[2022 javaone] fundamentals of diversity and inclusion for technologists

Speaker: Reza Rahman

For more see the table of contents


  • not a lot of social captical on this topic
  • Word cloud type slide with quotes about thngs people say to be dismisive. ex: ”I didn’t ean it that way”, ”Your English is pretty good”, ”You are overreacting”, ”Who are you to criticize us”
  • 67% of tech companies are made up of less than 5% Black employees (includes Nigerians, not just African Americans). Asians exceed population % in tech, but not in leadership
  • Women hold 25% computing roles. 47% of workforce is women. More eadership obs than tech jobs
  • People put blinders on/tune out the bad stuff

Why care

  • Diverse perspectives – solving global scae problems (unless niche), oxymeter and skin color, underwriting stats
  • Broadening reach – want people to want to use your product, spectrum of life experiences
  • Untapped potential – most important when tight labor force, educate more people
  • Greater prosperity – avoid zero sum mindset
  • Ethical imperative – perception about divisiveness in US


  • 80s mindset – African Americans and women
  • Encompoasses range of identiies and visibile/invisible differenes – race, etnicity, faith, socioeconomics, etc
  • Helps disarm conversation away from ”us vs them”


  • Intentionally creating an enviornment where diversity prospers and common good prevails
  • Fair, respectful, supportive and empowering
  • Diversity is a fact, inclusion is an act
  • How people feel at work
  • Respected, listed to, accepted, valued, included, welcomed, safe


  • Predjudicial treatment
  • Recognition this is wron
  • Often intentional/conisistent
  • Likely legal protected identies such as race/gender

Unconscious bias

  • Stereotypes/prejudices/preferences
  • Often intententional
  • Advantage one set of people o the detriment of others
  • Hardly anyone lacks unconscious bias – need to recognize this (eg: negative association)

Anti defamation league – pyramid of hate

  • Acts of bias
  • Prejudice
  • Discrimination
  • Bias-motivated violence
  • Genocide


  • Theoretical construct
  • Being truly equal – particularly with regards to resources and oppotunities
  • Doesn’t happen because of privileges (unearned advantages)


  • State of fairness
  • Intentional remedy impacts of inequality and injustice
  • Cartoon with slanted apple tree (inequality = one side falls, equality = same later so on side reach, equity = taller ladder, justice = fix tree so no longer slanted)


  • Deliberately downplaying part of identity to attempt to reduce effects of marginalization


  • Informed, intentional and consistent practice to understand, empathize an suppor tothers with the objective of grater fairness, diversity and inclusion
  • Continuum – apety, awareness, active advocate
  • Privately check on someone have questionable interaction
  • Don’t assume someone wants help
  • And so much more – see deck

My take

While it was a small audience (13 people), I’m glad this talk happened. Techies are unlikely to go to a whole event on his topic so one session representated a good opportunity. Reza noted that for some parts, the self selecting audience didn’t need to hear it. While this is true, you never know which part stews in your head and becomes useful later.