How AI Can Bridge the Language Barrier in Crypto

HodlX Guest Post  Submit Your Post

Ever since Web 3.0 captured the attention of the public eye during 2021’s bull run, smart contracts and their potential as a new technological resource have inspired ambitious research into transformative use cases across a multitude of industries.

However, even though the phrase ‘smart contract’ has become almost as ubiquitous as the word ‘crypto’ itself, their track record remains unimpressive in the real world and the number of people who have ever actually seen one remains low.

The fact that only developers can read and understand them made smart contracts unlikely candidates for ever becoming ‘real’ contracts.

And their most valuable feature – being unbreakable – could not increase productivity and safety in a lot of practical use cases because to most people, smart contracts remain a riddle wrapped up in an enigma.

But it is for historical reasons alone that we don’t expect programs to be readable by humans who are not developers.

This carries a high cost of opportunity that we pay, mostly, because we don’t know better.

An obvious solution to this unique problem is harnessing the power of AI, which has the potential to enable improvements to human quality of life and the creation of new opportunities that are difficult for us to imagine from our current base of understanding

The future of smart contracts and AI

Smart contracts can be used in place of intermediaries in many industries as diverse as insurance, mobility, real estate, entertainment, fine arts and law.

Any industry that currently requires a third party to verify a contract or method of exchange can and will be disrupted by the application of smart contracts, which will dramatically reduce cost.

AI has the ability to bridge the divide between smart contracts and non-technical individuals to make smart contracts accessible and useful for mainstream use cases.

This can happen in two ways – AI can help with translating existing smart contracts into plain English or it can help by translating plain English into smart contracts.

Either way, with generative AI we run into the problem of hallucinations, which are of special concern for program code that has a lot of value riding on it and so must be guaranteed to be exact.

On the periphery, the problems of bias and resource hunger lurk.

That’s where a special kind of AI comes into play that is in many respects the opposite of what is understood as AI today.

This type…