The Future of Managing Trust
Each science fiction work has portrayed a version of the future. With our current progress, we can already probabilistically discard some of those portrayals. AI has been a central subject for science fiction and IT since inception, but the blockchain is new and opens many, many doors. All of this happens while enormous chunks of data are being collected.
The Focal Point Is Trust Management
The common denominator for these technologies is trust. Most human interactions come down to trust; this is why we own property and believe no one will steal it and have legislation that protects us. This is why we have money; money is the primary currency of trust. Finance? Trust. Insurance? Trust. Contracts are the formalization of trust.
The blockchain enables decentralization by removing third parties that manage trust between two parties. I need the bank to manage the money I send to you. When I use Bitcoin there is no centralized third-parties. There is a third party actually, at the core. It is the miners that power the network, but they do that automatically with no possibility of altering the transaction itself and get a low fee, so compared to banks or other financial services, you can safely support the claim that in blockchain there is no third party.
Trust management governs our interactions: the government itself, our jobs, our contracts, and our money. You may imagine how disruption of such a human value like trust yields significant consequences. We already see some of them in our current society. I will give just one example:
We used to rely on radio personalities and DJs to find out new music. Now Spotify’s machine learning is a resource that provides most of the recommendations in music. So the AI has taken over a lot of the trust from humans regarding what to listen to.
AI & Trust
AI can become a superior form of trust management than the blockchain, as well as more comfortable to use. However, they will most likely work in conjunction where needed.
I could tell Siri, write a contract with John Doe about me selling him a car, Siri writes the deal and sends it to John Doe’s Siri. John Doe already instructed Siri he wants my car. The two Siris could even negotiate for us, draft a common piece they agree on telling us, we both confirm, then the two Siris store the final contract on Ethereum’s blockchain by performing secure transactions.
A significant problem in blockchain’s adoption is the difficulty of storing private keys, but what if we saved 10% inside one of Siri’s addresses and she would perform various purchases and contracts. Cross-linking AI and the blockchain would benefit both technologies and increase the adoption for both.
Big data is at the back of this, as it enables the AI to learn. The blockchain stores many transactions that are then easily processed by big data for relevant insight but the blockchain is very expensive and can only host small chunks of data.
Still, data from the blockchain is instrumental, even if only in conjunction with more data. Another use of the connection between big data and blockchain is storing a hash of big chunks of data and securely store and then verify if the data changed.
I chose the Meta explanation about managing trust itself as it empowers you to envision a multitude of use cases. Because for each technology alone, the use cases seem limitless.
One instance regarding marketing and the selling of data can be found in this article. It explains that the blockchain combined with big data analytics ensures transparency and traceability, the security of the anonymity of data, and I would add, the possibility to pay customers for their data, touching world markets easily because coins and tokens on the blockchain work globally with the exception of a few territories where it is illegal to use crypto. It offers confidence through transparency by clearly programmed smart contracts for vetting systems, and so on.
Here is an example on social media. You can make an app that learns people’s behavior using big data and machine learning, let’s say Facebook, but using the blockchain you can also create its currency for the platform, so people instead of liking or loving a post, they give one LIKECOIN. This will clean data from social media because the like is now free, you give it all the time, but if it were 0.01$, you might think twice. This makes feedback from such platforms more valuable and conversion to increase.
You can even have Dapps, apps that are secure and decentralized, which also have some components of the blockchain. In my opinion, these hybrids are the future in most use cases. Some crucial data is stored on the blockchain, but most of the data is stored in data warehouses and data lakes.
The tokenization of assets is enabled by tokens on the blockchain, as they are not duplicable as off blockchain tokens. By tokenizing assets, you grow secondary markets where you can trade by using AI and big data.
There are examples in voting systems, in medicine, in Genetics - by storing entire genomes in data lakes - and their hash on a blockchain.
The possibilities are truly unlimited, but these technologies need to grow more before they reach the true mainstream adoption. For now, mainly companies and early adopters use them, but I can’t wait for a future that is more decentralized and where machines handle most of the fundamental trust issues. Then, you will manage only the part of trust on who to date and whom to work with, but even those people may be suggested by a machine as well:
“Hey Siri, what’s up”
“Found this girl for you. She seems like your type. Just got out of a relationship and has a nice… rack.”
“She looks cool. Send her a Louis Vuitton token so she can buy a bag.”
“I don’t recommend that. She does not look that materialistic. Maybe send her a cute crypto kitty instead?”
“Ok, do that, if she replies, put me in contact.”
“Also buy her some flowers and send them to her address.”
To some, it may look dystopic, but you will still get to take the main decisions. The AI and the blockchain would just free up more of your time, that’s all.