Exploring Transgender Individuals’ Experience of Safety with Technology

Morgan Klaus Scheuerman 2018
Exploring Transgender Individuals’
Experience of Safety with Technology
Master’s Thesis by Morgan Klaus Scheuerman
Thesis Supervisors: Stacy M Branham, Foad Hamidi
1

ConclusionDiscussionFindingsMethods
Outline
Introduction Background
2

Outline
3

4Introduction
Research Questions
How can transgender individuals’ experiences of safety with technology
inform the way we consider designing technology?

Transgender:
an individual whose gender identity is different from the one
they were assigned at birth [87]
Introduction 5
1.4 million United States citizens identify as transgender [16]

Motivation
6Introduction

Trans Identity in the Headlines
7Introduction

46%
Experienced verbal
harassment
41%
Attempted suicide in their
lifetime.
47%
Experienced sexual assault
2015 U.S. Transgender Survey [60]
8Introduction

1
How Do Transgender Users
Experience Safety Online?
9Introduction
First Research Question

Misgendering:
misidentifying another person’s gender, either intentionally or
unintentionally[86]
10Introduction
56% of transgender people misgendered in workplace attempted
suicide [60]

Automatic Gender Recognition
● Introduction of transgender dataset
for facial recognition (BTAS 2013;
Mahalingam et al.) [82]
● Experimentation with transgender
dataset to accurately detect identity
across gender transition (ISBA 2016;
Kumar et al.) [70]
Camera
Advertisement
MALE
11BackgroundExample scenario

12Introduction
Second Research Question
1
What Do Transgender
Individuals and Technologists
Think about Automatic
Gender Recognition (AGR)
Technology?

Summary of Motivation
1. Rising discussion about transgender rights and identity
2. Statistics of violence and discrimination
3. Impact of misgendering
13Introduction

Outline
14

Defining Safety &
Harm in HCI
15Methods

Defining Safety
freedom from emotional, physical, and social harm
Children and Youth
● Exploration of parental concerns
about children with autism’s safety
on Minecraft (CSCW 2015;
Ringland et al.) [100]
Women
● Analysis of trolling strategies and
coping mechanisms for dealing
with trolling on a feminist forum
(Information Society 2002; Herring
et al.) [54]
16Methods

By Humans
● Examination of online privacy
concerns and practices of victims
of intimate partner abuse (CHI
2017; Matthews et al.) [84]
By Technology
● A discussion of embedded racism in
Google Search and ranking
algorithms (Algorithms of
Oppression 2018; Noble)[91]
17Methods
Defining Harm
the negative effect of abuse and/or safety issues

Trans Identity in
HCI
18Background

The Trans Community and Technology
● Examination of Facebook as a site of both stress and social support for
trans users (CSCW 2015; Haimson et al.) [47]
● Discussion about managing digital footprints for transgender users on
social media (CHI 2016; Haimson et al.)[48]
● Found complexity of information disclosure on social media for LGBT
parents (CHI 2016; Blackwell et al.) [14]
19Background

Algorithmic
Harm 20Background

Algorithmic Bias
● Analysis of varying technical biases (Transactions on
Information Systems 1996; Friedman & Nissenbaum) [40]
● Report on racial bias in predictive policing algorithms
(ProPublica 2016; Angwin et al.) [3]
● Found machine learning applied to textual data
displayed gender and racial biases (Science 2017;
Caliskan et al.) [21]
“Fag Face Mask.” Facial
Weaponization Suite by
Zach Blas. 2012. [15]
21Background

Outline
22

Participant
Recruitment
23Methods

Interview Design
2 pilots
13 participants
(3 technologists)
85 minute average
24Methods

Participant Demographics
25
Male / Trans
Masc
19%
Female / Trans
Fem
31%
Non-Binary
50%
Gender identity
Methods
People of Color
54%
White or White-
Passing
46%
Racial identity

Data Analysis
grounded theory coding techniques [24]
26Methods

Coding Categories
27
ResearchQuestion2
Impact of Being
Misgendered by AGR
Worse than a
Human
Better than a
Human
The Same as a
Human
RQ1
• 3 categories
• 10 sub-categories
RQ2
• 6 categories
• 20-subcategories
Example categorization Methods

Outline
28

Research Question 1:How Do
Transgender Users Experience
Safety Online?
29Findings

The 6 Facets of Harm to
Study Participants
3 dichotomies of harm:
1. Outsider/ Insider harm
2. Targeted/Incidental harm
3. Collective/Individual harm
30Findings

Outsider Harm
perpetrated by individuals outside of participants’
social circles or the larger transgender community
“The website 8chan—I stumbled across board called
‘transfags’, which is basically bunch of cis men talking
about how they want to brutally murder or hate crime
trans women and encouraging them to kill
themselves.”–P2
31Findings
6/13 participants

“[I deleted my] old name, and just shit that could
be dragged up to disparage me … People will
lurk on my page just to get material to fuel their
hate-filled whatever against me.” –P4
32Findings
Insider Harm
perpetrated by individuals within participant social
circles / LGBTQ community
4/13 participants

“People would message me [on dating
apps] and ask ‘What's in your pants, or
what really are you?’” –P1
33Findings
Targeted Harm
aimed directly at participants
4/13 participants

“[My queer friend’s] family members piled on him …
saying things like … ‘Why would you want gay marriage
if you’re just gonna get AIDS and we’ll have to pay for
your healthcare?’ … His family has not … no one is
speaking to him.” –P8
34Findings
Incidential Harm
harmful content witnessed by participants, but
which was not directed at them specifically
5/13 participants

Research Question 2:
What Do Transgender Individuals and
Technologists Think about Automatic
Gender Recognition (AGR)? 35Findings

AGR Reinforces Binarism
excludes, invalidates, and assures the
misgendering of non-binary identities
“We're excluded from the direction of the future … that’s sorta
what it feels like.” –P7
36Findings
6/13 participants

AGR is a Tool for Surveillance
fear that AGR could be used to persecute the trans
community
“A lot has been illuminated in recent years about abuses of power and
what can happen when people who have whatever bias are in control
of certain surveillance technologies … I’m also very aware of histories of
surveillance being used against queer communities or communities of people
of color.” –P8
37Findings
5/13 participants

AGR Undermines Autonomy
AGR is non-consensual
“[AGR] is (1) completely unnecessary, and (2)
undesired by many people who would be interacting
with the software without their consent.” –P4
38Findings
4/13 participants

AGR Threatens Safety
gender binarism, lack of autonomy, & surveillance
present threat to trans individuals
“It’s easier for a cis person to be like, “Oh, that's wrong.” But it’s more
of a daily fight for a lot of trans folks, so I could see that being …
harmful. And also, it could be a safety issue ... Like the fear of being
outed … That could have job consequences or physical safety
consequences.” –T1
39Findings
13/13 participants

Outline
40

Experiences of Abuse are Salient and
Diverse for Transgender Technology
Users
41Discussion

The Harm of an “External
Gaze”
42Discussion

Intentionality does not
Negate Impact
43Discussion

Outline
44

1. Design to address the
complexity and context of
harm.
45Discussion

2. Intentionality does not
matter when harm is done.
46Discussion

3. Understand that abusers are
users.
47Discussion

4. Provide support for
individuals harmed by or with
technology.
48Discussion

Contributions
● Contributing to experiences of transgender users in HCI
○ (i.e.: Oliver Haimson’s work)
● Building on studies of safety in HCI
○ (i.e.: Tara Matthews et al.’s exploration of safety for survivors of intimate abuse)
● Offering guidelines for designers to diminish harm to trans users
○ (i.e.: Jessica Vitak et al.’s mitigation of harassment of women online)
49Discussion

50
Limitations
Conclusion

Future Work
51Conclusion

Conclusion
52Conclusion

53
Exploring Transgender Individuals’ Experience of Safety with Technology
Master’s Thesis by Morgan Klaus Scheuerman
morgan.klaus@umbc.edu
Thesis Supervisors Stacy M Branham
Foad Hamidi
Thesis Committee Amy Hurst
Casey Fiesler

54
Publications
1. Gender Recognition or Gender Reductionism? The Social Implications of Automatic Gender Recognition System.
Foad Hamidi, Morgan Klaus Scheuerman, Stacy M Branham.
In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '17). Montréal, Canada. April
21-26, 2018.
Best Paper Award
2. “Is Someone There? Do they have a Gun?” How Visual Information about Others Can Improve Personal Safety
Management for Blind Individuals.
Stacy M Branham, Ali Abdolrahmani, William Easley, Morgan Klaus Scheuerman, Erick Ronquillo, and Amy Hurst.
In Proceedings of the 19th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '17).
Baltimore, Maryland. October 30 – November 1, 2017.
3. Learning the Language: The Importance of Studying Written Directions in Designing Navigational Technologies
for the Blind.
Morgan Klaus Scheuerman, William Easley, Ali Abdolrahmani, Amy Hurst, Stacy M Branham.
ACM CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA '17). Denver, Colorado. May 6-
11, 2017

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