OK.
Welcome everyone to the UIST Visions track.
This session will also include the Lasting Impact Award
presentation, which I'm happy to give.
I am Andy Wilson, and so it's my pleasure
to give the Lasting Impact Award this year.
So I'd like to begin by describing what the UIST
Lasting Impact Award is.
So each year, it honors a UIST paper or body of work
from at least 10 years earlier that made significant research
contributions with long-lasting impact
on the UIST community and beyond.
You can take a look at prior awards actually
and a whole bunch of other historical information
at this URL here.
So the committee this year, besides myself,
included Patrick Baudish of Hasso Plattner Institute,
and Takeo Igarashi from University of Tokyo.
So I think one of the reasons for UIST's enduring relevance
is that it so readily takes on new topics,
and so acts as the vanguard of HCI,
and even help launch new fields.
Rather than be dogmatic about what is or isn't a UIST topic,
we embrace whatever the community finds
exciting and groundbreaking.
So anyone who attended the 2010 conference in New York,
which Ken Perlin chaired that year, cannot help, really,
but notice something like this happening with the topic
of crowdsourcing.
Even if crowdsourcing was far outside your own field
of study, it was hard not to appreciate
the creativity of the work presented that year.
It was clear that something special was happening.
There were three papers that really stood out.
Greg Little and his co-authors presented
"TurKit: A Human Computation Algorithms on Mechanical Turk."
Michael Bernstein presented "Soylent: A Word Processor
with a Crowd Inside."
Jeff Bigham presented "VizWiz: Nearly Real-time Answers
to Visual Questions."
And one of these papers in particular
stood out for, I think, its clarity of vision
and even a little bit of audacity.
And so the Lasting Impact committee
is pleased to award one of these papers,
from that conference that year, for its pioneering integration
of crowdsourced human contributions
directly into user interfaces.
In testing the boundaries between interaction
and crowdsourcing, it inspired subsequent work
and helped establish crowdsourcing as a creative--
as a field of creative HCI research.
And so I'm going to roll the video associated
with that paper.
[VIDEO PLAYBACK]
- Soylent is people.
It explores what's possible when we
start embedding humans, paid crowd workers,
into our interfaces.
Soylent is an add-in from Microsoft Word that
gets human help to support tasks that Word can't do well,
shortening, proofreading, and open-ended editing via macros.
It does this by recruiting workers on Amazon's Mechanical
Turk service to solve hard AI problems for just a few cents.
One of Soylent features is called Shortn.
Shortn helps writers cut down their text.
It's tough to trim a document to meet a size limit.
It takes time, and it's hard to look objectively
at your own writing.
Shortn asks Mechanical Turk workers
to find parts of the document that
can be cut down without changing your meaning,
and then offer a few rewrites.
Its interface gives you direct control
over the length of the text.
Drag the slider to specify the length
you want for your paragraph, and Shortn
combines the edits to match.
We've shorten text ranging from blogs, academic papers,
and rambling emails, and we got cuts down to about 85%
of the input each time.
We paid workers about $1.50 per paragraph,
though if you're willing to wait longer,
you can pay closer to $0.30
Crowdproof is a distributed human proofreading service.
Microsoft Word misses all sorts of obvious grammar errors
that humans can catch.
Crowdproof finds these errors, explains in plain English
what the problem is, and offers anywhere from one
to five rewrites.
We've used Crowdproof to clean up texts,
like non-native English writing, bad Wikipedia pages,
and paragraphs full of errors that word can't find.
Word finds about 30% of the errors in these texts.
Crowdproof finds about 2/3 of them,
and fixes about 90% of the errors it finds.
Last is the Human Macro, a natural language
crowd scripting interface.
Usually, users would need to translate their ideas
into code which is tough.
Instead, the Human Macro lets you automate complex actions
by describing what you want naturally in words.
Launching the Human Macro opens a request form
where you can write what you want, like you would
a Craigslist post.
Our goal here is to keep users from launching buggy commands,
so we show a live preview of what the request will
look like, and let the user do a test run on a single paragraph
or sentence.
Our users have gotten the Human Macro
to transform a short story from past tense to present tense,
to find creative commons licensed images
to describe a paragraph, and to flesh out citation sketches
into real references section.
[END PLAYBACK]
Soylent [AUDIO OUT] Processor with a Crowd
Inside, and this was published at ACM UIST 2010.
Co-authors were Michael Bernstein, Greg Little,
Robert Miller, Bjorn Hartmann, Mark Ackerman, David Karger,
David Crowell, Katrina Panovich.
And I promoted Michael, and David Karger,
and Bjorn Hartmann as panelists right now.
And so I'm going to give the floor over to Michael,
and he'll say a few words.
So normally we would have Michael come up on stage,
and we would shake hands, take pictures.
But instead, we're going to have him appear as a panelist,
and congratulate him.
So I'm going to stop sharing.
And I see Michael and Bjorn.
Congratulations, again.
And there's David, as well.
So take it away Michael.
Great.
So I'm hoping you can see this.
Thank you so much to the committee for the thought
and consideration.
I think a lot has changed in 10 years.
We wanted to think about what's enduring,
what's not where reflections have been,
and what our calls to action are to try and take
this kind of work forward in a pro-social way.
So in 2010, and I think, it's fair to say
that a lot of things were different.
We were playing Angry Birds on our phones.
Mark Zuckerberg was in a somewhat different position
in the world than perhaps today.
And this iPad was like just a few months old.
And in 2010, when I went back and looked, I actually--
I noted that there were only four crowdsourcing papers
in HCI venues that were out there at the time
that Soylent came out, one by Niki Kittur and Ed
[INAUDIBLE] group at Park, Jeff Heer at Stanford,
Ben Benderson and Alex Quinn.
And the first one that started, I
think, leading into this push on what the ethics
and tactics of crowd work And, as Andy mentioned,
I think it would--
there were three papers all in the same year.
And Jeff Bigham work with VizWiz that wound up
creating an entire spread with his colleagues
and students of accessibility based crowd systems having
really, really big impact on a really important group, ours
on Soylent.
And then, I think, Jeff and I would probably
both want to highlight that Greg Little's work on TurKit
was critical infrastructure that we built--
we both built our systems on top of Greg's work which--
and all three of these showed up in the same year.
Jaime Teevan and Aniket Kittur, yesterday,
laid out some of the work that came out of this, where HCI--
and technically, HCI took all of this,
and started pushing, and thinking
about different kinds of crowd powered systems, ways
to coordinate collective intelligence.
And a new form of human computer interaction
sort of took hold in the community
for the next 10 years.
But I think we also had to ask this question that arose also
in the next 10 years, but would you
be happy if your own kids joined this workforce?
And while this was a somewhat academic question when
it got posed in 2012, I think in 2020,
we know a lot more about this, and I
think the answer is maybe not one that we're
entirely happy with yet.
In fact, Mary Gray just won a MacArthur genius award,
I believe last week, in large part due to her work
really calling out a lot of the issues that
have arisen in society as crowdsourcing
has gone mainstream.
So there's been both media and academic work really
pioneering this effort as well that I wanted to call out.
And I think that we have to ask ourselves moving forward,
what we need to do in both in terms
of crafting systems and policy?
We as technical leaders can talk to policymakers
to ensure that this future for workers and interaction
is a positive one.
We have the opportunity to be building these systems
that help convene groups of people or organized groups
to take advantage of that energy,
essentially bringing CSCW back in the UIST
or bring UIST back into CSCW.
Somewhere there are huge opportunities here,
but we need to be making sure that we're
attentive to the needs for these research.
In particular, the workers are going
to need to feel comfortable taking risks,
because right now, it's a very risky jaunt
to join these platforms in a computationally
mediated future of work.
And I think it's also incumbent on us
to talk about ways in which we can create
these opportunities that are going to be vastly
preferred to taking the traditional job
instead of just creating platforms
that workers turn to when their traditional jobs fall through.
And I think we have to ultimately recognize--
and I think this does a bit of a shortcoming
of the paper at the time that in the way that it was presented.
It's not exciting because it's access to a cheap labor.
I think it's exciting because it affords
the ability for computation to support collaboration
between diverse participants.
This mediation of computing through technological systems
and computation provides an incredible opportunity
if we can take advantage of it and do so in a responsible way.
So I want to really thank my co-authors, several of whom
are here with me on West Coast time,
and the workers in Mechanical Turk, and UIST itself,
and the committee for considering the paper.
So thank you so much to everyone.
Thank you, Michael.
And thanks for your insights.
They're really very nice.
And good to see you Bjorn and David.
Congratulations.
[CLAPS] I would invoke thunderous applause if I could.
And thanks for coming out today.