoin in 2008. It is the first decentralised digital currency. Bitcoin’s peer-to-peer network replaces the middle man — who are financial institutions and banks. The platform is taken away from a large business and given to the hand of the individuals. Now a single Bitcoin is worth over USD 50,000 at the time of writing this article. In addition, we have thousands of alternative cryptocurrency coins, including Ethereum, which is the second largest.
Ethereum isn’t simply a form of currency. There is the expectation that Ethereum will be how we assign ownership, such as the landscape of non-fungible tokens (NFTs). Individuals can build even software applications on this type of network.
Again, web 3.0 toted to save the world. Or are our expectations peaked?
Perhaps. We need to see cryptocurrencies fail and fail badly. If it can go past the near-extinction phase, we know there is something — although it won’t be as exciting.
I have fallen into the trap of excitement around hyped technologies. The first was with artificial intelligence, and now it’s to do with the business of web 3.0.
Referring to the Gartner Hype, we see that many new exciting technologies begin their lives with inflated expectations. Interest is eventually lost as failures start to creep in. Now, without the lens of marketing hype, genuine innovations come through.
Gartner Research. “Understanding Gartner’s Hype Cycles.” Gartner, 2018, www.gartner.com/en/documents/3887767/understanding-gartner-s-hype-cycles.
Nakamoto, Satoshi. “Bitcoin: A Peer-To-Peer Electronic Cash System.” SSRN Electronic Journal, 2008, 10.2139/ssrn.3440802.
Samuel, A. L. “Some Studies in Machine Learning Using the Game of Checkers.” IBM Journal of Research and Development, vol. 44, no. 1.2, Jan. 2000, pp. 206–226, 10.1147/rd.441.0206.