Kelsey Gilmore-Innis on Information Escrows.mp4

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Hi. Hi. My name is Kelsey Gilmore Innes. I'm the director of technology at Sexual Health Innovations, were a nonprofit devoted to building tech to further sexual health and well-being in the United States. We are currently working very feverishly on building and delivering Callisto, which is an online sexual assault reporting system for college campuses.

It's designed to be confidential, secure and survivor focused. We're rolling it out at two colleges this fall for freshman orientation, which is very, very, very soon. And it's designed to be an interface to existing Title nine reporting systems. We're taking an existing process and putting it online. We're also introducing a new idea that comes out of the academic paper, which is why I'm here talking to you at papers we love. So Information ESCOs is a concept introduced in the title of a 2012 Michigan Law Review article by Ian Ayres is an economist and a professor at Yale Law School. And Kate Unkovic, who is a grad student, UC Berkeley. And Escrow is a system designed for two parties who are undergoing a transaction to put some third material with a trusted third party. And it's released under conditions agreed to by both of them. The concept of information, ESCOs is sort of a newer thing. There's a couple of different kinds that actually already exist.

One is called a commitment escarole, which at the time I've most often seen it is like on in crime movies where it's like someone witnesses, someone committing a murder and they're like, wait, here's an incriminating thing about me.

Don't kill me. And actually, game theorists write papers about this, which is funny.

There's also the concept of a posthumous Oscar, which is their idea of a Esker, where information is released after the death of a person or an institution. So one form that this takes that you may have encountered is a software escarole where a company will put their source code in escrow with a licensing company. And if the company Soffer Company dissolves, that source code is released. Another one that's much more common is a shared interest escrow. And there's a couple of different like common applications of this negotiation and auctions. Actually, they've experimented with doing an escrow system where both parties will put in a range of acceptable offers. And the third party will only release the bids if they overlap in some way.

Dating askers actually, sue, if you ever like, in the early days of Facebook, you'd like find my crush and you put in like six people you have a crush on. And if any of them put your name in, then like they hook you up, which is kind of like Tinder. So in some ways, a Tinder is a shared interest group, although not actually cited sadly in this paper. Adoption. Actually, they've been exploring information Espers as a way in closed adoption states to connect birth parents and adopted children. Adults, adopted children. And the fourth category is allegation escarole, which is what the subject of this paper is about. An allegation has Kurzon Esker that holds claims about a crime and the claims are only released or really filed if a pre specified number of claims are all filed against the same defendant. And we're incorporating this into Callisto when talking about sexual assault. So we have an option in Callisto where you can choose to put your report in escrow and only have it filed to the school if someone else files a report with the same assailant. And the reason why this is a useful concept is this game theory concept of first mover disadvantage. And that's when Mayte being the first person to make an allegation, holds some sort of disadvantage. And so in the case of sexual harassment and sexual assault, fear of retaliation is a big one. It's not so much in those shared interests. Espers, we see sort of like a fear of lack of interests on the other part. But here, the fear is retaliation from parties not involved in the escrow.

The common, sadly common sort of strategy when people are defending against claims of harassment or assault is call is branded Denia a nut or a slut strategy where the accuser is cast as either someone who is mentally ill or has brought it upon themselves by being slutty.

Another reason why there might be fear, reasonable fear of retaliation in a sexual assault or sexual harassment scenario is that many harassers and rapists prey on vulnerable people. So the concept being that they've picked out someone who is particularly vulnerable to retaliation or threats of retaliation. The reason why you would see a disadvantage of being the first mover, it's kind of a he said she said thing. We see this in the Cosby case, which was a big deal in the news recently. Being the first person to come out with a claim of sexual assault is not a fun position to be in.

There's another way that there's a first mover disadvantage when you're talking about assault and harassment, and that is wrongdoing, uncertainty. So people like to talk about other grey areas with assault or harassment. I am not convinced there's as many as everyone likes to claim, but I think there are some grey area. Where especially considering sort of some of the cultural influences we're not a victim, isn't sure if they've been assaulted or harassed. And in a lot of cases, predators really thrive in that area.

It can create an avenue to open up an assault or an instance of harassment. If you know that the person you're you're sort of attacking isn't going to be able to to really blame, like claim with certainty that something bad happened to them.

These this this sort of brings these kind of assaults into a category and game theory that's called a stag hunt problem.

Game theory, relax, animals. That's also called a penguin problem. The basic idea there is where a group action together would get you a better outcome for the group. Right. But acting rationally as individuals without cooperation, individuals end up taking a less optimal action.

It's exacerbated here by not knowing who the other victims are, even if they exist. So the idea that information, escarole, is to reduce that first mover disadvantage. The other problem is, though, right, that you want to reduce the first mover disadvantage. But there's also a concern that if you offer a way for people to file complaints that never actually get seen by the appropriate authorities, you could actually reduce reporting in general. If you end up with a lot of what we call orphan complaints, which are complaints that go into the escrow but are never matched, you could end up with a lower rate of reporting, which is not exactly what those systems designed to do. So what this paper sets out to do is to model sort of what would happen if you introduced escrow into these reporting systems. And so it sets us up with some variables. And this reflects there up here, it's basically you have probability variables. Right. But the ones that we're concerned about is what is the probability that a victim of this crash of a crime that you have an escrow with will file a direct claim without the escrow? Right. And then what's the probability that someone who who suffers from this first mover disadvantage would actually file a claim? If someone else had already gone? This model reflects a couple of things that we know about claimants in crimes like these. One is that the first probability here, the PD is less than one. We know that not everyone is willing to file direct claims. The second one we know is more than zero because we've seen this over and over again in cases where someone will go public, will risk that first mover disadvantage.

And it'll turn out that there were people there were other victims along sometimes, you know, months or years that also now are willing to come forward.

In order to model how an espero would change the situation, you need a couple of other variables. These two variables are to model the effect of it. It's saying, well, OK, which how many victims would have filed despite the first mover disadvantage. But now with the available even Esker will Esker instead.

I mean, how many victims will put their their claims into the escrow instead of just not filing at all? There's also another variable, which is how many claims you have to get to trigger it. But basically, all the modelling indicated that two was probably optimal. So I've kind of dropped it in this. But that's also a variable.

So the question comes up, what numbers do you put in here? Right. And like the answer to that is kind of like we don't know, especially when you're studying underreporting like it's in the name. It's hard to study. Right. So what errors and Unkovic did was they. They're not being detrimental. When I say this, they made it up, right. They asked around.

They did some surveys. They looked at some existing studies and they came up with some reasonable numbers to put in there. And they modeled it. And so if you have numbers coming in here, you can model what the effect is. So, for example, this table, which is hard to read. You don't need to read anyway. Don't bother squinting. Don't hurt your eyesight. It's basically talking about a scenario where only 10 percent of victims will ever report and 20 percent of the remaining will come forward if there's another report. I picked five percent that would, Esker, instead of direct reporting and 15 percent would ask Rovere silence. Again, these are sort of arbitrary. I mean, it models what would happen based on various numbers of repeat offenders in this case. We see improvements here, especially for those repeat offenders who see improvements on the lines of fifteen to twenty percent, which is really significant.

Again, these were arbitrarily chosen, right? It's speculative at best.

But what's interesting about this, right, is you can actually take this and you can plug all different models in there for this simulation. And what you can do is come back and look at the results and use that to back model and be like, what kind of conditions are good for an escrow and what kind of conditions aren't we? We sort of here's one of the tables. There's a couple of tables in the paper like this, right, where they actually show you combinations of different models and they've released the data and you can go plug it into an Excel spreadsheet.

One of the big conclusions here is that underreporting is a huge factor in this problems where you have severe underreporting are going to actually be really benefited by an escrow situation being available. These are the ideal escrow conditions when we look at those variables. We modeled if you have like I said, if you have an underreporting problem, if there's a lower probability that people will make direct complaints. That lends itself to an escrow. If you have a high. If you think that there won't be a ton of conversions from direct to escrow, that's probably better for the escrow situation if the end point is getting more folks investigated.

Similarly, if you think more people will be willing to put their reports into the escrow. Who wouldn't have reported in any way before? That also helps. And we tend to think for sexual assault on a college campus. Both of these are true because of the sort of shame around it. And the very public and negative consequences that public accusers face.

Another one is this really works best if you have a high probability of multiple harassers. Right. Like, if you have a crime that, you know, people are going to repeat this, Esker works really well.

So there's good reason to think that.

Sexual assault in college is a crime that has a high probably a high probability of multiple assailants.

There is a study in 2002 by David Lisak, which found and in his study, he found that abouts of the six percent or so of men out of a large college sample who admitted to rape or attempted rape.

A startling 63 percent reported committing more than one. And they actually of those repeat harassers, they repeat assailants. They reported an average of six assault acts each. So that was a. That's a really, like, striking result. Right.

So here's where I come in with the stuff that's relevant to all of you as computer science, computer scientists who implement papers.

So benchmarking is really hard. And you may have noticed this in the news last week, at least a lot of people sent it to me. There a study that came out last week that actually gave really different answers than David Leasebacks study and said, well, actually, when we look at it, most of the rapes aren't committed by serial rapists. So that's interesting.

If you look at them, they use a different definition of rape. They survey a different college population. One of them was Boston commuter college students and other one was a Southern residential college with a large residential population counts. This new study counts everything within a year as one instance. It also studies only sexual assault, where the lead earlier leasebacks study looked at a bunch of different instances of interpersonal violence and specifically what it challenges. What the results challenge is the idea that repeat offenders show like a stable and high rate of perpetration over time.

They didn't find that in their new study. So which ones? Right.

Yeah. If you've ever won a benchmark, you know that the answer is like shrug emoticon. This scale is really important. Having a baseline is really important. The definition of what you're measuring is really important when you're in a benchmark. And these are all and I don't want to see easily manipulated because I think that that is important. It puts too much intent into what's going on. They're just hard to measure.

It's hard to measure. And in some ways, we have it easier in implementing Calista when we look at these numbers, because we at least have the advantage that our measurements are made on real life systems, which for a lot of academic papers. That's not the case. And it won't be for a long time, especially when you're looking at things that are intended to be implemented at large scale. And a lot of ways this is a project of measurement. We are interested if the results in this paper bear out, but we don't know if they will.

And there's so many unanswered questions about college sexual assault that we're we're building a system that is in and of itself a really important opportunity to get new numbers on it.

So let's say that this new study is right and we have a really low number of repeat predators, repeat assailants. Well, thankfully, in the paper, they actually go on after those those tables that I showed you. Let's talk about other costs and benefits of of implementing an escrow. And they're actually talking specifically about sexual harassment on college campuses. But we believe that these all apply to assault as well. The benefits are claimed selection. So there's some you know, it's not really necessary. There's not one crime here. Right. Like, there's a lot of different ways that assault looks on a college campus. So the thought is, is that more blatant crimes will be more likely to be directly reported. But we'll see sort of a triaging and a surfacing of repeat offenders who are doing that sort of uncertainty thing I was talking about. One thing that we think is a huge benefit. It offers a single venue for reporting so students can report an assault directly. They don't need to go to the escort and they are reporting assault directly through Callisto. And I don't know when the last time any of you have been on a college website before, but we actually think this is a huge value add in and of itself.

It's really hard to find the information about what resources are available and how to report on any given college Web site. Another one is that the skirl allows people to record evidence close to the event and store it while they go through the process of deciding if they want to take on that first mover disadvantage. And one of the schools we talked to, they reported an average of at best six months between assault and they're the victims first contact with the college title nine office. So that's a huge gap. And just in terms of memory and trauma and treatment, it's so much better to get that stuff done immediately starts a good important benefit in terms of costs. You have an imbalance of staleness. All those things I just said we offer to the survivors and the defendants, the people who are accused don't have that.

There is the danger that we will end up with implementing and, Esker, giving less weight to uncorroborated claims. And they describe this in the paper as the two byte rule where you can harass or assault someone once and you'll get away with it because you often have two claims to actually get any one investigated. That would be a bad thing. Another one that they talk about is false and bad faith complaints. And they really want to put this out because I thought this was really interesting. In fact, I would say about half of the paper by page is about bad faith complaints, which is, I think, a glaring difference between a whole law paper and a computer science paper.

And this, again, if anyone who's implemented anything will agree.

Right, like certain things like security. Right. Or bad actors are very rarely sort of emphasized. And I think that was really interesting and really helpful that someone had already really systematically thought through some of the risks and failsafes you could put in to deal with bad faith actors, which is really cool and helpful to us. So the last thing I need to talk about is the concept of spherical cows. This is like a joke from physics where if you ask a physicist to give you a real world, real world answered anything, they'll be like, well, assume a spherical cow.

There's a lot of assumptions built into this paper. There's a lot of assumptions built into any paper that's talking about anything. One thing that's kind of nice is they actually laid out in this paper what some of those assumptions were.

Some of them were that accusations were publicized when they are calculating those probabilities between the first round of acting and the second round of acting. Another one is that they just assumed they didn't build false claims into their calculations when they were doing statistical analysis. Another one that they pointed out, which is interesting, is they assumed when they were comparing the two that the likelihood of offences were the same.

But I mean, our goal in building this and in trying to improve the reporting process for college sexual assaults is to make a change in behavior. Right. Like knowing that there's this system and that there's support and that there's strong consequences for assault should change the likelihood of offenses. There's also a couple that we've run into that weren't in the paper, which also will probably be familiar. The situation for folks have implemented things. One is that in the paper, they assume that reporting in the Esker is automatically triggered. No matter how long the length of time is between a report and a trigger and that the schools notified first. And like this runs into all sorts of squeaky weird consent issues, which you really don't want to mess with when you're talking about people who've survived assaults. Another one is there. It's like I assume I assume a perfect matching algorithm, which is rough, actually. And it's it's an open question for us what information people do know about their assailants and what unique information people do know. I went to a school with 50000 students. I think there were four Bobby leads in my chemistry class alone. We're matching on name isn't really going to work. Actually, yeah. We looked up some common names to sort of like like prove this point. So we have to figure out a unique idea that people can use that doesn't fall afoul of laws about releasing student information. So that one's been a difficult one. A third one that's really interesting and that I already kind of talked about is that the Esker agent is unimpeachable. That's both that.

And then, you know, on a couple levels, one, I mean, on a basic security level. And I think, again, this is like this is this is going to be common when you're planning anything.

We very rarely handle security first when we're talking about implementing systems, but it's drastically important. Another one is, for example, when you're filing information with a third party and then there's a course court case about it.

We now have a attacker in the sense of information security, which we can't reasonably put up technical defenses against necessarily if we get subpoenaed. And not one has been tricky and interesting. And I'm actually really excited about the solution we've come up to. It's kind of a part of this system that has fun cryptographic implications. And if you want to come talk to me after, I'm like happy to chew your ear off about it. But that was definitely a spherical cow that was assumed in the paper that we can't really sort of bear out.

So to conclude, they finished the paper up by talking about applications. Some of the ones were excited about noncollege environments. The military is obviously a very interesting one. It's where this issue is very important. Sexual harassment in the workplace. That one's interesting, too. Like how does college is nice because it's a constrained environment. You have people who are in the same place for the same time, for the concerned amount of time workplaces and is true. Whistleblowing is one where there's obviously a first mover disadvantage. Adverse drug events is interesting because there's not much incentive. And Ian Ayres, who was the professor who wrote this paper, studies incentives. And there's not much real good incentives for doctors to report drug events. So he had some interesting thoughts about this spherical cow stuff that we start to get into. These last are really interesting. One of them proposed is a suspicion escarole for adultery.

So if multiple people suspect that your spouse is adulterous, they could file it somewhere and then you could be notified. Yeah.

That is like a five dimensional spherical cloud to me. But that's bad ideas, interesting and insecurity escrows. For example, if you were concerned that your breath smelled or your talk was boring, you might use some system to get, you know. Well, you know, if one person says my dog was boring, they're just petty. But if all of you think it was boring, then I want to know. So that's just some thoughts. Anyway, thank you for listening. You can check out more about the project at Project Kluster dot org. And I am super happy and excited. Talk about technical stuff with folks about it.

I think we barely have time for one or two questions. Do you have any questions?

When people report the assault or whatever happens, do they report it anonymously or with their full information?

That is a great question. It is a confidential but not an anonymous system, which is pretty important. Right, because, yeah, all of that first mover advantage, disadvantage stuff has to do with people making reports into their own name. But this is a system for people to make reports under their own name.

Ok, and second question, when let's say two people accused the same person of something, you go into more detail of who gets notified, what information and so forth.

Sure. So the paper actually talks about this. It's it's sort of part of that bad actors section as well, ideally from like a game theory standpoint.

You want both reports to go immediately.

It turns out, A, there's a lot of consent issues about that. Right. Like, it's not really an ideal situation for anyone, for someone to get a phone call out of the blue to be like, I just got this report about something that happened to you a year ago. Also, security wise, that means us hanging on to decrypted all information. That's really pretty sensitive. So we have sort of we've come up with a compromise. I was going to say we've cut the baby in half, but that's not really fair to us. We've come up with a compromise where the school is notified that reports have been made about this person and they're given the contact information of the people who are reporting. But the control over the actual account of what happened, that control always belongs to the survivor. And that's a really important principle of what we're doing. And I'm to right now.

But we talked about after there's all sorts of interesting legal and jurisdictional implications of what a school is compelled to do if they have reason to believe that there is a serial perpetrator going around.

So, yeah. Any more questions?

Oh.

I enjoyed great talk. So, yes, going with the whole theme of like implementing this paper is not merely an academic paper and sort of following up on that question in the same way that like a database paper tells you to build a database that doesn't tell you the interface. How do you like figure out how to actually like someone comes on board? You need this information. I mean, it's the same like. Right. Like typical funnel problem.

Yeah. A bit harder. Yeah. And actually I feel like it's a whole nother conference talk. That I hope that my co-workers do about the interface to this system. The designer in the project manager and me have done some really interesting work on Tropp trauma, informed design and interview design. So these are sort of fields in of their own right. And I think that, look, there's a reason why we did this right. It's not just the information esca. We all live on the Internet and Colston's even more so live on the Internet. And we do a lot of our day to day life, both good and bad on the Internet. I'm thinking on interfaces for traumatic situations or sensitive situations, see situations where security is paramount, situations where people could potentially be re traumatized in a really dramatic way. It's it's a brave new world.

And there's it's yeah, I there's a lot of interesting stuff. I sure Germany were together and he knows that I am not a front end or UX expert, so I just take the mockups that I'm given and I'm blown away by them.

But yeah, I hope that we will be coming to a conference near you soon and talking about the UX of this because it's super important.

Thank you, guys.

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