(October 31, 2018 Update: here’s a screengrab from CoinMarketCap, showing USD valuation of the entire crypto market at approximately $200B, which is 70–75% of the market capitalization of Wal-Mart. Every few years, we’ll come back to this, so please stay tuned.)
In our story announcing the publication of the CleanApp Whitepaper, we made a claim that we suspect will raise some eyebrows in the crypto community. Here is that claim:
Aggregated, optimized, streaming resource location data is not only intrinsically valuable: it’s far more intrinsically valuable than any other cryptocurrency, coin, or token in existence — including platform tokens like ETH or MIOTA.
If you’ve been following our work, you know that these claims aren’t meant to be incendiary or offensive. We’re big fans of Bitcoin, Ethereum, and every other crypto instrument we invoke to support our arguments. What we try to do with claims like this is to explore core assumptions and common blind spots with hard analysis. This makes everyone better off.
Here’s our support for this claim.
#TrashHash is a placeholder name for some future “toin” (token and/or coin and/or currency and/or etc.) that is awarded to actors who participate in different aspects of CleanApp processes. Right now, @littercoin (OpenLitterMap.com) is a working prototype of one type of #TrashHash, awarded for one type of CleanApp activity (reporting litter locations).
Individuals/firms can earn #TrashHash (or #TrashCash or #GoldKens, whatever the eventual name that attaches) through activities like:
(1) submitting different genres of incident reports (like locations and extent or waste, litter, and hazards);
(2) performing verification & other analytics activities with respect to earlier submitted reports;
(3) responding to the offending objects and/or conditions by cleaning them up (either through manual human labor, or any form of semi-autonomous or fully autonomous incident response, cleaning platform).
How Valuable is #TrashHash?
Nobody can give a precise value to a photo of a trash bin or an old dumpsite, just like nobody can give a precise value to a patent or any other form of property. Commodities acquire value only through exchange.
But we can answer the question in relative terms. We can posit the following, for instance:
A recent geotagged photo of an old dumpsite has more intrinsic worth, and more value, than 1 BTC.
Please note that when we say “intrinsic worth,” we’re still talking about some sort of a market exchange.
1 Littercoin > 1 Bitcoin?
As strange as this matchup may seem at first, from a rational economics perspective, the answer is absolutely “yes.” The best way to illustrate this is to imagine yourself stuck on a deserted island.
You are starving, naked, and have no material possessions. The only thing you have are lots of cash dollars that survived the shipwreck with you.
On the deserted island, the dollars are absolutely useless because there is nobody to exchange them with. There are no stores. Now imagine a stranger arrives on the shore and makes you the following offer:
In exchange for all of your USD cash, I will sell you either 1 Bitcoin (represented by the requisite hashes printed on a piece of paper) or 1 Littercoin (represented by a hash + GPS location to the incident report(s) associated with that Littercoin printed on a piece of paper).
Assume no other technology or variable, and the answer becomes clear. A rational you would take the Littercoin because the GPS coordinates give you a lead to a potential material bounty.
You do not know if you could ever use the GPS coordinates, you do not know whether the GPS coordinates lead to junk or treasure, but you know that they represent encrypted map coordinates. You have no idea whether you’ll be able to decrypt the coordinates, and/or if these particular coordinates will lead to a useful find. However, map coordinates are intrinsically more valuable than just an encrypted hash representing a Bitcoin balance.
Your chances of finding the stash of trash at the end of the end of your Littercoin’s GPS hash might be very low, but they are higher than Bitcoin’s 0% chance of leading you to resources that you might need to survive.
1 Littercoin > 1 ETH?
A darker version of the same hypothetical helps drive the point home. You’re still on a deserted island, except it’s a small island south of Ulawa Island in the Solomon Islands.
You’re still starving and all around you are signs warning you about mines and unexploded ordnance from the Battle of Guadalcanal, which was waged right where you are, 70+ years ago.
Your bundles of cash sit in suitcases all around your makeshift camp and the same stranger shows up:
In exchange for all of your cash, I’ll sell you 1 ETH or 1 Littercoin, containing a GPS location of a hazard that some user generated in the world somewhere.
A rational you should take the Littercoin because you realize just how maddening it is to walk on tiptoes around a minefield. And even though the Littercoin hazard map may seem illegible to you, it is far more valuable than an ETH hash because of the small chance that it contains a usable lifesaving hazard warning.
Again, the probability that you would also find a decryption engine (e.g., working smartphone) and the decrypted coordinates relate to a hazard around you may be slim, but they are higher than an ETH-hash’s 0% probability of useful geolocation data.
#TrashHash From Theory to Practice
Thus far, we’ve seen that #TrashHash should be valued more relative to fiat-like crypto, in the imaginary realm of (1) perfect information (2) zero friction (3) desert island “market.”
Now let’s do some real-world valuations by going back to a typical report at the heart of the CleanApp process:
At first, it looks like there is very little intrinsic worth to this CleanApp Report.
However, we know there are certain variables that start to lend this intent+photo unit much marketable value. Indeed, some variables can give extremely high value to a photo like this, even if the underlying subject matter at first seems unremarkable or unmarketable.
- Place: If the CleanApp Report above is sent from Rodeo Drive in Beverly Hills, CA — it is likely to be more “valuable” than a virtually identical report sent at the same time by a user in Beverly (Saskatchewan, Canada).
- User Rating: A CleanApp Report that’s generated by a reporter with a 4.9* peer-reviewed user rating is more “valuable” than a similar CleanApp Report generated by a reporter with a 2.3* average rating.
- Urgency: If this CleanApp Report is part of a chronological series of reports that show the dereliction of duty on behalf of the party responsible for cleaning up this trash bin, this report acquires much higher value as a result of being a part of a time series of like reports. Similarly, if this CleanApp Report is part of a burst of reporting activity by unrelated users in a short amount of time (say, one of 1,483 reports about this bin in the past hour), the sudden rise in reporting activity can suggest an urgent condition that may not be evident from the photo — but a condition that is sufficiently urgent that 1,483 people took the time to report this condition in just the past hour.
- Composition: CleanApp Reports are typically generated because users/citizens note that the object/condition being complained of is so at odds with the surrounding environment (indoors/outdoors) that remedial action is necessary. Often, this is done along with material composition data — which is vital for ML/AI-learning applications. Casual reporting like “Alexa, CleanApp these glass & plastic bottles everywhre” and “Google, CleanApp this milk spill in Aisle 7” provide important metadata for interpreting an underlying image report.
- Time: A single report may not have much value, but consistent reporting upticks at particular times may give valuable actionable data that materially improves outcomes.
- Material Bounty: A CleanApp Report that identifies a former or abandoned dumpsite may reveal a bounty of recyclable materials, particularly metals. By contrast, an incidental CleanApp Report may help locate a hazardous chemical, radiological, or even munition dumpsite.
- Normativity: machines are now very good at recognizing objects/images, but still lack basic situational awareness/contextual cognition regarding what to do with that data. Whether something is “trash” or “not trash” turns out to be an extremely complex socio-ontological decision. Humans make these decisions hundreds of times daily, often without pausing to think. CleanApp streaming data allows machines to learn and understand human normativity with respect to what is “trash” or “not trash,” “hazardous” or “not hazardous.” Machine-aided risk mitigation is an uncontroversial and very valuable current and future use of CleanApp data streams. At this stage, the fastest way to teach machines about human normative relationships with their lived environments is to crowdsource this data on global scales, which allows us to account for sweeping plurality of cultural approaches to waste & resource use.
- Celebrity: a CleanApp Report like the one above generated in Beverly Hills by Justin Beaver may have a value of X; a similar report generated at the same time in Beverly (Saskatchewan, Canada) by Justin Bieber may have a value that is orders of magnitude higher than X.
The list of possible factors that add or subtract value to/from a given CleanApp Report is limitless. Because these variables operate simultaneously, some may cancel others out. Some variables may magnify others. Some variables may serve as catalysts for much greater variable activity (such as a celebrity pointing her CleanApp spotlight on a particular object or hazard, followed by fan reporting behavior).
These variables are hard to study in silo, but they are very easy to understand through regression analysis.
User-Defined #TrashHash Value
Casual CleanApp users may not care about various analytical or research uses of their data, at first. But once CleanAppers begin to see the full value of their contributions to global CleanApp Analytics, we anticipate user expectations to coalesce around user-defined data-sharing regimes.
Letting users make the difficult decision of releasing their data into public domain, on an attributed or unattributed basis, etc., comes with growing pains. But user-defined privacy choices are the only way to resolve the myriad blind spots in artificial “market pricing” mechanisms concerning different variables above.
Honoring user-defined #TrashHash variables (publishing/marketizing only the data that individual CleanAppers feel comfortable publishing or marketizing) results in far more satisfying user experience. This in turn, boosts the value of the underlying resource location data.
#TrashHash Is An Inexhaustible Resource
Most cryptocurrencies attempt to artificially control inflation by arbitrarily limiting the money supply. “X Coin has only 3,500,000,000 XCoins in circulation!” “Y Token can never & will never mathematically exceed an issuance quotient of 120,000,000 Y Tokens.”
The reason many cryptocurrency issuers limit issue volume is because, at core, their currencies act as fiat-like instruments. They do not have intrinsic value. An artificial limit thus serves to create artificial scarcity.
#TrashHash turns this premise on its head. It takes what seems like a bug in the cryptocurrency paradigm (the ability to print coin on demand and thus dilute the market value of coin) — and turns it into a feature.
#TrashHash is pegged to actually scarce material resources. But its core value isn’t pegged to any immediately identifiable commodity (unlike so many blockchain title tracking schemes); instead, its value stems from relational data — the approach of a group of humans to a particular object or condition, in a particular place, at a particular time.
The underlying resources are scarce; but the permutational range of human relations with those resources is infinite. #TrashHash’s core value proposition is capturing a set of valuations with respect to a particular object/condition in given moments of time.
#TrashHash facilitates and records market transaction, infusing orders of magnitude more liquidity into commodity & service markets than has ever been attempted before.
#TrashHash Mirrors Human Behavior
The other key aspect of #TrashCash that makes it so valuable is that it mirrors human behavior (being bothered by waste of any kind, and reporting it to anyone who may have any ability to do anything about that waste) — instead of trying to change or modify human behavior.
The other key aspect of #TrashCash that makes it so valuable is that human behavior seems unlikely to change in a material respect in the foreseeable future. This suggests a continuing need for CleanApp reporting practices, and a continuing need for CleanApp response processes.
People hate litter; people love money. Something like @littercoin already aligns these interests transactionally. #TrashHash extends this concept to global verification markets & global response markets.
Crypto Needs TrashHash, Not Vice Versa
The other key aspect of #TrashCash that makes it so valuable is that CleanApp is platform ambivalent. In its simplest embodiments of reporter-verifier-responder transactions, the entire system can function autonomously, like a scalable smart contract structure.
Platform ambivalence provides a unique glimpse into the inner workings of a new security and data sharing paradigm.
Stated another way, a global commodity-backed token like @littercoin doesn’t need Ethereum in order to succeed; rather, Ethereum needs a commodity-backed token in order to succeed.
Littercoin can always jump platforms, embracing IOTA’s unique computational model, or another as-yet unreleased blockchain platform. But Ethereum & other DLT platforms need a commodity-backed token like @littercoin to show that DLT can not only offer “something actually meaningful to society,” but can actually offer hardcore material hyperutility.