One Reason Everyone Needs Blockchain

One Reason Everyone Needs Blockchain

Big data rules the world. Our everyday lives are filled with products – the smartphones we can’t live without, the websites we browse, even the thermostats in our homes. These smart products gather raw data for companies to store, analyze, and use, and then the raw data takes on exponentially greater value as more and more companies find increasingly efficient and intelligent ways to mine and interpret it. So why are big companies, not individuals, the ones who seem to profit? Blockchain may change this outcome.

A big advantage

The world’s largest companies (like Facebook, Netflix, Google, and Apple in the US and Alibaba, Baidu, and Tencent in China) have a significant advantage in the race to accumulate data because of their size – they have the vast reach, and by extension the capital, to collect, store, and analyze the massive amounts of information they gather. They also have the resources to hire the cream of the crop in data science and AI, who then build models to understand the data. The more data stored and analyzed, the more accurate the model. The result is self-fulfilling prophecy – the biggest and best get bigger and better. 

Is that really a bad thing?

The fact that large companies have taken advantage of their resources to better interact with data is not inherently negative, nor surprising. But there are problematic aspects to their dominance – one major one is that the barrier to entry becomes so high that innovation is limited to the companies with the capital to get involved. It also means that important information about their AI models remains behind closed doors. This isn’t an issue when it comes to our interactions with Siri, but it is significant when multiple publications detail how an AI model used for helping to sentence criminals is racially biased, and the manufacturer of the model refuses to discuss its makeup or allow others to examine the nuts and bolts that contribute to its behavior.

So, what can be done?

There is a potential way to neutralize, or at least lessen, these advantages – blockchain. Blockchains are defined most simply as structures of data linked and secured using cryptography, and they have potential to shift more and more power to algorithm builders and everyday people. They provide a way to take ownership of personal information in a world where data is commoditized; additionally, they offer a method to make information available to AI builders who may not work at a large company. The potential result is more accurate AI models, with the benefit of security and transparency.

Multiple networks exist that aim to reward people for sharing their information in a decentralized data marketplace – we will focus on Ocean Protocol, SingularityNet, SEED, and Tickeron.

Ocean Protocol

Ocean Protocol’s goal is to build a “decentralized data exchange protocol and network that incentivizes the publishing of data for use in the training of artificial intelligence models.” In layman’s terms: you are compensated (in Ocean tokens) if you upload data to the Ocean network and your personal data is used to train AI models.

This is valuable for multiple reasons. Take a Nest thermostat – Nest is constantly sending information from its users to Google, who receive it for free. With their significant resources, it wouldn’t be a stretch to imagine the company building an AI service that, through data, identifies when to contact you about replacing your windows. With a decentralized marketplace like Ocean’s, an ambitious AI scientist can license your data and use it to build their own service. Through blockchain, there is a cost-effective way to lease or buy your data while signifying clear ownership and maintaining data integrity (by confirming it is from a trusted source). Everyone is happy, and the risk of bias or error in the data is minimized by transparency.

SingularityNet

SingularityNet is working to be the first AI-as-a-service, blockchain-based marketplace. Their goal is to help the enterprising AI scientist in our previous example sell or rent her model to other scientists to use with their datasets. A search engine even helps users to find and integrate a model with additional complementary models. This would be useful if, for example, AI scientist #1 wrote a model studying home energy markets in San Francisco. Scientist #1 could combine that with models studying Oakland, Palo Alto, and San Jose, providing additional insight into energy consumption. Blockchain makes it clear the model is Alice’s intellectual property, and she would be compensated in SingularityNet tokens when someone uses her model. 

SEED

SEED is working to help us trust the increasingly-popular bots (think Apple’s Siri or Amazon’s Alexa) around us. As the bot market grows, according to SEED, from an estimated “$3 billion to $20 billion by 2021”, the chance of encountering a biased, inaccurate, or hijacked bot increases. SEED has established an open-source, decentralized network where any bot interactions can be viewed and verified. It provides the skeleton necessary to ensure that information fed into the bot can be assigned to an owner, who can then be compensated. Their marketplace allows bot creators to license or sell their builds to those who might need to use them, and their tokens compensate creators and data owners for the value they create within the SEED network. These services mean higher confidence in the quality of the bot and greater protection for user’s data.

Tickeron

Investors know that flipping on CNBC at any given time during the day means hearing a wide array of market forecasts and predictions. Whether it’s a stock or an industry that’s headed skyward or due for plummet, the sheer volume of advice is mind-boggling. Tickeron identified this as a major issue when it comes to financial intelligence, which Tickeron calls “FinIP.” How can the consumer know that they’re getting advice from a pundit or market analyst who is trustworthy, smart, and most importantly, who is right more often than they’re wrong? As it stands today, there is very little accountability for the talking heads who give all sorts of financial advice on a daily basis. That creates a problem for the consumer, because it is impossible to know which advice is actually valuable. 

But there is another problem in the world of FinIP – it is really only the behemoth Wall St. firms with huge marketing budgets who get traction on the web. What about the data scientist or quant who has no marketing budget but who has built a platform that can beat the market? How can they show the world of consumers and investors how successful their platform is? And most importantly, what mechanism exists for giving the consumer a trustworthy account of the advisor’s track record? 

Tickeron is seeking to use blockchain to change how the world of financial advice works. They are an SEC-regulated internet financial advisor that has developed a decentralized “marketplace” of artificial and human intelligence for the financial industry, where advisors and people making predictions have their track records logged and evaluated. The end result is having all of the participants in the marketplace establish verifiable seller reputations, which makes it easy for the consumer to know whose advice is superior. Tickeron’s marketplace would also establish a “protocol of commerce,” which would create a secure exchange between the creators of financial intelligence and consumers of it. 

A Promising Future

Blockchain-based AI is still in its nascent stages, but as blockchain becomes mainstream, increasingly more data will hit decentralized marketplaces. Everyday people will be able to monetize their personal data, developers will be rewarded for their contributions to the marketplace, and open, transparent systems will be the rule, not the exception.

Contributor

Allana|Expert

Financial analyst and market blogger with expertise in equity research, fundamental analysis, and macroeconomic trends. I regularly publish coverage on individual stocks, ETFs, and sector developments — combining rigorous financial analysis with clear, engaging writing for a broad investment audience.

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