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-[Elizabeth Davidson] 14:53:45
-Let's step back a minute. One of the things that I thought we might do in thinking about how to develop this paper, because I think we start with the Hicks paper.
-[Mike Chiasson] 14:53:54
-Mm-hmm.
-[Elizabeth Davidson] 14:53:54
-But use that as a very loose set of ideas and bounding and think, what is it that we want to do?
-[Elizabeth Davidson] 14:54:00
-what maybe a short-term project we could embark on is taking some
-[Mike Chiasson] 14:54:01
-Mm-hmm.
-[Elizabeth Davidson] 14:54:07
-some specific
-[Elizabeth Davidson] 14:54:09
-phenomenon and it probably should be related to AI, not only because AI is the current buzz, but because it really is
-[Mike Chiasson] 14:54:10
-Yeah.
-[Mike Chiasson] 14:54:13
-Yes.
-[Elizabeth Davidson] 14:54:17
-a big issue. And think about
-[Elizabeth Davidson] 14:54:21
-how it could be.
-[Elizabeth Davidson] 14:54:24
-what's happening here and how it might be otherwise
-[Elizabeth Davidson] 14:54:27
-what would it mean to actually participate
-[Elizabeth Davidson] 14:54:30
-in this now this is just not to say it's the right example at all, but it's something that
-[Elizabeth Davidson] 14:54:37
-I think brings up a lot of issues to me. It was an article about how
-[Elizabeth Davidson] 14:54:46
-In the US school system, a lot of states, even this state, which we have a statewide school system.
-[Elizabeth Davidson] 14:54:53
-the money for public education depends on the funding from the locale.
-[Elizabeth Davidson] 14:54:58
-So if you were in a high income
-[Elizabeth Davidson] 14:55:01
-high property value place, the property taxes provide more money the school system is better.
-[Mike Chiasson] 14:55:02
-Mm-hmm.
-[Elizabeth Davidson] 14:55:07
-if you're in a poor inner city
-[Elizabeth Davidson] 14:55:10
-very low. So there's various levelings that
-[Mike Chiasson] 14:55:11
-Mm-hmm.
-[Elizabeth Davidson] 14:55:14
-that the state governments will try to do to try to bring to indicate where
-[Elizabeth Davidson] 14:55:21
-supplemental monies are needed. And it often doesn't
-[Elizabeth Davidson] 14:55:24
-eliminate the gap that you try to bring it up somewhat.
-[Elizabeth Davidson] 14:55:28
-And even in Hawaii, where we definitely have different neighborhoods, but we have a statewide system, there's clearly differences because
-[Mike Chiasson] 14:55:29
-Mm-hmm.
-[Elizabeth Davidson] 14:55:36
-in schools in a school district where you have primarily kids from
-[Elizabeth Davidson] 14:55:41
-you know, more professional, educated
-[Elizabeth Davidson] 14:55:45
-parents, the teachers are happier there you know so it's hard to keep
-[Mike Chiasson] 14:55:50
-Mm-hmm.
-[Elizabeth Davidson] 14:55:50
-It's hard to keep teachers in the rural areas. So even if it's not a big funding difference.
-[Elizabeth Davidson] 14:55:55
-So anyway, that's the background that the state will come in and trying to a leveling of trying to improve
-[Elizabeth Davidson] 14:56:02
-this. And I think historically
-[Elizabeth Davidson] 14:56:05
-like how do you decide students are at risk? And they've used
-[Elizabeth Davidson] 14:56:10
-existing metrics.
-[Mike Chiasson] 14:56:12
-Mm-hmm.
-[Elizabeth Davidson] 14:56:12
-like
-[Elizabeth Davidson] 14:56:15
-We also have in the US like a school lunch system right that that uh
-[Mike Chiasson] 14:56:19
-Mm-hmm.
-[Elizabeth Davidson] 14:56:21
-And it's been problematic. Some kids don't have the money to buy the school lunch.
-[Elizabeth Davidson] 14:56:27
-And then you make the arguments are kids are hungry, they're not learning. Sometimes that lunch is the
-[Mike Chiasson] 14:56:28
-Mm-hmm.
-[Elizabeth Davidson] 14:56:32
-or if they have a breakfast program, that's the best way to get nutrition to low-income kids.
-[Mike Chiasson] 14:56:37
-Mm-hmm.
-[Elizabeth Davidson] 14:56:38
-So the metric is kids that qualify for subsidized or free lunch.
-[Elizabeth Davidson] 14:56:43
-So if you're sending your child to school
-[Elizabeth Davidson] 14:56:46
-And they said they are qualified for a free lunch.
-[Elizabeth Davidson] 14:56:50
-then that indicates that that's a metric.
-[Elizabeth Davidson] 14:56:54
-That's a category indicator that might reflect out broadly to many different things like
-[Mike Chiasson] 14:56:55
-Mm-hmm.
-[Mike Chiasson] 14:56:57
-Right.
-[Elizabeth Davidson] 14:57:01
-income of the parents.
-[Elizabeth Davidson] 14:57:05
-educational background to maybe
-[Elizabeth Davidson] 14:57:08
-maybe, you know, neighborhood, although sometimes depending on how things shift around you might have
-[Elizabeth Davidson] 14:57:13
-like in the United States, in Hawaii, I mean, we have this thing called geographic exception
-[Elizabeth Davidson] 14:57:18
-So if you could try to get your child into a school in a higher income area.
-[Elizabeth Davidson] 14:57:24
-But your child themselves might be at risk.
-[Mike Chiasson] 14:57:25
-Mm-hmm.
-[Mike Chiasson] 14:57:29
-Mm-hmm.
-[Elizabeth Davidson] 14:57:29
-in this metric so
-[Elizabeth Davidson] 14:57:31
-So the article that I read.
-[Elizabeth Davidson] 14:57:33
-related to how is AI coming into this and the state of nevada
-[Elizabeth Davidson] 14:57:37
-is using a private firm
-[Elizabeth Davidson] 14:57:40
-that is looking at
-[Elizabeth Davidson] 14:57:43
-student records.
-[Mike Chiasson] 14:57:44
-Mm-hmm.
-[Elizabeth Davidson] 14:57:44
-And they're using their own machine learning or
-[Elizabeth Davidson] 14:57:48
-proprietary algorithms
-[Elizabeth Davidson] 14:57:51
-to make assessments.
-[Mike Chiasson] 14:57:54
-Mm-hmm.
-[Elizabeth Davidson] 14:57:54
-about what is really at risk. And then, well, what is the outcome variable? So the at risk is failure to
-[Elizabeth Davidson] 14:58:01
-I don't know if it's failure to be promoted to the next grade
-[Elizabeth Davidson] 14:58:05
-for the younger grades of its failure to finish the degree so
-[Mike Chiasson] 14:58:06
-Mm-hmm.
-[Elizabeth Davidson] 14:58:10
-The idea is you want
-[Elizabeth Davidson] 14:58:12
-kids to graduate from high school because at least then they have the high school degree. But in order to get to high school, they have to get into high school, right? They have to progress through the lower grades.
-[Mike Chiasson] 14:58:20
-Mm-hmm.
-[Elizabeth Davidson] 14:58:21
-So I didn't have the details on exactly what the outcome variable was, but rather than using this
-[Elizabeth Davidson] 14:58:29
-higher level categorization of
-[Elizabeth Davidson] 14:58:32
-you know being uh
-[Elizabeth Davidson] 14:58:35
-being uh
-[Elizabeth Davidson] 14:58:38
-What was the word I used? Being eligible for subsidized lunch.
-[Elizabeth Davidson] 14:58:43
-They take…
-[Elizabeth Davidson] 14:58:44
-all these school records and who knows what those school records are, what combination of structured, unstructured data.
-[Mike Chiasson] 14:58:51
-Mm-hmm.
-[Elizabeth Davidson] 14:58:51
-what in the structured data, what categories are there
-[Elizabeth Davidson] 14:58:54
-They mush it up in their proprietary thing and they come up
-[Mike Chiasson] 14:58:57
-Yeah.
-[Elizabeth Davidson] 14:58:58
-with an assessment of this this child is at risk.
-[Mike Chiasson] 14:59:03
-Mm-hmm.
-[Elizabeth Davidson] 14:59:03
-So then the state says, well, we're not necessarily going to lower the amount of money that we're giving to this leveling, but now we're going to apportion it differently.
-[Mike Chiasson] 14:59:13
-Yes.
-[Elizabeth Davidson] 14:59:13
-And the effect has been like when they were looking at eligible for free lunch, they had in the state of Nevada, if I remember it right, had like 200,000 kids
-[Elizabeth Davidson] 14:59:23
-that were eligible for free lunch. So then they take however many money like
-[Mike Chiasson] 14:59:24
-Mm-hmm.
-[Elizabeth Davidson] 14:59:28
-say just $10 million.
-[Elizabeth Davidson] 14:59:31
-divide it by those kids and that money goes to the schools where the kids
-[Elizabeth Davidson] 14:59:34
-Cool. So a particular school might have like 20 of those kids, so 20 times 2000, that's what they have
-[Mike Chiasson] 14:59:39
-Mm-hmm.
-[Elizabeth Davidson] 14:59:40
-So under this algorithm, it went from 200,000 to 50,000.
-[Mike Chiasson] 14:59:45
-Hmm.
-[Elizabeth Davidson] 14:59:46
-And…
-[Elizabeth Davidson] 14:59:48
-So it was a great reduction in saying who is really at risk
-[Mike Chiasson] 14:59:51
-Mm-hmm.
-[Elizabeth Davidson] 14:59:54
-the money didn't go. So now those $50,000, rather than getting $2,000 per head, maybe you get
-[Elizabeth Davidson] 14:59:59
-,000 per head.
-[Mike Chiasson] 15:00:02
-Yep.
-[Elizabeth Davidson] 15:00:02
-So the pluses of this are that a school might actually get enough resources to do something.
-[Mike Chiasson] 15:00:10
-Mm-hmm.
-[Elizabeth Davidson] 15:00:10
-but you said in the article, they interviewed like different people. One was a principal and he said, you know, we used to have like
-[Elizabeth Davidson] 15:00:22
-identified kids, including kids that are literally homeless
-[Elizabeth Davidson] 15:00:22
-And now we have zero. Even the homeless kids didn't qualify as at risk.
-[Elizabeth Davidson] 15:00:28
-that another principal would say, yeah, you know, we used to have more, but now we have less, but we get enough money to actually do something.
-[Mike Chiasson] 15:00:31
-Mm-hmm.
-[Elizabeth Davidson] 15:00:35
-But here's the real kicker to me. So when people are saying, well, how are those
-[Elizabeth Davidson] 15:00:41
-decisions made
-[Mike Chiasson] 15:00:43
-Mm-hmm.
-[Elizabeth Davidson] 15:00:43
-it's not even the answer, well, who knows how AI works? It's all mysterious.
-[Elizabeth Davidson] 15:00:48
-It's like if that's proprietary
-[Mike Chiasson] 15:00:52
-Hmm.
-[Elizabeth Davidson] 15:00:52
-That's our proprietary algorithm. And we'll tell you generally, but we're not going to tell you how it comes up with those. You just have to accept it.
-[Mike Chiasson] 15:00:58
-Mm-hmm.
-[Elizabeth Davidson] 15:01:00
-So I saw a similar issue to this
-[Elizabeth Davidson] 15:01:03
-some time ago, before we were calling it AI, we were just calling it data analytics
-[Elizabeth Davidson] 15:01:08
-where in one, I think it might have even been the Houston school system
-[Elizabeth Davidson] 15:01:13
-Teachers were being fired based on an algorithm that would take in the test scores and other things about the teacher.
-[Elizabeth Davidson] 15:01:20
-And like, I think they actually had a policy that at any given year, you know, people, teachers would be rated great, terrible, and anybody in the terrible would get fired, right?
-[Mike Chiasson] 15:01:30
-Mm-hmm.
-[Elizabeth Davidson] 15:01:32
-they used to
-[Elizabeth Davidson] 15:01:33
-And they were using an algorithm to decide who was in the fire category. And they were firing teachers.
-[Elizabeth Davidson] 15:01:40
-based on this algorithm and the company refused to explain
-[Mike Chiasson] 15:01:44
-Mm-hmm.
-[Elizabeth Davidson] 15:01:44
-why and how a particular teacher was said to be
-[Elizabeth Davidson] 15:01:48
-should be fired and that they said that was proprietary and that there was a
-[Elizabeth Davidson] 15:01:55
-a court case i was
-[Elizabeth Davidson] 15:01:57
-I was reading this some time ago when i um it might have been as much as seven or eight, even 10 years ago, so I don't know how it came out. But the court case was about whether or not you could fire people based on test scores or fire teachers.
-[Elizabeth Davidson] 15:02:10
-It was a due process issue of
-[Elizabeth Davidson] 15:02:13
-if you can't explain to somebody how you came to the decision that they should be fired.
-[Mike Chiasson] 15:02:16
-Mm-hmm.
-[Mike Chiasson] 15:02:19
-Yes.
-[Elizabeth Davidson] 15:02:19
-then that's not due process because they were unionized. Now, of course, in
-[Elizabeth Davidson] 15:02:23
-if you're an employee at will.
-[Elizabeth Davidson] 15:02:25
-you can be fired for any reason, right? So you don't have those kind of protections. So I've always been a little bit interested in this
-[Mike Chiasson] 15:02:27
-Yes.
-[Elizabeth Davidson] 15:02:33
-issue of
-[Elizabeth Davidson] 15:02:35
-It's proprietary. Here's just this mysterious black box and we come up with a decision at X.
-[Mike Chiasson] 15:02:40
-That's right.
-[Elizabeth Davidson] 15:02:41
-And I think that this kind of thing is going to be
-[Elizabeth Davidson] 15:02:49
-applicable
-[Mike Chiasson] 15:02:49
-Yes.
-[Elizabeth Davidson] 15:02:50
-in many, many different areas from
-[Elizabeth Davidson] 15:02:52
-healthcare, like, you know, I'm getting to an age where I was talking to my doctor about
-[Mike Chiasson] 15:02:54
-Mm-hmm.
-[Elizabeth Davidson] 15:02:57
-you know getting like a colonoscopy because it's well you know you can do these pre-colonoscopies. So I said to well what do you think? She says, well, it's the gold standard. And she says.
-[Elizabeth Davidson] 15:03:06
-Plus at 75, we don't routinely screen people anymore.
-[Mike Chiasson] 15:03:10
-Hmm.
-[Elizabeth Davidson] 15:03:10
-So I said, okay, well, I'll go ahead and do it. But then I thought, so does that mean that after 75, you're at lower risk or that you're not worth the money?
-[Mike Chiasson] 15:03:13
-Yeah.
-[Mike Chiasson] 15:03:19
-Mm-hmm.
-[Elizabeth Davidson] 15:03:19
-But there's and I've been seeing this in the healthcare field increasingly when they weren't necessarily calling it AI, but doing analytics to predict
-[Elizabeth Davidson] 15:03:31
-behaviors predict outcomes and to decide who is worthy
-[Mike Chiasson] 15:03:36
-Mm-hmm.
-[Elizabeth Davidson] 15:03:36
-or not worthy. Now, sometimes if it's done in a positive way it's like
-[Elizabeth Davidson] 15:03:41
-decide who needs
-[Elizabeth Davidson] 15:03:43
-extra help as opposed to lesser help but you know there's there's been stuff in the US that's come out about
-[Mike Chiasson] 15:03:44
-Mm-hmm.
-[Elizabeth Davidson] 15:03:49
-they did this thing on how I think it was hard interventions and because black people are less likely to go to the doctor or get the care, they were considered to be lower risk when in fact they're by this algorithm, when in fact
-[Mike Chiasson] 15:03:56
-Yes. Mm-hmm.
-[Elizabeth Davidson] 15:04:02
-they die at a higher rate.
-[Elizabeth Davidson] 15:04:04
-So I was thinking that I don't know if that's
-[Mike Chiasson] 15:04:05
-Mm-hmm.
-[Elizabeth Davidson] 15:04:07
-the right issue, but I thought it was a really intriguing, it's a kind of an example where
-[Elizabeth Davidson] 15:04:13
-you think about there's so many things involved like the AI algorithm, how it actually operates
-[Mike Chiasson] 15:04:17
-Yes. Mm-hmm.
-[Elizabeth Davidson] 15:04:19
-Who controls that algorithm? What do we have a right to know? Who should have some input in this?
-[Elizabeth Davidson] 15:04:24
-What's the overall policy you know like it involves a number of things that
-[Mike Chiasson] 15:04:27
-Yes, it does, yeah.
-[Elizabeth Davidson] 15:04:29
-And, you know, when we think about the design of that AI algorithm.
-[Mike Chiasson] 15:04:33
-Mm-hmm.
-[Elizabeth Davidson] 15:04:34
-like one of our graduate students, Andrea is working with
-[Elizabeth Davidson] 15:04:38
-selfie show and my former student cave
-[Elizabeth Davidson] 15:04:41
-on this like the kind of ai you know how do you design ai algorithms uh
-[Mike Chiasson] 15:04:48
-Yes.
-[Elizabeth Davidson] 15:04:48
-ethically and um
-[Elizabeth Davidson] 15:04:50
-But I mean, that decision about designing an
-[Elizabeth Davidson] 15:04:54
-ethically like they're coming up with a framework, but it's here
-[Elizabeth Davidson] 15:04:59
-And there's this whole world around it. So I don't know if
-[Mike Chiasson] 15:05:00
-Mm-hmm.
-[Elizabeth Davidson] 15:05:03
-it would be, if you think it would be helpful if we took one or two examples like that and kind of parsed it out and then brought it back to what would this mean for
-[Mike Chiasson] 15:05:12
-Yeah, yeah.
-[Elizabeth Davidson] 15:05:13
-getting to design, what would it mean to participation and as a participation not
-[Elizabeth Davidson] 15:05:20
-only in the design of
-[Elizabeth Davidson] 15:05:22
-the artifact, but also in the design of
-[Elizabeth Davidson] 15:05:26
-the processes around it
-[Mike Chiasson] 15:05:28
-Yeah, yeah, no, no, those are very good examples. I mean, and very rich examples too right so
-[Mike Chiasson] 15:05:35
-I mean, it taps into the formal bias question which
-[Mike Chiasson] 15:05:39
-again comes up with Feenberg when he talks about people who end up, I call it, I use the expression in my head, end up on the wrong side of the category, right?
-[Elizabeth Davidson] 15:05:49
-Okay.
-[Mike Chiasson] 15:05:49
-Where they are deemed to be
-[Mike Chiasson] 15:05:52
-in a category that's detrimental to them, right? And that category has all sorts of political or resource financial implications. As you say, if you're under 75, suddenly you're in a category, but if you're over 75, you're not, right?
-[Mike Chiasson] 15:06:06
-basically cast on the ice flow and left to die as a result of an algorithm, right? So, I mean, to use the analogy, I guess, of the First Nations or the Inuit, right?
-[Elizabeth Davidson] 15:06:20
-Yeah, well, I have a feeling that they might like charge you with like something about you know like
-[Elizabeth Davidson] 15:06:29
-When we use that kind of an example, that's another, oh God, there's this really long article that's extremely
-[Mike Chiasson] 15:06:32
-Yes.
-[Elizabeth Davidson] 15:06:37
-thought-provoking. I just skimmed it this morning on
-[Elizabeth Davidson] 15:06:41
-diversity innovation diversity, equity, and inclusion at the University of Michigan and our system and especially at ann arbor
-[Elizabeth Davidson] 15:06:51
-And…
-[Mike Chiasson] 15:06:51
-Hmm.
-[Elizabeth Davidson] 15:06:52
-It was really…
-[Elizabeth Davidson] 15:06:55
-you know just things that are so embedded in our like like we don't mean anything harmful by it
-[Elizabeth Davidson] 15:07:01
-But we just say it and it's all of a sudden, you know, you're brought up on charges of being a racist or something.
-[Mike Chiasson] 15:07:02
-Mm-hmm.
-[Mike Chiasson] 15:07:06
-Oh, yes. Yes. Yes.
-[Elizabeth Davidson] 15:07:08
-Oh, my God. But yes, but I was going to, because I was going to follow up and say, well, when I'm on my ice ball, I'll try to keep a battery with cell phones so we can still chat.
-[Mike Chiasson] 15:07:16
-That would be good. That would be good.
-[Mike Chiasson] 15:07:19
-Yeah, but I think that formal bias piece is still there. I mean, you know, it might be a little remote, but as you dig back into Kant, there are views in Kant that there are things that only humans can do.
-[Mike Chiasson] 15:07:31
-And in his view, humans are the only ones who can be ethical creatures, right? I mean, to sort of boil it down to a simple
-[Mike Chiasson] 15:07:39
-a simple
-[Mike Chiasson] 15:07:40
-a simple view of his, right? And a part of it, I realized he was writing in the late 1700s. So maybe AI has advanced to a point where they can become ethical machines. But if you take his point of view that
-[Mike Chiasson] 15:07:53
-Only humans have the rationality to come to the ends.
-[Mike Chiasson] 15:07:58
-that should be achieved or should be desired, then we can't let the machines dictate it to us, right? Or at least certainly not explain how they managed to get to those outcomes in the first place.
-[Mike Chiasson] 15:08:09
-It's interesting that also Kant was quite critical of
-[Mike Chiasson] 15:08:14
-probabilistic ethics, right? So if then statements, he says, are effectively not ethics, right? So he comes to his categorical imperative, which is
-[Mike Chiasson] 15:08:24
-really kind of the golden rule, right?
-[Mike Chiasson] 15:08:27
-But she says that only any law can only any law that you developed has to be universally applicable for it to be
-[Mike Chiasson] 15:08:36
-an ethical position, right?
-[Mike Chiasson] 15:08:39
-So you can't come to a position which is detrimental to somebody else, right? So you can't simply assume an outcome that then causes harm elsewhere, right?
-[Mike Chiasson] 15:08:50
-And so there's a couple of things in that
-[Mike Chiasson] 15:08:53
-Which might be relevant to what we're doing, but maybe not. But it's certainly connected to Arant, who draws upon his critique of reflect of
-[Mike Chiasson] 15:09:00
-judgment, which Feenberg then draws upon in his work to argue his case for technical codes and for
-[Mike Chiasson] 15:09:09
-participation arising out of reflective judgment. It's actually Kant who came to reflective judgments, a critique of reflective judgment.
-[Mike Chiasson] 15:09:16
-which follows from his critique of practical reasoning, which is about ethics, which follows from his critique of pure reasoning, which follows empirical.
-[Mike Chiasson] 15:09:24
-critiques, right? And in it, he sort of argues a special place for humans that can only be dealt with by humans right so
-[Mike Chiasson] 15:09:33
-um which
-[Mike Chiasson] 15:09:34
-Again, may be relevant to this conversation, right, as we can talk about machines, whether machines can be ethically reasoned and be unaccountable
-[Mike Chiasson] 15:09:43
-Simply through their black box.
-[Mike Chiasson] 15:09:45
-No.
-[Elizabeth Davidson] 15:09:46
-So I'm thinking that maybe one thing that another thing we could do short term is maybe start a table of
-[Elizabeth Davidson] 15:09:53
-of terms and concepts, not all of which might end up in the paper but which
-[Elizabeth Davidson] 15:09:58
-might be things that we would want to employ in the paper or
-[Mike Chiasson] 15:09:59
-Yeah.
-[Mike Chiasson] 15:10:03
-Mm-hmm.
-[Elizabeth Davidson] 15:10:03
-talk through ourselves, even if they don't end up in the paper and like just like here's the concept here's
-[Mike Chiasson] 15:10:07
-Yeah.
-[Mike Chiasson] 15:10:10
-Yes.
-[Elizabeth Davidson] 15:10:10
-the kind of meaning or implications and here's the sourcing of it because that would be helpful to me because you've got
-[Mike Chiasson] 15:10:16
-Yeah.
-[Elizabeth Davidson] 15:10:16
-all of that stuff that your organic AI, all kind of like working around and like i haven't i haven't read can't and I'm sorry, I cannot commit to reading can't or I will commit to reading beanburg.
-[Mike Chiasson] 15:10:29
-Okay.
-[Elizabeth Davidson] 15:10:32
-at least some of Feenberg. But I mean, like, I feel like like you're like the organic AI and I'm your human centered interface.
-[Mike Chiasson] 15:10:34
-Yes.
-[Mike Chiasson] 15:10:41
-No, I appreciate that. I know I'm off in the clouds, right, which is helpful only to a small degree, right? But it's actually getting something on the ground.
-[Elizabeth Davidson] 15:10:49
-And so I think that's why it's fun to work together and to, you know, it's certainly educational and
-[Elizabeth Davidson] 15:10:57
-and enlightening for me to work with you.
-[Mike Chiasson] 15:11:01
-Yes.
-[Elizabeth Davidson] 15:11:01
-I said my goal is just to my contribution is sometimes just to
-[Elizabeth Davidson] 15:11:07
-to help you move from the clouds at least to get, you know, the tangible paper. But I think like um
-[Mike Chiasson] 15:11:09
-Yes.
-[Elizabeth Davidson] 15:11:15
-And if there are particular things or sections you think it would be valuable for me to read directly, we can. We've got about
-[Elizabeth Davidson] 15:11:23
-six months right we've got
-[Elizabeth Davidson] 15:11:25
-October, well, we're halfway through October, November, December, January.
-[Elizabeth Davidson] 15:11:29
-February, March. I don't know if it's, is it due early in March or later in March?
-[Mike Chiasson] 15:11:33
-Well, I actually had something which suggested that I might have been due in
-[Mike Chiasson] 15:11:37
-February, right? But I think it was a contradiction
-[Mike Chiasson] 15:11:41
-on the page itself.
-[Elizabeth Davidson] 15:11:41
-I think they ended up, yeah, well, we could clarify it with them, but I, you know, we have some time, but I think
-[Mike Chiasson] 15:11:47
-Hmm.
-[Elizabeth Davidson] 15:11:50
-where we ran into some problem, but unfortunately Dirk was interested in us coming with the Hicks papers we spent
-[Elizabeth Davidson] 15:11:57
-a lot of time, you know, we spent six months having a lot of really good, interesting conversations, but then we were kind of crunched with time to
-[Elizabeth Davidson] 15:12:04
-to get it into the paper format and then we had another opportunity to kind of
-[Mike Chiasson] 15:12:05
-Yeah.
-[Elizabeth Davidson] 15:12:09
-move it forward. And I think the way it moved forward really improved it a lot
-[Elizabeth Davidson] 15:12:13
-But I think we need to
-[Mike Chiasson] 15:12:14
-Mm-hmm.
-[Elizabeth Davidson] 15:12:16
-to think about maybe, I'm so excited you're coming to uh hicks
-[Mike Chiasson] 15:12:21
-Yeah, that's great.
-[Elizabeth Davidson] 15:12:21
-Are you going to bring the family or just you
-[Mike Chiasson] 15:12:24
-No, we looked into it. I mean, it's $5,000 just for me, right? So we decided it was just too expensive to get there this time around, right? And maybe with more planning and a little bit of advance, we could get it cheaper, right?
-[Mike Chiasson] 15:12:38
-So it is just me coming. It also turns out the conference is right when the kids start school. So we would have had to come earlier and then they fly back and then start the conference.
-[Elizabeth Davidson] 15:12:44
-uh…
-[Mike Chiasson] 15:12:48
-And then I didn't get the conference rate. I mean, I was waiting to figure out what to do with the family and then discovered all the conference rooms were taken up.
-[Mike Chiasson] 15:12:57
-So I booked, I booked something in the ocean tower, which is near it, but it's through
-[Elizabeth Davidson] 15:12:58
-Yikes.
-[Mike Chiasson] 15:13:02
-It's through like Airbnb as opposed to the conference group.
-[Elizabeth Davidson] 15:13:07
-It's probably…
-[Elizabeth Davidson] 15:13:09
-it's probably condos as opposed to
-[Elizabeth Davidson] 15:13:12
-So what dates are you going to, are you thinking of coming
-[Mike Chiasson] 15:13:13
-Yeah.
-[Mike Chiasson] 15:13:16
-Well, I think I already have it down. I think it's the fifth
-[Mike Chiasson] 15:13:21
-fifth through to the fifth through
-[Mike Chiasson] 15:13:23
-Let's see. I think I was there a day early, but then I'm there a day later than when the conference is. So I think it's about the fifth through to the
-[Mike Chiasson] 15:13:32
-th. So it's six days right
-[Elizabeth Davidson] 15:13:36
-And did you book a flight yet?
-[Mike Chiasson] 15:13:38
-Yep. Yep.
-[Mike Chiasson] 15:13:40
-Got that all working.
-[Elizabeth Davidson] 15:13:40
-So you're flying directly to Corona?
-[Mike Chiasson] 15:13:44
-Yeah, yeah, I think it's, I think on the way back, I have to go through Seattle, but on the way there, go through Vancouver.
-[Mike Chiasson] 15:13:51
-to Kona.
-[Mike Chiasson] 15:13:53
-I think that's what it was.
-[Mike Chiasson] 15:13:57
-Yeah.
-[Elizabeth Davidson] 15:13:57
-I'm not going to book my book.
-[Elizabeth Davidson] 15:14:00
-long strenuous 25-minute flight until
-[Elizabeth Davidson] 15:14:03
-closer. So what did you say that
-[Elizabeth Davidson] 15:14:06
-the fifth
-[Mike Chiasson] 15:14:07
-the fifth through to the 11th.
-[Elizabeth Davidson] 15:14:09
-. And then I think…
-[Elizabeth Davidson] 15:14:12
-Hexes.
-[Elizabeth Davidson] 15:14:13
-I did manage to book in the hotel. I have insider access to these things. I got to confess.
-[Mike Chiasson] 15:14:18
-Oh, very good. Yes.
-[Mike Chiasson] 15:14:21
-Yes.
-[Elizabeth Davidson] 15:14:22
-So I think…
-[Elizabeth Davidson] 15:14:28
-I booked from the 7th.
-[Elizabeth Davidson] 15:14:34
-to the
-[Elizabeth Davidson] 15:14:35
-th to the 11th. So you're coming in on Sunday.
-[Mike Chiasson] 15:14:40
-Yeah.
-[Elizabeth Davidson] 15:14:40
-Yeah.
-[Mike Chiasson] 15:14:42
-Oh, maybe it is the Monday. I should check. I'm just trying to pull it up on my screen here. I can't seem to find it.
-[Mike Chiasson] 15:14:49
-There'll be Kona. I also booked a
-[Mike Chiasson] 15:14:52
-a car as well so I could get around because it just seemed like it was complicated last time I was there to do that without
-[Mike Chiasson] 15:14:59
-without having a car around.
-[Elizabeth Davidson] 15:15:02
-I think a car is…
-[Elizabeth Davidson] 15:15:04
-you're going to probably have to pay to park it. That's going to be pretty expensive.
-[Mike Chiasson] 15:15:09
-Yeah, I think it's $48 a night or something, right?
-[Elizabeth Davidson] 15:15:11
-It's ridiculous. I think they're making like a ton of money just on parking these days, but I agree that a car is really useful. So I got to look at exactly what nights I booked at the hotel.
-[Mike Chiasson] 15:15:13
-It is, yeah.
-[Mike Chiasson] 15:15:20
-Hmm.
-[Elizabeth Davidson] 15:15:25
-But my time is…
-[Mike Chiasson] 15:15:26
-Mm-hmm.
-[Elizabeth Davidson] 15:15:28
-pretty open around there. So like, okay. But I think we should kind of look at that as an opportunity to really have some
-[Elizabeth Davidson] 15:15:40
-in-person time and see if we can
-[Mike Chiasson] 15:15:43
-Yeah.
-[Elizabeth Davidson] 15:15:44
-really maybe be working on like anytime you and I get together, we just have such fun talking to each other and
-[Elizabeth Davidson] 15:15:51
-exploring different ideas, we often don't get text out. But I think before that would be really great if we could
-[Elizabeth Davidson] 15:15:57
-got some
-[Elizabeth Davidson] 15:15:59
-you know use that as an opportunity. And that would give us then like another month or so to
-[Elizabeth Davidson] 15:16:06
-refine.
-[Mike Chiasson] 15:16:06
-Yeah. Yeah. I'd say my main purpose for coming is to have our conversation. I mean, obviously, it's nice to present too, but maybe catch up with some people I haven't seen for a very long time.
-[Elizabeth Davidson] 15:16:08
-the paper.
-[Mike Chiasson] 15:16:18
-But the main opportunity is to have a chat about the paper and things. And so that'd be great.
-[Elizabeth Davidson] 15:16:19
-Yeah.
-[Elizabeth Davidson] 15:16:23
-I think ultimately it'll be an easier trip for you than Bancrock, but I wish we were coming to Bangkok. Frederhausiederman enlisted me to be on this panel where he's all excited about futures research. And I'm like.
-[Elizabeth Davidson] 15:16:36
-Well, Mike would be much better on this panel than me, but he would be really good on this panel with me. So I'm having a little imposter syndrome for it, but it'll be fun enough.
-[Mike Chiasson] 15:16:42
-Yeah, yeah.
-[Elizabeth Davidson] 15:16:47
-And I just submitted something for a JIS
-[Mike Chiasson] 15:16:48
-It's great.
-[Elizabeth Davidson] 15:16:51
-development workshop. So I'd be curious to see if they'll
-[Elizabeth Davidson] 15:16:54
-But then at first, I'm a senior person. I can't do those. Those are for junior people. But then I said, I need help on this.
-[Mike Chiasson] 15:17:00
-Yeah, that's good. That's good.
-[Elizabeth Davidson] 15:17:01
-So I am going to Bangkok, but then when we get back.
-[Elizabeth Davidson] 15:17:06
-My future daughter-in-law
-[Elizabeth Davidson] 15:17:09
-kind of clarified that clarified
-[Elizabeth Davidson] 15:17:11
-she might want to go away somewheres with Brendan for over
-[Elizabeth Davidson] 15:17:14
-Christmas for a that the new thing is a baby moon as opposed to a honeymoon or baby moon before the baby actually arrives.
-[Mike Chiasson] 15:17:21
-Oh, that's good.
-[Elizabeth Davidson] 15:17:23
-Assuming that she's able to travel at that time. So the last couple of years we've descended on them at christmas so
-[Mike Chiasson] 15:17:24
-Yes.
-[Elizabeth Davidson] 15:17:31
-I'm starting to be extra cautious like she's starting to say, just because we're having a baby, don't think you're going to come and you know squat on our lies. I'm like, okay.
-[Elizabeth Davidson] 15:17:40
-So we're just going to go to LA for a week with Meredith and then come back here.
-[Elizabeth Davidson] 15:17:45
-So I will have some time between
-[Mike Chiasson] 15:17:46
-Very good.
-[Elizabeth Davidson] 15:17:48
-over the Christmas break, hopefully.
-[Elizabeth Davidson] 15:17:52
-So I think…
-[Mike Chiasson] 15:17:52
-Yeah. So it's actually the six. It's the six that come. So it is the Monday, I think, I think the conference starts on the 7th, doesn't it? I just wanted to make sure I was there so I didn't miss our presentation, which I don't think is scheduled in yet, right?
-[Mike Chiasson] 15:18:07
-No.
-[Elizabeth Davidson] 15:18:08
-Oh, no, it won't be. And then you're leaving on the 11th.
-[Mike Chiasson] 15:18:12
-Yeah, 11th. Not till the evening, though, like 1135. It's an overnight flight to
-[Mike Chiasson] 15:18:19
-Okay.
-[Elizabeth Davidson] 15:18:20
-Well, depending on
-[Elizabeth Davidson] 15:18:27
-R.
-[Elizabeth Davidson] 15:18:28
-If you're going to have a car, are you hearing me because I'm trying to get my
-[Elizabeth Davidson] 15:18:33
-Hands on it.
-[Mike Chiasson] 15:18:33
-Yeah, yeah, I missed you just a bit, but I hear you now.
-[Elizabeth Davidson] 15:18:37
-I'm trying to my headset is
-[Elizabeth Davidson] 15:18:40
-flights could go in and out.
-[Elizabeth Davidson] 15:18:43
-Although…
-[Elizabeth Davidson] 15:18:44
-I find people on the Big Island Drive, you know, drunk and crazy
-[Mike Chiasson] 15:18:49
-Hmm.
-[Elizabeth Davidson] 15:18:50
-So I don't particularly like driving on the big island
-[Elizabeth Davidson] 15:18:52
-But there's a lot to kind of explore on the big island too. The first time we had a hickson on the Big Island, Bill and the kids went with me and we did rent a car and we drove into, we flew into Hilo, drove and saw the volcano, Volcano National Park, and drove the south side.
-[Mike Chiasson] 15:18:57
-Yes. Yes.
-[Mike Chiasson] 15:19:04
-Hmm.
-[Mike Chiasson] 15:19:06
-Mm-hmm.
-[Elizabeth Davidson] 15:19:10
-And came up and then we went up into Waimea. Meredith and Bill have both spent a lot of time in that part of the Big Island when they were
-[Mike Chiasson] 15:19:11
-Mm-hmm.
-[Elizabeth Davidson] 15:19:16
-doing electronic health record things.
-[Mike Chiasson] 15:19:20
-Mm-hmm.
-[Elizabeth Davidson] 15:19:20
-But yeah, there's a lot of beautiful landscape
-[Mike Chiasson] 15:19:22
-Yeah, I've been to Hilo before, but I don't think we did get to the volcano because I think it was further down on the east side, right?
-[Elizabeth Davidson] 15:19:23
-And…
-[Mike Chiasson] 15:19:31
-But again, it was such a long time ago.
-[Mike Chiasson] 15:19:34
-I think, yeah.
-[Elizabeth Davidson] 15:19:34
-I just got there. I just got there this summer again for the first time in like 30 years when my great niece was here and
-[Mike Chiasson] 15:19:43
-Hmm.
-[Elizabeth Davidson] 15:19:44
-it was interesting because it constantly changes. And the very next day it was the part of the park was closed down because they were having a little bit of rumbling and
-[Mike Chiasson] 15:19:51
-Mm-hmm.
-[Elizabeth Davidson] 15:19:51
-A little bit later, there was some stuff squirting up and
-[Mike Chiasson] 15:19:55
-Yeah.
-[Elizabeth Davidson] 15:19:55
-Yeah, it is interesting. So I will take that into consideration as well. And I'm really looking forward to
-[Mike Chiasson] 15:19:59
-Yeah.
-[Mike Chiasson] 15:20:02
-Hmm.
-[Elizabeth Davidson] 15:20:05
-being there. And I think we can have some good conversations with Dirk too i think he's and others in the mini track
-[Mike Chiasson] 15:20:09
-Yeah.
-[Mike Chiasson] 15:20:13
-Yeah, I think that'd be good.
-[Elizabeth Davidson] 15:20:15
-So.
-[Mike Chiasson] 15:20:15
-I think there's two there's two sets of three, right? So I think there's two sessions with our group.
-[Mike Chiasson] 15:20:22
-So that'll be good from what I understood.
-[Elizabeth Davidson] 15:20:24
-Oh, yeah, I haven't seen any kind of a schedule or anything yet, so I don't know.
-[Mike Chiasson] 15:20:31
-Okay.
-[Elizabeth Davidson] 15:20:31
-So let's think about a regular time to talk, though, if possible. Regular helps me because I'm
-[Mike Chiasson] 15:20:37
-Yeah.
-[Elizabeth Davidson] 15:20:39
-often scattered.
-[Mike Chiasson] 15:20:40
-No, it helps me too, right? So again, this time
-[Mike Chiasson] 15:20:47
-Over the next couple of weeks works.
-[Mike Chiasson] 15:20:49
-the two o'clock, which would be 11 for you. Although actually we fall back so
-[Mike Chiasson] 15:20:54
-When do we fall back? Doesn't matter. I could still do one o'clock my time, which would still be 11 your time.
-[Mike Chiasson] 15:20:59
-Even after we fall back.
-[Elizabeth Davidson] 15:21:03
-So that works for me next week, the 30th.
-[Mike Chiasson] 15:21:08
-Mm-hmm.
-[Elizabeth Davidson] 15:21:09
-On the sixth, I'm going to be flying, I think, because I'm going to something in California.
-[Mike Chiasson] 15:21:16
-Mm-hmm.
-[Elizabeth Davidson] 15:21:17
-But I could do the
-[Elizabeth Davidson] 15:21:20
-election day, I might need a major distraction. I might also be like
-[Elizabeth Davidson] 15:21:28
-trying to uh trying to
-[Elizabeth Davidson] 15:21:30
-to keep sanity through
-[Elizabeth Davidson] 15:21:32
-alcohol or something, I don't know.
-[Mike Chiasson] 15:21:32
-Yes. Yes, yes, on the sixth stamp.
-[Mike Chiasson] 15:21:36
-Hmm.
-[Elizabeth Davidson] 15:21:36
-But other than that, this state
-[Elizabeth Davidson] 15:21:39
-And time looks pretty good.
-[Mike Chiasson] 15:21:41
-Okay, I'll send you a note then with
-[Mike Chiasson] 15:21:44
-with a kind of repeating pattern and we can toss out ones that don't work for either one of us, but I think they work for me for the most i think
-[Elizabeth Davidson] 15:21:50
-you know.
-[Mike Chiasson] 15:21:53
-Great up until December.
-[Elizabeth Davidson] 15:21:55
-So between now and then, if you have some time, I think
-[Elizabeth Davidson] 15:22:00
-One of the things that would be helpful for me is if you just started drafting, like these are some of the key concepts that
-[Mike Chiasson] 15:22:05
-Yeah.
-[Elizabeth Davidson] 15:22:06
-you think will come together
-[Mike Chiasson] 15:22:09
-Yeah.
-[Elizabeth Davidson] 15:22:10
-And did you, Xeralto, what is it called is it
-[Elizabeth Davidson] 15:22:14
-Zatoro?
-[Mike Chiasson] 15:22:16
-Oh, yeah, yeah, yeah. Zotero, yes.
-[Elizabeth Davidson] 15:22:17
-Yeah, you invited me to the Zatoro thing. I've now lost track of it, but it didn't seem to have any papers in it. Did you have a
-[Mike Chiasson] 15:22:24
-Oh, it should have it in now, right? So if not, just let me know.
-[Elizabeth Davidson] 15:22:29
-Let me see.
-[Elizabeth Davidson] 15:22:32
-Is that Zorato?
-[Mike Chiasson] 15:22:34
-So tarot, so tarot.
-[Elizabeth Davidson] 15:22:37
-Zeo.
-[Elizabeth Davidson] 15:22:39
-P-A-R-O.
-[Mike Chiasson] 15:22:39
-T-E-R-O, yeah.
-[Elizabeth Davidson] 15:22:41
-Let me see if I can get back into password reset. Oh my God. He wants me to have a password.
-[Mike Chiasson] 15:22:46
-Oh, no. Reset, though.
-[Elizabeth Davidson] 15:22:49
-Thank you.
-[Mike Chiasson] 15:22:49
-Yeah.
-[Elizabeth Davidson] 15:22:51
-I…
-[Elizabeth Davidson] 15:22:53
-I have a Dropbox password, apparently. I've got all my little notes here.
-[Mike Chiasson] 15:22:58
-I think the one good thing about Zotero is it opens up the PDFs and you can see all my markings in it and it highlights it off to the side. So it's handy that way, right?
-[Mike Chiasson] 15:23:09
-for reviewing articles and stuff. But if it becomes too much of a pain we can
-[Elizabeth Davidson] 15:23:14
-No, no, no. I just…
-[Elizabeth Davidson] 15:23:17
-it would be fun.
-[Elizabeth Davidson] 15:23:20
-Sometimes I hate Google Mail.
-[Mike Chiasson] 15:23:23
-Mm-hmm.
-[Elizabeth Davidson] 15:23:23
-That's, you know, our university uses it.
-[Elizabeth Davidson] 15:23:28
-Let me see.
-[Elizabeth Davidson] 15:23:34
-I will have no idea what my
-[Mike Chiasson] 15:23:40
-And you get a reset from it. Let's see.
-[Elizabeth Davidson] 15:23:44
-What would my password be? I'm sure I can, but what would it be? Oh, I think I see it written here.
-[Elizabeth Davidson] 15:23:56
-Let's see if that works.
-[Elizabeth Davidson] 15:24:01
-invalid credentials. Try something.
-[Mike Chiasson] 15:24:03
-Oh, no.
-[Elizabeth Davidson] 15:24:14
-Oh, I forgot a dash probably.
-[Mike Chiasson] 15:24:17
-Oh, okay.
-[Elizabeth Davidson] 15:24:20
-Let me see if this is going to work.
-[Elizabeth Davidson] 15:24:24
-Nope. One more time.
-[Mike Chiasson] 15:24:26
-No? Okay.
-[Mike Chiasson] 15:24:27
-there is a forgot your password link, I think, on it too so
-[Mike Chiasson] 15:24:45
-Just while you're doing that, I remember way back in the 90s when they were looking at artificial intelligence, but I think the symbolic logic kind.
-[Mike Chiasson] 15:24:54
-that exact bambis out and a few others looked at explanation systems that basically allowed you to
-[Mike Chiasson] 15:25:02
-go back and uh
-[Mike Chiasson] 15:25:05
-have an explanation of how a symbolic logic system reached its conclusion. I think it was kind of functionally to improve
-[Mike Chiasson] 15:25:14
-people's confidence in what
-[Mike Chiasson] 15:25:16
-was obviously in Ezac's mind the best outcome right but
-[Mike Chiasson] 15:25:21
-But there was a certain research to try to increase the credibility by explaining itself, right?
-[Mike Chiasson] 15:25:28
-I think more and more with these deep learning systems.
-[Mike Chiasson] 15:25:32
-these algorithms come back with things that even the designers don't know how it got to it.
-[Mike Chiasson] 15:25:38
-Which is what's a little on, which is hard for us to up to
-[Mike Chiasson] 15:25:44
-both pragmatically used, but also ethically to use as well. If a thing breaches a conclusion, how do we know how it got there?
-[Mike Chiasson] 15:25:52
-And why?
-[Elizabeth Davidson] 15:25:54
-I have had to…
-[Elizabeth Davidson] 15:25:58
-give up on the notion of understanding technology action sometimes.
-[Elizabeth Davidson] 15:26:05
-I'm just trying my new password to see if it will work.
-[Mike Chiasson] 15:26:08
-Okay.
-[Elizabeth Davidson] 15:26:14
-Okay, now there's all kinds of things in here. Okay.
-[Mike Chiasson] 15:26:17
-Yeah, I'll keep adding to it as well, right?
-[Elizabeth Davidson] 15:26:20
-Okay, so I'm going to, by next Wednesday, I will look through some of these to get better sense of where you are. You will…
-[Elizabeth Davidson] 15:26:28
-kind of either do like a little table or a little bit of kind of
-[Mike Chiasson] 15:26:31
-Yeah.
-[Elizabeth Davidson] 15:26:32
-bullet pointing of some of the key things that you would like to
-[Elizabeth Davidson] 15:26:36
-see addressed or you think would be relevant in the paper?
-[Mike Chiasson] 15:26:40
-Yeah, that's right. Yeah.
-[Elizabeth Davidson] 15:26:41
-Okay, so let's just keep that as our specific goal for next week.
-[Mike Chiasson] 15:26:42
-Yeah.
-[Mike Chiasson] 15:26:46
-Yeah, and I'll try to take out how to recruit volunteers to a church organization. It was an article that ended up in our design folder here.
-[Elizabeth Davidson] 15:26:55
-All right.
-[Mike Chiasson] 15:26:57
-Okay, great to chat, Liz. Yeah, I appreciate it.
-[Elizabeth Davidson] 15:26:58
-All right. It's good to see you. Good to see you too. I'm looking forward to getting into this. Just to let you know, my password that I thought I had, I just had the wrong
-[Mike Chiasson] 15:27:01
-Say hi to Belle.
-[Elizabeth Davidson] 15:27:09
-the wrong special characters. MikeDesign, 25.
-[Mike Chiasson] 15:27:12
-Oh, okay. Okay. Oh, wow. That sounds…
-[Elizabeth Davidson] 15:27:14
-I said, what else could that be the password for except