Ways in which technologies may bring different type of leisure experiences to a larger audience
Technology Based Entertainment and Leisure (34)
Find narratives by ethical themes or by technologies.
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- 6 min
- Vox
- 2020
Even virtual realities with unrealistic yet believable graphics are able to fool the brain’s sense of perception into believing that the digital environment still operates under the same rules as the real world. Connecting the technologies directly to one’s senses is more immersive than looking at a screen; although human brains have been able to process flat images for a long time, the direct sight connection to two screens with virtual reality makes perception a bit more muddled.
- Vox
- 2020
How Virtual Reality Tricks Your Brain
Even virtual realities with unrealistic yet believable graphics are able to fool the brain’s sense of perception into believing that the digital environment still operates under the same rules as the real world. Connecting the technologies directly to one’s senses is more immersive than looking at a screen; although human brains have been able to process flat images for a long time, the direct sight connection to two screens with virtual reality makes perception a bit more muddled.
Should virtual reality ever reach a point where it is indistinguishable from true reality in terms of graphic design or other sensory information? How could such technology be weaponized or abused? How accessible should the most immersive virtual reality technologies be to the general public?
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- 35 min
- Wired
- 2021
In this podcast, interviewees share several narratives which discuss how certain technologies, especially digital photo albums, social media sites, and dating apps, can change the nature of relationships and memories. Once algorithms for certain sites have an idea of what a certain user may want to see, it can be hard for the user to change that idea, as the Pinterest wedding example demonstrates. When it comes to photos, emotional reactions can be hard or nearly impossible for a machine to predict. While dating apps do not necessarily make a profit by mining data, the Match monopoly of creating different types of dating niches through a variety of apps is cause for some concern.
- Wired
- 2021
How Tech Transformed How We Hook Up—and Break Up
In this podcast, interviewees share several narratives which discuss how certain technologies, especially digital photo albums, social media sites, and dating apps, can change the nature of relationships and memories. Once algorithms for certain sites have an idea of what a certain user may want to see, it can be hard for the user to change that idea, as the Pinterest wedding example demonstrates. When it comes to photos, emotional reactions can be hard or nearly impossible for a machine to predict. While dating apps do not necessarily make a profit by mining data, the Match monopoly of creating different types of dating niches through a variety of apps is cause for some concern.
How should algorithms determine what photos a specific user may want to see or be reminded of? Should machines be trusted with this task at all? Should users be able to take a more active role in curating their content in certain albums or sites, and would most users even want to do this? Does the existence of dating apps drastically change the nature of dating? How could creating a new application which introduces a new dating “niche” ultimately serve a tech monopoly?
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- 10 min
- Kinolab
- 1998
Truman, the result of an unwanted pregnancy, was the first baby to be legally adopted by a corporation. From this adoption, he grew up on the set of a reality TV show in a massive sound stage, completely unaware that he was constantly being filmed and watched by viewers all across the world. As an adult, he begins to suspect that something about his reality is very wrong, and confronts his wife about this perception. Sylvia, a love interest of Truman, affirms her stance that documenting Truman without his consent is an unethical form of entertainment since he has no agency. Ultimately, he is able to reclaim this agency by leaving the show’s set and joining the real world.
- Kinolab
- 1998
Celebrity Culture, Streaming Life, and Reality Television
Truman, the result of an unwanted pregnancy, was the first baby to be legally adopted by a corporation. From this adoption, he grew up on the set of a reality TV show in a massive sound stage, completely unaware that he was constantly being filmed and watched by viewers all across the world. As an adult, he begins to suspect that something about his reality is very wrong, and confronts his wife about this perception. Sylvia, a love interest of Truman, affirms her stance that documenting Truman without his consent is an unethical form of entertainment since he has no agency. Ultimately, he is able to reclaim this agency by leaving the show’s set and joining the real world.
How is Truman’s situation somewhat mirrored in today’s digital society? How have digital technologies, particularly video streaming, perpetuated a culture of filming and sharing everyday activities? Has society passed a point where it is possible for a person to give consent before they are surveilled or filmed for entertainment purposes? How does data streaming, specifically in areas such as reality TV or influencer cultures, change the perception of reality?
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- 5 min
- Kinolab
- 2015
In this Steve Jobs biopic, he is depicted as a man whose ego and pride regarding his work obscures his ability to treat others with respect and kindness. Only after seeing his daughter Lisa make art using MacPaint does Steve Jobs consider providing more financial support to her and Chrisann, his ex-wife. He initially argues that he is not beholden to this financial support, given that his company already donates computers to less privileged schools.
- Kinolab
- 2015
Child Computer Use
In this Steve Jobs biopic, he is depicted as a man whose ego and pride regarding his work obscures his ability to treat others with respect and kindness. Only after seeing his daughter Lisa make art using MacPaint does Steve Jobs consider providing more financial support to her and Chrisann, his ex-wife. He initially argues that he is not beholden to this financial support, given that his company already donates computers to less privileged schools.
How can children in particular use digital technologies to express their creativity? Do digital technologies enhance or limit creativity in art? Whose responsibility is it to distribute educational technologies to under-resourced areas? Why is this action essential? How can tech monopolies, and individual tech giants, be more responsible with their massive amounts of wealth?
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- 2 min
- Kinolab
- 2020
Nightly is an app used prominently in dating and hookup culture in this imagined version of 2033. It includes features such as a rating and comment system, a consent requirement, and body cameras. This narrative details the experience of a woman named Nora as she uses the technology with a hookup
- Kinolab
- 2020
Online Dating Devices
Nightly is an app used prominently in dating and hookup culture in this imagined version of 2033. It includes features such as a rating and comment system, a consent requirement, and body cameras. This narrative details the experience of a woman named Nora as she uses the technology with a hookup
How is the future of dating impacted by advanced dating apps? How do we ensure consent in hookup culture, and how can technology help with this (such as bodycams and consent trackers)? Moreover, is it ethical to use ranking and rating systems on people, such as with online apps like those for dating or other services? Isn’t human interaction subjective?
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- 5 min
- Wired
- 2019
Monster Match, a game funded by Mozilla, shows how dating app algorithms are reinforcing bias through combining personal and mass aggregated data to systematically hide a vast number of profiles from user sight, effectively caging users into narrow preferences.
- Wired
- 2019
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- 5 min
- Wired
- 2019
This dating app exposes the monstrous bias of algorithms
Monster Match, a game funded by Mozilla, shows how dating app algorithms are reinforcing bias through combining personal and mass aggregated data to systematically hide a vast number of profiles from user sight, effectively caging users into narrow preferences.
What are some inexplicit ways in which algorithms reinforce biases? Are machine learning algorithms equipped to handle the multiple confounding variables at play in things like dating preferences? Does online dating unquestionably give people more agency in finding a partner?