Generative AI and Web3: hyped nonsense or a match made in tech heaven

Did I write this or was it ChatGPT?

It’s hard to say, isn’t it?

For the sake of my editorship, I’ll quickly follow that with: I wrote this article (I swear). But the point is, it’s worth exploring the limitations of Generative Artificial Intelligence and its areas of use for developers and users. Both are revealing. The same goes for Web3 and blockchain.

While we are already seeing the practical applications of Web3 and generative AI playing out in tech platforms, online interactions, scripts, games, and social media apps, we are also seeing a repeat of the responsible AI and blockchain 1.0 hype cycles of the mid-2010s.

“We need a set of principles or ethics to guide innovation.” “We need more regulation.” “We need less regulation.” “There are bad actors who poison the well for the rest of us.” “We need heroes to save us from AI and/or blockchain.” “Technology is too sensitive.” “Technology is too limited.” “There is no enterprise-level application.” “There are countless enterprise-level applications.”

If you only read the headlines, you will end up with the conclusion that the combination of generative AI and blockchain will save or destroy the world.

All over again

We’ve seen this piece (and every act and break) before with the hype cycles of both responsible AI and blockchain. The only difference this time is that the articles we read about the implications of ChatGPT may in fact have been written by ChatGPT. And the term blockchain has gained a bit more weight thanks to investments from Web2 giants like Google Cloud, Mastercard, and Starbucks.

That said, it is noteworthy that OpenAI’s leadership called recently for an international regulatory body similar to the International Atomic Energy Agency (IAEA) to regulate and, if necessary, curb AI innovation. The proactive move is easing awareness of both the vast potential of AI and society’s potentially crumbling pitfalls. It also indicates that the technology itself is still in testing mode.

The other important subtext: regulation of the public sector at the federal and sub-federal levels usually limits innovation.

As with Web3, and regardless of regulatory action or not, accountability must be at the heart of generative AI innovation and adoption. As technology evolves rapidly, it is important for vendors and platforms to assess every possible use case to ensure responsible experimentation and adoption. And, in particular, Sam Altman of OpenAI and Sundar Pichai of Google assignpartnering with the public sector to develop regulation is an important part of that equation.

It’s also important to expose limitations, report them transparently, and provide guardrails if and when issues arise.

While AI and blockchain have both been around for decades, the impact of AI in particular is now visible with ChatGPT, Bard, and the entire field of generative AI players. Together with the decentralized power of Web3, we are about to witness an explosion of practical applications that build on progress by automating interactions and advancing Web3 in more visible ways.

From a user-centric perspective (and whether we know it or not), generative AI and blockchain are both transforming the way people interact in the real world and online. Solana recently made it official with a ChatGPT integration. And exchange Bitget withdrawn from theirs.

Promising or puzzling, each signal indicates that it remains to be seen where the technologies best intersect in the name of user experience and user-centric innovation. From where I sit as the head of a layer1 blockchain built for scale and interoperability, the question becomes: How should AI and blockchain join forces to pursue Web3’s own ChatGPT moment of mainstream adoption?

Tools like ChatGPT and Bard will accelerate the next big waves of innovation on Web2 and Web3. The convergence of generative AI and Web3 will be like putting peanut butter and jelly on fresh bread, but you know, with code, infrastructure and asset portability. And as the hype is replaced by practical applications and constant upgrades, persistent questions about whether these technologies will reach the mainstream will be toast.

What does all this mean for business leaders?

Business leaders need to see generative AI as a tool worth discovering, testing, and integrating. Specifically, they should focus on exploring how the “generative” element can improve work outcomes internally with teams and externally with clients or partners. And they must continuously assess its enterprise-wide potential and its limitations.

It’s time to map and document where not to use generative AI, which is equally important in my book. Don’t rely on the technology for anything where you need to apply facts and hard data to output for community members, partners, teams or investors, and don’t rely on it for protocol upgrades, software engineering, coding sprints or international business operations.

On a practical level, business leaders should consider incorporating generative AI into administrative workflows to make their company’s day-to-day workflows faster and more efficient. Discover the seemingly universal utility of launching text or code-intensive projects across engineering, marketing, business, and executive functions. And as this technology changes every day, business leaders need to look at every possible new use case to decide if they want to experiment with it responsibly on their way to adoption, which includes working in Web3.

Mo Shaikh is co-founder and CEO of Apto Labs.