@ottomanbob

Memorizing decks of cards is a great way to cultivate focus muscles. I obtained baseline competency of this skill with about 4 days of moderate practice, then reduced my time by 80% over the course of a month. Here’s a graph of my “deck time” over the course of 32 recorded trials:

After about 3 weeks of daily practice, I clock in a pretty consistent 3:10 per deck. I might have considered that impossible just 30 days ago.

To develop this skill I used a combination of Tim Ferriss’ Bikeshop Pro method, meticulous tracking and measurement, and a handful of very cool apps. Ferriss and other memory advocates/athletes may recommend starting with “Bikeshop Lite” AKA the “Roman House” or “Memory Palace” method before moving to Pro. Frankly, I’d advise against this. It’s a waste of time.

Basics of Bikeshop Pro (ft. @ottomanbob)

I won’t go into detail here, I encourage you to instead refer to Ferriss’ post. Here’s a summary:

Assign every card in the deck a person, action, and object.

Create a route through an actual physical space with which you are familiar. I used my drive from high school to the beach, stopping at home on the way.

Choose 17 distinct locations on this route. As you flip through a deck combine the subject from one card, the action from the next, and the object from another. Place this image at the first location on your route.

Continue in triads for the rest of the deck, using the 52nd (leftover) card creatively in your last scene.

feel gud

Proud. by Jameswmann.com via Attribution Engine. Licensed under CC NC.

how I did it (and you can too)

Of course, nothing this cool is that simple and effortless. Here are some detailed actionable tips from journey to proficiency:

1. Assigning an image to each card was one of the trickiest parts of this whole process. I tried about three different organizational strategies before settling. I started with someone else’s Anki deck (see below), which had assigned images of celebrities to Diamonds and Clubs. (I can no longer find this deck online). For Spades and Hearts, respectively, I assigned a male friend and memorable girl from each grade level of my education. The King of Hearts, for instance, is my girlfriend doing yoga on a mat, whereas the King of Spades is my college roommate, Yves, lying facedown on a mattress. lmao.

When choosing your images be super duper intentional. There are so many things I would change if I were to start from square one. In my list there are three or four images that involve a person feeding, petting, or slapping a different small animal. All three of these actions and their objects are far too visually similar.

In addition, make sure your actions/verbs are versatile. “Bill Gates rebooting his computer” is very difficult to combine with “Wambui doing yoga on a mat.” How does one reboot a yoga mat? I’ve found more grotesque and visual verbs to be more effective. A quick list:

Shitting

Fucking

Masturbating

Jumping

Diving

Screaming

Roundhouse Kicking

Kissing

Ground and pounding

Some truly bizarre imagery from my Anki deck.

2. Use ANKI to memorize your newly minted images. This crude interface uses spaced repetition to ensure maximum returns on your image memorization. The mobile app is pricey as fuck, unfortunately, but it’s useful for nearly any sort of memorization exercise. I started with the 26 celebrity cards from this deck, then downloaded images for the remaining 26 cards. I completed my flashcards using the Anki desktop app, which is free, and the batch media importer plugin. Be careful when syncing the cards to your phone, it’s not intuitive, but it’s worth it.

3. Designing my route was a fun meditative exercise, as it required me to mentally travel through my favorite neighborhoods and take snapshots. I would recommend against choosing spots on the highway (too small) or sprawling areas like “Nalo Town” (too large). Ideal spots on the map are urban, with lots of texture and character. For instance “MidPac,” my high school, has lots of distinct features but is too big an area. When recalling my first triad, I often find myself browsing around the 50 acres of the campus, looking for an image I don’t recall.

“Maunalani Park,” conversely, just consists of some grass, a playground, a court, and a parking lot. I can mentally browse it in a matter of seconds. Plus there are lots of surfaces and items with which my characters can interact.

i.e. Bill Clinton fellating a sheep on the jungle gym.

4. After about two days of assigning images, locations, and practicing flash cards, I started with small batches of cards. 

It should be noted at this point that I have only practiced once with a proper deck of cards. Instead, I’ve been using iPhone app 52Cards. The app has an integrated timer, which is super useful, and is much better for practicing on the go/toilet.

Recalling 22 card batches, then checking my score. Here I began to notice that most of my errors were in “writing,” or constructing my scenes. Not during recall. I also made sure to take note whenever I hit a new PR (personal record).

5. After a couple days of small batch practice, I started doing full decks. This was the most grueling part of the whole process because it’s so goddamned long. I was shooting for accuracy, not speed, and every one of my first few decks would take at least ten minutes. It’s pretty uncomfortable for a millennial to stay laser focused for ten minutes straight. My first high accuracy (90%+) full deck took about 12 minutes! (I still practiced my flashcards on these days, as well.)

6. What gets measured gets managed. Despite all the aforementioned work, I attribute most of my success in developing this skill to meticulous and deliberate tracking and analysis. Over the month, I designed and refined a Google Sheet for recording my times and accuracy. Using a bunch of simple formulas, I’m able to gather a ton of insights to improve my practice.

(A)CPM = accurate cards per minute, SP(A)C = seconds per (accurate) card

This sheet has enabled me to graph my progress, calculate a trendline curve (third degree polynomial regression seen above) to predict future speeds, and observe other trends. Currently, there are 32 entries in my spreadsheet, but I’ve probably practiced on twice as many decks. I don’t record data for sessions I do on the toilet or tram, unless they are really remarkable. If I do, I’ll note qualitative data as to why.

Some insights from my spreadsheet:

I tend to hit new personal records after taking a one or two day break.

My two most recent PRs have been while listening to LCD Soundsystem and Father John Misty. This is likely due to the tempo of the songs, not their brilliant songwriting.

My speed seldom improves over the course of one day. Brain fatigue is real!

7. I prefer listening to music over using a metronome, though I’ll usually practice in silence if possible. 170+ BPM dance music like LCD Soundsystem proves to be particularly effective. Of course, I’m not actually turning cards at 200 BPM. It’s more like 30 BPM, at the start of each measure. If you can tolerate the tick of the metronome, I recommend the Pro Metronome app. The lite version should suffice for this application. 

8. Take Breaks! Once I started making serious progress, I got hooked, flipping decks at every dull moment. As a result my speeds actually decreased, and the whole process became less fun. I now force myself to take days off. Remember the purpose of this exercise is to cultivate focus, not distraction!

9. I thought this would be a cool party trick. It is. BUT after 2 glasses of wine, my accuracy tanks. W/R/T showing off at social gatherings, under-commit on speed and over-deliver. When I tried to show off at a dinner in Paris, I made the mistake of keeping everyone quiet for five minutes while I flipped cards. I think it would have been better to let people chat and instead take ten minutes.

Pin-up Cartoon Playing Cards by Andertoons via Attribution Engine. Licensed under CC BY.

in conclusion

I’m yet to observe the real long term benefits of toning and honing my focus muscles, yet I do feel some dramatic immediate effects. Now, when I look at a deck or decide to focus on something, it is much easier to turn off the outside world and extraneous thoughts in my head. This type of focus is something I recall regularly feeling doing homework in elementary school, before the internet ejaculated all over my brain. At the very least, card memorization is a badass party trick and a source of personal pride. And for a distraction behavior, it sure beats Facebook.

As my speed improves, I’ll update this post and move onto other focus exercises, like Rubik’s cubing and speed chess.

Inspired by Cal Newport’s Deep Work, I made a flowchart for my weekdays. I wanted a higher level strategy + algorithm that could I use any day of the workweek. The design process was surprisingly straightforward:

1. Listed all Deep Work strategies/action items I wanted to include. I did this in another blog post.

2. Slimmed down this selection to higher level actionable items. Referred to notes in BEAR to find other integratabtle routines and behaviors.

3. Mapped out a draft on paper.

4. Determined best flowchart software. Ended up using draw.io. It’s not super intuitive and there’s probably a better tool out there. Nonetheless, it offers complete functionality and gDrive integration. Can be a little troublesome when it comes to formatting and layout. 

5. First digital draft! Added note and schedule boxes in negative space.

6. A few days of trials. Unfortunately, this all started right before spring break, so I didn’t have too many days to properly beta test.

7. Second draft.

Realized that my box sizings were disproportionate to their purposes. Replaced “yes/no” items with red/green lines. Tightened up spacing.

8? Third draft in draw.io, then a sexy, more aesthetic version in Illustrator. I’d like to have a more pleasing visual of this thing printed onto a whiteboard or dry erase wall. Routine items could contain checkboxes and work could be listed in appropriate boxes.

afterthoughts

1. Designing a flowchart (in any software, I would imagine) is a bit finicky. If I were to start from scratch again, I’d lay out all my boxes, first, approximate their positions, then connect them with “flows.” 

2. Following an intentional, but liquid daily plan is super satisfying. Variation and excitement comes via different types of work challenges. But I’d like fun and recreation to play an exciting part in my days, too. Unfortunately I’m realizing, as my grilfriend’s pointed out, I don’t really do anything explicitly and exclusively for fun. There’s always intended personal growth, or worse ego-climbing in the subtext. 

Image by Ady Satria Herzegovina via Attribution Engine. Licensed under CC0.

re: the above, I’m not quite sure what to do. Drugs are super fun. So are my friends. But what about lego? Or Sudoku? It’s hard to think of an activity or hobby that I won’t approach from a growth perspective. I play basketball when I can, but I literally have a goal of slam dunking in the next 18 months. lol. Good meals are often fun without pretext. I’ll return to this point when I’ve made progress.

That’s all folks. hope it helps,

Cal Newport’s Deep Work is a triumph of self help. It embodies the qualities that make self improvement of the 21st century so great: driven by a desire to stand out from new age milieu and impractical horseshit, Newport pushes beyond the theories of Gladwell and idealism of Tim Ferriss to understand productivity. Newport’s an academic; an MIT educated professor of CompSci at Georgetown and he approaches his subject accordingly. Who gets shit done? How and why do they do it? And how does a beginner follow suit?

The central and opening argument of Deep Work is that the only way to ensure personal prosperity in an increasingly automated economy is to deliver quality knowledge work. Economic advantages aside, valuable knowledge work is a fulfilling pursuit for an individual and a way to ensure a deep love for one’s own career. 

**DEEP WORK **is serious-ass knowledge work that requires at least 90 minutes of unbroken focus to get into. Expertise and experience are required.

Once his thesis is established, Newport goes to incredible depths to provide a pragmatic structure for a life of Deep Work.

major personal takeaways:

Three types of deep work: monastic seclusion (Jung), bimodal (on/off every semester), rhythmic (daily habits enforced by a desire for continuity, but less predictable). There’s also the seemingly fantastic “journalistic” mode, in which one can enter deep work at a moment’s notice.

Strategy for rhythmic philosophy: “chain method.” Mark an X on your calendar for every DEEP WORK day. You will want to continue the Xs. Newport tallys his deep work hours. > Image via Attribution Engine. Licensed under CC0.

Misc tips: Have a standard daily starting time for your deep work. Make grand gestures (Rowling rented a swanky ass hotel to finish HP7). 

Don’t work alone. Selective collaboration is essential to breakthrough (see: adjacent positive breakthroughs). MIT had famous building that was accidental mishmash of depts. Caused breakthroughs. Shared common space for occasional interaction is far superior to open office plan.

5. 4DX business execution method: 

Focus on important stuff (pareto principal). 

Act on leads, not lag.

Keep score (i.e. calendar or hour tally). 

Weekly review, meetings on deep work.

RITUALIZE (obvi). Major Ferriss and many before him have popularized the importance of ritual. Think like an artist, work like an accountant:

WHEN/WHERE: Repeated locations and time frames.

Consistent “how you’ll work.” Use _freedom _app or pomodoro method. Cognitive enhancement routine included here.

Supplementation and support: methods for gathering materials, organizing work, structure of work.

Maximize Downtime. Idleness is a plus. But don’t be bored (dissatisfied with the present). Learn to live without distraction. This goes beyond mindfulness IMO. It’s about being inactive. But you don’t have to be thrilled or totally immersed in the moment. An elusive restfulness.

Replace distractions with focused work, then instead of distracting yourself, take breaks from focus. Idleness is vital for subconscious mind...

Productive meditation: take daily breaks to occupy body, but not mind. Focus on a specific problem. A walk in nature is much better than one in the city. Here’s how to PM:

Review variables (what am I working with?)

What are the next step questions?

Consolidate gains.

Repeat.

The important thing is to avoid loops. Direct your unconscious mind into new territory.

Learn to focus. Complex brain exercises are essential to laying down the deep work neurons. Newport recommends strategies for quick memorization of a deck of cards. After three days of practice, I’m able to memorize a deck in about 8 minutes. This was so fucking exciting. It reminded me off the deep cognitive joy I felt doing hard maths as a child and high school student. Other focus exercises I’ve tried or am trying: rubik’s cube (literally a one day skill), number and name memorization, chess. > Image by Israel Garcia via Attribution Engine. Licensed under CC0.

Internet blocks. 

1. No social media is a big one. I figured it out a couple of years ago but was a bit angsty in my reasoning. Turns out that the numbers add up: facebook doesn’t really make your life better. There’s the _any benefit fallacy _in which users argue for one great benefit ignoring the interminable downsides. (ie “I can stay in touch with my cousins!”) 

Have an internet Sabbath. I’m trying for saturdays.

Internet block periods during the day. An app can work, but a notepad is better as it will push for internal impulse control. Schedule your next 20 minutes of internet time. When you need to do research during your work, write down the topic and move on. When it’s time for the web, maximize it and get back to your offline mode ASAP.

DRAIN THE SHALLOWS. The term deep work refers to the alternative of the concept of “the shallows,” the space where our short attention spans play and stretch. Reading the NYT? Stop. Just cause its good journalism doesn’t mean it’s good for you. SAD!

Schedule your whole day. Your whole fucking day. I’m using gCal but Newport recommends a pen and paper strategy: > 1. Write your hours down the left column, skipping lines.

Schedule blocks no smaller than 30 minutes for routines, shallow work, deep work, breaks, etc. Batch shallow work and logistics together in “task blocks.”

Schedule disputed? Cross out your earlier blocks and move over a column, scheduling the rest of your day.

Conditional overflow blocks can be used for tasks whose length you have trouble predicting. If this, then that. 

Quantify activity depth. Know the value of the work your doing. Could a college grad learn to do this in a month or two? Yes? Then it’s shallow work. Deep work requires several months or years of experience and expertise.

**SHUT DOWN PROPERLY. **Have a shutting down routine and shoot for the same time everyday. Respect then end of your workday. You work 9-5. Not more, not less.

big one here, dealing with email. Make people who contact you do more work. Filter senders, not messages. Use process centric emails: “here’s what I am going to do, here’s what I want you to do, here’s how you’ll do it, how you contact me, and our next steps together.” Provide dates and times for meetings and don’t waste time or energy sending endless confirmations and thank yous.

There’s so much great actionable content in this book. I hope I’ll get around to listing more. I’ve also noted some of my own personal strategies when it comes to fostering deep work.

@ottomanbob’s tips:

**ORGANIZE YOUR DIGITAL LIFE. **KonMari that shit. Folders and deletions are as cleansing as pitching trash bags full of clothes. Use a black wallpaper or camouflage to hide your desktop icons.

2. **BEAR **is the greatest fucking program ever for note taking on OSX. It uses markdown and has a great minimal interface. Took a couple weeks to get the hang of it but holy shit. You can link notes together, create todos and routines, work on prose writing, etc. Blow google docs out of the water.

Monastic mornings. Ferriss and Newport argue for twice-daily email checks. I say, in addition to this, don’t even touch communication software and devices till 10 or 11 am, later if you can. 

**MINIMALIST WORKSPACE. **Unless you’re in vizarts, you probably don’t need anything but a notebook and laptop on your desk. Newport advocates for expensive notebooks, so you’re more intentional with your pages. > Image via Attribution Engine. Licensed under CC0.

conclusion

Always hope to add more. Thank you Cal Newport. Your book changed my life.

xx

Distributed Distribution: The Sharing Crisis and How We Must Solve It

The current means by which digital multimedia are distributed (legitimately) online are diverse and convoluted. These systems, ranging from the iTunes Store to Google Images to Netflix, are responsible for an exponential growth in both audiences and the libraries to which they have access. Though this boom in accessibility should merit a proportional growth in wealth for artists and creators, it is simply not the case. These existing models have inherited many of the flaws of previous “analog” distribution systems, often accentuating, rather than remedying their worst qualities.

The problems with online media distribution are abundant; disproportionate revenue shares between corporations and creatives, undercompensated mega artists, rampant piracy, garbled metadata, a half dozen equally-confusing options for streaming media… the list goes on.

While this crisis pertains to all forms of media, ranging from music to videogames, I, as a filmmaker, am specifically interested in dissecting and remedying it in relation to movies. However, it would be unwise and regrettable to approach this issue from this perspective exclusively as the problem is orthogonal and multifaceted; this is a shared crisis. I posit that the issues at hand are as existential and ideological as they are logistical, and because of this cannot be resolved in a compartmentalized manner. I will refer to these issues collectively as the distribution crisis. Severe disruptions in both the thinking of the public and the design of the systems at play are necessary to its resolution.

With the emergence of new technologies, specifically decentralized networks and cryptocurrencies, several alternative models for online media distribution become possible. The goal of this writing is to A) determine the precise origins of flaws in existing distribution systems B) determine the established and emergent technologies necessary for a new model C) describe in detail an ideal alternative distribution model and several derivatives of this proposition D) posit the methods and techniques necessary for the adoption of such a model E) predict the next order effects of the large scale implementation of such a system.

This writing is a research paper, a speculative design brief, and more prosaically a introductory exploration into an ideal future for artists. The ideas within refer to a multidisciplinary array of subjects, focusing especially on economics, software studies, and design philosophy. I am not nor do I claim to be a scholar of any of these topics. I am personally motivated to explore these subjects in relation to the distribution crisis, as I am affected as both an artist and audience member. Existentially, I believe the media distribution crisis is a microcosm of many of the larger issues facing our species today and some of the ideas presented herein can and have been adapted for and from other realms of speculative design.

Most of my research is derived from publicly accessible online data, direct observations of existing systems, and “whitepapers” for emergent technologies. In addition, philosopher Benjamin Bratton’s “The Stack: On Software and Sovereignty” has inspired much of the systems and software thinking herein, specifically in regards to the relationship and division between user, interface, and address layers in proposed systems. I have also included a healthy amount of personal intuition and occasional conjecture.

Centralization

At the core of all issues within the distribution crisis is the quality of centralization; an impractical design flaw inherited from archaic systems, dating back to the genesis of mass media. Previously, when media of any form was produced, whether it be a newspaper, vinyl record, or VHS tape, it was birthed at a central point, (usually a factory or printing press), and disseminated from there. Retail distributors of said media kept a portion of profits and the remainder kicked up to a management corporation, who paid both the manufacturer and a small or infinitesimal commission to the creator of said media.

This model, however disproportionate, was vital in the establishment of the mass media world we know today. Making a movie/album/book was a difficult process, but a much larger share of heavy machinery and coordination was necessary to share it on a large scale. With the internet, this is no longer the case. No tape, cellophane, or paper is necessary to move a piece of work from creator to audience. Just broadband. But we’re still using the old model, wherein a studio, label, publisher, or large corporation takes a huge chunk of artist’s profits. Today, media marketplaces and platforms chomp the biggest revenue share from creators. Spotify, the iTunes Store, Netflix, and YouTube have all grown exorbitantly wealthy on other people’s content.

The reason for this is a primary strength of centralized distribution models: their databases. An online media distribution system, whether it be a marketplace or streaming platform, controls and maintains the identity, distribution, and monetization of an artist and their work. These databases are massive, containing thousands, if not millions of songs and movies and other media, meticulously organized, indexed, and maintained. These centralized databases are why the common consumer subscribes to streaming media models. For a small fee, we are given access to a massive and orderly library of content, hopefully filtered through an intuitive user interface.

Though these databases are ripe with appeal and advantages, their centralization is extremely troublesome. They are data silos, completely compartmentalized from one another. Netflix and Amazon Prime Video may share an overlap of hundreds of thousands of films and shows, but their libraries are completely separate. Due to this compartmentalization, it is possible for the same piece of media to exist on a plethora of platforms, but the information and context surrounding them to be fragmented and isolated. An artist may be paid in five different ways on five different platforms, all of which severely undercompensate them. Their work may appear under five different names, in five different formats, with five unique audiences. The velocity their work receives on one platform may not transfer well to another platform, and when it does, it may not carry the identity and data necessary for proper attribution to the artist.

Let’s follow an all-too-common lifepath of a viral song. Artist A uploads Song B to Soundcloud, in hopes of promoting album sales on Bandcamp or iTunes. YouTuber C discovers Song B and shares it to his subscribers via a YouTube upload. Song B collects millions of views on YouTube, with no connection to the artist. Artist A discovers this upload and asks Youtuber C to link the video back to Artist A’s Social Media. A small percentage of clickthroughs lead to tens of thousand of new followers on Artist A’s Social Media. Some of these true fans purchase Artist A’s album on Bandcamp, wherein Artist A receives 70% of the profit, but most find the album on Spotify, resulting in hundreds of thousands of streams, for which Artist A receives less than one hundred dollars. Literally. Analogues of this phenomenon can be observed in the distribution of movies, television, and images, alike. Popularity seldom results in compensation.

What is worst about all of this is that data shows that consumers want to pay for their media. When it is intuitive, audiences will gladly pay up. [TK] Napster all but disappeared when the iTunes Store made it possible to purchase single songs for a dollar. When bittorrents emerged, making it easy to download entire albums and movies, distributors created the subscription streaming model, and millions of users hopped on. But these same users have become increasingly disheartened and alienated by these platforms. Serious fans would rather purchase physical merchandise or download media directly from its creator through mediums like Bandcamp or Louis CK’s direct-to-customer DRM-free model. More casual consumers become overwhelmed by the variety of streaming platforms, many turning back to piracy, or worse, abandoning their consumption altogether. Digital distribution is a nightmare for consumers and creators alike.

Decentralization

If we could decentralize our media databases, things would be very different. A diversity of apps and platforms would still exist, but they would be thin strips of code layered on a deep shared data reservoir. This reservoir could contain a master copy of all works, submitted and formatted as preferred by their respective owners. Views on Netflix, Hulu, or YouTube could all be written to the same count on a movie’s universal metadata. A view on any of these platforms could compensate an artist in the exact same way. The creator could have the same bio, profile picture, and fan base across multiple platforms. These platforms would no longer compete on the breadth of their database, but the quality of their interfaces and the user experiences they offer. Such are the promises of a public decentralized media database.

In 2009, an elusive software engineer named Satoshi Nakamoto introduced the Bitcoin payment system to the internet. Using peer-to-peer open-source software, Bitcoin became the internet’s first blockchain: a distributed and growing list of cryptographically-verified unalterable records or, more prosaically, a decentralized public database. In 2016, the Bitcoin blockchain holds 60 gigabytes of data on an average of 5000 “nodes,” or publically run servers. More information on the technology and folklore of Bitcoin can be found [TK].

Bitcoin, forgo all controversy and skepticism, has proved the viability of blockchain databases. It has shown that individuals, when incentivized by currency, will host data and offer computational power to a shared cause. Decentralized data is real.

Tokenization

The implementation, growth, and maintenance of a blockchain is best preceded by a tokenized incentive. While some parties may be motivated to host and compute a blockchain for political or personal reasons, their contributions, alone, are unlikely to be enough to sustain a large database. More importantly, a large and diverse population of nodes is imperative to the very definition of a decentralized database.

With a decentralized media database, both consumers, businesses, and creators may be attracted to the notion of hosting. However, their motivations are not aligned without a token. A cryptocurrency hardcoded into the blockchain programs both humans and machines and aligns their incentives. In order to receive or write data to a tokenized blockchain, a user must circulate currency and contribute to its microeconomy. The token is attractive to all stakeholders in the platform and the blockchain, itself, cannot operate without it. Moreover, the value of a token is based on the value of the database on which it is built. This includes, but is not limited to the data maintained on the blockchain, the speed and efficiency with which the chain operates, and the health of the community of users that interact through it.

The value of the token is not just in aligning incentives. It is also an effective means for bootstrapping and user acquisition. The creators of a blockchain are in charge of the allocation of tokens. Developers may speculate on the value of their blockchain and allocate a share of tokens to themselves. These tokens are, initially, worthless. They only acquire value when the blockchain itself does. This further incentivizes developers to create a quality database.

Developers may also allocate an initial share of tokens to user acquisition. New users on the blockchain may be compensated in tokens just for joining. This poses no risk to no users and is a powerful enticement to engage with a new technology. It is literally free money. In the case of a media blockchain, developers could compensate creators in tokens for adding their content to the database.

The true value of a blockchain is in the service that its network and database can provide to users. It is the goal of a blockchain’s developers to grow this value and, in turn, increase the value of the tokens they hold. Developers do not “own” a blockchain, but they are intimately acquainted with it, and thus should be able to build killer applications for it. By creating a free application in the aforementioned “thin layer” over a decentralized database, developers can attract users and value.

On the high conceptual level, the strength of a token in blockchain implementation may be puzzling. It may be easier to think about tokenized blockchains as a logical evolution of the co-op business model:

A co-op is a business corporation that offers every member and employee an equal share of decision-making power and economic ownership. The model is both egalitarian and democratic, but offers no power hierarchy: it is decentralized. The success of the co-op business relies on the participation of and work of all of its employees, like any business, but employees are more incentivized to contribute to the business because their compensation is determined by the health of their company.

The co-op model protects employees from selfish leadership, as their is no opportunity for a larger owner in the company to liquidate his or her shares and/or layoff employees. The co-op model also prevents careless scaling. Inefficient growth means lower pay for everyone.

The primary overlap between tokenized networks and the coop model is that many users may have a share in the value of a “business” from its conception. Tokens, however, usually do not provide a holder with a vote or voice in the direction of a blockchain. Tokens holders can contribute to the health of a blockchains interior economy by spending, receiving and circulating their token, within it.

The stakeholders in a traditional co-op are the employees of a corporation, itself. In a tokenized network, both the developers and users have tokens. Developers hold token because its value appreciates with the use and value of their network. In the future, they can sell their tokens to other users, or spend them as users. (Users are not limited to one side of a transaction.) Their profit relies on the strength of the network and microeconomy they develop.

In the case of a co-op bakery, customers interface with the bakery like they would any other brick and mortar store. They do not pay a membership fee nor vote on the leadership and interior politics of the bakery. In fact, they probably prefer not to. The bakery provides a good/service for the customer, the co-op model provides a service for the employee.

The inclusion of customers as shareholders in the co-op could lead to a variety of issues. First and foremost, there inherently will be more customers than employees. This means that customers could implement advantageous policies (prices and cost-ineffective products) for themselves that hurt the wages of the employees and profitability of a business as whole. While customers may not want to do this (they have incentive to keep the bakery running), they do not inherently have the same share in the bakery that the bakers do. Their incentives may be aligned existentially, but there is no mechanism to enforce these beliefs. Profit dividends distributed to consumers may fruit some economic alignment, but the survival of the bakery is of far more significance to the bakers, as it is their livelihood. The primary function of the co-op model is to combat a centralized governance of an organization that could later lead to a questionable distribution of wealth and poor treatment of employees, specifically.

The tokenized blockchain takes the principles of a co-op one step further: all stakeholders have aligned incentives, but may not have the same share in the economy. This a more naturalistic and feasible approach to democratized and decentralized business. The health of the microeconomy is a priority to players of all sizes within it.

A Blockchain for Movies

If we speculate on an alternative future for movie distribution with tokenized blockchains in mind, a near-utopian model of sharing becomes visible. This model, which I will refer to as “PopCoin,” can be thought of as a legitimized and more sustainable rethinking of the notorious free and open source “Popcorn-Time.”

Popcorn-Time is a software interface built on a centralized catalog of neatly arranged bittorrents of pirated movies and television. The PopCorn-Time metadata collection contains posters, descriptions, ratings and subtitles for a large library of bittorrents. These bittorrents, which can be accessed outside of the software, are more easily streamed through the reliable Popcorn-Time interface. User experience is also improved by access to contextual data and an established reliability and trust in the Popcorn-Time developers, who only link to quality torrented media. More about Popcorn-Time can be found [TK]

The PopCoin model, conversely, still relies on decentralized and torrented media, but shares it legally. Metadata is hosted on a blockchain that not only indexes information about the movie, but also who has a license to stream or download it. Users are compensated in PopCoin for their contributions and hosting of this “PopChain.” The movies, themselves, may be hosted by fans, studios, and investors, who are all compensated by the PopChain for sharing with their peers. A user can spend their PopCoin to stream or download a movie. Peers who help deliver the file receive a small share of this PopCoin, while the majority is sent to the movie’s owner. By eliminating a middleman like Netflix or iTunes, creators are able to slash prices for their media while receiving more profits. This is the brilliance of decentralization.

Developers of the PopChain allocate a share of PopCoins for themselves, and distribute an initial allocation to serious independent movie fans. Developers then take another share of tokens and give them to filmmakers who agree to have their work cataloged on the PopChain. These developers then develop a free PopCoin interface that makes the PopChain accessible to common users. Speculating on the potential of the PopChain, financially motivated investors may purchase PopCoin from developers, fans and filmmakers, bringing more monetary value to the token. If PopCoin provides better experiences for users and compensation for filmmakers than existing platforms, it has the potential to disrupt online movie distribution. This disruption starts with a network effect.