PHIL 2550G UWO Wk 4 Do You Have a Utopian or Dystopian View Concerning Technology Essay

Reflection Question for this Week: You have two options. [1] For those who submitted a reflection for week 3, i want you to reassess your answer based on what you read and learned this week. Has your position changed in any way? Have you gained new insights into the issues of gender and technology? Why/Why not? Explain OR [2] Do you have a utopian or dystopian view concerning technology? Explain why and support your position with at least two examples.

• You may speak using the first person.
• While this is not a super formal piece of academic writing, please follow the usual guidelines of good grammar, spelling, punctuation. Try to structure your reflection so it doesn’t feel like a rant. Execution is key here! Oh and yes, you may swear if you feel the need to.
• To cite readings simply name the author and the page number from the text. Direct quoting is not necessary, summary is always nice, but if you do make sure you clearly show where it comes from.
• You may include in your reflection an example in your life, or the media, or film, etc. – a real concrete example to illustrate your reflection. Make sure to include websites or information to cite this example.
• If you go over the word limit that is fine. If you are under it, that’s not fine.
• Submit your typed reflection, with your name on it, to the DropBox tab here in Owl by Sunday 11 July 11:59pm. If you do a tech-based reflection, you can try to use the DropBox but if it doesn’t allow you to upload there please email it to me by Sunday 11 July 11:59pm. Note: If you need more time to complete this just inform me – i have no issue with late submissions so long as i am aware and you get the required number into me by end of term.
• To upload to DropBox, simply click on the tab, and near your name is a drop down menu called “actions” – click it and then you’ll see ‘upload files’. Select that. You don’t necessarily get an email receipt, so if you want to make sure it is there you can email me to say you uploaded it and to confirm it.
• As per the syllabus, it is optional to do the reflection this week. You have to do 4 in total over term, and which weeks you do a reflection is up to you.

If you choose to submit written reflections, the word count is 750 – 1000 words. The syllabus also provides some tech-based options if you wish to pursue a reflection that is expressed in a medium other than written.

Related links (Highly recommend):

• Decoding Sexism in AI | Isabella Morona | TEDxPhillipsAcademyAndover: https://youtu.be/a9IkLhv3TTY
• Gender Bias in AI and Machine Learning Systems: https://youtu.be/Z7-DjqgO2ws
• When AI Sees a Man, It Thinks ‘Official.’ A Woman? ‘Smile’: https://www.wired.com/story/ai-sees-man-thinks-official-woman-smile/
• Even artificial intelligence can acquire biases against race and gender: https://www.sciencemag.org/news/2017/04/even-artificial-intelligence-can-acquire-biases-against-race-and-gender
• AI software defines people as male or female. That’s a problem: https://www.cnn.com/2019/11/21/tech/ai-gender-recognition-problem/index.html
• Harmony The First AI Sex Robot: https://youtu.be/0CNLEfmx6Rk

PHIL 2550: Sex or Gender In the Digital
Age
Week 4:
Digital Gender
Agenda
•
Discuss two readings on issues related to digital gender from the last decade:
Foka and Arvidsson focus on the internet, & Collett and Dillion look at AI
•
Both readings were composed after research conferences, they tell the story
of what work is being done by scholars as well as what work still needs to be
done
•
Think of how what is said in both ties back to prior readings we have covered
•
These articles are setting foundational contexts about digital gender for the last
two weeks
Digital Gender: A Manifesto (2014)
•
Focus is on the internet/Cyberspace relationship to gender
•
Utopian Vs Dystopian views (p. 2)
•
This manifesto seeks to shed light on how digital technology/internet seems intimately
tied to both preserving & disrupting normative views of gender & sex
•
(p. 4) 7 themes are discussed (it says 8 but it is really); each theme highlights work
from authors & viewpoints that comprise the utopian & dystopian
•
Conclusion: we need to move beyond thinking of digital gender as only online & begin
seeing that it is very much of the social world we live in; pay attention to how the
digital intermingles with social making & unmaking of norms, categories & oppression
AI & Gender: 4 Proposals for Future Research (2019)
•
Focus on Artificial Intelligence; report outlines 4 of the weightiest challenges to
gender equality presented by recent developments in AI; Authors offer 4 research
proposals to help effectively combat these
•
The 4 research themes overlap in many ways
•
Intended to be provocative rather than prescriptive; proposals as mechanisms of
awareness about challenges & problems that require practical action
•
(pp. 4 – 5) The 4 summarized: Bridging Gender Theory & AI Practice; Law & Policy;
Biased Datasets; & Diversity in the AI Workforce
•
(p. 7) Definitions of gender & AI
AI & Gender: 4 Proposals for Future Research (2019)
•
#1: links to Butler on gender performatives – how gender identity is constituted
through repetitive stylized acts through/on the lived body;
•
AI is part of a repeating process, one that is amplified louder through its
increased presence globally (p. 8)
•
3 notable AI systems/aspects of systems that reproduce controlling &
restrictive conceptions of gender & race: Humanoid Robots; Virtual Personal
Assistants; Gendered epistemology
•
AI is perpetuating & reinforcing binary, gendered stereotypes
Raj meets Siri
Sex doll AI
AI & Gender: 4 Proposals for Future Research (2019)
•
#2 Development & rise of AI is linked to economic prosperity & political power,
often those are what underly laws & policies about AI; there are dangers here
for marginalized people as well as gender equality
•
3 areas of law & policy related to AI that will impact distribution of power &
gender equality: Data & Privacy; Technological design; & Labour (pp. 14 – 15)
•
These areas would benefit from additional gender-based research; there has
been little attention paid to interpreting laws & policies through a gender lens
or how these could be exploited to strive for gender equality
Digital algorithms
Alexa & Siri
Self Checkout
Care Robots
AI & Gender: 4 Proposals for Future Research (2019)
•
#3 Biased datasets; Bias comes from people who create & program, not machines themselves;
biases embedded in AI systems amplify inequality & project past our current biases into the future
•
3 sources of bias with AI systems: Datasets, Algorithms, Lack of transparency; the focus here is
on the first
•
Datasets can reproduce societal biases in many ways, such as along race & gender lines (p. 19);
White male data dominate datasets
•
(p. 20) Discriminatory Bias & Genuine Difference; in many cases data is not objective
•
3 areas where dataset biases can result in major harm: Crime & Policing; Financial Services; &
Health technology
•
Main source of bias is the lack of diversity in the AI workforce
Google translate English pronoun default
Autocorrect, Autocapitalize & Autocomplete
AI & Gender: 4 Proposals for Future Research (2019)
•
#4 The lack of diversity; Women had made major historical contributions to computer science;
Computer programming used to be perceived as merely clerical, low-skilled work, but once it
became culturally more valuable women were pushed out leading to a lack of gender diversity in
coding, designing, programming, & engineering of AI tech (p. 25)
•
Group with most privilege & power in society produce the dominant epistemology, social theory,
conceptual frameworks; those involved with technology are dictating & framing how society
functions & will function (p. 26)
•
The way to overcome biases is to have a diverse workforce with tech at every stage
•
Comfort in Reflection & gendered normalization
•
To address inequalities, 2 things must be addressed: Education in STEM normalized for women
(& everyone) & Diversity in AI workforce by design (pp. 27 – 28)
Include women in texts & teachings
Expose STEM equally to all kids
Questions? Comments?
Discussion Questions
•
What is the picture of gender you get from reading these two pieces? What
does gender in the 21st century online or in AI look like?
•
Are we any closer to getting over binaries? Or gender stereotypes? Or gender
essentialism?
•
What does digital gender tell you about the social reality of gender today?
•
Are you a utopian or a dystopian here?
•
Will the proposals work to remedy the problems related to gender online & in
AI?
Week 4 Notes: Digital Gender
Digital Gender: A Manifesto (2014)
• Focus is on the internet/Cyberspace relationship to gender
• This manifesto seeks to shed light on how digital technology/internet seems intimately
tied to both preserving & disrupting normative views of gender & sex; scholars noted
clear opportunities within
•
•
•
•
•
•
Utopian Vs Dystopian views (p. 2)
Utopian: digital technologies could facilitate bodily transcendence; provide a medium
whereby individuals could reconstruct their identity free from bodily stereotypes; digital
technologies could provide both liberation and emancipation, not only through genderplay and notions of cyborgs and technological drag but also in its potential to democratize
the active production of an ever more digitized world; Claims were even made that the
networked organization of the Web inherently supported feminist and democratic work
Dystopian: the Web was constituted dominantly as a “white male playground” with
pornography as an extreme example of online sexism, and the capacity of digital
technology to fuel sexualized violence and online harassment; men often monopolized
discussions online, even when they were directly related to women and their gendered
experiences; associated with a “masculinized netiquette” through which “deviant”
women and men were both victimized and harassed: Indeed, several scholars have
pointed to how such “flaming” dramatically reduce women’s and men’s ability to take
place and participate online – highlighting the potential of digital technologies to
enforce gendered behaviors and norms.
You could say the utopian sees the web as a fresh new world separate from our living
world (digital gender vs lived gender), it is free from our societal gendered norms where
we can create new, and the dystopian sees the web as an extension of our world but with
capabilities of being worse because of loopholes digital realities bring and anonymity
providing a shield.
(p. 4) There are 7 themes discussed (it says 8 but it is really); each theme highlights work
from authors & viewpoints that comprise the utopian & dystopian
Conclusion: we need to move beyond thinking of digital gender as only online & begin
seeing that it is very much of the social world we live in; pay attention to how the digital
intermingles with social making & unmaking of norms, categories & oppression
AI & Gender: 4 Proposals for Future Research (2019)
• Focus on Artificial Intelligence; report outlines 4 of the weightiest challenges to gender
equality presented by recent developments in AI Authors offer 4 research proposals to
help effectively combat these
• Gender isn’t the only intersection at play here – there is also issues of race and sexuality
and ethnicity too, but the main focus will be on gender broadly
• The 4 research themes overlap in many ways
• Intended to be provocative rather than prescriptive; proposals as mechanisms of
awareness about challenges & problems that require practical action
•
•
•
•
•
•
•
(p. 7) Definitions of gender & AI provided
#1: Bridging Gender Theory and AI Practice; links to Butler on gender performatives
– how gender identity is constituted through repetitive stylized acts through/on the lived
body; AI can play a role in the repeating process, as it becomes more dominate in our
lives globally this repeating is amplified – it repeats and reinforces gender stereotypes; 3
notable AI systems/aspects of systems that reproduce controlling & restrictive
conceptions of gender & race: Humanoid Robots; Virtual Personal Assistants; Gendered
epistemology
#2 Law & Policy; Development & Rise of AI is linked to economic prosperity &
political power, often those are what underly laws & policies about AI; there are dangers
here for marginalized people as well as gender equality; 3 areas of law & policy related to
AI that will impact distribution of power & gender equality: Data & Privacy;
Technological design; & Labour (pp. 14 – 15)
#3 Biased Datasets; Bias comes from people who create & program, not machines
themselves; biases embedded in AI systems amplify inequality & project past our current
biases into the future; Main source of bias is in the lack of diversity in the AI workforce;
3 areas where dataset biases can result in major harm: Crime & Policing; Financial
Services; & Health technology
#4 Diversity in AI Workforce; Women had made major historical contributions to
computer science; Computer programming used to be perceived as merely clerical, lowskilled work, but once it became culturally more valuable women were pushed out
leading to a lack of gender diversity in coding, designing, programming, & engineering
of AI tech (p. 25); Group with most privilege & power in society produce the dominant
epistemology, social theory, conceptual frameworks; those involved with technology are
dictating & framing how society functions & will function (p. 26); The way to overcome
biases is to have a diverse workforce with tech at every stage – education in STEM and
take measures to make sure the workforce is diverse
https://blogs.miamioh.edu/edt431-531/2020/11/diversity-in-the-stem-field/
Conclusion: if we continue the way we are AI will continue to perpetuate and maintain
gender-based discrimination; Gender bias is embedded in the design of the systems, and
these systems 1. reinforce restrictive gender stereotypes, 2. law and policy creation are
not focused on gender equality, 3. widespread use of biased datasets, and 4. a lack of
diversity in the AI workforce.