But how many typical blockchain users know what rules will put them on the alert list?
There seems to be a non-zero possibility of good or benign actors getting caught in this analysis. Colin Harper wrote about this issue (with regards to mixing specifically) in a previous Bitcoin Magazine article, “The Bitcoin Mixing Case At The Center Of The Fight For Transaction Privacy” :
“Honest, privacy-savvy Bitcoin users should have nothing to worry about legally, so long as they have nothing to hide, Jesse Spiro, head of policy at Chainalysis, told Bitcoin Magazine … But Spiro’s comment betrays the consequence of this surveillance: Honest users can get caught in the crossfire.”
Future Directions: Automation Of Flags And False Positives
If you’ve ever encountered a positive-outcome vending machine malfunction, you’ve come upon the upside of an error and automation of that error — the machine continues to dispense snacks for free. (Yes, I know, Bitcoiners don’t eat that stuff).
As another example, anyone with a credit card has seen the number of false positives with regards to fraud. When you automate anything, if the methodology is imperfect, you can then automate errors at a more efficient and faster rate.
To make the platform more efficient and able to handle a higher number of smaller cases, many sessions talked about automating the data analysis and flagging of issues.
For false positives with a bank or credit card, the issue is a minor inconvenience. However, being falsely flagged for nefarious activity within other systems can put you under the wheels of that system and it can be difficult to prove innocence and extricate oneself. The systems mentioned included organizations such as the U.S. Internal Revenue Service, police and international crime units and banking systems worldwide.
It was noted during the conference that input from more data systems are going to be sourced, aggregated and otherwise used within the Chainalysis platform. It is yet to be seen what that will mean for generating false positives around what the platform deems to be “criminal” activity using platforms like Bitcoin.
Chainalysis, Privacy And Censorship-Resistance
In 2019 , Chainalysis made a public statement of its privacy policy in response to public scrutiny around the privacy implications of deanonymizing blockchain transitions. If you don’t have financial privacy, you are not censorship resistant. Bitcoin is not censorship-resistant without privacy.
This is at the heart of the concern around the Chainalysis tools and its ability to do financial surveillance.
Chainalysis provides useful metrics that counteract false narratives. These include data on how much cryptocurrency is really used for “criminal” activities and data about cryptocurrency adoption by country and demographics.
However, the Chainalysis investigative analysis tools that are used against what most would view as “bad actors” can also easily be used against anyone. Its tools could also be used to suppress rights and freedoms where certain or arbitrary laws do not enable those rights and freedoms.
As world entropy increases, the greater good would be served if Chainalysis were to develop protocols regarding who it will sell their products to and what its definition of “crime” is in order to reduce the likelihood that they cause harm unintentionally.
Chainalysis may be enabling others to surveil the blockchains for nefarious actors. But privacy experts and Bitcoin plebs should also be watching and surveilling Chainalysis for similarly bad actors and actions.
This is a guest post by Heidi Porter. Opinions expressed are entirely their own and do not necessarily reflect those of BTC Inc or Bitcoin Magazine.