Artificial intelligence (AI) has taken huge leaps forward in recent years, driven by a combination of factors. Firstly, Web 2.0 paved the way for “big data” – vast amounts of quantitative and qualitative data covering many aspects of human behavior, collected by companies such as Google. Secondly, developments in cloud computing led to the rapid evolution of neural networks that have the processing capacity for such huge volumes of data.
Jointly, these factors have enabled the development of machine learning, which is one major application of AI. Machine learning is rooted in statistical pattern recognition – essentially using large volumes of data to predict a particular outcome, based on precedent.
This progression has led to various potential applications for AI technologies. Such applications are already running – or otherwise in development – in areas covering finance (using AI in investment decisions) to medicine (streamlining diagnoses) to transport (driverless cars), among others. The rapid increase in scope and range of AI has led some analysts to predict that revenue from the AI market could grow from around $640M in 2016 to $36B by 2025.
Nevertheless, the widespread implementation of AI still faces a number of problems (which are explored below). The development and increasing acceptance of blockchain technology have the power to unleash the full potential of AI. Blockchain companies like Senno, Singularity.Net and DeepBrain Chain are putting themselves at the forefront of the AI game to show how this can be done.
So what are these AI problems, and how are blockchain startups aiming to overcome them?
The problem of trust
For AI to gain mainstream acceptance, the general public needs to trust that it can work. Currently, AI development takes place behind closed doors, within private companies who have no interest in disclosing their AI algorithms.
Blockchain, on the other hand, operates on a principle of open trustlessness that makes it feasible to verify data points and assumptions used to drive machine-made decisions. Additionally, blockchain enables an immutable record of those decisions. Creating this level of transparency and auditability can help to increase human trust, and also to create a way for AI machines to trustlessly interact with one another.
The “AI Takeover” Scenario
Although the exploration of the AI takeover scenario has so far been confined to the realms of science fiction, it has been the subject of stark warning even from public figures such as Stephen Hawking. However, if a machine could only execute decisions automatically within a pre-defined set of criteria, then any world-takeover attempt could legitimately fall at the first hurdle. This kind of limitation is exactly what a blockchain-based smart contract is designed to achieve.
Singularity.Net aims to create a decentralized marketplace for AI services. They acknowledge that sharing AI between different agents makes the possibility of the technological singularity – an artificial super-intelligence that can self-improve – very real. Smart contracts could be the only current way to ensure that such growth cannot run away with itself.
Financial barriers to entry
Today, the investment required in AI development is huge. Only very large organizations such as Google have the financial clout to be able to make the significant R&D investments required to carry out meaningful AI development. This prevents even the most creative SMEs from taking initiatives to develop AI technologies to suit their own needs. At a fundamental level, the crowdfunding capability of ICOs and token sales can now make it easier for small, entrepreneurial companies to gain access to investment that could be used to fund AI development.
However, the blockchain solution runs deeper than just increasing access to funds. It is thought that as much as 30% of an R&D budget for AI can be swallowed up by the sheer computational power needed to run AI simulations. This is one problem that blockchain company DeepBrain Chain is aiming to solve – their solution involves decentralizing the computing power needed to run AI platforms to nodes in exchange for coin rewards.
Data-related barriers to entry
Big data is still possessed solely by the major Web 2.0 companies who collect it. For the sake of developing the next level of machine learning, big data needs to be more widely accessible to AI agents within the new blockchain ecosystems like Singularity.Net and DeepBrain Chain. This is where another blockchain startup – Senno – comes into play.
Crowdsourced data for AI decision-making
Senno is a blockchain-based sentiment-analysis platform. In short, it aims to assemble and encrypt big data about human sentiment on any given subject from a variety of contributors, with the goal of using it to drive widely-accessible AI analytics.
User sentiment data will be collected (in exchange for tokens), consolidated and encrypted . The computing power needed to crunch such vast quantities of data is decentralized in a similar way to the power needed to mine cryptocurrencies. Users who want access to public opinion or crowd wisdom analytics will pay in Senno tokens for real-time access.
The fact that the Senno AI machine will provide analytics driven by real-life human sentiment has significant power. Not only does this mean that companies using Senno will be making decisions aligned with the sentiments of real humans, but it could also work to enhance trust in the AI decision process. Additionally, AI decisions based on human choices reduce potential issues in machine ethics.
The future of AI with blockchain technology
The revenue impact of using AI and big data to drive decisions has massive potential. Studies undertaken by McKinsey Global have shown that the US healthcare sector alone has the potential to create more than $300B every year through the use of big data to drive decisions. However, in order to achieve such gains in sectors as broad as that of US healthcare, big data needs to be made accessible – and digestible – to more users than just large organizations. The implementation of blockchain technology offers an ideal solution to this industry-wide challenge.
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