What happens when two major technological trends see an synergy or overlap in usage or co-development?
We have blockchain’s promise of near-frictionless value exchange and AI’s ability to conduct analysis of massive amounts of data. The joining of the two could mark the beginning of an entirely new paradigm. We can maximize security while remaining immutable by employing AI agents that govern the chain. With more companies and institutions adopting blockchain-based solutions, and more complex, potentially critical data stored in distributed ledgers, there’s a growing need for sophisticated analysis methods, which AI technology can provide.
The combination of AI and blockchain is fueling the onset of the “Fourth Industrial Revolution“ by reinventing economics and information exchange.
1. Precision medicine
Google DeepMind is developing an “auditing system for healthcare data”. Blockchain will enable the system to remain secure and shareable, while AI will allow medical staff to obtain analytics on medical predictions drawn from patient profiles.
2. Wealth and investment management
State Street is issuing blockchain-based indices. Data is stored and made secure using blockchain and analyzed using AI. It reports that 64% of wealth and asset managers polled expected their firms to adopt blockchain in the next five years. Further, 49% of firms said they expect to employ AI. As of 01.2017, State Street had 10 blockchain POC’s in the works.
3. Smart urbanity
To supply the energy, distributed blockchain technology is implemented for transparent and cost-effective transactions between producers and consumers, while machine learning algorithms can even hone in on transactions to estimate pricing. Green-friendly AI and blockchain help reduce energy waste and optimize energy trade. For example, an AI system governing a building can oversee energy use by counting in factors like the presence and number of residents, seasons, and traffic information.
4. Legal diamonds
IBM Watson is developing Everledger using blockchain technology to tackle fraud in the diamond industry, and deploying cognitive analytics to heavily “cross-check” regulations, records, supply-chain, and IoT data in the blockchain environment.
5. More efficient science
The “file-drawer problem“ in academia is when researchers don’t publish “non-result” experiments. Duplicate experiments and a lack of knowledge follow, trampling scientific discourse. To resolve this, experimental data can be stored in a publicly accessible blockchain. Data analytics could also help identifying elements like how many times the same experiment has happened or what the probable outcome of a certain experiment is.
There are forecasts that AI will play a big role in science once “smart contracts” transacted by blockchain require smarter “nodes” that function in a semi-autonomous way. Smart contracts (essentially, pieces of software) simulate, enforce and manage contractual agreements and can have wide-ranging applications when academics embrace the blockchain for knowledge transfer and development.
6. IP rights management
Digitalization has introduced complicated digital rights to IP management, and when AI learns the rules of the game, it can identify actors who break IP laws. As for IP contract management, for music (and other content) industry, blockchain enables immediate payment methods to artists and authors. One artist recently suggested the blockchain could help musicians simplify creative collaboration and making money. Ujo Music is making use of the Ethereum blockchain platform for song distribution.
7. Computational finance
Smart contracts could take center stage where transparent information is crucial for trust in financial services. Financial transactions may no longer rely on a human “clearing agent” as they automatized, performing better and faster. But since confidence in transactions remains dependent on people, AI can help monitor human emotions and predict the most optimal trading environment. Thus, “algotrading” can be powered by algorithms that trade based on investment patterns correlated with emotions.
8. Data and IoT management
Organizations are increasingly looking to adopt blockchain technologies for alternative data storage. And with heaps of data distributed across blockchain ledgers, the need for data analytics with AI is growing. IBM Watson merged blockchain with AI via the Watson IoT group. In this, an artificially intelligent blockchain lets joint parties collectively agree on the state of the device and make decisions on what to do based on language coded into a smart contract. Using blockchain tech, artificially intelligent software solutions are implemented autonomously. Risk management and self-diagnosis are other use cases being explored.
9. Blockchain-As-A-Service software
Microsoft is integrating “BaaS modules” (based on the public Ethereum) in its Azure that users can create test environments for. Blockchains are cheaper to create and test, and in Azure they come with reusable templates and artifacts.
10. Governance 3.0
Blockchain and AI could contribute to the development of direct democracy. They can transfer big hordes of data globally, tracing e-voting procedures and displaying them publicly so that citizens can engage in real-time. Democracy Earth Foundation aspires to “hack democracy“ by advocating open-source software, peer-to-peer networks, and smart contracts. The organization also aims to fight fake identities and reclaim individual accountability in the political sphere. IPDB is a planetary-scale blockchain database built on BigchainDB. It’s a ready-to-use public network with a focus on strong governance.