Smart Contract Patent Update

A quick update on the growing smart contract patent landscape. I’ve written before about the number of patents mentioning smart contracts here, here, and here. The number of filings continue to grow at a rapid pace.

As of May 30, 2018, we know of 267 patent filings in the USA that mention “smart contracts.” These filings include issued patents, and published patent applications. There are surely more we do not know about. The chart below shows a breakdown of filings by the year they were filed.

 

Blockchain Mini-Syllabus

A mini-syllabus to understand the hype

When reading about the Blockchain space it can be very hard to separate the wheat from the chaff, especially for people just starting to learn about the technology. This problem is compounded by the prevalence of so much hype literature, and fluff, that does not do a good job of explaining why someone should actually care about this technology.

So, in an effort to address that problem I have put together a mini-syllabus of articles about blockchain, cryptocurrency, and smart contracts that are able to explain what is going on at a high level, and give concrete reasons why this technology may be so transformative.

Before I list the articles, and give a brief synopsis for each, I want to acknowledge that this effort is by definition incomplete, and somewhat subjective. There are many articles that could have been chosen, but these five articles have held up well, and will likely continue to hold up well in the future. Also, the articles were chosen for their broad treatment of the technology and it’s potential societal impact.

The Articles

  1. Why Bitcoin Matters — Marc Andreessen
  2. The Dawn of Trustworthy Computing — Nick Szabo
  3. Bitcoin and Blockchain: Two Revolutions for the Price of One? — Richard Brown
  4. Programmable Blockchains in Context — Vinay Gupta
  5. Money, Blockchains, and Social Scalability — Nick Szabo

If you read these five articles you should have a decent sense of what a blockchain is, what cryptocurrency is, and why those things may have a very large impact on how trust is managed in our world. I highly recommend you read the articles in the listed order, so you can build on the themes laid out in each article.

1. Why Bitcoin Matters

Marc Andreessen, the cofounder of Netscape and of az16, lays out the case for why Bitcoin is an important invention, but also dives into the business case for Bitcoin and other cryptocurrencies. This editorial is a good entry point to understanding the “so what” of cryptocurrency.

2. The Dawn of Trustworthy Computing

Nick Szabo’s entire blog, “Unenumerated”, is worth checking out given the breadth of topics covered, but also the depth Szabo goes into for each topic. This post gives you a full picture of how much we trust computers to behave in certain ways, and why a new way of managing trust enabled by blockchain may change many facets of society.

If you’re feeling ambitious, make sure to check out his “Wet code and dry” post that he links to at the bottom of the post.

3. Bitcoin and Blockchain: Two Revolutions for the Price of One?

Richard Brown is the head of technology at R3 where he is working on rebuilding finance with distributed ledger technology. In this post, Brown masterfully explains why large organizations are intrigued by blockchain, but not necessarily Bitcoin. The rest of Brown’s blog covering concepts in finance and where things are heading is worth your time.

4. Programmable Blockchains in Context 

Vinay Gupta helped coordinate the release of Ethereum in 2015. In this post, he lays the foundation for why something like Ethereum is compelling by giving a history of the technology that came before blockchain.  This post is a great primer on how humans have managed data in the digital age.

Bonus post: check out Gupta’s “A Brief History of Blockchain” at the Harvard Business Review.

5. Money, Blockchains, and Social Scalability 

Lastly, we have another Szabo blog post. I told you his blog was worthwhile. In this post, Szabo tackles issues of scalability related to blockchain, in particular, the issue of social scalability, which he defines as:

the ability of an institution –- a relationship or shared endeavor, in which multiple people repeatedly participate, and featuring customs, rules, or other features which constrain or motivate participants’ behaviors — to overcome shortcomings in human minds and in the motivating or constraining aspects of said institution that limit who or how many can successfully participate.”

This is the longest post, but arguably the most important of the five.

Conclusion

If you read these five blog posts you will not know everything there is to know about blockchain, cryptocurrency, and smart contracts. You will, however, have a very good handle on the basics, and should be able to understand the promise of this new technology class.

Presidential Victories

Everything you ever wanted to know about presidential margins of victory

The 2016 presidential election sparked considerable interest in margins of victory in presidential contests. President Trump and his team claimed that his margin of victory was “massive.” Politifact did an excellent job debunking that claim using data from political scientist John J. Pitney. The Washington Post also did a great job covering this, as well as Nate Silver at 538.

This post covers some of the same ground as those listed above, but is directed to all of the presidential elections, not just 2016. I compiled all the data for each presidential election, including electoral college and popular vote numbers, from UC Santa Barbara’s excellent “The American Presidency Project.” What follows are some interesting data on margins of victory in presidential elections.

What is a margin of victory?

Before we dive into the data, it’s important to clarify what is meant by “margin of victory.” A margin of victory is the difference in votes received between candidates for office. The election of the president of the United States is determined by whoever wins the majority of electoral college votes, but as a society we also track the number of popular votes candidates receive. As such, both the electoral college and the popular vote are covered in this post.

Comparing margins of victory across the years requires defining the margin of victory in terms that can be applied across the years. You can’t just compare the raw numbers, because the population has changed over the years. Accordingly, it makes sense to calculate the margin of victory in terms of the percentage difference between the winner and the runner-up.

Since the winner of the Presidency is decided by the Electoral College we’ll start by looking at the data concerning electoral college votes, then the popular vote, and then a combination of both electoral college and popular vote.

Electoral College Data

To win the Presidency a candidate must win a majority of the electoral college votes at stake. Today, a majority consists of winning at least 270 electoral college votes. So, what does the data show? Well, the average electoral college margin of victory is 44.6%, and the median electoral college margin of victory is 39.2%. Yes, but how do the president’s stack up against each other? The chart below lists the presidents from largest electoral college margin of victory to smallest electoral college margin of victory.

The first thing that jumps out about this chart is George Washington’s unopposed victories. If you were not already aware, in both elections President Washington won every single electoral vote, however, Washington was not the only candidate considered.

Right up there with Washington is Reagan, FDR, and perhaps surprisingly, Nixon. Throw in James Monroe and you have the only presidents to have an electoral college margin of victory above ninety percent. The president with the closest electoral college victory to the average electoral college victory? Ulysses S. Grant with a 45.6% margin of victory. The president closest to the median electoral college victory? Bill Clinton. Both times. In 1992 with a margin of 37.6%, and in 1996 with a margin of 40.8%.

On the opposite end of the spectrum you have the slimmest electoral college winners: Woodrow Wilson with 4.4% in 1912, John Adams with 2% in 1796, George W. Bush with 1% in 2000, Rutherford B. Hayes with 0.2%, and John Quincy Adams with -6% in 1824. Yes, John Quincy Adams won the Presidency after losing the electoral college, and the popular vote. The election of 1824 was quite the mess.

Popular Vote Data

We as a country did not track the popular vote until the election of 1824. The winner of the popular vote is not the winner of the Presidency, as Hillary Clinton, Al Gore, Grover ClevelandSamuel Tilden, and Andrew Jackson can all attest.

Going over the same statistics as for the electoral college, the average popular vote margin of victory is 8.7%, and the median electoral college margin of victory is 7.5%. Again, how do all the president’s stack up against each other? The chart below lists the presidents from largest popular vote margin of victory to smallest popular vote margin of victory.

Take a bow if you had Warren G. Harding as the president with the largest popular vote margin of victory in US history. Bonus points if you had his right hand man “Silent Cal” as the runner-up. The top of the list also includes FDR, LBJ, and Nixon. William Taft has the closest margin of victory to the average margin of victory with 8.6% in the election of 1908. The president closest to the median popular vote victory? FDR in 1944 when he was elected for the fourth time with a margin of 7.5%.

On the opposite end of the spectrum you have the five popular vote losers that won the presidency: George W. Bush with -0.5% in 2000, Benjamin Harrison with -0.8% in 1888, Donald Trump with -2.1% in 2016, Rutherford Hayes with -3% in 1876, and John Quincy Adams with -6% in 1824.

Combined Electoral College and Popular Vote

Why would we want to consider the combined electoral college margin of victory and popular vote margin of victory? Well, for one thing, the combination of the two is a better indicator of broad support behind a presidential victory. As we have seen, a candidate can win the electoral college, but lose the popular vote, and vice versa. If a candidate is one of the top performers in both the electoral college vote and the popular vote that is a good indicator of their support, but that is also a decent indicator of how successful their presidency may be, as well as whether they might be re-elected.

The average combined margin of victory is 50.9%, and the median combined margin of victory is 47.2%. Once again, how do all the president’s stack up against each other? The chart below lists the presidents from largest combined margin of victory to smallest combined margin of victory.

The top of the list includes FDR (twice), Nixon, Reagan, and LBJ. Ulysses S. Grant has the closest margin of victory to the average combined margin of victory with 51% in the election of 1868. The president closest to the median combined margin of victory? Martin Van Buren in 1836 with 47.2%.

On the opposite end of the spectrum you have the five weakest combined margins of victory: George W. Bush with 8.9% in 2004, Woodrow Wilson with 7.5% in 1916, George W Bush (again) with 0.5% in 2000, Rutherford Hayes with -2.8% in 1876, and John Quincy Adams with -16.1% in 1824.

There appears to be a correlation between performance in the electoral college and popular vote, which is illustrated by the chart below. The data is drawn from the tables above.

The chart above plots the combined margins of victory for each president from 1824 to 2016.  The y-axis represents the popular vote margin of victory.  The x-axis represents the electoral college margin of victory. Three presidents have been highlighted: FDR’s dominating election in 1936 is off in the upper right corner of the chart; Harding’s election in 1920 with the largest popular vote margin of victory, and JQ Adams abysmal performance in 1824 in the lower left of the chart. From the chart the relationship between electoral vote margin and popular vote margin means a 20% increase in electoral vote margin roughly translates to a 5% increase in popular vote margin. In fact, the slope of the trendline for the chart is .2149.

Another way to look at these combined margins of victories is chronologically. You can see large margins during times of war or periods of unrest. The bar chart below shows the combined margins of victory.

From this chart you can see that presidents seem to either do very well, or barely win election.  Sixteen presidents have a combined margin of victory of 75% or higher, sixteen presidents have a combined margin of victory of less than 27%, and eight presidents have a combined margin of victory between 27% and 75%. You’re either popular, or not.

Two-Term+ Presidents

What about two-term+ presidents? Well, we’ve only had seventeen of those, and of those seventeen only thirteen were reelected after 1824, which is the cutoff point for our combined margin of victory statistic. The chart below shows each election that a two term+ president won including the initial election.

FDR dominates the upper right quadrants of this chart. GWB is two of the data points in the far lower left. The average popular vote margin of victory in elections that a two term+ president won is 9.4%, and the median is 9.1%. As for the average electoral vote margin of victory that is 49.3%, with a median electoral vote margin of victory of 43.2%. The following table shows all the data for reelected Presidents sorted by their combined margin of victory.

Again the most popular Presidents from before are at the top and there are no surprises at the bottom. The more meaningful data for reelected Presidents is how they did in their first election. That table is below, and a chart of the data  below that.

Four of the reelected Presidents have combined margins of victory over 75% (FDR, Reagan, Wilson, and Eisenhower), five of the reelected Presidents have combined margins of victory between 40%-75% (Grant, Jackson, Lincoln, Clinton, and Obama), and four reelected Presidents have combined margins of victory less than 40% (McKinley, Nixon, Cleveland, and GWB). GWB is the only President to have lost the popular vote and been reelected President. He won the popular vote in his reelection campaign.

Conclusion

What does it all mean? Well, it appears that Presidents either have a fairly strong margin of victory to get them elected, or not all that much. Regardless, the data is extremely clear that the sitting President’s victory is one of the weaker victories in our history.

Five Implications of Blockchain Technology

Lawyers are a natural fit to understand the implications of blockchain technology on society. Why? Lawyers can understand the implications of blockchain technology, because blockchain technology deals with concepts that lawyers have been wrestling with for millennia, namely: trust, exchange, agreement, consensus, and value.

Trust

Arguably the most central concept for organizing human society is trust. The degree to which people trust each other, and how they manage those trusted relationships is often intermediated by lawyers. Lawyers craft agreements for clients based on the level of trust between the parties to the agreement. Lawyers are not necessary for trust to exist, but they often bridge a “trust gap” between parties that do not know each other well. In this sense, lawyers function as trusted third parties.

With the advent of Bitcoin the trust equation changed. Now it is possible to “trust” information sent over a network you don’t trust among a group of participants you also don’t trust. To be sure, there is an element of trust that still exists. Namely, the participants in the network must trust the way the network is run, and the technology that underpins the network. The point is that lawyers have a natural affinity for managing trust relationships, and they should not be turned off by this new technological approach.

Exchange

What does it mean when parties exchange something between each other? The concept of exchange, giving something to someone else and receiving something in return, is the foundation of all trade and many of our interactions as people. Exchange has many issues associated with it, such as:

  • What are the terms of the exchange?
  • Are the terms of the exchange clear?
  • When has the exchange started?
  • When is the exchange complete?
  • When would it be unfair for it to not finish?

Many more issues can arise, but these sorts of questions are common place in the legal world.

For networks that use a blockchain, distributed ledger, shared ledger, or other decentralized exchange network, the answers to these questions are often found in the network protocol. The protocol determines how exchanges work and what types of exchanges are possible. Similarly, the protocol will also determine the involvement of other parties in said exchange. Knowing the rules of exchange is something that lawyers already advise their clients on, and answering those same questions with respect to blockchain applications is something they can and should do.

Agreement

In many cases agreements are often contracts, and contracts involve at least two parties coming to a meeting of the minds as to the terms of their agreement. That’s a wordy way of saying “I’ll do X, if you do Y.” Historically, agreements have been memorialized in a contract. Problems arise when one of the parties claims that the terms of the contract weren’t met, or that the contract was invalid.

Blockchain technology creates the opportunity to create binding agreements on a blockchain network. A potentially huge shift in the practice of law is likely to come in the form of smart contracts. A smart contract is a way for at least one party to memorialize the terms of an agreement in computer code that is distributed across a blockchain network.

The lawyer’s traditional role of helping clients come to an agreement on a contract will not change as a result of smart contracts. What may change is how that agreement is memorialized. Here lawyers would do well to learn about smart contracts and how to code them. With each passing year more and more clients will want that option.

Consensus

Traditionally, consensus on the veracity of information in a network (be they financial networks, groups of experts, etc.) has involved reconciliation processes and other mechanisms to determine what information and records are correct.

Perhaps the biggest change brought on by Bitcoin and other blockchain networks is a new way of achieving consensus on information transacted on a network. As transactions occur on a blockchain they are packaged into blocks of transactions. If certain conditions are met that block becomes part of the official record and the chain of blocks grows. If enough participants in the network agree, that block becomes part of the official record and consensus is achieved.

Determining when and how consensus is achieved is well within a lawyer’s toolkit. Being able to assess whether information is part of the official record is something lawyers already do, and something lawyers will have to do more of when their clients wish to use blockchain technology.

Value

A concept more abstract than trust may be value. What is valuable to one may be valueless to another. How and why we value something may be intrinsic to the thing in question, or extrinsic to that thing. Regardless of why something has value, lawyers often help their clients determine the value of things. They also help clients secure valuables, as well as ensure their client receives fair value in an exchange.

In disputes, lawyers often have to advocate why something should be valued a certain way on their client’s behalf. The fact that magic internet money is valuable to some, and not valuable to others, is largely irrelevant to the job of an attorney. Thinking abstractly about why something is or isn’t valuable is already a large part of the job.

Conclusion

Lawyers should not be worried about blockchain technology. In fact, they should embrace this new paradigm shift towards decentralized interactions. The legal issues lawyers deal with day to day will not be disrupted by this new technology space. They will merely be presented in a new format.

Blockchain Naughty List

I proposed on Twitter a list of the most misused words in the blockchain and cryptocurrency space.

My list was Immutable…Trustless…Game theory…Smart contracts…Cryptocurrency…Blockchain…

Not surprisingly my list was wholly inadequate. I omitted several words that are constantly misused. Thankfully, many people chimed in to round the list out.

Middleman…Distributed…Transaction…Ledger…Mechanism design…Decentralized…Censorship resistant…Disintermediation…Anti-fragile…Secure…Advisor…

I know I’ve misused all of these words. There are probably more words that should be included.

Generally speaking, I think the misuse of these words is a consequence of this being a new industry that is ridiculously multi-disciplinary. It is very easy to be imprecise when talking about the concepts involved in the space. Plus, no one in this space is an expert in all the different disciplines at play.

Basically, we should all probably tighten things up and keep on learning, because I think Angela Walch is right about how people are currently incorrectly using the jargon that makes up this space.

“Basically any word that describes how the tech is beneficial or what its characteristics or capabilities are.”

Smart Contract Patents

It’s about that time again to check in and see how many patent filings mention smart contracts. The first time I wrote about this was in June ’16 here, and then again in March of this year here. Smart contracts are very much a part of the current zeitgeist (sidebar, if you ever want to feel like an idiot read Hegel), and all the rage in the B2B world.

The first time this search was run there were seven hits. The second time the search was run there were fifty-six hits. This time? One hundred and thirty six filings mention smart contracts. This is less than seven months since I last ran the search when the number was fifty-six. Of those filings, eight are issued patents and 128 are published patent applications.

The first chart below shows the growth in filings by publication year. The second chart below shows the number of filings by the year they were filed.

 

Each year there are more and more patent filings that we know about that are related to smart contracts. What the second chart shows us is the growth in the number of filings. Those numbers are not final, as there are undoubtedly still more filings that are not yet public. Based on the trend shown by these numbers its not unrealistic to assume that twice as many patent applications have been filed in 2017 that mention smart contracts than were filed in 2016. That would be around 150 patent applications filed in 2017 making use of smart contracts.

More broadly speaking, the growth in the number of filings that mention smart contracts is in line with what we would expect from the maturing blockchain industry. I wrote about this emerging blockchain patent landscapein March of this year. Companies, large and small, are moving to protect their innovation in this space. Bigger numbers are on the horizon.

Blockchain Patents

Say you’ve got a great idea to use “blockchain for [insert literally any problem domain]”. First off, congratulations! That sounds cool. Now you think to yourself, “I should patent that!” Maybe.

Before you go through the long and costly process of seeking patent protection there are some questions you should ask yourself, or your attorney should ask you.

Do you really need a blockchain?

This is the most important question, and one that requires serious introspection. Are you pursuing a blockchain technology solution because you are trying to capitalize on a hot new trend? Do you just need a new data storage solution? Have you really hammered out the pros and cons of using blockchain technology? Do you want to build your own blockchain, or use a public blockchain or some private blockchain service?

Your answer to these questions will of course depend on your goals, constraints, and the data you are dealing with. If you are convinced that you do want to pursue a blockchain technology solution to your problem you should have answers to at least the following questions.

What data do you hope to store using blockchain technology?

It doesn’t make sense to throw any old data in a blockchain. I mean, you certainly can, but that would be wasteful. Typically, you want to put “significant” data in a blockchain. For example, data that might be usefully stored on a blockchain may be mission critical data that you don’t want to lose, however, then the question becomes is access to said data time-sensitive? If the answer is yes then a blockchain solution may not be a good fit.

Have you considered any privacy restrictions on the data you are dealing with? For example, is the data personally identifiable information, such as healthcare data? If it’s healthcare data, have you properly walked through permission controls that need to be put into place? “We’re just storing a hash of the data!” you say, and yes that’s great, but are you really comfortable with that? Similarly, how will the data be entered into the system? Is the data going in solely under human direction? Is there some type of machine-machine communication going on?

Good candidate datasets for storage in a blockchain solution are “shared datasets that are shared amongst parties that do not fully trust each other.” That is, parties that may be incentivized to change data to the detriment of other parties involved in the network. Remember, blockchains are tamper-evident and so can cut down on funny business by participants that don’t have a majority of the computing power necessary to overrun the blockchain the data is stored in.

How are transactions handled?

Transaction verification should be trivial, but if you are not dealing with public blockchains (e.g. Ethereum, Bitcoin) then you may need/want additional verification steps. If so, what are the additional steps taken as part of the verification process? Even if your idea involves the use of public blockchains you may want to include additional transaction verification steps that occur prior to interfacing with the public blockchain.

Similarly, how is consensus handled in your blockchain solution? Inventing a new consensus algorithm is probably not a good idea. It’s better to use an existing consensus mechanism. This calculus changes if your blockchain solution does not make use of tokens that are native to your new fangled blockchain network. If you are not using tokens (e.g. bitcoin, ether) as part of your solution, why are you trying to use blockchain technology again?

Does this interface with legacy systems?

How do you envision your blockchain solution fitting into your existing business model? The blockchain solution will either interface with legacy systems or seek to replace legacy systems. Both paths have their own pitfalls, and their own patent considerations.

Along these lines, is your blockchain solution going to be solely internal to your business, client facing, or a combination of both? You need to consider exactly how your use of blockchain technology interacts with these internal systems and external systems.

Who is allowed to participate?

A blockchain network is made up of all sorts of different participants. Have you figured out who can participate in your blockchain network and how? Do you use an existing blockchain network, such as Bitcoin or Ethereum? If so, have you considered privacy requirements for your data, and how they might be met on those networks?

If you are designing your own blockchain network, are there checks performed prior to participation in the network? What would those checks look like? Accordingly, do you have a validation process in place to validate information used as part of any checks on participation? This is less of an issue if you are spinning up some sort of permissioned blockchain where there is a certain level of trust afforded each participant.

Conclusion

Blockchain technology is not a panacea for every problem you face. In fact, blockchain technology is really best suited to situations where you have participants on a network that don’t fully trust each other, want to update valuable data, and don’t fully trust the network. If that is not your situation, you need to think about at least the questions posed above, but probably many more.

Denominated in Bitcoin

You often see people in the Bitcoin community use the market capitalization of Bitcoin to compare it to the money supply of other countries. In particular, the M1 Money Supply of countries is used as a metric to measure the value of all bitcoins against. For example, Jameson Lopp recently cloned the CIA’s numbers on M1 Money Supply around the world including the value of all bitcoins, which shows Bitcoin in 32nd place. These statistics are interesting, and certainly indicative of how far Bitcoin has come. At the same time, this is a narrow way to think about Bitcoin and its growth.

There are no shortage of people that believe Bitcoin, or more generally cryptocurrencies, will replace fiat money in the future. Thinking in these terms, why limit Bitcoin to the M1 Money Supply? Won’t Bitcoin become the market, as in all transactions will occur on the Bitcoin blockchain? Putting aside the probability, or desirability, of that outcome what does the world economy look like if it is denominated in bitcoin?

A couple of assumptions. Gross Domestic Product, or GDP, is more or less the standard metric used by economists to measure the economy of one country against the economy of another country, and so, that is what I’ll use. The underlying GDP and population numbers are from 2015 courtesy of the World Bank. GDP is problematic, but it’s a decent measure of the total “value” in an economy, and remember we’re talking about a scenario where all value is transacted through bitcoin. I’m using the total number of bitcoins mined, as of yesterday, (~16.66 mil according to blockchain.info) as the number of bitcoins. Sure, I could use twenty one million as the number of bitcoins, but we haven’t hit that number yet and we don’t know what the world’s economies would look like when that number is hit.

The chart below shows the country, the population, the Bitcoin In Country, or “BIC,” and the Bitcoin Per Person, or “BPP.” I’ve listed the top twenty-five countries, and the bottom twenty-five countries according to BIC. So, how many bitcoin does each economy have?

 

There is nothing terribly surprising about the countries listed above, because they are the largest economies in the world. What is interesting is what their economies look like in terms of bitcoin, and in particular the number of bitcoin held by each person in that economy. But, what about the bottom twenty-five countries?

 

Again, if you’re familiar with the poorest countries in the world you should not be surprised by the list of countries above. What is extraordinary is that if you have 8 bitcoin you would have more bitcoin than the entire economy of Tuvalu. Does this make sense? I have no idea, but it’s shocking to think about. If you had 353 bitcoin you would have more bitcoin than each economy of the bottom 25 countries.

Conclusion

Denominating countries’ markets in bitcoin is another way to get a handle on what Bitcoin adoption means. BIC and BPP are indicators that help illustrate that point. Whether Bitcoin replaces all value transaction is a very open question, but if Bitcoin were to do that a person would not need to have a lot of bitcoin to have more bitcoin than many countries in the world.

Update: I added the full list of countries if you want to peruse them below.

Misconceptions About Bitcoin

Bitcoin, blockchain, smart contracts, ICOs, word salad. 2017 has been a big year for cryptocurrencies, and blockchain technology. Bitcoin is the original cryptocurrency, and it is a massive understatement to say that it is not widely understood, but below are a few common misconceptions widely held.

“You have to buy a whole bitcoin.”

False. You can buy a fraction of a bitcoin, because bitcoin is by design extremely divisible. In fact, a single bitcoin is actually divisible down to eight decimal places: 0.00000001. That is in part why people are so excited about the possibility of micro-transactions using cryptocurrencies, because unlike the US Dollar (which is divisible down to two decimal places: 0.01) you can send very very small amounts of bitcoin on the network.

“I can hold bitcoins in a wallet.”

Not exactly. There actually aren’t any bitcoins in the bitcoin blockchain. At least not in the sense of pennies, nickles, dimes, and quarters. What is “held” at addresses are “unspent transaction outputs.” These are known as UTXOs. UTXOs are used as inputs into new transactions on the bitcoin network. Also, when you see a bitcoin “balance” when you open your bitcoin wallet you aren’t actually seeing an amount of bitcoin held by the wallet software. What you see is a total of UTXOs that you control through the use of private keys associated with the UTXOs. Put it this way, you can’t take your “bitcoin” in your “wallet,” and go home. The UTXOs live on the bitcoin network, and your wallet software allows you to access it.

“Bitcoin is anonymous.”

Not really. It is much more accurate to say that bitcoin is pseudoanonymous. With a combination of the Tor browser, VPNs, dark magic, and dumb luck maybe you could make bitcoin “anonymous,” but before you go down that route you should talk to Ross Ulbricht about how well that works.

Conclusion

There are many more misconceptions about bitcoin, but these are three I see time and time again. If you want to learn more about bitcoin you should check out Bitcoin.org, or CoinCenter.org. Both great sites, and great resources. Of course you can always just read the Wikipedia page.

Free Speech

I made a handy flowchart to help you determine whether your free speech rights are being trampled.