Superabundant design

Cryptocurrencies are surreptitiously inhabited by a nature of excessiveness. Logics of overabundance are expressed in different levels: first and more important, on the core technique used for the double purpose of securely validate transactions and produce tokens, also known as mining. Second, as a consequence of the former, in the energy consumption and production of waste of specialized mining hardware. Particular logics of excess are expressed in the large and futile surplus of algorithmic power, energy, and waste embedded in cryptocurrencies’ operation of a successfully secure transaction system.
In Bitcoin, the prototypical cryptocurrency, the intrinsic value of the tokens settles under an algorithmic regime of language quite related to excessiveness. A very introductory video explains that “the bitcoin network is secured by individuals called miners. Miners are rewarded newly generated bitcoins for verifying transactions.” (WeUseCoins). Miners are machines that verify the signed public keys for each transaction and which validate these into blocks in a public registry (i.e. the Blockchain). The job for successfully validating and packing the transactions produces new tokens for the miner, and generates a Proof-of-Work. The former is the result of a ‘puzzle’, which can be then easily checked by any other machine in the network. Since the design of the system seeks a controlled pace, if the coins are generated to fast (because there are more and/or stronger miners) the ‘puzzle’ becomes harder (Nakamoto).
The analogy of a puzzle is only appropriate within its algorithmic dimension, that means it must be understood not as a toy or a game, but as a problem that must be solved by following a set of rules. More accurately, the puzzle consists in generating aleatory hashes (a string of numbers and letters with a defined length) until one of them fulfils the requisites asked for the difficulty (in the case of Bitcoin, a number of zeroes at the beginning of the resulting hash). Due to the random non-repeatable number involved in the operation, the ‘nonce value’, it is especially difficult to create a ‘desirable’ hash. Every attempt to come up with a successful hash uses a new random number, thus randomizing the result. Difficulty is hence, in this context, associated with probability and far from tribulation. Regarding Bitcoin, difficulty is an algorithmic adversity.

Difficulty (D) is now (19th September 2015) set on 59,335,351,233.87, which translates as a 225xD number of average hashes to find a block. This means one opportunity to build a block for every 19,909,640,081,173,010,000 (A) tried hashes. The only way to deal with the odds involved in this operation is to have a machine capable of generating as many number of attempts per second as possible. A state-of-the-art dedicated unit available today can manage to make 5,500,000,000,000 [SP20 Jackson by Spondoolies-Tech]. To calibrate the surplus involved, it is better to think of it in negative terms: unlike the lottery (at which a lonely miner would have better odds) where every non-winner plays a passive role, the miner is a machine that actually uses computational power to actively generate 19,909,640,081,173,009,999 (A – 1) useless hashes. It is hard to think of a greater surplus for a system.

Waste and energy

The excessive nature of the puzzles that mechanically produce hashes takes place on a logical level, but it also transforms itself into a material overflow. Controlled production of tokens directly translates into a relevant issue of consumption of energy and production of waste. From the deployment of the device up until the middle of 2010, mining was a task that any modern CPU could handle, even thought the process would push it to its limits and heavily reduce its lifetime. Until mid-2011 the workload moved to GPUs, but was rapidly surpassed by FPGA’s (Field Programmable Gate Arrays), which reduced energy consumption while achieving more hashes per second. The next natural step were ASIC miners (Application Specific Integrated Circuit) at the beginning of 2013. [For a history of Bitcoin mining hardware, up until the end of 2013, see (Taylor)].
Even thought the network was maintained at the beginning by every enthusiast with a computer and some energy to spare, today the mining industry is populated with pools and dedicated farms. This evolution was foreseen in Bitcoin’s design (Nakamoto, ‘NCML’). In pools, different miners contribute their processing power to calculate a block together. The reward is then distributed among them, usually accordingly to the computational power given, although each pool has its own share protocols). Each one of these clustered miners can have one or multiple ASIC’s. Mining farms on the other hand are dedicated places that behave in an undistributed fordist fashion, and are even located in old factories or abandoned stores, which house swarms of ASIC’s (‘Bitcoin Mining in an Abandoned Iowa Grocery Store’). The energy consumed in farms is noteworthy. A one year old paper estimated (Malone and O’Dwyer) that the mining network at the time was on par with the electricity consumption in Ireland. Mining units have improved in the last year and also its energy efficiency, but the difficulty enlarged too, resulting on a considerable energy footprint problem. An specific still operating farm has been told to have 10,000 S3 mining units (‘My Life Inside a Remote Chinese Bitcoin Mine’). The Antminer S3 is able to produce 441 GH/s and consumes 800W/TH: that is roughly 4761 Watts in a day, for just one unit. A farm with 10,000 of these units would consume 47,616 KW a day. Comparing these figures with home energy consuming estimates in the U.S. (‘How Much Electricity Does an American Home Use? – FAQ – U.S. Energy Information Administration’) shows that just this farm consumes 1,571 times more energy than an average household.
Mining, at this point of the evolution of the device, is a race, and reducing the energy footprint is not grounded in pollution awareness, but in costs cutting. And while mining units become progressively more energy efficient, they simultaneously become more obsolete. A constant refill of state-of-the-art equipment is necessary to stay in the race. Obsolescence of hardware is not exclusive to the Bitcoin phenomenon, smartphones and all sorts of gadgets are ‘recicled’ every year as a complex economical and cultural outcome of, among other things, planned obsolescence -an appealing subject for marketing and industrial economics some decades ago, but recently reborn within the scope of ecological awareness (Guiltinan). But unlike the smartphone market, mining units do not suffer of a short life because of its hardware resistance, cheap materials or fashionable ideologies of consumption, ‘planned obsolescence’ for ASIC’s resides in the scarcity model of Bitcoin’s design. Tokens have a fixed limit (21 million) and are getting harder to obtain, so the fast production and consumption cycles of the hardware are intrinsic to the system. At least until the mining becomes unprofitable, in such scenario the number of miners diminish and with it the difficulty (which, again and recursively, makes the people interested in mining to go up). Difficulty, however, rarely drops, and on the long run describes a stepping curve (‘Bitcoin Difficulty Chart – Chart of Mining Difficulty History’), which makes mining hardware to age fast.
Being specific circuits optimized for hashing, ASIC’s do not have a second life. Unlike GPU’s, they are useless for any other tasks, which makes them completely worthless after its useful, yet short, life. Since there is no second hand market for mining units, they rapidly add up to High Tech trashing problems. Electronic waste arguably conforms today about the same amount as plastic packaging waste (in municipal numbers) (Puckett and Smith). Most of the e-waste is recycled in foreign countries because of low labor costs, and loose environmental regulations both externally (at least in the, U.S. for export of hazardous materials) and internally (waste handling in the host countries). Arguably, around 80% of e-waste is exported to Asia, and 90% of these exports goes to China. The hashing power that runs throughout the bitcoin network, i.e. the most and more powerful machine miners, clusters in China too. On a rough estimate (‘Bitcoin Hashrate Distribution – Blockchain.info’) more than 50% of the hashing power is concentrated in Chinese mining pools and a significant part of the rest is in the U.S., meaning that most bitcoin’s e-waste hazardous recycling labor will end eventually in poor communities of Asia.

Surplus logics

The number of mines and of ASIC’s in them is obscure. Nonetheless, the quantity of e-waste coming directly from mining does not compare to the waste produced by other gadgets, like those of the smartphone industry. The discussion around excess is not so much framed in quantity, however, but in its lifespan and purpose: hardware mining units are limited to the one and only task of producing hashes. The substantial empty computational work, energy usage, and e-waste produced in the mining operation has no other goal, and so far no other purpose, than to keep the machine running. Cryptocurrencies’ personal system of consumption is a medium to an end, and whether this surplus is void or not hangs from the latter. To the question if Bitcoin mining is a waste of energy Bitcoin Foundation (‘FAQ – Bitcoin’) answers that “Spending energy to secure and operate a payment system is hardly a waste”. The former phrase can be reformulated as “it is not a waste, as long as the system works”. The idea of waste is superseded by efficiency, and annulled in a scenario where the system is fully operative.
The competence and superior security of the system, underpinned by the former logics of wastage, is what gives Bitcoin and other cryptocurrencies a compelling symbolic value. An economic value is added to this initial computational worth after media attention and market performance effectively consider the tokens of this system as assets or financial objects. A rush to adopt and exploit the venues followed, as the system became more and more public, in great part due to its speculative disposition, which ended in more traditional representations of excess in the form of financial bubbles.
Due to the layered nature and fuzz of cryptocurrencies, it is difficult to avoid the accumulation of different expressions of symbolic, economic and informational value. Cryptocurrencies and its ecosystems are expressed in diverse financial fields; social platforms, project platforms (i.e. Github), mainstream and dedicated news (i.e. Coindesk), scholar research, and its own material network and Blockchain. Open research questions arise from the multiple informational sources of the object: How to frame research within this information overload? What is research surplus here? How much of the object’s nature resides in its very excessive performances and how much is made up through mere contemporary compulsive research? Are the former logics of wasted surplus to keep systems running exclusive to Cryptocurrencies, or is it the subtle milieu of a networked/algorithmic society? It has been argued that information technologies, material production and disposal included, operate as technologies of excess and, recursively, the devices involved in these cycles are “the very devices through which we can trace emerging forms of proliferation” (Gabrys 33). As research gets involved with the digital, both as an object of study and as a methodology device, the surplus that comes from within it is inherited in different forms. In the case of cryptocurrencies, a network communicates uninterruptedly to share an undetermined number of registry’s copies, in order to create what probably are the first truly unique digital tokens. Peculiarly, the token is a non-duplicable unity enabled by the performance of a multiplicity of machines, the entropy of a large number, and the logics of (an illusive) overabundant machine labor.

References

‘Bitcoin Difficulty Chart – Chart of Mining Difficulty History’. CoinDesk. N.p., n.d. Web. 28 Sept. 2015.
‘Bitcoin Hashrate Distribution – Blockchain.info’. N.p., n.d. Web. 28 Sept. 2015.
‘Bitcoin Mining in an Abandoned Iowa Grocery Store’. Motherboard. N.p., n.d. Web. 28 Sept. 2015.
‘FAQ – Bitcoin’. N.p., n.d. Web. 28 Sept. 2015.
Gabrys, Jennifer. Digital Rubbish: A Natural History of Electronics. Reprint edition. University of Michigan Press, 2013. Print.
Guiltinan, Joseph. ‘Creative Destruction and Destructive Creations: Environmental Ethics and Planned Obsolescence’. Journal of Business Ethics 89 (2009): 19–28. Print.
‘How Much Electricity Does an American Home Use? – FAQ – U.S. Energy Information Administration (EIA)’. N.p., n.d. Web. 28 Sept. 2015.
Malone, D., and K.J. O’Dwyer. ‘Bitcoin Mining and Its Energy Footprint’. Institution of Engineering and Technology, 2014. 280–285. CrossRef. Web. 23 July 2015.
‘My Life Inside a Remote Chinese Bitcoin Mine’. CoinDesk. N.p., n.d. Web. 28 Sept. 2015.
Nakamoto, Satoshi. ‘Bitcoin: A Peer-to-Peer Electronic Cash System’. Consulted 1 (2008): 2012. Print.
—. ‘CML: Bitcoin P2P E-Cash Paper’. Archive. Cryptography Mailing List. N.p., 1998. Web. 12 Apr. 2014.
Puckett, Jim, and Ted Smith, eds. Exporting Harm: The High-Tech Trashing of Asia. Seattle, Wash.: Diane Pub Co, 2003. Print.
Taylor, Michael Bedford. ‘Bitcoin and the Age of Bespoke Silicon’. Proceedings of the 2013 International Conference on Compilers, Architectures and Synthesis for Embedded Systems. Piscataway, NJ, USA: IEEE Press, 2013. 16:1–16:10. ACM Digital Library. Web. 23 July 2015. CASES ’13.
WeUseCoins. What Is Bitcoin? (v2). N.p., 2014. Film.

Advertisements