As a large scientific and technical community that has a direct impact on many people from different backgrounds around the world, Diversity and Inclusion are crucial for the data management community. ACM explains these goals as follows. Diversity is achieved when the individuals around the table are drawn from a variety of backgrounds and experiences, leading to a breadth of viewpoints, reasoning, and approaches (also referred to as \u201cthe who\u201d). Inclusion is achieved when the environment is characterized by behaviors that welcome and embrace diversity (\u201cthe how\u201d). Both are important in our writing and other forms of communication, such as posters and talks.<\/p>\n<\/div>\n<\/div>\n
[\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column][vc_tta_accordion][vc_tta_section title=”Inclusion” tab_id=”1712757167214-ba7819dc-503c”][vc_column_text]<\/p>\n
Be mindful of not using language or examples that further the marginalization, stereotyping, or erasure of any group of people, especially historically marginalized and\/or under-represented groups (URGs) in computing. Of course, exclusionary or indifferent treatment can arise unintentionally. Be vigilant and actively guard against such issues in your writing. Reviewers will also be empowered to monitor and demand changes if such issues arise in your submissions. Here are some examples of such issues for your benefit:<\/p>\n
Examples of exclusionary and other non-inclusive writing to consider avoiding:<\/h4>\n\n- Implicit assumption:<\/b>\u00a0An example of database integrity constraints: \u201cEvery person has a mother and a father.\u201d This example is exclusionary and potentially hurtful to people from single-parent households and people with same-sex parents.<\/li>\n
- Oppressive terminology:<\/b>\u00a0Using the term \u201cMaster-Slave\u201d to describe a distributed data system architecture. This can be hurtful to people whose families have suffered the inhumanity of enslavement. A good source of alternative terms to oppressive language often used in computer science can be found in\u00a0this article<\/a>.<\/a><\/li>\n
- Marginalization of URGs:<\/b>\u00a0An example of attribute domains: \u201cThe Gender attribute is either Male or Female.\u201d This example is exclusionary and potentially hurtful to people who are intersex, transgender, third gender, two-spirit, agender, or have other non-binary gender identities.<\/a><\/li>\n
- Lack of accessibility:<\/b>\u00a0Using color alone to convey information in a plot when good alternative data visualization schemes exist. This can be exclusionary to people who are color-blind. Please consider using patterns, symbols and textures to emphasize and contrast visual elements in graphs and figures, rather than using colors alone. Use a color-blind friendly palette that is designed with accessibility for visually impaired people. Avoid bad color combinations such as green\/red or blue\/purple.<\/a><\/li>\n
- Stereotyping:<\/b>\u00a0Reinforcing gender stereotypes in names or examples of roles, e.g., using only feminine names or presentations for personal secretary or assistant roles.<\/a><\/li>\n<\/ul>\n
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Going further, please also consider actively raising the representation of URGs in your writing. Diversity of representation helps create an environment and community culture that could ultimately make our field more welcoming and attractive to people from URGs. This is a small but crucial step you can take towards celebrating and improving our community\u2019s diversity.<\/p>\n
Examples of infusing diversity into writing to consider adopting:<\/h4>\n\n- Embracing different cultures:<\/b>\u00a0Names of people are a visible way to enhance diversity of representation in writing. Instead of reusing overused names in computing such as Alice and Bob, consider using names from a variety of languages, cultures, and nationalities, e.g., Alvarez and Bano. Avail of the many online resources on this front for ideas, e.g.,\u00a0<\/a>this article<\/a>\u00a0on names across different cultures.<\/li>\n
- Embracing differences in figures:<\/b>\u00a0Depictions of people or people-like icons in illustrations are also a good avenue to enhance diversity of representation. Consider depicting people of different gender presentations, skin colors, ability status, and other visible attributes of people.<\/li>\n
- Embracing gender diversity in pronouns:<\/b>\u00a0Consider using a variety of gender pronouns across your named examples consciously, including \u201che\/him\/his,\u201d \u201cshe\/her\/hers,\u201d and \u201cthey\/them\/theirs\u201d. Likewise, consider using gender-neutral nouns when referring to generic roles, e.g., \u201cchairperson\u201d or just \u201cchair\u201d instead of \u201cchairman,\u201d and gender-neutral pronouns for such roles.<\/li>\n<\/ul>\n
[\/vc_column_text][\/vc_tta_section][vc_tta_section title=”Responsibility” tab_id=”1712757272142-f3a599fe-3dfc”][vc_column_text]Finally, if your work involves data-driven techniques that make decisions about people, please consider explicitly discussing whether it may lead to disparate impact on different groups, especially URGs. Consider discussing the ethical and societal implications. For example, see this article discussing the potential for disparate impact of facial recognition in healthcare and strategies to avoid or reduce harm. This SIGMOD Blog article also gives a comprehensive overview of various dimensions and approaches for responsible application of data management ideas. We hope our community can help permeate this culture of responsibility and awareness about potentially harmful unintended negative consequences of our work within the larger computing landscape.[\/vc_column_text][\/vc_tta_section][vc_tta_section title=”Acknowledgments and Further Reading” tab_id=”1712757294168-00141cda-5ea7″][vc_column_text]<\/p>\n
\n- ACM Diversity and Inclusion:\u00a0Webpage<\/a><\/li>\n
- ACM SIGMOD Blog article on \u201cData, Responsibly\u201d:\u00a0Webpage<\/a><\/li>\n
- AMA Journal of Ethics article on \u201cWhat Are Important Ethical Implications of Using Facial Recognition Technology in Health Care?\u201d:\u00a0Webpage<\/a><\/li>\n
- Article on \u201cInclusive CS Examples\u201d:\u00a0Webpage<\/a><\/li>\n
- Article on \u201cTerminology, Power and Oppressive Language\u201d:\u00a0Webpage<\/a><\/li>\n
- Helpful materials from UCSD CSE Diversity, Equity, and Inclusion Committee: Webpage<\/a><\/li>\n
- NeurIPS CFP on Broader Impact Statement:\u00a0Webpage<\/a><\/li>\n
- Wikipedia listing of names across cultures:\u00a0Webpage<\/a><\/li>\n<\/ul>\n
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Going further, please also consider actively raising the representation of URGs in your writing. Diversity of representation helps create an environment and community culture that could ultimately make our field more welcoming and attractive to people from URGs. This is a small but crucial step you can take towards celebrating and improving our community\u2019s diversity.<\/p>\n
Examples of infusing diversity into writing to consider adopting:<\/h4>\n\n- Embracing different cultures:<\/b>\u00a0Names of people are a visible way to enhance diversity of representation in writing. Instead of reusing overused names in computing such as Alice and Bob, consider using names from a variety of languages, cultures, and nationalities, e.g., Alvarez and Bano. Avail of the many online resources on this front for ideas, e.g.,\u00a0<\/a>this article<\/a>\u00a0on names across different cultures.<\/li>\n
- Embracing differences in figures:<\/b>\u00a0Depictions of people or people-like icons in illustrations are also a good avenue to enhance diversity of representation. Consider depicting people of different gender presentations, skin colors, ability status, and other visible attributes of people.<\/li>\n
- Embracing gender diversity in pronouns:<\/b>\u00a0Consider using a variety of gender pronouns across your named examples consciously, including \u201che\/him\/his,\u201d \u201cshe\/her\/hers,\u201d and \u201cthey\/them\/theirs\u201d. Likewise, consider using gender-neutral nouns when referring to generic roles, e.g., \u201cchairperson\u201d or just \u201cchair\u201d instead of \u201cchairman,\u201d and gender-neutral pronouns for such roles.<\/li>\n<\/ul>\n
[\/vc_column_text][\/vc_tta_section][vc_tta_section title=”Responsibility” tab_id=”1712757272142-f3a599fe-3dfc”][vc_column_text]Finally, if your work involves data-driven techniques that make decisions about people, please consider explicitly discussing whether it may lead to disparate impact on different groups, especially URGs. Consider discussing the ethical and societal implications. For example, see this article discussing the potential for disparate impact of facial recognition in healthcare and strategies to avoid or reduce harm. This SIGMOD Blog article also gives a comprehensive overview of various dimensions and approaches for responsible application of data management ideas. We hope our community can help permeate this culture of responsibility and awareness about potentially harmful unintended negative consequences of our work within the larger computing landscape.[\/vc_column_text][\/vc_tta_section][vc_tta_section title=”Acknowledgments and Further Reading” tab_id=”1712757294168-00141cda-5ea7″][vc_column_text]<\/p>\n
\n- ACM Diversity and Inclusion:\u00a0Webpage<\/a><\/li>\n
- ACM SIGMOD Blog article on \u201cData, Responsibly\u201d:\u00a0Webpage<\/a><\/li>\n
- AMA Journal of Ethics article on \u201cWhat Are Important Ethical Implications of Using Facial Recognition Technology in Health Care?\u201d:\u00a0Webpage<\/a><\/li>\n
- Article on \u201cInclusive CS Examples\u201d:\u00a0Webpage<\/a><\/li>\n
- Article on \u201cTerminology, Power and Oppressive Language\u201d:\u00a0Webpage<\/a><\/li>\n
- Helpful materials from UCSD CSE Diversity, Equity, and Inclusion Committee: Webpage<\/a><\/li>\n
- NeurIPS CFP on Broader Impact Statement:\u00a0Webpage<\/a><\/li>\n
- Wikipedia listing of names across cultures:\u00a0Webpage<\/a><\/li>\n<\/ul>\n
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[\/vc_column_text][\/vc_tta_section][vc_tta_section title=”Responsibility” tab_id=”1712757272142-f3a599fe-3dfc”][vc_column_text]Finally, if your work involves data-driven techniques that make decisions about people, please consider explicitly discussing whether it may lead to disparate impact on different groups, especially URGs. Consider discussing the ethical and societal implications. For example, see this article discussing the potential for disparate impact of facial recognition in healthcare and strategies to avoid or reduce harm. This SIGMOD Blog article also gives a comprehensive overview of various dimensions and approaches for responsible application of data management ideas. We hope our community can help permeate this culture of responsibility and awareness about potentially harmful unintended negative consequences of our work within the larger computing landscape.[\/vc_column_text][\/vc_tta_section][vc_tta_section title=”Acknowledgments and Further Reading” tab_id=”1712757294168-00141cda-5ea7″][vc_column_text]<\/p>\n
- \n
- ACM Diversity and Inclusion:\u00a0Webpage<\/a><\/li>\n
- ACM SIGMOD Blog article on \u201cData, Responsibly\u201d:\u00a0Webpage<\/a><\/li>\n
- AMA Journal of Ethics article on \u201cWhat Are Important Ethical Implications of Using Facial Recognition Technology in Health Care?\u201d:\u00a0Webpage<\/a><\/li>\n
- Article on \u201cInclusive CS Examples\u201d:\u00a0Webpage<\/a><\/li>\n
- Article on \u201cTerminology, Power and Oppressive Language\u201d:\u00a0Webpage<\/a><\/li>\n
- Helpful materials from UCSD CSE Diversity, Equity, and Inclusion Committee: Webpage<\/a><\/li>\n
- NeurIPS CFP on Broader Impact Statement:\u00a0Webpage<\/a><\/li>\n
- Wikipedia listing of names across cultures:\u00a0Webpage<\/a><\/li>\n<\/ul>\n
[\/vc_column_text][\/vc_tta_section][\/vc_tta_accordion][\/vc_column][\/vc_row][vc_row][vc_column]
- ACM SIGMOD Blog article on \u201cData, Responsibly\u201d:\u00a0Webpage<\/a><\/li>\n