#STEM Inclusion at #bps19

The Biophysical Society meeting is less than a month away, and I am excited to share that I will be running a session at the meeting entitled Nurturing a More Inclusive STEM Enterprise by Understanding our Biases (abstract below).

This workshop will take place on Tuesday, March 5 from 1:15 to 2:45 at the Baltimore Convention Center. You must be registered for the meeting to attend this session. We will include a play-act scene of a classroom and are hoping to get an awesome discussion on how we can all be better, more inclusive scientists. #WeCanAllBeAllies

Here’s the Abstract:

We are all biased. Google’s PeopleAnalytics suggests that we as people can only consciously process about one millionth of the information that we receive at any moment. Instead, we rely heavily on our unconscious reasoning abilities to make decisions. Even though we scientists are trained to be objective and evidence based, we, too, use cognitive shortcuts in our every day interactions. This means we rely on our expectation biases, e.g. what we think we think about categories of people, things, situations. This behavior leads to unconscious errors in decision making that leads to discrimination in science against people who do not meet the stereotypical description of what a scientist looks like. This session will approach the phenomenon of unconscious bias as a science problem by examining the data in this area and by discussing tools that we can all use to nurture a more inclusive scientific enterprise. Attendees are encouraged to learn about their own biases by completing the Project Implicit Gender-Science IAT, Race IAT and Sexuality IAT tests at https://implicit.harvard.edu/implicit/.

 

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Hopkins Faculty Promote Better Climate in Machine Learning

Reblogging this 30 March post from the Homewood Women’s Faculty Forum. It is so great to see so many of our colleagues support better climate.

https://hopkinscsw.wordpress.com/2018/03/30/hopkins-faculty-promote-better-climate-in-machine-learning/

On March 30, 122 Hopkins faculty, post-docs, and grad students make a call to promote welcoming environments for women at machine learning conferences. In recognition of egregious behavior at recent conferences, they urge the preeminent conference in the field–called NIPS–to create a stronger code of conduct and to change its name, symbolizing a new era of inclusiveness in the field. The letter is copied below.

For background, please see “Statistics, we have a problem” and Guardian article “Google AI researcher accused of harassment, female data scientists speak of ‘broken system,’” both from December 2017. Additionally, you can see faculty responses from U-Mass and Duke.

Dear NIPS board members,

As researchers in machine learning and data science at Johns Hop kins University, we write as advocates of a welcoming and diverse machine learning community. Recently, some disappointing behavior at NIPS 2017 has come to our attention, and has led one lab here to ban participation in NIPS 2018. We understand that steps are being taken to evaluate changes to the meeting in light of this behavior. In addition, the acronym of the conference is prone to unwelcome puns, such as the perhaps subversively named pre-conference “TITS” event and juvenile t-shirts such as “my NIPS are NP-hard”, that add to the hostile environment that many ML researchers have unfortunately been experiencing.

These incidents have brought up uncomfortable memories for some of us whose career paths have been affected by unwelcoming or harassing behavior. NIPS is at a time of significant expansion and change. We believe that serious actions are essential for the continuing health of the community.

We are aware that the NIPS board has appointed Diversity and Inclusion chairs and i s working towards a strengthened code of conduct to set behavioral expectations. As you know, templates for such codes of conduct are available from other conferences. We support this move, and further hope that conference attendees will be actively encouraged to speak up when they observe social behavior that may make other attendees uncomfortable. We also fully expect that this code of conduct will specify consequences for harassment and are in keeping with recent policy changes from NSF that mandate reporting of harassment.

We also recommend a more radical reform: rebranding of the meeting, including a change to the name of the conference. Certainly the NIPS name has a long and distinguished history, and it is an unfortunate coincidence that it is vulnerable to sexual puns. Changing the name at this time could serve as a powerful symbolic move which, in conjunction with other changes, would signal the Board’s commitment to improving the culture of the field and making the conference a leader in inclusion.

We appreciate that NIPS has hosted and prominently featured the Women in Machine Learning and Black in AI workshops, and we look forward to further efforts to welcome contributors to the field from a range of backgrounds. Our own ML community at Johns Hopkins includes and is taking active measures to welcome people with diverse gender identity and expression, sexual orientation, age, disability, physical appearance, body size, race, ethnicity, nationality and national origin, and religion. Locally, Johns Hopkins just announced its progress report on Diversity and Inclusion; we are taking steps to ensure harassment-free and equal inclusion within our data science community at JHU. We hope to eliminate disincentives to participation in ML research at our own university, and would be glad to help with efforts to do the same in the field at large.

Thank you for your concern and quick action.

Sincerely,
1. Joel S. Bader, Professor, Department of Biomedical Engineering
2. Brian Caffo, Professor, Department of Biostatistics
3. Jason Eisner, Professor, Computer Science
4. Michael L. Falk, Vice Dean for Undergraduate Education, Professor, Departments of
Materials Science and Engineering, Mechanical Engineering, and Physics
5. Donald Geman, Professor, Applied Mathematics and Statistics
6. Jeffrey Gray, Professor, Chemical & Biomolecular Engineering
7. Gregory D. Hager, Mandell Bellmore Professor of Computer Science and Director of the
Malone Center for Engineering in Healthcare
8. Philipp Koehn, Professor, Department of Computer Science
9. Jeffrey Leek, Professor, Departments of Biostatistics and Oncology
10. Daniel Q. Naiman, Professor, Department of Applied Mathematics and Statistics
11. Gary L. Rosner, Professor, Departments of Oncology and Biostatistics, Chair of the
Division of Biostatistics and Bioinformatics and Director of the Research Program of
Quantitative Sciences of the Sidney Kimmel Comprehensive Cancer Center
12. Alexander Szalay, Bloomberg Distinguished Professor, Physics and Computer Science
13. René Vidal, Professor of Biomedical Engineering, Director of Johns Hopkins
Mathematical Institute for Data Science (MINDS)
14. Laurent Younes, Professor and Chair, Department of Applied Mathematics and Statistics
15. Alan Yuille, Bloomberg Professor, Cognitive Science and Computer Science
16. Mark Dredze, John C Malone Associate Professor, Department of Computer Science
17. Peng Huang, Associate Professor, Departments of Oncology and Biostatistics
18. Rachel Karchin, The William R. Brody Faculty Scholar, Associate Professor, Departments
of Biomedical Engineering and Oncology
19. Feilim Mac Gabhann, Associate Professor, Department of Biomedical Engineering
20. Luigi Marchionni, Associate Professor, Department of Oncology
21. Michael C. Schatz, Bloomberg Distinguished Associate Professor of Computer Science
and Biology
22. Cristian Tomasetti, Associate Professor, Departments of Oncology and Biostatistics
23. Ravi Varadhan, Associate Professor of Biostatistics
24. Hao Wang, Associate Professor, Department of Oncology
25. Sarah J. Wheelan, Associate Professor, Department of Oncology
26. Raman Arora, Assistant Professor, Department of Computer Science
27. Alexis Battle, Assistant Professor of Biomedical Engineering
28. Najim Dehak, Assistant Professor, Department of Electrical and Computer Engineering
29. Elana J. Fertig, Assistant Professor of Oncology, Associate Director of the Research
Program in Quantitative Sciences of the Sidney Kimmel Comprehensive Cancer Center
30. Loyal A. Goff, Assistant Professor of Neuroscience & Genetic Medicine
31. Stephanie Hicks, Assistant Professor, Department of Biostatistics
32. Andrew Jaffe, Assistant Professor, Department of Mental Health
33. Kai Kammers, Assistant Professor, Department of Oncology
34. Emily Riehl, Assistant Professor, Department of Mathematics
35. Daniel P. Robinson, Assistant Professor, Department of Applied Mathematics and
Statistics
36. Suchi Saria, Assistant Professor of Computer Science, Statistics and Health Policy
37. Robert B. Scharpf, Assistant Professor, Departments of Oncology and Biostatistics
38. Ilya Shpitser, John C Malone Assistant Professor of Computer Science and Biostatistics
39. Benjamin Van Durme, Assistant Professor, Department of Computer Science
40. Zheyu Wang, Assistant Professor, Departments of Oncology and Biostatistics
41. Yanxun Xu, Assistant Professor, Department of Applied Mathematics and Statistics
42. William Gray-Roncal, Assistant Research Professor, Department of Computer Science
43. Bahman Afsari, Instructor, Department of Oncology
44. Narges Ahmidi, Assistant Research Scientist, Malone Center for Engineering in
Healthcare
45. Richard Brown, Associate Teaching Professor, Department of Mathematics
46. Benjamín Béjar, Associate Research Scientist, Department of Biomedical Engineering
47. Helen Cromwell, Administrative Manager, Department of Oncology, Biostatistics
48. Ludmila Danilova, Research Associate, Departments of Oncology and Biostatistics
49. Wei Fu, Senior Biostatistician, Department of Oncology and Biostatistics
50. Rumen Kostadinov, Research Associate, Department of Pediatric Oncology
51. Sean Kross, Associate Faculty, Department of Biostatistics
52. Anand Malpani, Assistant Research Scientist, Malone Center for Engineering in
Healthcare
53. Alisa Moore, Administrative Coordinator, Departments of Oncology and Biostatistics
54. Sara More, Associate Teaching Professor, Department of Computer Science
55. Bongsoo Park, Research Associate, Department of Environmental Health and
Engineering
56. Christine Piatko, Assistant Research Professor, Department of Computer Science
57. Thomas Sherman, Biostatistician, Department of Oncology
58. James C. Spall, Research Professor, Department of Applied Mathematics and Statistics
59. Tamas Budavari, Department of Applied Mathematics and Statistics
60. Wikum Dinalankara, Postdoctoral Fellow, Department of Oncology
61. Shannon E. Ellis, Postdoctoral Fellow, Department of Biostatistics
62. Guilherme Starvaggi Franca, Postdoctoral Fellow, Center for Imaging Science
63. Peter F. Hickey, Postdoctoral Fellow, Department of Biostatistics
64. Jonathan P. Ling, Postdoctoral Fellow, Department of Neuroscience
65. Daniel Malinsky, Postdoctoral Fellow, Department of Computer Science
66. Daniel Mendat, Postdoctoral Fellow, Department of Electrical and Computer
Engineering
67. Garrett Nicolai, Postdoctoral fellow, Department of Computer Science
68. Genevieve Stein-O’Brien, Postdoctoral Fellow, Department of Oncology Biostatistics and
Institute of Genomic Medicine
69. Luciane Tsukamoto Kagohara, Department of Oncology
70. Zhihui Zhu, Postdoctoral fellow, the Center for Imaging Science
71. Jonathan Andersen, Research Assistant & Student, Undergraduate Program in
Neuroscience
72. Jonathan Augustin, PhD Candidate, Biochemistry, Cellular and Molecular Biology
Program; Neuroscience Department
73. Daniel N. Baker, Graduate Student, Department of Computer Science
74. Leandros Boukas, PhD Candidate, Institute of Genetic Medicine
75. Vikram Chandrashekhar, PhD Student, Department of Biomedical Engineering
76. Nanxin Chen, PhD Student, Department of Electrical and Computer Engineering
77. Emily Davis, PhD Student, Institute of Genetic Medicine
78. Kipper Fletez-Brant, PhD Candidate, Institute of Genetic Medicine
79. Yixin Gao, PhD Candidate, Department of Computer Science
80. Yuan He, PhD candidate, Department of Biomedical Engineering
81. Rachel Hegeman, Graduate Student, Department of Computer Science
82. Katharine Henry, PhD Candidate, Department of Computer Science
83. Jonathan D. Jones, Graduate Student, Department of Electrical and Computer
Engineering
84. Gaurav Kumar, Graduate Student, Department of Computer Science
85. Connor Lane, Graduate Student, Department of Computer Science
86. Natalie Larsen, Graduate Student, Department of Computer Science
87. Adam Li, PhD Student, Department of Biomedical Engineering
88. Rebecca Marvin, Graduate Student, Department of Computer Science
89. Effrosyni Mavroudi, PhD Candidate, Department of Biomedical Engineering
90. Molly O’Brien, Graduate Student, Department of Computer Science
91. Princy Parsana, PhD candidate, Department of Computer Science
92. Nathan Roach, Graduate Student, Department of Biology
93. Ashis Saha, Graduate Student, Department of Computer Science
94. Evan Schwab, PhD Candidate, Department of Electrical and Computer Engineering
95. Benjamin D. Shapiro, Graduate Student, Department of Computer Science
96. Eli Sherman, Graduate Student, Department of Computer Science
97. Rachel Sherman, PhD Student, Department of Computer Science
98. Heather C. Wick, PhD Candidate, Institute of Genetic Medicine
99. Siddharth Mahendran, PhD Candidate, Department of Electrical and Computer
Engineering
100. Sebastian J. Mielke, PhD Student, Department of Computer Science
101. Anirbit, Department of Applied Mathematics and Statistics
102. Leslie Myint, PhD Candidate, Department of Biostatistics
103. Razieh Nabi, Graduate Student, Department of Computer Science
104. Arun Asokan Nair, Graduate Student, Department of Electrical and Computer
Engineering
105. Carolina Pacheco, Graduate Student, Department of Biomedical Engineering
106. Srivathsa Pasumarthi, Graduate Student, Department of Computer Science
107. Chris Paxton, PhD Candidate, Department of Computer Science
108. Adam Poliak, PhD Candidate, Department of Computer Science
109. Sachi Sanghavi, Graduate Student, Department of Cognitive Science
110. Kayode Sanni, PhD Candidate, Department of Electrical and Computer
Engineering
111. Peter Schulam, PhD Candidate, Department of Computer Science
112. Ayushi Sinha, PhD Candidate, Department of Computer Science
113. David Snyder, PhD Candidate, Department of Computer Science
114. Aditya Upadhyayula, Graduate Student, Department of Psychological and Brain
Sciences
115. Long Wang, PhD Candidate, Department of Applied Mathematics and Statistics
116. Zach Wood-Doughty, Graduate Student, Department of Computer Science
117. Shijie Wu, Graduate Student, Department of Computer Science
118. Xiang Xiang, PhD Candidate, Department of Computer Science
119. Fangzheng Xie, PhD Candidate, Department of Applied Mathematics and
Statistics
120. Florence Yellin, PhD Candidate, Department of Mechanical Engineering
121. Corby Rosset, Alumnus ‘17, M.S.E & B.S. Computer Science
122. Xiaoge Julia Zhang, Alumnus ‘17, PhD & MHS, Department of International
Health, Department of Biostatistics

White Privilege. Male Privilege. In Science.

The next workshop is scheduled for Tuesday, April 12th at 5:30pm in Gilman 55. Professor Jeffrey Gray (ChemBE Dept) will lead a discussion on white male privilege in science. Pizza and drinks provided.

When one considers race and gender equity in science, discussions often focus around barriers faced by women and minorities.  The inverse idea, that men and white people have specific advantages, or “privilege,” in their scientific careers, can be challenging because it suggests that individual achievement arises not only due to individual efforts but also due to structural advantages in the scientific culture for white people and men.

Join us for this workshop where we will discuss the concept of “privilege” specifically in the scientific and academic spheres.  We will review data from social scientists studying privilege and data on NIH funding rates, share personal experiences, and consider appropriate and practical responses.

Suggested reading for the workshop:

1. Peggy McIntosh, “Unpacking the Invisible Knapsack,” Peace and Freedom Magazine (1989).

Other relevant papers that will be presented:

2. Mujcic and Frijters, “Still Not Allowed on the Bus: It Matters If You’re Black or White!” IZA Discussion Paper No. 7300 (2013).

3. Ginther et al., “Race, Ethnicity, and NIH Research Awards,” Science, (2011).

Questions?  Email Prof. Gray (jgray@jhu.edu).  No RSVP required, but if you know you’ll make it, drop Prof. Gray a note for the pizza and drink count.

AchievingGenderEquityFlyer

Next Workshop Announcement: Tues Nov 17, 2015

By popular demand, the topic of mentoring will be covered.

Place: Maryland 109

Time: 6 pm

Pizza will be served.

Seminar on Enhancing Women in STEM

Karen Fleming will present a seminar entitled “Enhancing the Potential of Women in STEM”.

This is our main opening event sponsored by our award from the Johns Hopkins University Diversity Leadership Council. The seminar will take place on Thursday, Oct 1 from 3:30 to 4:30 in Maryland Hall and will serve to kick off the academic year of journal club discussion in that department.

This event is open to the public!

Workshop Today!

Can Evidence Impact Attitudes? A study on the reaction to the 2012 Handelsman paper.

Details here.

Maryland 109, 6pm

September 15, 2015 Workshop: Can Evidence Impact Attitudes?

We will kick off the fall with a workshop on the question of whether or not evidence can impact attitudes. This is a really interesting paper that analyzes the public reactions to the evidence of gender bias in STEM fields.

The workshop will take place on Tuesday September 15 at 6pm in Maryland 109. If it is a nice day, we’ll be able to open the double doors and enjoy the fresh air. Pizza and beverages will be served.

Come prepared to discuss the following paper:

Corinne A. Moss-Racusin1, Aneta K. Molenda1, and Charlotte R. Cramer (2015) Can Evidence Impact Attitudes? Public Reactions to Evidence of Gender Bias in STEM Fields Psychology of Women Quarterly39: 194-209.

If you followed the workshops last year, you will be familiar with the Handelsman 2012 PNAS study whose reaction this workshop paper discusses. If not, it may help to review the 2012 study. The bottom line is that the 2012 article showed that both male and female faculty show an unconscious gender bias that favors male job applicants. This was true for US STEM faculty of all ages and over several disciplines. After its publication, there was quite a bit of press on the article, and the paper we will discuss this fall considers the reactions of the public.

Did the public believe the original study? Or did the evidence lead to a negative backlash? Could reactions be categorized by gender or anything else? We will think about and discuss these questions in this fall’s inaugural workshop on overcoming bias and barriers to women in STEM.

If you think you’ll come and want to eat pizza, please RSVP to me (Karen.Fleming@jhu.edu) so I can be sure to order enough!

Workshop Today!

I’m looking forward to a lively discussion at the workshop this afternoon (Apr 21) in Shaffer 100 at 6pm.

Panel Speakers include:

Trina Schroer, Professor, JHU KSAS Dept. Biology
Dorothy Beckett, Professor, University of Maryland Dept. Chemistry
Jie Xiao, Assoc. Professor, JHMI Dept. Biophysics & Biophysical Chemistry
Lori Graham-Brady, Professor, JHU WSE Dept. Civil Engineering
Christine Newman, Asst. Dean for Engineering Education, JHU WSE

After a brief presentation you’ll be able to ask them questions about their experiences. This will hopefully get a conversation going about what you can do to enhance your career success in STEM.

CORRECTION: Faculty Panel on April 21st!!!

Our apologies, the title of the last post on the faculty panel had the incorrect date listed. The Faculty Panel is on April 21st at 6pm in Shaffer 100.

April 21st, 2015: Faculty Panel on Empowering Women in STEM

This is the final 2014-2015 Workshop in which we will recap gender issues that are affecting women’s scientific careers and will hear from prominent and successful women in science.

To accommodate all attendees, the location for this workshop has been moved to Shaffer Hall, room 100, on April 21st at 6pm.

Panel Speakers include:
Trina Schroer, Professor, JHU KSAS Dept. Biology
Dorothy Beckett, Professor, University of Maryland Dept. Chemistry
Jie Xiao, Assoc. Professor, JHMI Dept. Biophysics & Biophysical Chemistry
Lori Graham-Brady, Professor, JHU WSE Dept. Civil Engineering
Christine Newman, Asst. Dean for Engineering Education, JHU WSE

Topics to be discussed will include confidence differences in women and men, implicit biases held by both men and women, gender-expected behaviors & stereotypes, and bias in hiring & evaluation practices.

Please spread the word about these workshops. Here is a printable flyer for the April 2015 meeting 2015_0421_FacultyPanel_Flyer. Pizza and beverages will be served. If you think you will attend, RSVP Karen so she can order enough pizza. It would be a bummer if we ran out of pizza!