Inclusive tech, (how) is that possible?
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This document discusses inclusive technology and how to make technology benefit everyone. It begins by asking if inclusive tech is possible and defines inclusive tech as technology that benefits all people. It then provides examples of where technology has not been inclusive, such as voice recognition software being more likely to recognize male voices. The document discusses how biological factors and binary thinking can lead to bias in technology. It advocates considering diversity in data collection and design, being transparent about algorithms, and involving diverse groups in the design process. The overall message is that while technology can help humanity, we must ensure it is developed and applied in a sustainable and inclusive way.
Inclusive tech, (how) is that possible?
- 1. Inclusive tech, (how) is that possible? Marion Mulder
- 2. Inclusive tech, (how) is that possible? • Is inclusive tech possible? Spoiler alert: YES (but its hard work) • What do I mean when I talk about inclusive tech? I’ll take you along on my journey of exploration • That ‘thing’ about biological and genetics aspects; what’s going on? why is that? Symptoms & underlying causes. In short: Bias and by Binary Thinking • Opportunities & Possible Solutions
- 3. Future Maker Creating a world I want to live in
- 4. Equality for all Taking away hurdles
- 5. How do I try to do that?
- 6. Activism
- 8. Digital Transformation work on digital strategies and implementations of solutions
- 9. Inclusive Tech Technology that benefits everyone Privilege:
- 10. So what could possibly go wrong, right?
- 11. Some examples of where it did not go quite right…. Sales of helmet in Asia (of US brand) were low… Turns out the average head size in the database was not diverse enough Image source: Che-Wei Wang – mindful algorithms: the new role of the designer in generative design - TNW conference 2018
- 12. Some examples of where it did not go quite right…. Automatic translations also changes gender
- 13. Some examples of where it did not go quite right…. Google’s image classifier wrongly assigned black people
- 14. Some examples of where it did not go quite right….
- 16. https://www.nytimes.com/interactive/2020/11/21/science/artificial-intelligence-fake-people-faces.html Because we can, should we?
- 20. Source: Virginia Dignum – UMEA University Because we can, should we? How correct is the data really?
- 21. Because we can, should we? Criminal face detection AI Source: Juriaan van Diggelen - TNO
- 22. Contributing to the effect on society Documentary on Netflix on modern day slavery in the US judicial system. As a consequence of the Law & Order Business Model
- 26. On October 25, 2017, Saudi Arabia granted citizenship to Sophia Robot. In August 2019, in a positive and long-overdue development, the authorities announced major reforms to the discriminatory male guardianship system. Among other things, these allowed women aged over 21 to apply for and obtain a passport and travel without the permission of a male guardian; women aged over 18 to register the birth of a newborn child, the death of a relative and their own marriage or divorce, as well as to apply for and obtain a family record; and women to act as the head of a household. 12/11/2019 “Saudi Arabia just declared homosexuality, feminism and atheism as ‘extremism’ It’s a girl….
- 27. I’m sorry, I don’t understand….. Google’s speech-recognition software was 70% more likely to recognise male speech than female speech 2016 Rachel Tatman, linguistics at the University of Washington
- 28. So what’s causing it, and what can we do? In short: Bias based on (binary view on) biological aspects
- 29. Why Biology Matters There are reasons why biology matters in technology (design), think for example of a smart phone generally not fitting women’s hands, or medicine behaving differently for men an women due to hormones. But in many cases we should ask ourselves “should we? really?” And at the same time we should ask ourselves is this really a gender thing or is this just a ‘people with smaller hands thing’ or a ‘people with uteruses/ specific hormone behaviour thing’?
- 30. Why Biology Matters There are reasons why biology matters in technology (design), think for example of a smart phone generally not fitting women’s hands, or medicine behaving differently for men an women due to hormones. But in many cases we should ask ourselves “should we? really?” And at the same time we should ask ourselves is this really a gender thing or is this just a ‘people with smaller hands thing’ or a ‘people with uteruses/ specific hormone behaviour thing’? PS: gender =/= women! It is the entire spectrum of men – women. Meet ‘default man’ skinny white dude 1,75m hight
- 31. Why Biology Matters There are reasons why biology matters in technology (design), think for example of a smart phone generally not fitting women’s hands, or medicine behaving differently for men an women due to hormones. But in many cases we should ask ourselves “should we? really?” And at the same time we should ask ourselves is this really a gender thing or is this just a ‘people with smaller hands thing’ or a ‘people with uteruses/ specific hormone behaviour thing’? PS: gender =/= women! It is the entire spectrum of men – women. Meet ‘default man’ skinny white dude 1,75m hight
- 32. Dealing with human Bias • Bias: expectations derived from experience regularities in the world. Knowing what programmer means, including that most are male. • Stereotypes: biases based on regularities we do not wish to persist. Knowing that (most) programmes are male. • Prejudice: action on stereotypes. Hiring only male programmers. Bias, stereotypes, prejudice; discrimination potentially being programmed into the future Source: Joanna Bryson at AI Summit - Caliskan, Bryson &Narayanan 2017 Ada Lovelace
- 33. Live isn’t binary M U L D I M E D I A • The problem with binary is that there’s usually a hierarchy in ‘m; one is better that the other: man/woman, white/black, abled/disabled, in a relationship/single, straight/gay, left brain/ right brain, economy/environment, us/them, etc. • What if we started looking at the world from a non-binary perspective and more as a spectrums?
- 34. How we view the world isn’t static yesterday ≠ today ≠ tomorrow
- 35. So if we DO collect data or use historical data sets……
- 36. Just because we can, should we? What is the by-catch/ what are side effects?
- 37. Just because we can, should we? What is the by-catch/ what are side effects? (How) is this helping Human Kind in a sustainable way?
- 38. Design & TEST Human in the Loop systems • Consult non-technical experts and resources • Involve diverse groups in your design, data gathering, testing • Transparency (explainable) of your decision making and algorithms • Analyze –synthetize –evaluate -repeat
- 41. Access & Accessibility Is what you are making available to everyone? Should this ‘problem’ actually be solved by (this) technology? AmazonBasics voice-controlled microwave oven
- 42. Access & Accessibility Is what you are making available to everyone? Should this ‘problem’ actually be solved by (this) technology?
- 44. Be the face of the change you want to see join a community
- 45. Lets create the future together!