Welcome, everyone. This panel is part of a series from ACM DEI Council and we have a series of panels that we have been running for various awareness and heritage months, and this is one of the parts of that series. And basically, the title of that is to celebrate, embrace accessibility, and the contributions from researchers with disabilities. And so with that panel today joining us are a group of researchers and academics as well as those from industry who will be able to share their experiences and current work as well as their insights into the future kind of viewpoint of accessibility as technology and innovation moves forward. And so I wanted to introduce the panelists for today, and as I introduce them, well, I will do a quick introduction of each of them and then they will go through and introduce themselves for a few minutes. But the general overview of this is that we'll have some panelists introductions.
We have a set of questions that we have, and then afterwards we will have some time for questions from the audience. And the panel will last about an hour. So I will start with Dr. Shaun Kane. He is joining us from Google. Then follow is Dr. Raja Kushalnagar from Gallaudet University, as well as Dr. Rua Mae Williams from Purdue University. And I as your moderator, Dr. Stephanie
Ludi from the University of North Texas. Thank all of you for joining us as panelists today. And so I wanted to start with you, Shaun, if you could briefly introduce yourself. Sounds great, yeah. So hey, everybody. I'm Shaun Kane. I'm currently a Research Scientist
at Google Research and working in the general area of responsible AI and disability. To say a little bit about my background, so I've been an accessibility researcher my entire career. I actually grew up with a disability that affects my motor abilities. And one side effect of that I think that you might see coming up when I talk about my work is I've pretty much always needed to figure out different ways of performing tasks and solving problems. I did not plan to go and follow the accessibility career route. I started to get very interested when I was an
undergrad in accessibility from a creativity and design perspective. So one project I remember fondly is I was at an engineering expo and saw a demo someone made of a wheelchair accessible blacksmithing station. And I was just really taken by the creative work to do that, you know, to solve that kind of problem. So my grad work was in human computer interaction with a focus on accessibility. A lot of my early work was related to touchscreen accessibility for blind and low vision users. But through my career I've worked across different
disabilities and different technologies based on where I've seen the greatest need or opportunity. I've also had the privilege of working in a few roles in academia and industry. Like I said, I currently work at Google Research as a research scientist and my team at Google focuses on taking a socio-technical perspective on technology. Right now much of that work is about generative AI. And since I work largely in the area of accessibility, much of my current work is focused on how to understand and measure ableism in generative AI models and to measure disability inclusion, and also how to bring users with disabilities into the process of designing systems that include AI. Great, thank you. Raja?
Hello, my name is Raja Kushalnagar, I'm a professor at Gallaudet University, I actually don't know how to pronounce my last name, it's actually totally fine. The interpreters often don't know how to pronounce my last name. I just emphasize the most important thing, the one way for accessible information and for communication. You know, one way is via voice, one way is through sign language or captions. Important is to get that information across. So this is just one example of how my personal experience actually informs and shapes and designs my work. So basically I got in through basic technology, growing up, I was born deaf. My parents enrolled
me in a small private school, but it was a low instance occurrence for deaf students at that school. I was the only deaf student there at the entire school. Mainstreamed. Small set of friends, small set of teachers. So that was the kind of accommodations I got used to, I was able to understand the context because there was a small group of people around me. So I was doing good on all of my work assignments and that was fine. I then decided to go to a big state university,
UC Berkeley. Because of the larger size school, I started to get lost. I had As, and then I had Bs, and then I had Cs, which turned to Ds. More and more information was getting lost because the accommodations were not working for me. So as you know, information starts to get lost, it starts to then ramp up your abilities or disabilities. And so I got to a point where I
just couldn't continue and I decided to actually transfer to a smaller university, with much less student body. I had similar friends, similar group of teachers, similar to what I had in my high school experience. And that actually worked for me as well. So I graduated and I realized, you know, accessibility, those certain accommodations don't work for me so I need to figure out what I'm going to do and how is that going to help me access accessibility services in my workplace. So I decided to, after working a couple of years in software development, I was a software developer, I decided to go back to school to start doing some research and that's where I started my first research on medical imagery. But I realized that wasn't quite exactly what I was looking for. I wanted more of a challenge. And so I wanted a little bit more information
and doing some more research on accessible communication technology. So switching fields, I've switched there and I've been in this field now for the past 15 years. I think a lot about design and people who are deaf, hard of hearing, blind, low vision, and what does it mean to have information and communication be accessible via technology and have that translated or applied in their most appropriate language. So I have been in academia through a variety of different locations,
started at one university, then moved on to Gallaudet University, which is a deaf and hard of hearing college in Washington DC focusing all on design and technology, focusing on like the UI and now actually shifting gears towards AI, and allowing us different ways to use technology for information and communication sharing. Great, thank you. That's it for me.
Rua Mae? Hi, I am Rua Williams and I still get confused when people say doctor, I'm like, who are they talking about? And my research is in the area of technology and research ethics for disabled people and disabled ways of making technology. My academic pathway was always very non-direct. So I had multiple minors in undergrad. I also almost failed out of college when I first got there, I was on academic probation, and after undergrad I went to work in the video game industry and I made games for a number of years and then I only got my master's degree because I needed it in order to be an instructor at the University of Florida. So in order to teach graduate students how to make games, I had to have a graduate degree. So I got one. And then after that I had no intention of going to get my PhD, but it happened anyway. And I didn't ever intend to go into accessible technology or anything related to disability either, I was going to do things related to science communication and things like I had an interest in fisheries and aquatic sciences, basically like ecological sciences and the way that we don't have a strong public grasp of what's happening to our planet. Instead, what happened was I began, for various reasons, reading
the human computer interaction research as it related to treatment for autism. And this was very personal for me because there's a family history of institutionalization for members of my family, my children are diagnosed with autism and ADHD and I also have a diagnosis of autism and ADHD. And as I read this work, I really struggled with the way that the discipline I was supposed to be going into was talking about my family and I just couldn't put it down. I couldn't stop looking at the way that we, even in research where we think that we're helping people, we're saying terrible things about them. And so that started me looking at basically the reform of research practices in relation to accessible and assistive technology and people don't like it, and I'm here now, okay. Alright, thank you. And I'll just say just a couple quick words about myself. So my
name is Stephanie as I mentioned before, and I'm legally blind, visually impaired, which means I have some vision and since birth I was mainstreamed, as some of the panelists also mentioned, having had very few accommodations in going through K-12, I actually found in my case when I went to university that I had more accommodations available to me. It was kind of ironic, but it still made computer science very difficult actually starting computer engineering. And I just found computer science was more aligned with my interests. My dream, even though I am not a part of that effort, was to have a self-driving vehicle just because I'm not able to drive. So it's wonderful seeing that come from the work that people are doing today. My work, my interest is in computer science education broadly, however, I have done a lot of work related to computer science education, pre-college or afterwards, as well as those who are developers in industry who are themselves blind and visually impaired. So that's kind of where my work has gone in terms of research. And with that I have also held, like some of the other panelists,
other academic positions. So in addition to being a professor, I have also been associate chair, interim chair, and I'm currently associate dean for the college that I'm in. And so with our various perspectives, we have a small set of questions that I wanted to read. So I'll read them one at a time and we will be calling on the input from each panelist. And so I will refer to
each panelist by name so that way they know the question, that it's their time. Question one is, what are examples of persistent challenges in accessibility? With these challenges, what do you view as the biggest opportunities for positive change? And I wanted to start with Shaun. Right, yeah, so this is a great question. I would say, as I was thinking about this, one persistent challenge that I see is that we are constantly creating new accessibility problems, which is probably good for the careers of the people on this panel, but might not be worth it in terms of impact on people. I think the fundamental ways that we tend to develop technology, we being everybody is one that creates accessibility problems. So it means every advance in technology or every new implementation of a technology, we can expect that there'll be some accessibility problems there. I think it's also normalized to some degree
that the first version of a technology won't be completely accessible and that accessibility can be added later. So this perpetuates the same accessibility problems, but it's also true that people with disabilities are often early adopters of technology. And so if we don't get the accessibility piece right at the beginning, then we might be missing out on that opportunity. And so, technology's moving so rapidly right now, if we're not doing this right, then people with disabilities might be excluded from the advances and won't be able to give critical feedback until it's a lot harder to fix problems. In terms of the biggest opportunities, I would say awareness of accessibility has grown over the past decade and before that probably. When I've taught courses in the last few years, you know, students often already have an awareness of what accessibility is and they're excited to try and solve accessibility problems.
I think the field of accessibility research has also grown a lot, both in size but also diversity of approaches. And so like when I was new to the field, it seemed like everyone was essentially a technologist who saw their work as creating new technologies or creating fixes. Now I think we have researchers who take a more critical approach or researchers who focus on the intersection of tech and policy, and that creates a lot more opportunities for improving accessibility. Great, thank you. Raja? Yeah, I agree with Shaun. I think that the technology is obviously evolving and changing.
It creates new barriers or potentially new opportunities. And I think that it has improved since, you know, the involvement of people with disabilities in this field throughout the entire process through design development and building creation, which I think is critical. I think if we look at like 100 years ago, for example, movies, you know, they didn't have audio technology people who would basically, that's why we had silent films and then deaf people had full accessibility equivalent to their hearing counterparts because there was no sound. And so then they could just watch the film. Then they added technology. And so within a couple of years the entire movie
industry became spoken films. And so a lot of deaf people didn't have access to films, they lost that opportunity, and technology, then they started adding captions, but obviously they were not implemented immediately. This is over a course of 50 years now of implementing captions. You know, people are writing beautiful dreams of different scripts and wanting to add captions into movies, but they didn't happen until much later. And so now, in our current age, we now have with
different audio engineers and different people in technology, we have different people who are actively thinking about how to make technology more accessible for the greater audience and really thinking about it from day one and getting people with disability involved from the get go. But to be honest, there's still more room to grow, there's still a lot more, we're just really at the cusp. So we're still seeing barriers and challenges. Hopefully we don't have to wait another 50 years for technology to then catch up and to address some of these barriers. Thank you. Rua? So I write a lot about the disconnect between what we do as researchers and what disabled people want and need. But another really major problem that I've begun focusing on is the disconnect between
what researchers are making and what policy allows disabled people to access. And so it doesn't matter whether or not we're making things that are aligned with disabled people's desires, they can't get it either way. So we continuously make these projects and make our careers off of these projects that it's not even that we're making bleeding edge technology that won't hit consumer markets for 20 years, it's that that stuff will never make it through the medical industrial complex in the way that it has controlled the bodies that disabled people can have. And so this is a major problem in assistive and adaptive technology, but it's also a major opportunity for researchers to begin not only using user-centered and participatory and community-based methods, but to integrate within those policy analysis and advocacy schemes within their research agendas so that the things that they are building and making with community are actually going to change the policy landscape in such a way that people can actually access the technology that they want. So those are the things that I am focusing on most recently is basically the different ways to both change and circumvent the kinds of policies that are just posing as barriers to disabled autonomy. Great, thank you. And before we move on, I just wanted to mention just a couple other
items that kind of go along with things raised by the panelists. And one is that one thing that has been fairly persistent at times in terms of how that manifests might be a little different is the societal expectations of persons with disabilities. There certainly have been difficulties and challenges in terms of being able to get like opportunities to be able to pursue various types of educations. And I'm speaking from a global standpoint, not just a a US-centric one.
And other challenges certainly can go along with that in terms of employment just because, not just in the US but certainly globally, the unemployment rate of persons with disabilities is very high and it can change between different groups of persons with disabilities, but just speaking generally, which can lead to income disparity issues which can then translate into issues with being able to purchase or otherwise acquire different technologies that are being developed or are being introduced to the market. So sometimes there can be challenges there that do persist, but again, those kind of cross a bit outside of the computer science and computing fields but are just relevant just because they do impact those that would use or be able to appreciate what is being researched or introduced by the market in terms of industry. And so those are certainly challenges. Will they change? I think in time probably ebbs and flows, there are probably a lot of things related to policy as well as other issues. But I just wanted to note that
is one aspect of challenge that sometimes is not aware by most people, especially when one doesn't have a friend or are otherwise affected by the community in terms of various challenges that people have. And so I just wanted to mention that, which would kind of go into our next question. So what trends in accessibility research do you view as having great potential to facilitate greater access to information services and activity? So with this question, I wanted to start with Raja. Okay, I would say let's start with generative AI. I think that
has been a game changer for really all people, which does include people with disabilities like image description, using simplified English translations. But still obviously there's a lot of other portions of like context and bias that needs to be addressed. Making sure that the design fits people with disabilities, and just raising the bar for everybody and not just thinking about everything on a level playing field but just raising the overall accessibility of it. So that's my thought on that. Great, thank you. Rua? I love and appreciate Raja, but I strongly disagree with the idea that generative AI is facilitating information access. It is, in my opinion, causing a significant amount of
degradation of the reliability of information for all people. And I think that disabled people are the most vulnerable to the kinds of misinformation that generate AI spits out. There's basically no, it's not even just a matter of eventually tweaking the database and tweaking the learning algorithms, it is not capable of producing the truth the way that the methods are used. On the other hand, what has proliferated more beneficial information has actually been social media. And then this is not accessible technology research per se. However, the way that we study, the way that people form communities and online spaces has led us to understand these kinds of knowledge transfers better. But the way that disabled people can share with each other, basically life hacks has been transformative for a number of people. And also for some people,
particularly those who have conditions that are more resistant to medical validation, let's say, that they can find people who at least experience the same things and they know quote, unquote, "they're not crazy." Now that's not to say that I don't believe that there are going to be potentials of kinds of like algorithmic decision making supports. I just think that we're currently doing them very, very poorly and it's very, very concerning 'cause right now the algorithmic decision-making supports that we have are directly leading to the deaths of disabled people every day. So I am very mean about AI and I apologize. Next. Well, we might delve a little bit more into this one and I just wanted to make sure Shaun also had his shot to input on this.
Alright, I'm so excited for there to be some spice in the conversation. I mean, I think it's great to be having these conversations. Yeah, I mean, I wrote some, took some notes around generative AI, obviously I think it's an area that everybody is talking and thinking about and to Raja's point, I would say, when I talk to people about some of, kind of where we are now, I think of problems that if you went to an accessibility research conference even like maybe three or four years ago, people would say like, we're nowhere close to where we are now in terms of things like image description, even things like sign recognition, that there's progress happening in those spaces. That's not to say that it's a panacea or that it is good enough, right? I mean, I think there's a bigger picture question of how do we make sure that we build systems the right way and don't use this as a way to decide that we don't have to care about people with disabilities or that they can solve the problems on their own. You know, I use the example of captioning and image. Well now actually AI systems can generate image captions, as Rua points out, there might, we should be very careful in how we interpret that and what kind of oversight we might do for that. But there's also an AI caption image is probably gonna be quite
different than what the original creator might have captioned. And so the quality could be lower. You know, I'm personally wary of the idea that, that AI will mean that people don't have to think about disability or that there's this narrative of, well, when we have AI, we're not gonna have to deal with this problem anymore. And so when I talk to folks about generative AI and disability, I try to frame this as a way to potentially do that work better, about to give an example around image captions, I mean, in alt text, I've talked to so many people who are researchers who like, oh, I wanna put alt text in my images for my paper and I don't know how to do it and I'm not confident about it. And I see that as a place where maybe there's an opportunity to give some nudge, right? Or even if it's helping people learn how to do more themselves. I think as both of my co-panelists have pointed out, I think we need certain societal structures and expectations in place to make sure that we're able to leverage that. The last point I would make, I would say
in as much as I have a position about this as a researcher, I see value in leaving making some of these trade-offs up to people with disabilities. So I've had quite a few conversations with folks, just personal conversations recently, other disabled people saying like how often do you get advice from a physician that's bad or that you have to add a level of scrutiny to or a level of interpretation to. And so to say, often we are used to not trusting the output of systems and obviously that's not true for everybody and there's a lot of skills that need to go into that.
But I hope, as these conversations move forward, we have a place to say, how do we take intentional risks and allow people to take intentional risks if there's a potential benefit to that? Does anyone else want to follow up? I just remembered and I just wanted to point out one of the major problems that I have in even coming up with examples and supports for people to basically learn how to argue with AI, right? Learn how to, relies on kind of feeding that beast. And when I think about the resources that are required to run generative AI right now, I kind of start to like panic and I can't even bring myself to build those resources for people because they require basically me to dump gallons of water into the ground. Like, and so one of the reasons why I wanted to bring that up is that when climate crisis accelerates, not only will it disable more people, but the people that our political structures will intentionally leave to die are the disabled people. And so it's always been tricky for me that so many people in assistive and accessible technology have this interest in a technology which is demonstrably terrible for the environment when those consequences will be felt the most by disabled people. Raja, did you wanna add anything? Yes, I think generative AI does have a potential to disclose people with disabilities. I think there's definite lack of representation within the model itself. I think, you know,
it can be harmful unless people are thinking about it in a creative space. I think there is also, it can potentially help independence sometimes in some ways depending on, obviously your disability, I think it's one step forward, one step back, with automatic captioning, that was a game changer for some individuals, but it doesn't necessarily understand me. It still leaves me behind. And so obviously it's a mixed bag of things and I suspect that that's going to be true for all. And again, how to kind of just raise and elevate for everybody and get everybody a sense of equality using technology.
Well, thank you all. It just shows you that any topic and certainly generative AI is one really great example of this. That there's a lot of different facets and a lot of depth to this topic that it isn't just one straight and simple answer. It's something that will be ongoing in terms of the conversation, in terms of implications, not just for the people that use it as diverse of a group as that is, but also in terms of resources, and how it's generated, the technology involved. And those conversations certainly are
being held in other areas as well for particular occupations, for example. So it just shows you that that conversation is not as simple and it's not going to be something that is a quick one, it's something that needs to be ongoing and to really include everyone. And so that's why having diverse groups that are part of the conversation is so critical at all levels. So kind of talking about different aspects of this conversation, whether it be generative AI or other, I just going into question three, what differences do you see in accessibility research conducted in academia and industry? So that could be things that are in common, things that you see as different. And so I wanted to start with Shaun, since you are currently at Google. All right. Yeah, this is a question that I hear often as someone who has bounced back
and forth a little bit. Just to start with a comment, a thought, so when I was a professor, one of my deep sources of frustration was that we were doing research that I saw as important and we would write a paper about it and often that would be the end of it. And I always felt it was really hard to do anything beyond that. And I've spent a few years in industry now and find kind of a similar end result, but often for different reasons, right? I mean, I think it goes back to these, the broader issues of societal structure and to what degree does both like our society and the technology infrastructure that we use support people who do things differently or people who have different perception on the world. And I think there are a lot of factors there that just make it really hard to make things better, right? And obviously we could go to a whole discussion of what that would even mean, but so I think where there are shared challenges, right, and I hope that we come back to having shared goals about really wanting to make things better for people and to empower people. In terms of industry versus academia, I often say we should reject the binary of academia versus industry because every job, every project is different. I also strongly
encourage people to seek partnerships going in both directions. You know, if you're faculty, I think it's great to seek opportunities in industry to understand the challenges that folks in industry experience. Likewise, I'm thinking a lot about how to better connect with academics. To answer, give a partial answer to the question, one difference that I see, again, based on my own experiences is when we say industry, we often mean a very specific and narrow type of company and a technology company. And often from a set of companies and the acronym. And so those companies, I would say, draw from a really different talent pool than academia does. And so I think,
again, I was saying earlier there's importance of having diverse disciplinary perspectives. And I don't always see that in tech companies. I think companies often maybe try that, but aren't successful in having that kind of diversity. But I would say a lot of the problems are,
often a lot of the challenges, at least in my experience, are local, are an aspect of local culture rather than this is how academia works or this is how industry works. Okay, thank you. Rua? Thanks. I think that when it comes to thinking about this question, it's really important not to keep the false dichotomy between academia and industry as natural and inevitable. They're
actually deeply entangled and enmeshed and embed with each other. For example, many of the funding bodies are deliberately seeking academics to make connections with industry partners or to at least propose the possibility of the outcomes of that research becoming transferable, like becoming market products. And so, and then also you have the problem of the increasingly capitalist structure of the United States University itself. So there's like not really a difference between like Google as an entity and Stanford as an entity. Like they have the same motivations and priorities in a lot of ways. What you do get down to is the difference in motivation between the individual researchers, right? And now at a base level, most researchers are just interested in the puzzle, right? But a lot of times, the motivation that they're being given from their superiors is different. So an industry researcher might be sort of compelled to be studying things for the
purposes of improving the product, right? And by improving the product that necessarily eventually means making the product more profitable, right, even if they desire to make the product better for the people, what actually gets taken on board from the research arm to the development arm tends to be what makes it more profitable. This is why Google fired the entire ethics department. So, and I'm just picking on Google because we keep talking about them, they're not special. And in academia, you have people who maybe, like Shaun, have these lofty ideas that the things that they make can actually make a difference and then they get obstructed by the structures of academia and of our government at large in our society, right? But there's not really a difference that, like Shaun said, like the outcomes tended to be the same, but the reasons were different. And so I think that thinking about the two things as different makes it harder for us as individual researchers to collaborate with each other in subversive ways to create a better world. So, I don't know, I think maybe I just said unionized research, but next.
Okay, Raja, how about you? Yeah, so yes, I agree that academia and industry often collaborate and potentially the roles of academia kind of get passed on to the next generation of researchers and developers and potentially the customers as well. And I think that academia does impact society, and I do see society becoming more inclusive than they have over the past 40 years or so. I mean, growing up without any access, without any rights, without any commitment to accessibility, and now society has become better. But now the question is where is society getting their
values? Where are they gonna be able to improve? You know, like for autistic accessibility and different varieties of disabilities, and maybe it's from academia and maybe it's from industry, maybe it's a little bit of both. But I think I see a lot of values in practice within like the students' thinking and how they're thinking about the importance of incorporating community and incorporating design and then sending that out to the broader population through industry. We do get people reaching out to Gallaudet University often about how to improve their products, how to improve and think about these issues from the design phase. Sometimes the values will show up more on an individual level, but at a systematic level, they're continuing to push potentially the same old narrative and needing to push what's not true is that all people, sorry, that people, everybody should be included and respected and at the academic level through the industrial level. I mean sometimes it's, you know, across systems and sometimes they are in conflict with each other. And so I think that that continues to and needs to continue to change and evolve. Well, thank you. So definitely there have been a lot of good points brought up as they have
for all the questions. I just wanted to call out a couple. So one is that certainly that industry and academia are not just their own silos. There is a lot of interaction. The question was presented that way just because in the perception of most, it usually is perceived that way. So
I'm glad that that was discussed and there are certainly a lot of opportunities for engagement as well as was mentioned with populations that can give input through participatory design or other ways of evaluating products, whether it be early on or later. And sometimes those are done with universities and sometimes they're done with organizations outside of the traditional like academic or industrial kind of areas. It could be advocacy groups and other groups as well. And it, yeah, being respectful certainly is very key to that. And it's not just a, hey, I need you to
check this off. You know, it's really to really get input that is valued, right? And then is further integrated with the product or whatever it is that's being developed. And obviously across the world, this may look slightly different in terms of how that's done, but there might be a lot of commonalities that thinking about like the EU as an example, where they have a lot of ways of funding different types of research and having organizations work together, whether it be in small or in the large, as well as industry itself that have global presence. And so just wanted to call those things out. But like some of the other areas that we've discussed, it's not necessarily, doesn't necessarily look the same for everybody. And one of the other items that kind of goes along with that, that hasn't been explicitly called out is that accessibility can appear a little differently for different groups. And because of that, you can't assume that if it looks a certain
way, then it's accessible for everyone. And so keeping that in mind in terms of whether it be a spectrum or a range of abilities or limitations or constraints as people have, those all need to be taken into consideration. It's not just one profile that is being designed for. So again, that's kind of popped up for degenerative AI as well as some of the other areas. Can I make a quick point? Sorry to break my turn. Sure.
I realized after one thing I really wanted to call out is also just academia and industry and also individual institutions often vary greatly in terms of the degree to which they support people with disabilities within them. And so I really, I think panels like these are great and I'm happy to be a part of it, but I think they also sometimes communicate a survivorship bias, which is to say like, look, it's actually going well everywhere, we've got people in all these different backgrounds in these positions. And you know, I'll say personally for me, some of these moves or considerations around industry versus academia have been around where am I able to succeed and do work. And so I think for folks who are watching, I think that's a place where there's so much work to be done and I don't know, I don't think there is on earth an institution that couldn't do a bit better about how to include scientists with disabilities as part of their organizations.
That's a very good point. And actually, that leads us into actually our next question because that could easily flow into the message, right? So our last question that we have, and we should have some time to take some audience questions as well, is what is your takeaway message to those in the audience regarding accessibility and any related topics? And so what Shaun just spoke about could easily be one of those topics. Rua? Man! Takeaway. So yeah, so my recommendation for anyone who is seeking to be a researcher in this space, or is currently a researcher in this space, is to think very deeply about something that I learned from Ruha Benjamin in particular in one of her books, the "Viral Justice" book. And in that book she talks about how the world is full of problems and the problems are everywhere, and you can't do them all, right? But that doesn't mean that the thing that you are doing is useless just because something else seems more urgent at the same time, everything that is happening is connected. And so what Ruha says in her book is to find your plot, which basically means like, find the piece of land that you will work, right? And so when you're thinking about becoming a researcher in this space or any other space, look for the place that you feel you can do the most good and grow the most fruit, I guess. That as long as you are doing your best and feeling fulfilled, then that is the
most good that you can be doing, right? And so if you're doing something that feels like a struggle, sometimes it's the environment, sometimes it's the ground, right? And sometimes it's the task and you have to figure out which one it is so that you can make a choice. You know, for example, like Shaun, to move from one venue or sphere to the other, you have to find your plot. That's my message. Okay, thank you. And Raja? Let's see. My message would be, I think that academia has, the special gift in
academia is of mentorship. I think the whole generational knowledge of people that have learned from before us, I think including people who have 40, 50 years of experience in this field. So when we're thinking about going one step forward, two steps back, trying to change that and incorporating where we've been, where we've come, and explaining kind of like what are the benefits of people and including people in helping us shape the next generation within research, within practice, within mentoring, which who are gonna go off to industry, gonna go off to be members of society and making sure that it's truly inclusive from the onset from the designing of technology and computers.
Great, thank you. Shaun? Yeah, I will share some wisdom that I received. So this is something that one of my PhD advisors, Richard Ladner, said to me that changed how I think about the work that I do. You know, he was saying essentially, when we think about people with disabilities, it can be really helpful to look at disabled people from the perspective of skills and knowledge and their experience as problem solvers, and I think as a society, we've been getting better, at least in the US around inspiration porn and looking at people with disabilities as victims or as sources of inspiration. But one of the things that he had said to me was, "Okay, well, when you're
doing research with people with disabilities, you should take the same approach that you would have if you were, let's say, interviewing some domain expert, like a physician or a lawyer, and give them the same kind of respect and level of input and pay as someone who's really highly trained in their field." And I found that perspective very helpful in both in my own work, but also sometimes in communicating with others about how to engage with projects around accessibility. That's a great point from all of you. And I'll just follow up just really quickly. Certainly, plus one for me on all of that was mentioned, and basically my takeaway is that, and perhaps it's just what was mentioned just described slightly different is that, you know, persons with disabilities are not others. You know, they're just not other people that you don't interact with or that you don't know. Disability cuts across everything else. And it can vary, you know,
it's not just the profile of what is considered disability, even though many people may have a stereotype. And so with that, you will have people with disabilities at all levels of life in terms of education, in terms of occupation, in terms of income, everything really. And because of that, they're not other, people with disabilities are with all of us, right? Whoever, you know, thinking of us as just everyone. And with that and kind of going back to what was stated in terms of being inclusive and considering the perspective they have, because there will be different perspectives on some things just as others may have different perspectives for other reasons, that it is important to include. And for me, when I went into research, it was I guess not quite selfish because certainly the sixth grade me of wanting to work on a self-driving car was just something that was aspirational. But when I think of the challenges
that I went through and wanting to make things to have better tools, to have more opportunities, to make sure people know that they're there and that's part of that expectation and aspiration, but not as a savior type of way, but want to be supportive and to kind of let people know what's possible when sometimes the expectations aren't there. And so it is something that is important for all of us because one of the things that I sometimes still run into is when people talk about persons with disabilities, they use the word normal as in not, which is definitely something that is a little cringey for me because with the work that I do, including the person that I am and those that I know is everyone's normal, there's no idea of what normal is, even though people tend to throw around the word very indiscriminately. I mean, in reality, we're all together and it's just, while some accommodations or tools might be useful to help particular groups of people, in a lot of ways, those same tools help everyone in different ways. And so that's something to also keep in mind as well, is it's not just for
a very small group of people, there are a lot of things out there, Raja mentioned captions as well as other as what would be considered at times assistive technology can help a lot of people if you think about how technology is used and can be used in different ways as an example. But we do have a few more minutes. And so with that, I just want to see if anyone else has any follow ups or anything else they wanted to mention that we just didn't get a chance to talk about. This is Raja. For the panelists, talking about member research and how to communicate with people who have a similar identity to yourself, I would say it is always a challenge to try to communicate both, someone's identity and their experience. For myself, identity as a deaf person, so I understand from a deaf perspective, and I have other things to help navigate me and my journey, but I do like the approach that you're asking the expertise of that member of that community. So asking other deaf individuals how can I, help me understand you,
help me learn what I need to know, what other different technologies should be aware of that maybe is applicable to your specific disability. And I think mutual respect goes a long way, and I think that that typically works for me, myself as a deaf person and in my career. And that's the conversation with other deaf folks as well is that we consider ourselves an expert in the field. Did anyone wanna follow up? I will. So, you know, the question that we had in the QA was from Alexandra about member research
and people who do identity relevant work. Basically the problem of being the insider outsider and navigating boundaries and tensions in that research. One of the things that I see a lot, particularly from young researchers who are very often in environments where they don't have a mentor that shares their lived experience, is that they will begin very eagerly designing studies to study their in-group basically because we have this experience of knowing that we have this knowledge that is routinely denied and even controverted by the establishment, right? And so there's this eagerness to go and study that and write about it and basically show the dominant research that you're wrong, right? But what often happens with that when they don't have that mentorship from sort of like another insider or outsider, is that that research can accidentally be very exploitative. We've talked a lot about disabled people being domain experts in a lot of ways, and you also have disabled people who are chronically under or unemployed. And oftentimes I will see recruitment requests for people to participate in anonymized research on a topic that those participants would otherwise be making money for that consultation.
And sometimes there is a compensation like 25, $50, it's just not the same. At the same time, that population has a hard time declining that because they often disproportionately live in poverty. And so there's this problem where as graduate students and as academics, we forget because we are also disabled how much privilege we had to get there. And we forget that, there's not, the only difference between us and the participants that we are recruiting is privilege, luck, access to class capital. And that difference is a significant impact, but that,
like expertise wise, your knowledge is not more valuable than the participant's knowledge. And so what I caution young researchers against is to be accidentally building your career off of the labor of your own people, but the people that you have privilege over, right? And so to be thinking about that and how can you more ethically navigate that tension, I don't have the perfect advice for it that I can give you in a sentence, but it's something that we can figure out collectively. Okay, I think we're about out of time. We had a great conversation and I thank the
panelists again as well as those of you in the audience. And I think we touched on a lot of different points and it just, again, I think demonstrates the breadth as well as the depth of the conversation surrounding accessibility. And I hope that there are several takeaways from those that tuned in today and that inspire you to kind of continue your own conversation around this subject. But again, thank you today. Thank you for all of you for coming and I appreciate and hope you have a good rest of your day.
2024-07-15