All Narratives (328)
Find narratives by ethical themes or by technologies.
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- 3 min
- Tech Crunch
- 2020
This narrative explains that the push for technology to help with accessibility for disabled groups, especially blind or visually impaired individuals, has spurred scientific innovation which is to the benefit of everyone.
- Tech Crunch
- 2020
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- 3 min
- Tech Crunch
- 2020
What will tomorrow’s tech look like? Ask someone who can’t see.
This narrative explains that the push for technology to help with accessibility for disabled groups, especially blind or visually impaired individuals, has spurred scientific innovation which is to the benefit of everyone.
What are the benefits of developing technologies and innovations which aim to solve a specific problem? How might this lead to unprecedented positive innovations? How can accessibility become a priority, and become adequately incentivized, in tech development, instead of other priorities such as profit?
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- 4 min
- Reuters
- 2020
Facebook has a new independent Oversight Board to help moderate content on the site, picking individual cases from the many presented to them where it is alright to remove content. The cases usually deal in hate speech, “inappropriate visuals,” or misinformation.
- Reuters
- 2020
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- 4 min
- Reuters
- 2020
From hate speech to nudity, Facebook’s oversight board picks its first cases
Facebook has a new independent Oversight Board to help moderate content on the site, picking individual cases from the many presented to them where it is alright to remove content. The cases usually deal in hate speech, “inappropriate visuals,” or misinformation.
How much oversight do algorithms or networks with a broad impact need? Who all needs to be in a room when deciding what an algorithm or site should or should not allow? Can algorithms be designed to detect and remove hate speech? Should such an algorithm exist?
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- 3 min
- TechCrunch
- 2020
This short article details a pledge inspired by the practices of the French government for tech monopolies to be more responsible in the areas of taxes and privacy. As of 2020, many have signed onto this initiative.
- TechCrunch
- 2020
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- 3 min
- TechCrunch
- 2020
Dozens of tech companies sign ‘Tech for Good Call’ following French initiative
This short article details a pledge inspired by the practices of the French government for tech monopolies to be more responsible in the areas of taxes and privacy. As of 2020, many have signed onto this initiative.
What does accountability for tech monopolies look like? Who should offer robust challenges to these companies, and who actually has the power to do so?
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- 5 min
- Gizmodo
- 2020
The data privacy of employees is at risk under a new “Productivity Score” program started by Microsoft, in which employers and administrators can use Microsoft 365 platforms to collect several metrics on their workers in order to “optimize productivity.” However, this approach causes unnecessary stress for workers, beginning a surveillance program in the workplace.
- Gizmodo
- 2020
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- 5 min
- Gizmodo
- 2020
Microsoft’s Creepy New ‘Productivity Score’ Gamifies Workplace Surveillance
The data privacy of employees is at risk under a new “Productivity Score” program started by Microsoft, in which employers and administrators can use Microsoft 365 platforms to collect several metrics on their workers in order to “optimize productivity.” However, this approach causes unnecessary stress for workers, beginning a surveillance program in the workplace.
How are excuses such as using data to “optimize productivity” employed to gather more data on people? How could such a goal be accomplished without the surveillance aspect? How does this approach not account for a diversity of working methods?
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- 7 min
- ZDNet
- 2020
Dr. Gary Marcus explains that deep machine learning as it currently exists is not maximizing the potential of AI to collect and process knowledge. He essentially argues that these machine “brains” should have more innate knowledge than they do, similar to how animal brains function in processing an environment. Ideally, this sort of baseline knowledge would be used to collect and process information from “Knowledge graphs,” a semantic web of information available on the internet which can sometimes be hard for an AI to process without translation to machine vocabularies such as RDF.
- ZDNet
- 2020
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- 7 min
- ZDNet
- 2020
Rebooting AI: Deep learning, meet knowledge graphs
Dr. Gary Marcus explains that deep machine learning as it currently exists is not maximizing the potential of AI to collect and process knowledge. He essentially argues that these machine “brains” should have more innate knowledge than they do, similar to how animal brains function in processing an environment. Ideally, this sort of baseline knowledge would be used to collect and process information from “Knowledge graphs,” a semantic web of information available on the internet which can sometimes be hard for an AI to process without translation to machine vocabularies such as RDF.
Does giving a machine similar learning capabilities to humans and animals bring artificial intelligence closer to singularity? Should humans ultimately be in control of what a machine learns? What is problematic about leaving AI less capable of understanding semantic webs?
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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
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- 35 min
- 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?
Gadget Lab: Breaking Up, Hooking Up