News Article (130)
Find narratives by ethical themes or by technologies.
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- 7 min
- Wired
- 2020
In discussing the history of the singular Internet that many global users experience every day, this article reveals some dangers of digital technologies becoming transparent through repeated use and reliance. Namely, it becomes more difficult to imagine a world where there could be alternatives to the current digital way of doing things.
- Wired
- 2020
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- 7 min
- Wired
- 2020
Hello, World! It is ‘I’, the Internet
In discussing the history of the singular Internet that many global users experience every day, this article reveals some dangers of digital technologies becoming transparent through repeated use and reliance. Namely, it becomes more difficult to imagine a world where there could be alternatives to the current digital way of doing things.
Is it too late to imagine alternatives to the Internet? How could people be convinced to get on board with a radical redo of the internet as we know it? Do alternatives need to be imagined before forming a certain digital product or service, especially if they end up being as revolutionary as the internet? Are the most popular and powerful digital technologies and services “tools”, or have they reached the status of cultural norms and conduits?
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- 5 min
- Business Insider
- 2020
This article tells the story of Timnit Gebru, a Google employee who was fired after Google refused to take her research on machine learning and algorithmic bias into full account. She was terminated hastily after sending an email asking Google to meet certain research-based conditions. Gebru is a leading expert in the field of AI and bias.
- Business Insider
- 2020
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- 5 min
- Business Insider
- 2020
One of Google’s leading AI researchers says she’s been fired in retaliation for an email to other employees
This article tells the story of Timnit Gebru, a Google employee who was fired after Google refused to take her research on machine learning and algorithmic bias into full account. She was terminated hastily after sending an email asking Google to meet certain research-based conditions. Gebru is a leading expert in the field of AI and bias.
How can tech monopolies dismiss recommendations to make their technologies more ethical? How do bias ethicists such as Gebru get onto a more unshakeable platform? Who is going to hold tech monopolies more accountable? Should these monopolies even by trying to fix their current algorithms, or might it be better to just start fresh?
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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?