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Category: academic

The Internet of Garments

Here’s a brief treatment I wrote on the concept of an Internet of Garments [IoG] and the notion of provenance which is a key effect of IoG implementation at scale.

Throughout history clothing has played the role of a medium signifying the wearer’s status, identity and group belonging. Clothing often acts as the first, and sometimes only, signifier of the wearer’s socio-economic status, occupation, class position, ethnic group, tribal affiliation, religious denomination, or subculture.  As a piece of wearable media, clothes communicate this information through their shape, color, arrangement, pattern, the combination of garments, and even the nature of the fabrics being worn. For example, Mediterranean antiquity associated silk and the purple dye with royalty and high social standing, in the case of purple die due to its rarity and in the case of silk due to its unique provenance.

Our identity is inextricably tied to our clothing

Similarly, Medieval Europe understood very well the role of clothing as wearable media, with sumptuary laws regulating in detail the clothing appropriate to one’s social status, and prohibiting well-off merchants from wearing clothing associated with the nobility. Even today, from corporate executives, to schoolchildren, soldiers, and prisoners, we rely on uniform clothing and a set pattern of garments to signal status and identity. In that context, our garments should be understood as always already talking about us, relentlessly and incessantly.

Importantly, the ongoing revolution in wearables and Internet of Things (IoT) related objects, is leading to the emergence of smart garments and a paradigm of connected clothing – an Internet of Garments [IoG]. The IoG involves scenarios in which garments might consist of all or some of sensors, advanced materials, antennas, memory, and processing power. Such garments inevitably become uniquely identifiable and capable of communicating with their environment, therefore transitioning from analogue clothing to computational media.

While the IoT ostensibly talks to you, for example through devices such as the Amazon Echo, the IoG primarily talks about you, for example through data stored in your garments. Every physical product in this new paradigm has a digital history, allowing consumers to trace and verify its origins, as well as attributes and ownership. Ubiquitous connectivity allows the precise mapping of production processes and the tracing of materials from animal to distributor and consumer – in other words, establishing provenance.

Provenance

The notion of provenance stands for the process of establishing and authenticating a record of origin, as well as the logistics of production, distribution and usage of a given fabric. In the context of IoG, it stands for the garment’s entire life cycle across the supply chain, from the fabric’s prehistory with a specific animal (in case of wool) or collection of materials (synthetics), through its conversion into a garment, its travels through the logistical chain, its interfacing with a specific customer, and its history afterwards.

In the IoG a merino wool sweater’s provenance begins here. Everything from living conditions to food and ethical treatment is part of the provenance ledger.

In the case of wool garments for example, this involves all available data about the source animal [date and place of birth, conditions of life], all data about the producer [location, labour practices, ethical treatment of animals, supply chain], all data about processor and distributor [location, labour practices, quality of process, supply chain], as well as the consumer [location, wearing patterns, etc]. Moreover, the ability to map and access at will logistical information about a product gives us a level of high provenance granularity acting as a guarantee of ethical and certified location, as well as ethical production processes.

The process can be visualized conceptually as consisting of two distinct phases: establishing provenance and authenticating it. In the context of the wool industry, the establishing phase allows a wool producer to map and follow the entire logistical chain from animal to distributor, while the authentication phase allows distributors and customers to continuously verify the provenance of a fabric or garment. Therefore, when viewed over time in the context of IoG, provenance acts both as an interface between producers and users, and as a marketing/semantic interface between different user groups. Importantly, in both of these roles provenance acts as a dynamic bill of existence or ledger for a garment.

The final provenance interface and the main platform for a provenance-based reputation system in fashion.

In its role as an IoG interface between producers and users, this ledger offers an animal-to-shop perspective, and a way to inject ethical and sustainable production practices throughout the process. In its role as a marketing/semantic interface between different user groups, the ledger acts as a passport, certifying the provenance of the wearer within the context of an ethical standard and fashion statement/brand identity. Understood this way, when provenance is considered dynamically over a time period, what emerges is a reputation system based on the publicly available supply chain information, the quality and ethical positioning of the source materials, labour practices, etc. In that context, the concept of provenance should be understood in terms of expanding quantification and the emergence of a dataistic paradigm in wearables, as well as specifically in the garment industry and fashion.

Comparative hierophany at three object scales

This is an essay of mine to appear in an upcoming book I am co-writing with a few colleagues, titled 100 Atmospheres: Studies in Scale and Wonder. The book is coming out in August 2018 from Open Humanities Press, and it will be available in 4 different versions: as a standard paperback through Amazon, as free download through the Open Humanities Press site, through Scalar as an interactive space, and through Big Fag Press as a limited edition hardcover. Exciting!

 

Complex systems and glitch

The more complex and orderly the system, the more it is prone to confuse its internal states for external reality. It confuses its internal order for external one.

That is why when things glitch and get weird we see new and strange states appear. The system’s internal cohesion momentarily glitches or breaks, and we get the chance to reframe our cognitive image of reality.

That’s when we learn.

Fail Early Fail Often

Here are the prezi slides from a guest lecture I gave on the Fail Early Fail Often philosophy [#fefo], as well as the methodology of Fast, Inexpensive, Simple, Tiny [#fist].

And below are some related gifs I made for the occasion:

Distributed swarms, OODA loops, and stigmergy

This is a third paper in a cycle on distributed swarms, OODA loops and stigmergy co-authored with a PhD student of mine. The paper is titled Distributed Swarming and Stigmergic Effects on ISIS Networks: OODA Loop Model, and was published in the Journal of Media and Information Warfare. This is probably the densest and most interesting paper in the series, as we analyse information warfare waged by distributed swarms in the context of network-centric warfare theory, stigmergic adaptation, and John Boyd’s work on the OODA loop concept. For me the most interesting elements of the paper involve our discussion of Von Moltke’s concept of auftragstactic in the context of maneuver warfare in the information domain.

On the use of Telegram in lone wolf attacks

This is a paper I co-authored with two collaborators, one of which is a PhD student of mine, titled Encrypted Jihad: Investigating the Role of Telegram App in Lone Wolf Attacks in the West, and published in the Journal of Strategic Security. We examine the role played by Telegram, one of the most popular social media apps offering end-to-end encrypted communications, in the command and control [C2] operations of distributed terrorist organizations. Specifically, I was interested in illustrating how encrypted platforms such as Telegram can be used as part of a complex stigmergic communications strategy relying on memetic impact both within the distributed network and outside of it. In brief, Telegram acts as a standalone communication platform where core C2 vectors are encrypted and obfuscated from counter-terrorism efforts, while all other communication is built for maximum memetic potential, relying on stigmergic impact among otherwise unconnected nodes acting as lone wolves.

Black-boxing the Black Flag

This is a paper I co-wrote with a PhD student of mine, titled Black-boxing the Black Flag: Anonymous Sharing Platforms and ISIS Content Distribution Tactics, currently in peer reviewWe analyse ISIS’ use of anonymous sharing portals in its content distribution operations as part of a broader information warfare strategy focused on withstanding degrading attacks by popular social media portals. What is interesting about this paper is that we use a key notion from actor network theory – the black box – to conceptualise the role of anonymous sharing portals in the propaganda operations of distributed terrorist networks.

Network architecture encounters

These are some loosely organized observations about the nature of network topologies in the wild.

In terms of both agency and information, all entities, be they singular [person], plural [clan/tribe/small company], or meta-plural [nation/empire/global corporation] are essentially stacks of various network topologies. To understand how the entities operate in space these topologies can be simplified to a set of basic characteristics. When networks are mapped and discussed, it is usually at this 2-dimensional level. However, in addition to operating in space, all entities have to perform themselves in time.

This performative aspect of networks is harder to grasp, as it involves a continuously looping process of encountering other networks and adapting to them. In the process of performative adaptation all networks experience dynamic changes to their topologies, which in turn challenge their internal coherence. This process is fractal, in that at any one moment there is a vast multiplicity of networks interacting with each other across the entire surface of their periphery [important qualification here – fully distributed networks are all periphery]. There are several important aspects to this process, which for simplicity’s sake can be reduced to an interaction of two networks and classified as follows:

1] the topology of the network we are observing [A];

2] the topology of network B, that A is in the process of encountering;

3] the nature of the encounter: positive [dynamic collaboration], negative [dynamic war], zero sum [dynamic equilibrium].

All encounters are dynamic, and can collapse into each other at any moment. All encounters are also expressed in terms of entropy – they increase or decrease it within the network. Centralized networks cannot manage entropy very well and are extremely fragile to it.

Positive encounters are self explanatory, in that they allow networks to operate in a quasi-symbiotic relationship strengthening each network. These encounters are dynamically negentropic for both networks, in that they enable both networks to increase coherence and reduce entropy.

Negative encounters can be offensive or defensive, whereby one or both [or multiple] networks attempt to undermine and/or disrupt the internal coherency of the other network/s. These encounters are by definition entropic for at least one of the networks involved [often for all], in that they dramatically increase entropy in at least one of the combatants. They can however be negentropic for some of the participants. For example, WW2 was arguably negentropic for the US and highly entropic for European states.

Zero sum encounters are interesting, in that they represent a dynamic cancelling out of networks. There is neither cooperation nor war, but a state of co-presence without an exchange of entropy in a dynamic time-space range. I believe this is a rare type of encounters, because the absence of entropy exchange can appear only if 1] there is no exchange of information or agency, or 2] the amount of agency/information exchanged is identical from both sides. Needless to say, this process cannot be easily stabilized over a long time period and either morphs into one of the other two states or the networks stop encountering each other.