How you know your vote counts
It can sometimes seem that voting doesn't matter. This video, from the Security Digital Democracy MOOC, breaks down why that isn't true, and how and where to see the effects of your vote.
Welcome back to Securing Digital
Democracy. Since computer scientists have had so many
criticisms of electronic voting systems. Some people have, have thought this was a
very strange thing. What were these, these high tech people
thinking? Were they suddenly Luddites?
But what computer scientists and researchers in the voting field know is
that there are ways to use technology well.
And ways to use it poorly. That there's some things technology can do
securely and some things that's it's very hard to make technology do securely.
In this lecture, our focus is going to be on some new ideas about how to use
technology in the voting process in order to make it more secure.
I'm going to introduce a series of technologies that have been developed by
researchers in this field and give you an idea of what the future of technology and
voting might look like. But before we begin, I'd like to talk for
a few minutes about some of the criteria, some of the desirable properties for
voting systems that people in voting, in voting research, in voting practice talk
about all the time. And when we're evaluating voting systems
both old ones and new ones, it's important to think about how well they meet these
criteria. The first property, and probably the, the
most abstract one and the one we talk about most, is the idea of transparency.
People talk about the need for election transparency in relation to things like
DRE voting machines. What we mean by transparency is the, the
property that the voters can observe and understand the election process.
This is important for several reasons. Transparency allows voters to observe and
thereby understand why their votes are being counted.
It allows voters to understand what the rules are.
It allows them to make sure that election officials are doing their jobs.
For those reasons, we might propose a more full definition of transparency.
And this one comes from Joe Hall, which is that, a fully transparent election system
supports accountability as well as public oversight comprehension and access to the
entire voiting process. Another extremely desirable property is
what we call verifiability. Verifiability means that voters have some
means to convince themselves rationally speaking, that the election outcome is
correct without having to just blindly trust that the technology is functioning
correctly, or that the election authorities are honest.
An example of a voting system that has the verifiability property might be paper
ballots where people are free to go and observe the counting process because then
the voter can directly convince themselves with their senses that the outcome is
correct. On the other hand, a system that is not
verifiable is paperless DRE's. Because in a paperless DRE, the only count
of the votes is happening by black box software in a way that, that people can't
observe and where people just have to have faith that the software is correct.
Another important property is auditability.
And that means that the system has some way that it can be manually checked after
the election to ensure that the votes have been counted properly.
Optical scan voting has this property. Because we have a set of, of paper ballots
that we can spot check or recount to make sure that the totals are correct.
I'll talk more about auditing elections later in this lecture.
Finally a property that has been defined with respect to software used in the
voting process is an idea called software independence.
And this is an idea that was coined by this man, Ron Rivest, who, for those
security nerds in the audience, is an American cryptographer who is the R in the
RSA cryptosystem. Ron's idea is that a voting system is
software independent if an undetected change or error in the software cannot
possibly cause an undetectable change or error in an election outcome.
Now, this is a really powerful idea. Because it allows us to distinguish
between systems where we have no choice but to blindly trust that the software is
secure and correct. And systems where we have some means of
catching any, any problems or cheating attempts that the software might be
making. And examples of systems that provide this
property of software independence are, are, optical scan systems and DREs with
paper trails. So long as we are catching any problems by
auditing those paper ballots or paper trails after the election.
So I'll, I'll talk a little bit more about software independence when we talk about
auditing. So those are some of the most desirable
properties in elections. Now let's see some ways that systems can