Costolo, Dick, 148
Cramer, Jim, 158
Creepingbear, Shane, 53–56
Criado-Perez, Caroline, 156
criminal justice
and COMPAS, 119–121, 125–129, 136, 145
predictive policing software, 102
sentencing algorithms for, 10
culture fit, 24–25, 25, 189
curators, of Trending Facebook feature, 165–169, 172
daily active users (DAUs) metric, 74, 97–98
Daniels, Gilbert S., 39
Dash, Anil, 9, 187
data. See personal data; proxy data; training data
data brokers, 101–104
Data Detox Kit, 102–103
DAUs (daily active users) metric, 74, 97–98
default settings
and “average” users, 38–39
bias in, 35–38, 61
and cultural norms, 198
default effect, 34, 65
defined, 34–35
and Facebook, 108–109
and gender of game avatars, 35–36
and marginalized populations, 37, 66
and Uber’s location tracking, 106, 108
Delano, Maggie, 28–31, 33
delight, 8, 79, 90, 93–94, 96
democracy, and tech industry, 9–10, 149, 154, 165–166
demographics, and development of personas, 45–47
deportations, 195, 200
design aesthetics, 143–144
Design for Real Life (Meyer and Wachter-Boettcher), 40, 64, 96
design teams
and “average” users, 38–40, 44, 47
and default settings, 34–35
and delight, 94
devaluing of women’s roles in, 21
and diversity/performance correlation, 184–186
and form fields, 49–51
and Glow app, 30
and ill-considered Twitter updates, 160
and inattentional blindness, 95–97
lack of diversity in, 11, 14, 16–17, 20, 28, 35
and personas, 28, 32–33, 44
and photo autotagging, 136
software reflecting values of, 149–150
and stress cases, 40–44, 90, 96
and Year in Review Facebook feature, 5
Deszö, Cristian, 186
digital forms
and collection of gender information, 62–66
and cultural norms, 198
definition of, 51–52
demanding accountability in, 75
microaggressions in, 70–73
Nextdoor’s Crime and Safety report, 67–71, 71, 73–74
and problems with personal names, 40, 52–59, 72, 75
and racial bias, 50, 59–62
and sexual abuse, 49–50
and titles, 66–67, 71
Disney, 158
disruption, tech industry’s desire for, 8–9, 150, 184, 191–192
diversity. See also gender bias; racial bias
companies’ efforts to improve, 22–26, 182–184
correlation with performance, 184–186
in design teams, 11, 14, 16–17, 20, 28, 35
and Facebook, 19, 21–22, 23–25
and innovation, 186
and Slack, 190–191
tech industry’s lack of, 9, 11, 14, 16, 18–20, 116, 135–136, 150, 157–158, 169, 171–176, 182, 196
and Twitter, 155–156
Dorsey, Jack, 155–156
edge cases, 38–40, 50, 137
Electronic Frontier Foundation, 108
The End of Average (Rose), 38–39
engagement, as goal of interaction design, 74
ethics
at Facebook, 172
and Gamergate, 157
and meritocracy of tech, 176, 189
and racial bias on Nextdoor, 74
and tech products’ ethical blunders, 6, 13, 26, 199
at Uber, 108, 180, 187, 191–192
Etsy, 32–33, 32
Eve by Glow app, 31, 31, 33
Eveleth, Rose, 137
Facebook
and Americans’ online status, 2
artificial intelligence feature, 171
and cares about us metric, 97
collection of gender information by, 63–66, 63, 64
creators’ values and biases, 168–172
and data brokers, 104
default privacy settings, 108–109
and fake news, 165–166, 199
Friends Day feature, 84–85
and gender of profile picture avatars, 36
and the Hacker Way, 170–171
and Halloween icons, 80
and journalism industry, 199
Moments feature, 85, 97
News Feed feature, 144, 168–169
On This Day feature, 83–84, 97
and presidential election of 2016, 10
problems with personal names, 53–59, 75
and proxy data use, 112
and selection of ads users see, 10
Trending feature, 149, 165–169, 172
and value of user data, 97
What Facebook Thinks You Like browser extension, 103
and workforce diversity, 19, 21–22, 23–25
Year in Review feature, 4–6, 5, 79, 83
facial-recognition software, 137
Fairness, Accountability, and Transparency in Machine Learning (FAT/ML), 128
fairness criteria, 127–128, 136
Fake, Caterina, 171–172
fake news stories, 10, 149, 165–166, 170, 199
Ferguson, Missouri protests, 163, 166
fertility, and menstrual tracking apps, 28–30, 33
financial performance, and diversity, 186
Fisher, Carrie, 148
Flickr, 135, 155, 171
forms. See digital forms
Fowler, Susan, 177–180
free speech, 154, 157, 164
Friedler, Sorelle, 128, 136, 145–146
Friends Day, 84–85
Fugett, Dylan, 119–120
Gamergate, 151, 154, 157
Gates, Bill, 182
gay people. See LGBTQ community
gender bias. See also diversity
and companies’ personal name policies, 54–59
and default settings, 35–38
devaluing of women’s roles, 20–21, 176
in edge cases, 38
and Etsy, 32–33
and form field design, 50, 71
and game avatars, 35–36
and Google’s use of proxy data, 109–112
in menstrual tracking apps, 28–33
and meritocracy of tech, 173–176, 180
and negging, 91–92
and normalizing TV programming, 47–48
and online abuse and harassment, 147–154, 156–160
and Reddit, 161–163
Slack’s lack of, 190–191
and smartphone personal assistants, 6–7, 7, 36–37
and startups’ venture capital, 175
and team performance, 184, 186
and tech educational pipeline, 21–26, 181–184
in tech industry, 6–7, 7, 13–21
and Twitter’s executive leadership, 157–158
at Uber, 108, 177–181, 187–189
and word-embedding systems, 138–140
and Milo Yiannopoulos, 150–154, 157
gender information, companies’ collection of, 62–66
Ghostbusters II (film), 150–151
GitHub, 175
Gizmodo, 165–166, 169
Glass Room installation, 101–102
Global Positioning System (GPS), 105
Glow app, 29–33, 30
Gmail, and collection of gender information, 62
Gonzalez-Cameron, Aimee, 72
Google
and algorithms, 123, 136, 144
design aesthetic of, 143
and pervasiveness of technology, 3
and photo autotagging, 129
–130, 129, 130, 132–133, 135–138, 145
photo memories feature, 85
privacy policies of, 109
purchase of YouTube, 2
sexual harassment at, 178
smartphones of, 6
trustworthiness of, 142–143
use of proxy data, 109–112
and Word2vec, 138–142, 145
and workforce diversity, 19–20
Grace Hopper Celebration of Women in Computing, 22–23
Grant, Heidi, 189
Greenshpan, Moshe, 137
Grey, Jacqui, 189
Greyball scandal, 199
Grey’s Anatomy (TV show), 47
Groeger, Lena, 35
the Hacker Way, 170–171
Hampton Creek’s Just Mayo, 187
harassment online, 59, 147–154, 156–164, 170
hashtags, 156
Hatzenbuehler, Mark L., 198
Ho, Ed, 152
Ho, Kevin, 30
Hoffman, Kevin M., 87–88
Holder, Eric, 178, 180
Hon, Calvin, 77–78
Hon, Dan, 77–78, 82
Horseman, Emily, 73
How to Get Away with Murder (TV show), 47
Huffman, Steve, 161
humor. See misplaced celebrations and humor
Hunch app, 171
Huston, Cate, 183
identity
and companies’ collection of personal data, 102
and companies’ name policies, 55–59, 71
and digital forms, 60–65, 71, 73, 75
and edge cases, 137
and Facebook’s use of proxy data, 113–114
and lack of design team diversity, 196
and stress cases, 38, 40
Immigration and Customs Enforcement, 200
inattentional blindness, 94–96
innovation, and diversity, 186
Instagram, 3
interaction design, 52, 73–74
In The Plex (Levy), 143
iPhones, 2, 34, 105–108. See also smartphones
Jeong, Sarah, 161–162, 164
Jobs, Steve, 182
Jones, Leslie, 151
Jones, Tim, 108
Joy, Erica, 17
Kage, Earl, 134
Kalanick, Travis, 178–179
Kelly, Megyn, 166
Kiefer Lee, Kate, 89–90
Kills the Enemy, Robin, 54
Kodak, 133–135
Kramer, Adelaide, 153
LaFrance, Adrienne, 36
Lamont, Amélie, 17
law enforcement
and COMPAS, 119–121, 125–129, 136, 145
predictive policing software for, 102
Lee, Nancy, 19
lesbian people. See LGBTQ community
Levchin, Max, 30
Levy, Stephen, 143
LGBTQ community. See also marginalized populations
and companies’ collection of gender information, 62–64
and companies’ name policies, 54–55, 58
and edge cases, 38
and Etsy, 32–33
importance of tech to, 195–197
and normalizing TV programming, 48
and same-sex marriage, 196–198
and Milos Yiannopoulos, 153
Lil Miss Hot Mess, 55
location tracking, 105–108
Lone Hill, Dana, 54
McAdoo, Greg, 175
McBride, Sarah, 175
machine-learning products, 121, 128, 132, 135, 136, 140, 146
Mack, Arien, 95
McKesson, DeRay, 81
Mad Money (TV show), 158
MailChimp, 89–90
marginalized populations
and default settings, 37, 66
and digital forms, 51, 61, 72, 75
and digital products’ personal data collection, 116–117
importance of tech to, 195–197
market negging, and opt-ins, 91–92, 97
Martin, Erik, 162–163
Martin, Trayvon, 141
Martinez, Chris, 30
Maslow, Abraham, 3
maternity policies, 16
MAUs (monthly active users) metric, 74, 97–98
May, Rob, 139
Mayer, Marissa, 143
Medium publishing platform, 87–88, 180
menstrual cycle tracking apps, 28–33
Mental Models (Young), 46
meritocracy
and ethics, 176, 189
tech industry as, 173–177, 180
Uber as, 180
Messer, Madeline, 35, 37
metadata from emails, 102
Meyer, Eric, 4–5, 40, 64, 79, 82, 89, 96
Meyer, Rebecca, 4–5, 5
microaggressions, 70–73
Microsoft, 6, 36–37
Miley, Leslie, 158
misplaced celebrations and humor, 78–85, 87–90, 114–115, 200
Moments Facebook feature, 85, 97
monoculture, tech industry as, 188–189
monthly active users (MAUs) metric, 74, 97–98
Mosseri, Adam, 168
Mozilla, 102
multiracial populations, and form field design, 60–62
mystification of tech, 9, 11–12, 26, 143, 188, 191–193, 199
National Public Radio (NPR), 1, 40–44
National Security Agency (NSA), 102
National Suicide Prevention Lifeline, 6
Native Americans, Facebook’s rejection of names of, 53–57
natural language processing, 138
negging, 91–92, 97
Neighbors for Racial Justice, 69
Netflix, 144
neural networks, 131–133, 138
News Feed Facebook feature, 144, 168–169
Nextdoor app, 67–71, 71, 73–75
Noble, Safiya, 10, 113
non-binary people. See LGBTQ community
Northpointe, 120, 125–127
Note to Self podcast, 130, 171
Nye, Bill, 1
Ohanian, Alexis, 161, 164
O’Neil, Cathy, 112, 126
online time, growth of Americans, 1–3
On This Day Facebook feature, 83–84, 97
opt-in pop-ups, 90–92, 97
oversight, tech industry’s desire to avoid, 187–189, 199
Page, Shirley, 133
Palantir, 199–200
Pancake, Beth, 57
Pao, Ellen, 162
Parker, Bernard, 119–120
PayPal, 175
Penny, Laurie, 153
personal data
and algorithmic systems, 145
collected during mobile usage, 116–117
digital products designed to collect, 105–117
tech industry’s responsibility for, 146
value of, 96–98
personalization of online content, 86–90, 99
personal names, digital forms’ problems with, 40, 52–59, 71–72, 75
personas, 27–33, 29, 44–47, 110
Phillips, Katherine W., 184–186
photo autotagging, 129–130, 129, 130, 132–133, 135–138, 145
pickup artist (PUA) community, 91–92
Pinterest, 42
political bias, and Trending Facebook feature, 165–167, 169
Practical Empathy (Young), 46
privacy
and digital products’ collection of personal data, 115, 117
and Facebook, 108–109
and Google, 109
and Uber, 107–108
ProPublica, 103, 112–113, 120, 126–127
proxy data, 109–114
PUA (pickup artist) community, 91–92
PureGym, 6
push notifications, 198
Quantified Self movement, 28
queer people. See LGBTQ community
Quinn, Zoe, 157
racial bias. See also diversity
and COMPAS, 120, 125–129, 136
and default se
ttings, 37, 61
and facial-recognition software, 137
and form field design, 50, 59–62
and Google’s photo autotagging, 129–130, 129, 130, 132–133, 135–138
and meritocracy of tech, 173–174, 176, 180
as microaggressions, 72–73
and Nextdoor’s Crime and Safety report, 68–71, 71, 73–74
and normalizing TV programming, 47–48
and personas, 45–46
and photographic technology, 133–135
and proxy data, 112–113
and Reddit, 161–163
and team performance, 184–186
and tech educational pipeline, 21–26, 181–184
in tech industry, 13, 17–18, 20, 200
on Twitter, 151, 154
and Twitter’s executive leadership, 157–158
and word-embedding systems, 141
rape, and smartphone personal assistants, 6–7, 7
recruiting, 23–26
Reddit, 149–150, 160–164, 166
regulation, tech industry’s desire to avoid, 187–189, 199
Relman, John, 112
retweets, 156
Rhimes, Shonda, 47–48
Rock, David, 189
Rock, Irvin, 95
Roof, Dylann, 141–142
Rooney, Mickey, 7, 8
Rooney, Sally, 85–86, 98
Rose, Todd, 38–39, 47
Ross, David, 186
Roth, Lorna, 134
Sacks, David, 175
Salesforce, 158
same-sex marriage, 196–198
Samsung, 6, 36
Sandberg, Sheryl, 23
Sankin, Aaron, 163
Sarkeesian, Anita, 157
Savage, Tag, 98
Scandal (TV show), 47
Seamless app, 114
search engines, 10, 138, 141–142. See also specific search engines
Selby, Louise, 6, 66
Sequoia Capital, 175
sexism. See gender bias
sexual abuse, and form fields,
49–50
“Shirley Cards,” 133, 134
Shrill (West), 149
Silicon Valley. See tech industry
Silicon Valley (TV show), 8–9
Singhal, Amit, 178
Siri
failure to understand crises, 6–7, 7
female voice of, 36
teasing humor of, 88–89
Sister Roma, 55
Slack app, 2, 189–191
Slate, 5, 61, 168
smartphones
and gender bias, 6–7, 7, 36–37
screen size limitations of, 42
and Uber’s location tracking, 105–108
use of by marginalized populations, 116–117
Snapchat, 7–8, 8, 37
South by Southwest Interactive conference, 155
Sparapani, Grace, 8
Spotify, 62
Srebro, Nathan, 127
startups, 16–17, 27, 98, 107, 174–175, 192
Steinem, Gloria, 66
Sterling, Alton, 81
stress cases, 38, 40–44, 90, 96
subreddits, 149, 160–164
suicide, 6–7, 197–198
Sweeney, Miriam E., 142
Tactical Technology Collective, 102