Workology Podcast Ep 128: Accessibility in the Gig Economy

Episode 128: Future of Work: Accessibility
for the Gig Economy

Episode Link: http://workolo.gy/ep128-wp
Intro: [00:00:01] Welcome to the Workology podcast a podcast for the disruptive
workplace leader. Join host Jessica Miller-Merrell, founder of Workology.com as she
sits down and gets to the bottom of trends tools and case studies for the business
leader HR and recruiting professional who is tired of the status quo. Now here's Jessica
with this episode of Workology.
Jessica: [00:00:26] Welcome to a new series on the Workology podcast that we're
kicking off that focuses on the future of work. This series is in collaboration with the
Partnership on Employment and Accessible Technology or PEAT. You can learn more
about PEAT at peatworks.org.
Jessica: [00:00:43] The economy is strong and there is an assumption that everyone
who wants to find work can be gainfully employed quickly and easily. However a 2015
study by the annual disability statistics compendium reported that while employment for
people without disabilities is 75.4 percent the employment rate for people with
disabilities is 34.4 percent. Crowd work, Also known the gig economy could be the
answer for providing people with disabilities an opportunity to generate income while
also providing them flexibility. Welcome to the Workology podcast. We are continuing a
series on the Future of Work. This series is in collaboration with the Partnership. on
Employment and Accessible Technology or PEAT. Today I'm joined with Jeff Bigham.
He is an associate professor at Carnegie Mellon University. Jeff welcome to the
Workology podcast.
Jeff: [00:01:37] Great to be here. Thanks for having me.
Workology Podcast | www.workologypodcast.com | @workology

Jessica: [00:01:39] Can you talk with us a little bit about your background?
Jeff: [00:01:42] Sure. I'm a computer scientist by training and so I got my
undergraduate and graduate degrees in computer science. I started out my Ph.D. work
thinking that I wanted to work on our artificial intelligence. So trying to make computers
law eventually as intelligent as people are able to help people with very difficult task.
And I started that. But a bit of the way through I kind of got frustrated with what we were
able to do with artificial intelligence with automation.
And I wanted to start you know helping real people and I happened to connect with a
professor at the University of Washington where I who ended up being my adviser on
projects around accessibility so trying to make computers that work well for people with
disabilities. This turns out was a really great way for me to bring in the work that I was
really excited about technically the artificial intelligence work into real tools that helped
real people in this case people with disabilities. The same way I got connected with this
is that I also kind of eventually got frustrated with what the artificial intelligence
technology would allow us to do when we were building tools.
And so I started augmenting what we were doing with the computer with the intelligence
of real people so people we would find out on the web who we could pay a little bit of
money to kind of make our computers smarter. And so you know algorithms wouldn't
have to just be what the computer could do that could also be what the computer with
people on the web could do to support people with disabilities. And so this ended up
eventually being called human computation or crowdsourcing. And in the last few years
it's really connected with this idea of the gig economy where you hire people for small
amounts of time to do bits of work for you. And so I guess that's kind of my background
the short abbreviated version of how I got here.
Jessica: [00:03:29] Great. And it's thank you for setting the stage because we are
talking about the gig economy and its accessibility. Can you talk a little bit more about
your research and some some of the work that you've done because I'll have some links

in the transcript of the podcast? It's very interesting around the hearing impaired and the
sight impaired.
Jeff: [00:03:49] Yeah sure. So some of the first projects that I did at the intersection of
computer science and the gig economy were around supporting people who are blind.
And so we had an iPhone application that a blind person could use to take a picture of
something they'd like to know about. Ask a question of what they'd like to know and
then we would get an answer back to them within about 30 seconds. So this was an
application called the ISS and it was available online the App Store. We had about ten
or fifteen thousand users and they were 100,000 different questions. And what was
interesting about it as you might have guessed is that we weren't doing this with with
computers alone because even though computer vision which is kind of the field that
tries to do that sort of thing automatically has gotten a lot better.
The technology can't yet answer arbitrary questions about anything in the world. So we
were recruiting people from the web paying you know a small amount of money for a
small amount of their time to answer these questions. And so that's one of the first
projects that got me started is relatively simple and since then we've done all sorts of
different things so we had similar projects where we've been converting speech and say
a lecture two words on a screen. So captioning the lecture deaf or hard of hearing
people and doing that not with automatic technology which still doesn't work well
enough to do that to do it reliably enough but using people again we were crowded out
on the web and in this case we had to get a group of them because it turns out it's really
hard to type that natural speaking rates.
We had to get a bunch of them together all kind of contributing to this task and then
stitch those things back together into one final captioning stream that the person could
look at to follow the lecture. So those are kind of two different projects and we've got a
whole bunch of other things but that's what kind of got me excited about it is because
you know I kind of grew up with this notion that of all this great science fiction
technology is going to be coming out. But you know it's kind of slow to get here and it
even though I'm really impressed by what we've been able to do in artificial intelligence
and computer science in achieving some of that. It turns out that by bringing in people

you're able to get there sooner and kind of understand like what we'd actually want to
build and get it out to people to benefit to benefit them in their lives.
Jessica: [00:05:58] I think sometimes we forget about the people aspect we just
assume we make an assumption that the technology is just going to do exactly what we
want it to do like close captioning. Live stream captioning I think is particularly important
with the popularity of livestream video that you see all over with social media and the
web, but those things the technology hasn't caught up yet. So you're saying that there
are a lot of human sort of computation elements to those areas.
Jeff: [00:06:26] So it's still it's still true that for say closed captioning if you see closed
captioning on a television it's still done by people. There have obviously been lots of
work that's tried to make it done ought to be done automatically and they're kind of
getting better and there's ways you can kind of use both people and the technology to
make it on to get it done a little cheaper. But still it's the people behind the scenes and I
think this is true of a lot of the technology that we see all of this great stuff that's out
there and we assume that it must be just that the computers are very smart but in lots of
different ways it's often people that are that are powering it behind the scenes in a way
that makes it seem like it's just the computer. But almost all of this is some interesting
mix of people and computers working together.
Jessica: [00:07:11] Well, let's go back and talk a little bit about Crowd work and maybe
the benefits of crowd work for individuals with disabilities.
Jeff: [00:07:19] Yes, so I mean one of the big differences between what we call it crowd
work or gig gig work is the flexible nature of it. And so the way these these
marketplaces usually work is that you know you can choose to sign up to be part of the
pool of available workers and then when work comes in you can in different ways either
choose to accept it or not. And so this is maybe people would be more familiar with how
this works and say like an Uber case right. So you can sign up to be an Uber driver and
you know you can decide when you're going to work and you can decide whether or not
you're going to take a ride. When and when a request comes in and there's a little bit of
a you know Uber's case in particular you know they do various things to encourage you

to work at certain times and you know discourage you from not accepting rides but
generally that's that's the idea. You can sign up to be a worker take work when it's
available if you want.
This is true with lots of different types of work and so online you can sign up to be a
worker on various platforms. One of the ones that we work with a lot is called
Mechanical Turk which is run by Amazon so the same Amazon that you you might buy
a lot of products with and have them shipped to your home. With Mechanical Turk you
can sign up to be a worker. And in this case you're not driving a car for them you're
doing a little job. So you're taking a bit of audio and you're converting it to text or you're
looking at an image and you're saying like what's in that image or you're looking at an
image of a receipt when you're kind of transcribing that kind of start to imagine what
these are being used for. So maybe some of this is being used to keep track of
expenses or something anyway so there's all these little jobs you can sign up for.
The parts of this that might be beneficial to some people with disability is the idea that
it's flexible that you can kind of work when you want you know you don't necessarily
have to put in a straight eight hour standard workday. Maybe you can kind of work and
as you're able over time you know you don't. You don't have to travel so the big promise
of digital labor was we wouldn't have to spend as much time commuting which can be
much more difficult for some people with disabilities. So for all these reasons it might be
beneficial. This idea of kind of more flexible work. Of course there's also problems which
I imagine we'll get into but those are kind of the benefits that we see that could be could
be beneficial.
Jessica : [00:09:43] Let's talk about maybe some of the downsides. Which one of them
that I see is that some of these tasks are really entry entry level and sometimes really
low paying or what are some of the other downsides that you see.
Jeff: [00:09:59] So this has been a this has been a problem with these platforms the
marketplaces for this sort of work. And part of it's due to the fact that because anyone
can sign up there's not really a long history that each employer would have with each
worker and so they don't really have a sense of what expertise that worker brings.

You know they really can't as easily put up jobs that require certain expertise or
knowledge about the employer or the work that's being done. And so in general it's
been kind of the lower level work. These various efforts to try to improve this so to push
more toward the expert work so to enable employers to have a better sense of who
they're hiring to even enable workers to kind of have a longer longer history or build a
longer history with with employers and certainly the wage issue across all of these
platforms is a big concern. And it's not really clear. It's essentially before networked
analogy you know there were still contractors.
Jeff: [00:10:57] It's just that it tended to not be worth being a contractor for you know a
minute long job right. That wouldn't have really made sense. But now with network
technology it's actually pretty easy to connect to a worker who's willing to do a minute
long job for you. And unfortunately, our our legal framework has not quite caught up to
that. So one difference between a true contract worker and a traditional worker is you
know there's not the same types of guarantee of pay and benefits and things like this.
And we're already seeing this kind of shakeout where maybe certain types of gig labor
is not is not actually a contract and know the courts are kind of figuring that out. I hope
that we figure out some of that because I think there's a lot of promise in that. We talked
about the benefits. These are these are problems for everyone who would be a crowd
worker. I think that people with disabilities face a couple of other interesting challenges.
So in particular it turns out that one nice thing about traditional work at least in the
United States is that if you have a disability or you can request or are guaranteed
certain types of accommodations from your employer. This is not as easily true with with
the gig work where if you're working with somebody for just a minute or two it's not
really clear who's responsible for providing accommodations. We're also seeing
because kind of one can just post work and you know goes up for a little while and
come back down. We're seeing that a lot of that work is created and kind of presented in
a way that is not accessible so that people with certain disabilities cannot do it even
though they'd be perfectly capable of doing the work.

Jeff: [00:12:46] And so there's these different challenges and it's kind of difficult to even
get a handle on it because as opposed to you know a large company where you could
go if you saw over time a pattern of that large company not accommodating people with
disabilities as they are required to do. You could actually go talk to that company. You
could potentially even go through legal means to try to force them to do what they're
supposed to do with these short jobs. People post things and take them down. It's really
difficult to even know who to talk to or to have. The chance to find the times. So that is
up there for a little while. And so it presents these new problems and I think this is
something we're still getting a handle on. But I think it's really important to get ahead of
because we we believe and it seems as though this sort of work is and will continue to
become more and more popular. Maybe not everyone will be on mechanical turk worker
but it seems like the idea of flexible labor is really attractive to employers.
And so we imagine that they're going to try to keep pushing this to be more and more of
their workforce. And so we need to get ahead of it from lots of different means both the
kind of how do we bring in some of the nice qualities of traditional work into this like you
know building expertise over time guarantees of pay other things like that that would
apply to everyone. And then also things like how do we make sure that people with
disabilities in particular are not shut out of this increasingly big part of what work is.
Jessica: [00:14:16] I think this is a interesting dilemma. I do really hope that the public
policy right will have some law or some court decisions that might help influence us to
move in that direction.
I would also like to see companies say if I'm maybe using a Mechanical Yurk or some of
these other web based platforms that are focused on the gig economy maybe really
taking some time and putting some effort into thinking about how they can make their
gig's or their projects or tasks attractive to people with disabilities so that they're kind of
helping to further this this area.
Jeff: [00:14:58] Yeah yeah I think I think that it's one of these things where I guess over
the years that I've worked in accessibility which has not been that long but after 15 or 20
years you know I've been I've become a little bit pessimistic about that sort of approach

working at scale so you always have a handful of companies that for a variety of
reasons either personal connection or you know maybe even a prior lawsuit will go
above and beyond their peers.
Jeff: [00:15:25] And I think that's awesome and that should be supported and we should
be celebrating people like that. But in general I think that there are still lots of reasons
why it doesn't happen like lack of awareness and we can try to build awareness but lack
of awareness or you know it's always seen as even though I think there's arguments
against this that you know it's this extra cost that a company claims they cannot afford
or it's something that they intend to do but they'll get around to it later. And so I think
that it's hard. And even even the you know changing policy doesn't necessarily change
this I mean you know there's policy but then there's enforcing that policy there's kind of
interpreting what it means to be accessible and at what point it needs to be accessible
and it needs to be accessible to me with lots of difficulties in this.
I mean as researchers one of the things that we have done is try to build tools that
make it easier for people without expending extra effort or resources to make things that
are just out of the box accessible or to have people who come to a task have them be
able to trigger something that then reformat that task so that it's more accessible to
them. And so I think there's lots of different ways that this can be pushed pushed on.
But I do think it's something that you know it used to be we were concerned I think very
legitimately concerned that the Web was not as accessible as it could be. And now the
Web is taking on a greater and greater role in everything in our lives including now
employment. I think that it's becoming more and more important that we figure out how
to do something to solve this.
Jessica: [00:16:58] Let's take a little bit of a reset here. This is Jessica Miller-Merrell
and you're listening to the Workology podcast in partnership with PEAT. Today and we
are talking about machine learning and inclusion with Jeff Bigham. You can connect
with Jeff on Twitter at Jeff Bigham @ jeffbigham.
Announcer: [00:17:15] The Workology Podcast Future of Work series is supported by
PEAT. The partnership on Employment and Accessible Technology. PEAT's initiative is

to foster collaboration and action around accessible technology in the workplace. Is
funded by the U.S. Department of Labor's Office of Disability Employment Policy ODEP.
Learn more about PEAT @peatworks.org. that's p e a t w o r k s dot org.
Jessica: [00:17:45] Jeff, in one of your recent research articles which I'll include in the
transcript of the podcast you mention the importance of these crowd workers to skill up.
Can you talk about why this is important and maybe what they can do?
Jeff: [00:18:00] Yeah so this is this is in general connecting back to that theme that we
talked about of you know how do we how do we make it so that crowd work which does
have this kind of tendency to be short kind of independent you know jobs where where
workers are assumed not to have any particular skill because that skill might not be
known. How do we gradually make it so that more of the qualities of traditional work are
are in crowd work.
And so one of the things that is nice about at least good employment is that you can
over time build expertise in that employment and that over time you can kind of skill up
to maybe new jobs new roles maybe greater responsibility. And so as a first step at this
we were trying to see if we could build in two tasks that workers are already doing
trainings so that they that workers were be able to graduate into doing higher skilled
work that might be better paid that might have better prospects long term for them.
And so it's a really hard task but one of the things we were trying to do was in the
context of just audio transcription so converting an audio file into text. It turns out you
can do this as a non expert worker so who is someone who doesn't have a lot of training
in this. But it's really slow so if you know there's an hour of audio or there's a half hour of
this podcast and a non expert worker who can type and and listen to the podcast but
doesn't have special skills in doing this. If they try to do it it takes them about four to five
times as long as the as the podcast to caption it.
So that that ends up being a long time and they end up not being paid very well to do it.
But there's all these different methods you could use to type faster. And so one of the
expert skills there is called stenography. So this is using corded keyboards so typing

kind of multiple keys at once typing not just letter by letter but typing what is you can
think of as kind of phonemes so like a word would only have a word that might have
many letters maybe could be typed with only a couple of chords. So we are teaching
workers who didn't have this special skill.
The chords that they might need to eventually graduate into being a stenographer as
they were earning money which seems to be important especially for people on these
platforms who for whom money is often the primary motivator. And so you can imagine
though extending this to all kinds of things. So you know could you as a crowd worker
train to do almost anything that you want or could you earn a college degree while
you're making money as opposed to you know our university system now.
It works very differently where you put out a bunch of money you know take out a lot of
loans in many cases and then that over many years you graduate to two high skilled
work maybe you could actually earn money while you did it. And so that's the ideas that
we were exploring with that.
Jessica: [00:21:09] And I would think that as as an employer or a company who is
working with with good workers if you found someone that was reliable completed their
tasks on time and did high quality work that you would want to encourage them to
upscale their skills to be able to do more work for you because of your track record for
success.
Jeff: [00:21:30] Yeah and I think some of it's just building in the tools that allow work
that will allow employers to even tracks things like that. So the way that many of the
platforms are set up right now it's difficult to tell who's really doing a good job.
You can figure it out if you put in effort. But one of the reasons why put people put work
up on crowdsourcing platforms now is because there's a lot of work to do. I mean a very
standard type of task is you know I might have a million images that I need labeled and I
put them up on a crowd platform so that I can get them all label reasonably quickly. The
problem once you get to that scale is not only don't you have you know the internal
resources to do the work yourself.

You also may not even have the internal resources to evaluate all of that work at least
in a kind of manual way in which you might easily recognized the best workers.
Certainly people build up models of what workers seem to be doing the best job over
time and they try to recruit those workers again. But then they may not even have a
good idea and this is part of I think where the research is important. Well what's the next
step like. What's the ladder that will take this worker who's doing maybe a relatively low
level image labeling task. What's the ladder that gets them to a more interesting you
know expert skill over time. And so I think that's kind of where we're trying to still figure
figure thing about.
Jessica: [00:22:56] Do you think that's the responsibility of the web based platform to
be able to help make suggestions on how to scale up or kind of for like the next sort of
level of expertise or is it the responsibility of the employers?
Jeff: [00:23:10] Oh it's a good question. I mean I think that many of us are thinking
about kind of the sort of the ethics of this sort of employment and it seems like in
practice the platforms will have a much better opportunity to be able to do something
here because you know an employer depending on you know how they use the platform
may not even have work at the different levels of skill. They may only have a job you
know here and there and so they may not even get the kind of experience with a worker
over time that you'd need to make such judgments.
And so I think in practice that might need to be the platform. You know it's a different
question to ask. You know should they. And you know who's responsible. And these
sorts of things. And I do think the platforms should should be both for you know it being
the right thing and also just for their long term interests. Think a lot more about workers
and how they can better support workers make sure that they're treated fairly. And all of
these things. And so I guess from that perspective it seems like it always has to be the
platforms and it probably should be the platforms as well.
Jessica: [00:24:16] I think as competition among platforms grow right there more and
more every day trying to get the interest level out of the gig workers to come on over

submit their profiles. It would behoove them to help those individuals scale up in those
areas so that they can keep having the best highest quality workers with the best skill to
offer to to these employers.
Jeff: [00:24:42] Yeah. And I think part of it is you know I think I think there's there's two
sorts of people that the platforms are trying to attract. One is they're trying to attract the
workers and one of the other is they're trying to attract the employers and you can
probably see in the near term interests of the company that's trying to do this. They
probably see him attracting the employers who were paying the money as being the
best for their best use of their time.
But I agree that over the longer term it seems like attracting good workers keeping
workers happy making sure that they are improving and and feel satisfied with the
platform it seems like that's the long term when what are some ways art that you're
seeing in terms of these web based platforms that are making their systems and
software and technology more accessible to individuals with disabilities.
Jessica: [00:25:34] Well you know I haven't seen a lot.
Jeff: [00:25:36] I think well you know there is there was one fun example where I think I
think there was an early story about how there was Uber driver who was deaf and it got
a lot of popular press and I think it was one of especially the most more positive press
that that Uber has gotten. And so you know Uber has now put into their app various
support for drivers who are deaf. So if you get a driver who is deaf you know there's an
alert you get on your phone and it says Just a heads up your drivers deaf and there's
support for you to communicate back and forth with with the driver.
So I think that's a really interesting thing. I mean I think it happened my my opinion is
that it happened because they just happened kind of accidentally maybe Uber didn't
even expect it but then it did happen and people saw that as a really positive thing. And
then when Uber Uber saw that and they built it into their app because of that. And so I
think you probably there's probably more examples of this sort of kind of ad hoc kind of
accidental you know stories developing into support. But I would definitely like to see a

lot more. I mean I think that most of the platforms really haven't done much of anything
to support people with disabilities in particular.
And especially you know where and when the platform allows requesters to submit jobs
in whatever form they want. There's very little feedback that those and those requesters
or employers get about what's accessible what's not what's the expectations for the
platforms. And so. So I think there's these point examples but but really we need to be
doing a lot better.
Jessica: [00:27:11] You know hopefully maybe I mean I'm an optimistic that podcasts
or conversations like we're having right now and with some of the other folks is part of
this series can help change that because my hope is that these platforms people who
are helping build these web based platforms will take a listen and say, “Hey, Oh I hadn't
thought about this particular point of view.” Maybe we can kind of move the needle a
little bit more forward and drive some awareness.
Jeff: [00:27:40] Yeah I think that would be that would be wonderful.
Jessica: [00:27:42] I do want to ask you about some of your research because I
thought this was a really interesting work that you're doing and one of them one of your
research was focused on study participants who were blind and they had different
responsibilities and tasks that they were required to complete.
Jeff: [00:28:01] But if they didn't complete the tasks on time or at a particular level they
placed blame on themselves for failing to complete the task instead of looking at the
access the tech the lack of accessible technology that was for the individuals to be able
to use. What suggestions do you have in terms of maybe technology or ways to help
increase the performance and productivity for people with disabilities. From your work.
Sure yeah. So there's been a lot of work that has explored how to make the Web more
accessible and more usable for for everyone including people with disabilities. One of
the first steps is there are these great guidelines that are put out by the E3 see the
world wide web consortium.

The SCAG WCA. So these are basic things that you can do if you're creating a web
page that can make sure that at least in theory people with disabilities will be able to
access the web page and use it where it gets tricky and where we're probing with our
research is when the page maybe is technically accessible or maybe it's not but there's
a usability problem that prevents people with disabilities from being able to not only
accomplish their. Task but actually figure out what's going on. So in the example you
mentioned what we're exploring was this concept of not knowing what you don't know
and so if you go to a web page it's often kind of tricky to know if if you're unable to
complete a task you expect to be able to do on that Web page then.
Is that because of the information maybe not being there on being there at all? Is it
because you can't figure out how to do it and if you happen to be a person with a
disability or in our case then that study a person who's blind? Is it because the
information that you would need to complete the task is actually hidden from you or is
inaccessible so maybe you a blind person very often does not use a mouse because
you can't see the cursor?
And so maybe you have to interact with the web page using the mouse. And so it's
there, but you wouldn't know it's there because you'd have to use a mouse to figure out
that it's there. And so we were kind of probing at that issue. I think I think it pushes this
understanding of what accessibility is to being as much about often about usability as it
is accessibility. And so unfortunately on the Web we're still at the stage where we can't
get people to do even the basic things reliably to make their web pages accessible. But
you know we're still pushing to understand well what are in practice are the problems
that people run into how we might resolve those that sort of thing.
Jessica: [00:30:56] Well this has definitely been enlightening for me and I'm thinking
about my own Web site and the different things that I might be able to do to make it
more accessible to all different kinds of people and and their background. So I
appreciate your time today. Where can people go to learn more about you and what you
do.

Jeff: [00:31:16] So my web page is my first and last name JefferyBigham.com. So that's
a great place to start. We have all of our research papers up open so that you can just
read them if you want and a bunch of fun videos too about the projects we've worked on
so I'd say people should start there.
Jessica: [00:31:32] Awesome. Well thank you so much for taking the time to talk with
us. Appreciate it. Great. Thank you so much.
Jessica: [00:31:38] Inclusion comes in all forms and I'm inspired by Jeff's research as
well as others and the technology that supports these efforts. As the gig economy
continues to grow and the war for talent becomes even more competitive companies will
need to look beyond the traditional way of hiring recruiting and employment for all types
of individuals including people with disabilities.
Exit: [00:31:59] Thank you for joining the work Algy podcast a podcast for the disruptive
workplace leader who is tired of the status quo. This is Jessica Miller-Merrell. Until next
time you can visit Workology.com to listen to all our previous podcast episodes.

Episode Link: http://workolo.gy/ep128-wp


Workology Podcast Ep 128: Accessibility in the Gig Economy

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Workology Podcast Ep 128: Accessibility in the Gig Economy