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Transhuman Crypto Cloudminds

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The Transhumanism Handbook


Considering the mutual benefits of blockchain and transhumanism, this essay proposes crypto cloudminds as a safe mechanism by which the human mind might transcend its unitary limitations by permissioning partial resources to join a multi-party mind (comprised of human and machine minds) in a cloud-based environment. Cloudminds could have diverse purposes including problem solving (addressing future-of-work issues with Maslow Smart Contracts), learning, experience, exploration, innovation, artistic expression, and other personal development activities. Crypto cloudminds could be multicurrency, operating with payment remuneration, security, and (especially) ideas as the denominations of measure. For thriving in the future, mind node peers could enter “Yes-and” Payment Channels with one another for collaborative idea development. For surviving in the future, good-player behavior could be game-theoretically enforced with the simultaneous privacy-transparency property of blockchains, together with the immutable peer-confirmed consensus algorithm and audit-log checks and balances system. Overall, blockchains might serve as an institutional technology that is the basis for treaties and progress in a multi-species society of human, algorithm, and machine, guiding the way to positive transhuman futures.

“Science is the great antidote to the poison of enthusiasm and superstition.”

–Adam Smith (The Wealth of Nations, 1776 [1])

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  1. Smith, A. (1776, 2003). The Wealth of Nations. Blacksburg VA: Thrifty Books.

    Google Scholar 

  2. Kurzweil, R. (2006). The Singularity Is Near: When Humans Transcend Biology. New York: Penguin Books.

    Google Scholar 

  3. Bostrom, N. (2016). Superintelligence: Paths, Dangers, Strategies. Oxford: Oxford University Press.

    Google Scholar 

  4. Dowd, M. (2017). Elon Musk’s Billion-dollar Crusade to Stop the AI Apocalypse. Vanity Fair.

    Google Scholar 

  5. Miller, R.S. and Shorter, G. (2016). High Frequency Trading: Overview of Recent Developments. U.S. Congressional Research Service. 7–5700. R44443.

  6. Kirilenko, A., Kyle, A.S., Samadi, M., and Tuzun, T. (2014). The Flash Crash: The Impact of High Frequency Trading on an Electronic Market. U.S. CFTC.

    Google Scholar 

  7. Cowen, T. (2013). Average Is Over: Powering America Beyond the Age of the Great Stagnation. New York: Dutton.

    Google Scholar 

  8. Frey, C.B. and Osborne, M.A. (2013). The Future of Employment: How susceptible are Jobs to Computerisation. Oxford. See also:

  9. The Economist. (2016). US Population Survey. Federal Reserve Bank of St. Louis.

  10. Bland, B. (2016). China’s robot revolution. Financial Times.

  11. Chan, J. (2017). Robots, not humans: official policy in China. New Internationalist.

  12. Swan, M. (2015). Blockchain Thinking: The Brain as a DAC (Decentralized Autonomous Corporation). IEEE Technology and Society. 34(4):41–52.

    Google Scholar 

  13. Swan, M. (2019). Blockchain Economic Theory: Digital Asset Contracting reduces Debt and Risk. In Swan, M., Potts, J., Takagi, S., Witte, F., Tasca, P., Eds. Blockchain Economics: Implications of Distributed Ledgers – Markets, communications networks, and algorithmic reality. London: World Scientific.

    Chapter  Google Scholar 

  14. State of the Dapps. Retrieved October 7, 2018:

  15. Swan, M. (2017). Is Technological Unemployment Real? Abundance Economics. In Surviving the Machine Age: Intelligent Technology and the Transformation of Human Work. Eds. James Hughes and Kevin LaGrandeur. London: Palgrave Macmillan. 19–33.

    Chapter  Google Scholar 

  16. Scholz, T. (2016). Platform Cooperativism. Challenging the Corporate Sharing Economy. New York: Rosa Luxemburg Stiftung.

    Google Scholar 

  17. Anzilotti, E. (2018). Finland’s Basic Income Pilot Was Never Really A Universal Basic Income. Fast Company.

  18. Swan, M. (2015). Blockchain: Blueprint for a New Economy. Sebastopol CA: O’Reilly Media.

    Google Scholar 

  19. Hebblethwaite, C. (2018). IDC: Global blockchain spending to hit $9.2 billion in 2021. The Block.

    Google Scholar 

  20. World Economic Forum. (2015). Deep Shift: Technology Tipping Points and Societal Impact. Survey Report.

    Google Scholar 

  21. Davidson, S., de Filippi, P., Potts, J. (2018). Blockchains and the Economics institutions of capitalism. Journal of Institutional Economics. 1–20.

    Google Scholar 

  22. Swan, M. (2018). Blockchain Economics: “Ripple for ERP” integrated blockchain supply chain ledgers. European Financial Review. Feb-Mar: 24–7.

    Google Scholar 

  23. Merkle, R. (2016). DAOs, Democracy and Governance. Cryonics Magazine. July-August. 37(4):28–40.

    Google Scholar 

  24. Swan, M., dos Santos, R.P. (2018-Submitted). Smart Network Field Theory: The Technophysics of Blockchain and Deep Learning. Concurrency and Computation: Practice and Experience. Wiley.

    Google Scholar 

  25. Swan, M. (2016). The Future of Brain-Computer Interfaces: Blockchaining Your Way into a Cloudmind. Journal of Evolution and Technology. 26(2).

    Google Scholar 

  26. “BINA48.” Wikipedia. Retrieved October 7, 2018:

  27. Rock, D. and Grant, H. (2016). Why Diverse Teams are Smarter. Harvard Business Review.

    Google Scholar 

  28. Martins, N.R.B., et. al. (Submitted). Human Brain/Cloud Interface.

    Google Scholar 

  29. Walker, M. (2018). Why We Sleep: Unlocking the Power of Sleep and Dreams. New York: Scribner.

    Google Scholar 

  30. Swan, M. (2018). Blockchain consumer apps: Next-generation social networks (aka strategic advice for Facebook). CryptoInsider.

    Google Scholar 

  31. Zhao, W. (2017). A Russian Airline Is Now Using Blockchain to Issue Tickets. Coindesk.

    Google Scholar 

  32. Gazprom. (2018). Gazprom Neft and S7 Airlines become the first companies in Russia to move to Blockchain Technology in Aviation Refueling. Press Release.

    Google Scholar 

  33. Domonoske, C. (2018). California Sets Goal Of 100 Percent Clean Electric Power By 2045. NPR.

    Google Scholar 

  34. National Energy Board. (2018). Provincial and Territorial Energy Profiles. Government of Canada. Retrieved October 7, 2018:

  35. Sherchan, W., Nepal, S., Paris, C. (2013). A Survey of Trust in Social Networks. ACM Comput Surv. 45(4). Pp. 47:1–47:33.

    Article  Google Scholar 

  36. Harris, L. (2016). Dignity and Subjection. Présence Africaine. 1(193):141–159; 59–77.

    Article  Google Scholar 

  37. Young, I.M. (2011). Justice and the Politics of Difference. Princeton: Princeton University Press.

    Google Scholar 

  38. Swan, M. (2018). Blockchain Enlightenment and Smart City Cryptopolis. CryBlock’18 Proceedings. Workshop on Cryptocurrencies and Blockchains for Distributed Systems. Munich, Germany. June 15, 2018. Pp. 48–53.

    Google Scholar 

  39. Allen, D.W.E. (2019). Entrepreneurial Exit: Developing the Cryptoeconomy. In Swan, M., Potts, J., Takagi, S., Witte, F., Tasca, P., Eds. Blockchain Economics: Implications of Distributed Ledgers – Markets, communications networks, and algorithmic reality. London: World Scientific

    Google Scholar 

  40. Twenge, J.M. (2017). Have Smartphones Destroyed a Generation? The Atlantic.

  41. CDC. (2018). Suicide rising across the US: More than a mental health concern. CDC Report.

    Google Scholar 

  42. Swan, M. (2018). Smart Network Economics: Payment Channels.

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Author’s Note

This essay in the book won the first prize in the Humanity Plus Essay Competition “Mutual Benefits of Blockchain and Transhumanism”:

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Correspondence to Melanie Swan .

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Blockchain (distributed ledger) Technology

A blockchain is an immutable, cryptographic (cryptography-based), distributed (peer-based), consensus-driven ledger. Blockchain (distributed ledger) technology is a software protocol for the instantaneous transfer of money and other forms of value (assets, contracts, public records, program states) globally via the internet.


A cloudmind is a cloud-based collaboration of human and machine minds (with safeguards and permissions). “Mind” is generally denoting an entity with some capacity for processing, not the volitionary action and free will of a consciousness agent.

Crypto cloudminds

Crypto cloudminds is the idea of implementing cloudminds with the safeguards of blockchain technology.


Cryptoeconomics is an economic transaction paradigm based on cryptography; more specifically, an economic transaction system implemented in a cryptography-based software network, using cryptographic hashes (computational proof mechanisms) as a means of confirming and transferring monetary balances, assets, smart contracts, or other system states. A key concept is trustless trust, meaning removing as much human-based trust as possible to make the economic system trustworthy (relocating human-based trust to cryptography-based trust).


Cryptosecession is the idea of employing blockchains as an institutional technology to opt out of traditional governance and legal structures.

Deep Learning Chains

Deep learning chains are a class of smart network technologies in which other technologies, blockchain and deep learning, converge as a control technology for other smart network technologies. Deep learning chains have the properties of secure automation, audit-log tracking, and validated transaction execution of blockchain, and the object and pattern recognition technology (IDtech) of deep learning. Deep learning chains might be used to control other fleet-many internet-connected smart network technologies such as UAVs, autonomous driving fleets, medical nanorobots, and space-based asteroid mining machines.

Deep Learning Neural Networks

Deep learning neural networks are computer programs that can identify what an object is; more technically, deep learning is a branch of machine learning based on a set of algorithms that attempts to model high-level abstractions in data by using artificial neural network architectures, based on learning multiple levels of representation or abstraction, such that predictive guesses can be made about new data.


IDtech is identification technology, the functionality of object recognition as an in-built feature in technology. IDtech is similar to FinTech, RegTech, TradeTech, and HealthTech; technologies that digitize, standardize, and automate operations within their respective domains.

Payment Channel

A payment channel is a contractually-obligated payment structure that elapses over time, protecting and obligating two parties who need not know and trust each other [42]. The payment channel operates in three steps. First, Party A opens a payment channel with Party B and posts a pre-paid escrow balance (the escrow deposit is broadcast to the blockchain, and a corresponding refund transaction for the same amount is signed by both parties, but not broadcast). Second, Party A consumes a resource (or provides a service such as programming hours) against the escrow balance, and activity is tracked and updated (in revised refund transactions that both parties sign but do not broadcast). Third, at the end of the period (or at any time), the cumulative activity is booked in one net transaction to close the contract. In addition to the FinTech innovation of parties not knowing each other being able to digitally contract in a protected manner over time, payment channels might also provide scalability to blockchains by only logging net transactions.

Smart Contract

A smart contract is a software program registered to a blockchain for confirmation (time-datestamping provenance), and possibly some form of automated execution. To be legally-binding as an eContract, smart contracts need to have the four elements of “regular” contracts: two parties, consideration, and terms.

Smart Networks

Smart networks are intelligent autonomously-operating networks. Exemplar smart network technologies include blockchain economic networks and deep learning pattern recognition neural networks.


Technophysics is the application of physics to the study of technology (by analogy to biophysics and econophysics), particularly using statistical physics, information theory, and model systems for the purpose of characterizing, monitoring, and controlling smart network systems in applications of arbitrarily-many fleet item management and system criticality detection.

Token Economy

The token economy is the situation in which web-based communities issue their own cryptotoken money supplies. The tokens serve as an accounting system for coordinating a local economy between members, a tracking system that can be used to link participative contributions with remuneration (solving the credit assignment problem). In Web 3.0, users expect to participate meaningfully in communities, meaning being remunerated for contributions, accessing resources, and voting on community decisions.

Web 3.0 (the crypto web)

Web 3.0 refers to the idea of cryptoeconomic business models such as data markets and computation markets running on the “internet’s new pipes” of distributed network systems, content-addressable file-serving, and IDtech. Web 1.0 (the static web) involved the transfer of static information and Web 2.0 (the social web) created the expectation that website users can interact, like, and engage with content and other users. In Web 3.0 (the crypto web), users expect to participate meaningfully in economic communities by being remunerated for contributions (such as software code, digital art, and forum posts), and by being able to vote on decisions and access resources.

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Swan, M. (2019). Transhuman Crypto Cloudminds. In: Lee, N. (eds) The Transhumanism Handbook. Springer, Cham.

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