Accountability (34)
Find narratives by ethical themes or by technologies.
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- 5 min
- GIS Lounge
- 2019
GIS, a relatively new form of computational analysis, can often contain algorithms with biases based on biases present in the training data from open data sources, with this case study focusing on the tendency of power-line identification data being centered around the Western world. This problem can be improved by approaching data collection with more intentionality, either broadening the pool of collected geographic data or inputting artificial images to help the tool recognize a greater number of circumstances and thus become more accurate.
- GIS Lounge
- 2019
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- 5 min
- GIS Lounge
- 2019
When AI Goes Wrong in Spatial Reasoning
GIS, a relatively new form of computational analysis, can often contain algorithms with biases based on biases present in the training data from open data sources, with this case study focusing on the tendency of power-line identification data being centered around the Western world. This problem can be improved by approaching data collection with more intentionality, either broadening the pool of collected geographic data or inputting artificial images to help the tool recognize a greater number of circumstances and thus become more accurate.
What happens when the source of the data itself (the dataset) is biased? Can the ideas present in this article (namely the intentionally broadening of the training data pool and inclusion of composite data) find application beyond GIS?
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- 16 min
- Kinolab
- 2003
In a distant future, the majority of humanity has been wiped out, and most of the planet is flooded. ECOBAN is a city which runs on technological power, avoiding destruction and pollution by using a machine which converts pollutants into power. However, Marrians, who live on the exterior of the city in the destroyed world, are responsible for performing the labor to harvest these pollutants, without any of the benefits. Essentially, Ecoban keeps its technology to itself, not sharing it with the “contaminated” underclasses. Shua, a renegade Marrian hacker, attempts to shut down the DELOS system, the technology which powers Ecoban and has destroyed the surrounding environment entirely. He ultimately succeeds in his mission, breaking the DELOS system which gave Ecobans a privileged life and at last bringing back blue skies.
- Kinolab
- 2003
Technological Regulation of the Environment and Division
In a distant future, the majority of humanity has been wiped out, and most of the planet is flooded. ECOBAN is a city which runs on technological power, avoiding destruction and pollution by using a machine which converts pollutants into power. However, Marrians, who live on the exterior of the city in the destroyed world, are responsible for performing the labor to harvest these pollutants, without any of the benefits. Essentially, Ecoban keeps its technology to itself, not sharing it with the “contaminated” underclasses. Shua, a renegade Marrian hacker, attempts to shut down the DELOS system, the technology which powers Ecoban and has destroyed the surrounding environment entirely. He ultimately succeeds in his mission, breaking the DELOS system which gave Ecobans a privileged life and at last bringing back blue skies.
How can it be ensured that technology built with the aim to reverse climate change or otherwise aid the environment helps all people, and not just certain higher classes? How can governments or leaders support “Robin Hood” hackers who disrupt technology for a greater good? Who is responsible for bridging digital divides and bringing technological equality to disadvantaged communities, and how should this be approached? How should technology be created to be accessible to all communities?
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- 10 min
- MIT Technology Review
- 2020
This article explains the ethical warnings of Timnit Gebru against training Natural Language Processing algorithms on large language models developed on sets of textual data from the internet. Not only does this process have a negative environmental impact, it also still does not allow these machine learning tools to process semantic nuance, especially as it relates to burgeoning social movements or countries with lower internet access. Dr. Gebru’s refusal to retract this paper ultimately lead to her dismissal from Google.
- MIT Technology Review
- 2020
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- 10 min
- MIT Technology Review
- 2020
We read the paper that forced Timnit Gebru out of Google. Here’s what it says.
This article explains the ethical warnings of Timnit Gebru against training Natural Language Processing algorithms on large language models developed on sets of textual data from the internet. Not only does this process have a negative environmental impact, it also still does not allow these machine learning tools to process semantic nuance, especially as it relates to burgeoning social movements or countries with lower internet access. Dr. Gebru’s refusal to retract this paper ultimately lead to her dismissal from Google.
How should models for training NLP algorithms be more closely scrutinized? What sorts of voices are needed at the design table to ensure that the impact of such algorithms are consistent across all populations? Can this ever be achieved?
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- 5 min
- Gizmodo
- 2021
Thorough investigation led to the conclusion that bots played a role in the economic disruption of GameStop stocks in early 2021. Essentially, the automated accounts aided in the diffusion of materials promoting the purchase and maintenance of GameStop stocks as a ploy to act as a check on wealthy hedge fund managers who bet that the stock would crash. The wholistic effect of these bots in this specific campaign, and thus a measure of how bots may generally be used to cause economic disruption in online markets through interaction with humans, remains hard to read.
- Gizmodo
- 2021
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- 5 min
- Gizmodo
- 2021
Bots Reportedly Helped Fuel GameStonks Hype on Facebook, Twitter, and Other Platforms
Thorough investigation led to the conclusion that bots played a role in the economic disruption of GameStop stocks in early 2021. Essentially, the automated accounts aided in the diffusion of materials promoting the purchase and maintenance of GameStop stocks as a ploy to act as a check on wealthy hedge fund managers who bet that the stock would crash. The wholistic effect of these bots in this specific campaign, and thus a measure of how bots may generally be used to cause economic disruption in online markets through interaction with humans, remains hard to read.
Do you consider this case study, and the use of the bots, to be “activism”? How can this case study be summarized into a general principle for how bots may manipulate the economy? How do digital technologies help both wealth and non-wealthy people serve their own interests?
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- 30 min
- UNIVERSITY OF WÜRZBURG GRADUATE SCHOOLS
- 1982
Hardware specialist Automatic Jack is roped into a dangerous hacking scheme with his partner Bobby Quine while they compete for the affections of Rikki. Their plan is to use deadly malware to infiltrate the protections of Chrome, a mysterious overlord of cyberspace who hoards massive amounts of wealth. They enact this plan by entering cyberspace within a program and visualizing the data held within this digital network which connects people all across the globe.
- UNIVERSITY OF WÜRZBURG GRADUATE SCHOOLS
- 1982
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- 30 min
- UNIVERSITY OF WÜRZBURG GRADUATE SCHOOLS
- 1982
Cyberspace and Internet Imaginations: “Burning Chrome” by William Gibson
Hardware specialist Automatic Jack is roped into a dangerous hacking scheme with his partner Bobby Quine while they compete for the affections of Rikki. Their plan is to use deadly malware to infiltrate the protections of Chrome, a mysterious overlord of cyberspace who hoards massive amounts of wealth. They enact this plan by entering cyberspace within a program and visualizing the data held within this digital network which connects people all across the globe.
How can malware be used for good, and when should it be used for good? How do imaginations of the internet influence how people perceive this mysterious yet pervasive network? In what ways would making aspects of the internet into tangible images help people understand it better? How should the most powerful stakeholders in a given digital architecture be challenged? How might immersion into cyberspace give people more agency?
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- 7 min
- Venture Beat
- 2021
As machine learning algorithms become more deeply embedded in all levels of society, including governments, it is critical for developers and users alike to consider how these algorithms may shift or concentrate power, specifically as it relates to biased data. Historical and anthropological lenses are helpful in dissecting AI in terms of how they model the world, and what perspectives might be missing from their construction and operation.
- Venture Beat
- 2021
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- 7 min
- Venture Beat
- 2021
Center for Applied Data Ethics suggests treating AI like a bureaucracy
As machine learning algorithms become more deeply embedded in all levels of society, including governments, it is critical for developers and users alike to consider how these algorithms may shift or concentrate power, specifically as it relates to biased data. Historical and anthropological lenses are helpful in dissecting AI in terms of how they model the world, and what perspectives might be missing from their construction and operation.
Whose job is it to ameliorate the “privilege hazard”, and how should this be done? How should large data sets be analyzed to avoid bias and ensure fairness? How can large data aggregators such as Google be held accountable to new standards of scrutinizing data and introducing humanities perspectives in applications?