Themes (326)
Find narratives by ethical themes or by technologies.
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- 5 min
- Gizmodo
- 2020
This article describes the new Amazon Sidewalk feature and subsequently explains why users should not buy into this service. Essentially, this feature uses the internet of things created by Amazon devices such as the Echo or Ring camera to create a secondary network connecting nearby homes which also contain these devices, which is sustained by each home “donating” a small amount of broadband. It is explained that this is a dangerous concept because this smaller network may be susceptible to hackers, putting a large number of users at risk.
- Gizmodo
- 2020
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- 5 min
- Gizmodo
- 2020
You Need to Opt Out of Amazon Sidewalk
This article describes the new Amazon Sidewalk feature and subsequently explains why users should not buy into this service. Essentially, this feature uses the internet of things created by Amazon devices such as the Echo or Ring camera to create a secondary network connecting nearby homes which also contain these devices, which is sustained by each home “donating” a small amount of broadband. It is explained that this is a dangerous concept because this smaller network may be susceptible to hackers, putting a large number of users at risk.
Why are “secondary networks” like the one described here a bad idea in terms of both surveillance and data privacy? Is it possible for the world to be too networked? How can tech developers make sure the general public has a healthy skepticism toward new devices? Or is it ultimately Amazon’s job to think about the ethical implications of this secondary network before introducing it for profits?
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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-
- 51 min
- TechCrunch
- 2020
In this podcast, several disability experts discuss the evolving relationship between disabled people, society, and technology. The main point of discussion is the difference between the medical and societal models of disability, and how the medical lens tends to spur technologies with an individual focus on remedying disability, whereas the societal lens could spur technologies that lead to a more accessible world. Artificial Intelligence and machine learning is labelled as inherently “normative” since it is trained on data that comes from a biased society, and therefore is less likely to work in favor of a social group as varied as disabled people. There is a clear need for institutional change in the technology industry to address these problems.
- TechCrunch
- 2020
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- 51 min
- TechCrunch
- 2020
Artificial Intelligence and Disability
In this podcast, several disability experts discuss the evolving relationship between disabled people, society, and technology. The main point of discussion is the difference between the medical and societal models of disability, and how the medical lens tends to spur technologies with an individual focus on remedying disability, whereas the societal lens could spur technologies that lead to a more accessible world. Artificial Intelligence and machine learning is labelled as inherently “normative” since it is trained on data that comes from a biased society, and therefore is less likely to work in favor of a social group as varied as disabled people. There is a clear need for institutional change in the technology industry to address these problems.
What are some problems with injecting even the most unbiased of technologies into a system biased against certain groups, including disabled people? How can developers aim to create technology which can actually put accessibility before profit? How can it be ensured that AI algorithms take into account more than just normative considerations? How can developers be forced to consider the myriad impacts that one technology may have on large heterogeneous communities such as the disabled community?
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- 5 min
- Tech Crunch
- 2020
During Google’s attempt to merge with the company Fitbit, the NGO Amnesty International has provided warnings to the competition regulators in the EU that such a move would be detrimental to privacy. Based on Google’s historical malpractice with user data, since its status as a tech monopoly allows it to mine data from several different avenues of a user’s life, adding wearable health-based tech to this equation puts the privacy and rights of users at risk. Calls for scrunity of “surveillance capitalism” employed by tech giants.
- Tech Crunch
- 2020
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- 5 min
- Tech Crunch
- 2020
No Google-Fitbit merger without human rights remedies, says Amnesty to EU
During Google’s attempt to merge with the company Fitbit, the NGO Amnesty International has provided warnings to the competition regulators in the EU that such a move would be detrimental to privacy. Based on Google’s historical malpractice with user data, since its status as a tech monopoly allows it to mine data from several different avenues of a user’s life, adding wearable health-based tech to this equation puts the privacy and rights of users at risk. Calls for scrunity of “surveillance capitalism” employed by tech giants.
When considering how companies and advertisers may use them, what sorts of personal statistics related to health and well-being should and should not be collected by mobile computing devices? How can devices originally built to stand on their own as one technological artifact become more convenient or harmful to a user when they become part of a technological architecture?