Valuing Student Perspectives and Experiences in Data Science

How Can the Data Science Community be Accessible to People with Disabilities?

Disability is not a simple concept with a small number of possible values. It has many dimensions, varies in intensity and impact, and often changes over time.
The World Health Organization estimates that 15 percent of people worldwide have some form of impairment that can lead to disability. Almost all of us will experience sensory, physical or cognitive disability in our lives.
As defined by the United Nations Convention on the Rights of People with Disabilities, disability “results from the interaction between persons with impairments and attitudinal and environmental barriers that hinders their full and effective participation in society.”
In other words, a disability is mainly a problem if the person is not able to participate fully in society. We have the power to reduce those barriers.
venturebeat.com/2018/12/03/how-to-tackle-ai-bias-for-people-with-disabilities/

When working with a deaf student, it is considered very rude for a hearing person to “make up” new signs.
If a deaf student is working with a sign language interpreter, make eye contact with the student, not the interpreter, when the interpreter speaks the words out loud. Your conversation is with the student, not the interpreter.

DO identify yourself when initiating a conversation and use the person’s name when talking to them.
DON’T censor your language to avoid using words like “look.”
DO describe the layout of large rooms, including how the furniture is arranged.
DON’T be afraid to ask questions. It’s better than making assumptions.
DO give a verbal indication when you leave a conversation or a room.
DON’T speak to or touch a guide dog. They are working.
DO provide electronic copies of materials in advance.
DON’T use highly stylized typefaces. Stick to sans-serif fonts like Arial or Calibri.
DO add alternative text tags to graphics.
www.perkins.org/stories/nine-essential-tips-for-working-with-people-who-are-blind www.dhs.wisconsin.gov/blind/adjustment/dos-donts.htm

To ensure AI-based systems are treating people with disabilities fairly, it is essential to include them in the development process. Developers must take the time to consider who the outliers might be, and who might be impacted by the solutions they are developing.
The best path ahead is to seek out the affected stakeholders and work with them towards a fair and accessible system.
When we can identify and remove barriers limiting accessibility for people with disabilities from our technologies we often develop results that support greater access by others as well.

This is the perfect place to make a real difference in the increasing the varied perspectives and experiences of the data science community.
We will be reaching over 1800 students a year who will go out to work in data science-related careers.
We have the opportunity to turn a lot of people on to data science if we do our jobs well.
But we also have the opportunity to turn a lot of people off to data science we don’t pay attention to the culture of The Data Mine. Let’s be thoughtful!

It is an important part of your job as a T.A. to create a welcoming data science community here in The Data Mine.
There is not one right type of person or one right way of approaching a problem in data science.
We can all learn from each other.
We all bring strengths and insights.
You will be learning from your students, too.

Everybody is WELCOME and NEEDED in data science.