Chapter 7 ~ Looking at the
Industry through a Cultural Lens
In this chapter, you'll explore the social constructions that create discrimination. In general, the high-tech industry has a diversity problem, which can potentially be remedied by the use of artificial Intelligence, diversity initiatives, and legislation.
You'll write about new concepts and examine a company through a cultural lens to analyze its diversity in relation to an ethical theory.
7.1 Introduction to discrimination and inclusive design.
Have you ever been discriminated against in school, at work, or socially, based on your age, gender, culture, race, class, or abilities? Or, has your privilege insulated you from discrimination? Which of the following five problems is your experience most likely due to?
Open the terms in these lenses to review their meaning...is your understanding of them up-to-date?
(Open and close one at a time for best results.)
Continue reading about marginalized groups as well as the concept of inclusive design:
Reading List
Refer to writing instructions under each page of the template provided in step 7.5. Open articles in new tabs and add them to your bibliography tool.
- liberals and conservatives. Learn more about this infographic...
- genders. Read more about the Gender Identity and Expression Map.
- races and cultures.
- citizens, immigrants, tourists.
- the neurodiverse.
- the disabled.
Inclusive Design
- The Radical Frontier of Inclusive Design.
- The No. 1 thing you’re getting wrong about inclusive design.
7.2 Leaky pipeline.
Reading List
Refer to writing instructions under each page of the template provided in step 7.5. Open articles in new tabs and add them to your bibliography tool.
- Are We Really Closing The Gender Gap In Tech? (2021)
- If Investors Really Listened To Data, They’d Be Investing In Women.
- Gender trends in computer science authorship. Or, read a summary of the paper by the NYTimes: The Gender Gap in Computer Science Research Won’t Close for 100 Years
- Countering the Negative Image of Women in Computing
- Female scientists are up against a lot of unconscious bias. Here’s how to fight it.
7.3 Explore bias in artificial intelligence.
Many major tech companies are now using AI to help hire developers as well as detect and eradicate bias in product development.
Reading List
Refer to writing instructions under each page of the template provided in step 7.5. Open articles in new tabs and add them to your bibliography tool.
- Failing Fast: the Impact of Bias When Speeding up Application Security (2021)
- Algorithms aren't all created equal.
- Here’s How Instagram Will Use AI To Take On Its Bullying Problem.
- What Do We Do About the Biases in AI?
- Google got rid of 'Smart Compose' pronouns because humans are sexist.
- Can AI make the gender gap at work disappear?
- Letting tech firms frame the AI ethics debate is a mistake.
- Artificial Intelligence (AI) in Government Act and Sen. Harris tells federal agencies to get serious about facial recognition risks.
- AI and Marketing: Why We Need to Ask Ethical Questions.
-
Business Insider writers try HireVue's AI.
What problems can occur with HireVue's application?
Learn more: Facial recognition is increasingly common, but how does it work? - Why Amazon’s Automated Hiring Tool Discriminated Against Women
- Time-Out for Google
- A review of possible effects of cognitive biases on interpretation of rule-based machine learning models
7.4 Hiring laws to deter discrimination.
The USA requires government agencies and businesses that receive government funding to hire according to several laws under the Department of Labor, which may affect you in the future:
Reading List
Refer to writing instructions under each page of the template provided in step 7.5. Open articles in new tabs and add them to your bibliography tool.
- Equal Opportunity Employer
- Affirmative Action
- Pay Transparency Nondiscrimination Provision
- United States Citizenship and Immigration Services E-Verify service
- Americans with Disabilities Act
Besides laws, many companies offer special programs to train, support, and boost diversity among their employees:
- Internship
- Apprenticeship
- Unions
- Veterans Preference
- Diversity initiatives
- Diversity statements
- Fair Chance Ordinance (some states)
- Slavery & Human Trafficking Statement
7.5 Set up the Template and Reading List.
Use the following template link to complete this research and writing assignment.
- Login to your OSU Google Account.
- Launch this chapter's
- Do not request permission to use the file. Login to your OSU Google Account.
- Once you have the file open:
- → .
- Rename the new file so it includes your "First and Last name" in place of "Template".
- Move the file into a folder for this course.
- Add your name to the cover page.
- Read instructions on the cover page. When in doubt about how to write in the templates, refer back to this page for clarification.
- Refer to the green instructions below each page to understand what is required.
- The last page requires a bibliography.
7.6 Edit, download, and submit the file.
- Ctrlc or ⌘c Copy the bibliographic entries you made during the Explore Topics reading and research. On the last page of the template, Ctrlv or ⌘v paste in the bibliographic entries. Select the list and apply the bullet or numbered list icon. Update the font size to 14 if necessary. Add more pages if necessary.
- Check and correct grammar and spelling using the built-in functions.
- From the menu, choose Download as PDF.
- Check to confirm that hyperlinks work in the new PDF file. If they do not work, then in the Assignment Commenting Box, leave a note stating which platform, operating system, and browser you used to print or download the PDF file.
- Copy the file to a backup folder on your hard drive.
- Submit the PDF file by uploading it in the Canvas Assignment screen.
- Confirm that your file has uploaded by looking for the document icon in the Grades area.