Posts Tagged ‘HCI’

What Comes After CHI? The Systems of Truth Workshop

March 5, 2018 1 comment

The Center for Human-Computer Interaction (CHCI) at Virginia Tech just wrapped up its third workshop in the “What Comes After CHI?” series, this one focused on the theme “Socio-technical Systems of Truth”.  Kurt Luther was the primary organizer, and information about the workshop is at  The workshop is described as such:

This two-day workshop, held March-1-2, 2018 … will explore interdisciplinary perspectives on designing socio-technical systems of truth. We advocate for human-centered systems of truth that acknowledge the role of belief, testing, and trust in the accretion of knowledge. We focus on processes of questioning and accountability that enable a deeper understanding of the world through the careful, comprehensive gathering and analysis of evidence. We will consider the entire investigative pipeline, from ethical information gathering and archiving, to balanced and insightful analysis, to responsible content authoring and dissemination, to productive reflection and discourse about its implications.

This post lists some of my own observations about the things of interest to me and is not meant to be at all comprehensive. Look to the workshop site for more comprehensive summaries.

The workshop kicked off with faculty lightning talks, featuring 8 faculty from 4 different departments and centers around campus.  I talked about the intersection of core HCI topics—particularly things that I care about, like claims and personas—connect with the themes of this workshop.  I included results from surveying my 105-person introductory HCI class. I used Shuo Niu’s AwareTable system to mine the student answers for occurrence and frequency, revealing workshop-relevant terms (e.g., social (40), media (14), bias (15), ethical (20)), key course concepts (e.g., claim (4), persona (6), artifact (6), scenario (6), constraint (3)), and topics mentioned in the invited guest bios and abstracts like dead (3), nude (4), and the scary gap between academia and industry (3).  You’ll have to read up on the invited guests to learn the relevance of those last few terms!

The big highlight of the workshop was to have four invited fellows in attendance: Mor Naamen, Alice Marwick, Travis Kriplean, and Jay Aronson. Each gave a talk, followed by discussant comments and open discussion.  There were also several breakout groups that explored relevant topics, and a reception and dinner.  A quick take on each of the talks and the other events.

Mor Naamen spun off the notion of “systems of trust”, where trust is the result of truth.  He focused on his research into Airbnb, showing (among other things) that longer profiles, and profiles that cover more topics, correlate with high trustworthy ratings.  So what’s the right thing to say in your Airbnb profile? Things like “We look forward to hosting you.”  And the wrong thing? Providing a life motto.

So what about fake news? Mor noted that there’s not a good reliability/credibility signal.  Possible solutions? Local news, where familiarity and relevance is high.  Proof that statements are true (but how to do that?).  Discussant Tanu Mitra pushed that notion, seeking to identify ways to encourage people to call out fake news, with the danger of risking (or helping?) their own reputation.

Alice Marwick talked about fake news: how it is created, why it is shared, how it evolves into our consciousness, and how it is (and can be) debunked.

Are people who share fake news “dupes”?  That’s been proven false multiple times over.  They share stories that support pre-existing beliefs and signal identity to like-minded others.  Algorithmic visibility and social sharing contribute to this.  What to do? Understand where fake news resides in media ecosystem, take polarization and partisanship into account in fact checking, and scrutinize algorithms and ad systems.

During the Q&A led by Carlos Evia (and afterward), Alice noted that it’s difficult for the average citizen to know what to do when someone you know (someone you’re related to) puts forth information that’s clearly false.  It’s hard to foster dialog when people are repeating stories that mirror a deeply-felt belief. The many fact-checking sites out there (Snopes, Politifact) do not seem to influence behavior, and corrections often lead to more repetition of misinformation.

Travis Kriplean put forth 3 categories of systems of truth, with examples of systems that fall into each category that he has crafted.  The categories (and systems) include:

  • empirical (fact$,
  • intersubjective (, reflect, deslider,com,
  • reflective (cheeseburgertherapy, dellider,

Andrea Kavanaugh took the lead on the discussion. One statement by Travis during the discussion that resonated with me was his statement that people have to be part of the loop—though it was unclear how that could happen with a web site.

Travis used the notion of claims a lot. But not in the Toulmin or Carroll or Sutcliffe or McCrickard sense of the word. He seemed interested in claims as hypotheses, to be debated with the help of systems.

Jay Aronson talked about methods to organize and analyze event-based video. The early part of Jay’s talk addressed how technology is a double-edged sword. It can be used for “good”, but also for harm. He emphasized the need for a trusted human in the loop, which I read as an “Uncle Walt”; i.e., Walter Cronkite, or a Billy Graham, to work the controls.

The bulk of Jay’s talk featured an examination of a video he created to show a murder that took place at a Ukraine protest.  He stitched together a collection of mobile phone videos that were taken at the protest.  There are often tons of videos of disasters, so how can you sync them?  The obvious way seems to be to look for similar (visual) objects in the videos, but that’s hard. Audio proved to be easier: by identifying and connecting similar loud sounds, Jay could connect videos taken from different locations.

Jay hired animators to connect the videos, which made him somewhat uncomfortable. These sketch-based animations make assumptions that aren’t present on the video, though they stitch together a compelling argument. Jay cautions against de-coupling the video from the people; they need to be coupled to maintain “truth”.

Deborah Tatar, in her discussion, noted the ability to query video is very important–YES!  But it took around a year to produce the video, so a query system that doesn’t take 6 months to answer anything more than a trivial question seems far away.

Breakout groups were each centered on a series of questions. A common theme was the effort to define terms like “system” and “truth”, and efforts to define people’s role in systems of truth. This section details my perspective on some of the discussions in breakout groups.

So who do we need?  Is it Walter Cronkite or Billy Graham? Mor’s work suggests that someone local may help to turn the tide, like the “News 2 at 5pm” anchor. Were/are any of these people more trustworthy than Rachel Maddow, Bill O’Reilly, and the like?  Or just less criticized?  Or is there some different sort of person we need?

How do we determine what’s true?  And do so by avoiding provocative phrases like “pants on fire” (and “lying”, per the Wall Street Journal controversy from 2017. So is there a set of words that are provocative, that should be avoided?  And if a system helps with that, could it avoid such words From Snopes:

I realize this is quite possibly a novel idea to the Daily Caller writer, but here at we employ fact-checkers and editors who review and amend (as necessary) everything we publish to ensure its fairness and accuracy rather than just allowing our writers to pass off biased, opinionated, slanted, skewed, and unethically partisan work as genuine news reporting.

Perhaps some Daily Caller writers could give that approach a try sometime.

I realize that it may be fun for an organization like Snopes to put the smackdown on an organization that puts forth factually-inaccurate articles like Daily Caller. But is the closing snark helpful for advancing the argument, particularly to those who wish to think positively about Daily Caller?

The systems that Travis developed helped to prompt a lot of discussion in one breakout group on systems that help with decision-making.  IBIS-based systems were a big part of that, including gIBIS, QOC, and Compendium.  Steve talked about his thesis work, which was related to IBIS.  And I interjected about claims as a hypothesis investigation technique.

The reception and dinner provided a great venue for further discussion.  Students presented posters at the reception, held in the Moss Arts Center lobby area.  Big thanks to my students, Shuo Niu and Taha Hasan, for putting together posters about their work for the event. The dinner was upstairs in the private room at 622 North.

Next steps seemed to start with a writeup that would appeal to a broad population, including a VT News posting and possibly an interactions article. Some sort of literature review might fit well into someone’s Ph.D. dissertation.  Design fictions, part of one breakout session, might help spur thoughtful discussion.  And follow-up workshops at CHI and elsewhere seem like a good next step.

I suggested putting forth a series of videos, perhaps as a class project for students in the Department of Communication at VT–they’ve put together other compelling video collections.  The videos could be made available on YouTube for use in classes and other meetings.

It was great to see the different perspectives at the workshop, and I’m particularly grateful to the invited speakers for taking the time to connect with us.  Looking forward to the next steps!


Claims and patterns in HCI

October 27, 2011 1 comment

I gave a claims-centered talk to a small discussion group last week–including four researchers with over 100 years of combined experience in the field of human-computer interaction. The question about the difference between claims and patterns question came up, with the following distinction reached. Claims are hypothetical, intended to be debated and changed based on the context. They are smaller than patterns, and many (most!) lack the rigor that are found in established patterns libraries—but those traits also make them easier to process and change as well. Patterns purport to be the truth, meant to capture things that have been decided after a great many instantiations and studies and experiments and such. There’s typically a collection of people who work toward maintaining the library, with additions and changes to it occurring rarely and with careful deliberation.

For a discipline like HCI, in which changes in context have great influence over the way a user interface should look and act, it seems that claims often would be the better choice. Does that mean claims are good and patterns are bad? Not at all…but it does mean that great care should be exhibited in choosing which to use for a given design problem. Patterns seem well-suited for domains like web development, in which there’s an assumption that a typical individual working alone at a desktop or laptop machine is seeking to accomplish a task. By “typical”, I mean, e.g., that the person has close to 20/20 vision (perhaps corrected), cognitive skills sufficient to process a fairly complex screen of information, motor skills sufficient to use a mouse and keyboard, and some experience using a web browser. But as soon as those typical traits are violated in your target user population, or as soon as you start designing for noisy or busy or mobile situations, or when you’re seeking to do something very different with your interface, it’s necessary to question the truths—which seems to be a strength of claims.

These lessons were underscored in one of my current projects—designing work support interfaces for young people with moderate to severe cognitive disabilities. So many of the mobile interface claims just don’t hold when designing for people with cognitive disabilities: button sizes have to be bigger (sometimes with only a single “button”), the number of choices have to be limited (to two or at most three!), and single-switch scanning should redundantly be employed to communicate on-screen text. In addition, the experiences have to be tailored differently: repetition in experience and questioning is often more important than reflection, and great care must be taken in the use of appropriate symbol sets. An expert at mobile interface design would almost have to “start over”, throwing away (or, at a minimum, reconsidering) all knowledge about how to design the interface.

A lot of so-called “truth” in interface design goes away when the context changes. That doesn’t mean it’s a bad idea to capture design truths, just that they should be treated with scientific skepticism when encountered in a new design problem. Capabilities of humans can differ depending on user population characteristics, as can the situations in which an interface will be used. My current thought is to use claims in this way: making it clear in design activities that they are meant to be challenged and questioned, not taken at face value. It’s there that I think the greatest value for claims (and the distinguishing value from other knowledge capture approaches) can be realized.

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