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 provide these.
