Blockchain + AI = ?

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.

Modern saga “The Fox and the Hedgehog”: generalists vs. specialists

About 2,700 years ago, Archilochus wrote that “The fox knows many things, but the hedgehog knows one big thing.” Taking that as a starting point, Isaiah Berlin’s 1953 essay “The Fox and the Hedgehog” contrasts hedgehogs that “relate everything to a single, central vision” with foxes who “pursue many ends connected … if at all, only in some de facto way.”

And so we have become a society of specialists with much heralded “learn more about your function, acquire ‘expert’ status, and you’ll go further in your career” considered the corporate Holy Grail. But is it?

The modern corporation has grown out of the Industrial Revolution (IR). The IR started in 1712 when an Englishman named Thomas Newcomen invented a steam-driven pump, to pump water out of a mine, so the English miners could get more coal to mine, rather than hauling buckets of water out of the mine. That was the dawn of the IR. It was all about productivity, more coal per man-hour; and then it became more steel per man-hour, more textiles per man-hour, etc.

The largest impact of the IR was the “socialization” of labor. Prior to the IR, people were largely self-sufficient, but the IR brought increased division of labor, and this division of labor brought specialisation, which brought increased productivity. This specialisation, though, decreased self-sufficiency and people became increasingly inter-dependent on one another, thus socialised more. Also, with the division of labor the individual needed only to know how to do a specific task and nothing more. Specialization also caused compartmentalization of responsibility and awareness. On a national level, it has allowed nations to become increasingly successful while the citizens become increasingly ignorant. Think an average American. You can be totally wrong about almost everything in life, but as long as you know how to do one thing good you can be a success, and in fact in a society such as this increased specialization becomes advantageous due to the extreme competition of our society. Environments with more competition breed more specialists.

But is the formula that ushered humanity in 20th century of rapid technological industrialisation and economic development still valid or as impactful in 21st century as it was for last 300 years? In our modern VUCA world, who (specialist OR generalists) have a better chance of not only surviving but thriving?

According to a number of independent research papers, employees most likely to come out on top of companies and becoming successful in long term are generalists—but not just because of their innate ability to adapt to new workplaces, job descriptions or cultural shifts. For example, according Carter Phipps (author of Evolutionaries) generalists (will) thrive in a culture where it’s becoming increasingly valuable to know “a little bit about a lot.” More than half of employees with specialist skills now consider their job to be mostly generalist despite the fact that they were employed for their niche skills, according to another survey. Among the survey respondents, 60% thought their boss was a good generalist, and transferable skills – such as people skills and leadership – are often associated with more senior roles.

We’ve become a society that’s data (from all various specialisation, industries and technologies) rich and meaning poor. A rise in specialists in all areas — science, math, history, psychology — has left us with huge amount of data/info/knowledge but how valuable is it without context? Context in a data-rich world can only be provided by generalists whose breadth of knowledge can serve as the link between various disciplines/contexts/frameworks.

A good generalist, David Christian gave his 2011 TED talk called “Big History” of the entire universe from the big bang to present in 18 mins, using principals of physics, chemistry, biology, information architecture and human psychology.

To conclude, it seems that specialisation is becoming less and less relevant due to 1) increasing, interconnected and overlapping data and information that permeates all aspects of our lives, 2) increasing VUCA-ness of social, political and economic situations of individuals and nations, 3) need to envision and derive from a bigger context or connect few contexts/disciplines/frameworks. All points seem to be better addressed by generalists.

No Industrial Revolution in Ancient Greece?

One of the oldest and hardest puzzles in economic history is the failure of Ancient Greek Eastern Mediterranean civilization to make some kind of breakthrough to more rapid development of labor-saving technology, to faster technological progress, and to an industrial revolution. There have always been three theories as to why this did not happen:

The “insufficient density” theory–not enough thinkers, not enough tinkerers, not enough ability to shape metal finely and precisely for the set of those interested in scientific progress and technological development to reach critical mass.
The “lack of a market economy” theory: those who would have sought wealth and power through entrepreneurship and enterprise in a modern market economy instead, because trade was small in volume and under the thumb of politics, went into the army or into politics. This misallocation of talent stalled human progress.
Fuzzier explanations based on the role of slavery in classical civilization and on the elective anti-affinity between the existence of slavery on the one hand and elite interest in boosting productivity on the other.

In 2002, there appeared an article in the Economist shedding light on Greek metalworking prowess and interest in astronomical models. According to the article, few corroded lumps — the last remnants of an elaborate mechanical device – were extracted by accident by a Greek sponge diver in 1900. The Antikythera mechanism, as it is now known, was an astronomical computer capable of predicting the positions of the sun and moon in the zodiac on any given date according to Yale scientist Derek Price. Price believed that the mechanism was strongly suggestive of an ancient Greek tradition of complex mechanical technology which, transmitted via the Arab world, formed the basis of European clockmaking techniques. This fits with another, smaller device that was acquired in 1983 by the Science Museum, which models the motions of the sun and moon. Dating from the sixth century AD, it provides a previously missing link between the Antikythera mechanism and later Islamic calendar computers, such as the 13th century example at the Museum of the History of Science in Oxford. That device, in turn, uses techniques described in a manuscript written by al-Biruni, an Arab astronomer, around 1000AD.

The origins of much modern technology, from railway engines to robots, can be traced back to the elaborate mechanical toys, or automata, that flourished in the 18th century. Those toys, in turn, grew out of the craft of clockmaking. And that craft, like so many other aspects of the modern world, seems to have roots that can be traced right back to ancient Greece.

Therefore the evidence chips away somewhat at first theory.

The Greek word oikonomia (οἰκονομία) designates mainly the oikos (οἶκος), meaning the home or hearth. Xenophon’s dialogue Oeconomicus is concerned with household management and agriculture. The Greeks had no precise term to designate the processes of production and exchange and no word describing or being equivalent of market-based economy.

However as famous American historian Murray Rothbard pointed out, Xenophon outlined the important concept of general equilibrium as a dynamic tendency of the economy by stating that when there are too many coppersmiths, copper becomes cheap and the smiths go bankrupt and turn to other activities, as would happen in agriculture or any other industry. He also saw clearly that an increase in the supply of a commodity causes a fall in its price. These thoughts correspond to the collective wisdom of modern market economy, chipping away on the second theory. There are other sources arguing the power of the market mentality attained in Ancient Greece.

There is no countering the third theory – not from my side at least!