Ways in which technology can assist persons with disabilities
Assistive Technologies (19)
Find narratives by ethical themes or by technologies.
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- 11 min
- Kinolab
- 1993
Geordie uses a brain-computer interface, which projects his consciousness into a mobile avatar controlled by his neural impulses, to explore distant ships. This humanoid avatar is able to perform tasks that go beyond human capabilities, such as shooting phaser beams from the hands. However, upon discovering the dead crew of the Raman, it is revealed that the lines separating his virtual reality and true reality are blurred.
- Kinolab
- 1993
Interface: The Virtual Extension of the Self
Geordie uses a brain-computer interface, which projects his consciousness into a mobile avatar controlled by his neural impulses, to explore distant ships. This humanoid avatar is able to perform tasks that go beyond human capabilities, such as shooting phaser beams from the hands. However, upon discovering the dead crew of the Raman, it is revealed that the lines separating his virtual reality and true reality are blurred.
What non-fantastical applications might you be able to think of for a technology similar to this, especially in regards to transferring neural impulses into a machine? What are the consequences of giving machines unbridled access to our thoughts? How can machines get in the way of perception of objective reality?
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- 5 min
- MIT Tech Review
- 2020
The Semantic Scholar is a new AI program which has been trained to read through scientific papers and provide a unique one sentence summary of the paper’s content. The AI has been trained with a large data set focused on learning how to process natural language and summarise it. The ultimate idea is to use technology to help learning and synthesis happen more quickly, especially for figure such as politicians.
- MIT Tech Review
- 2020
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- 5 min
- MIT Tech Review
- 2020
AI Summarisation
The Semantic Scholar is a new AI program which has been trained to read through scientific papers and provide a unique one sentence summary of the paper’s content. The AI has been trained with a large data set focused on learning how to process natural language and summarise it. The ultimate idea is to use technology to help learning and synthesis happen more quickly, especially for figure such as politicians.
How might this technology cause people to become lazy readers? How does this technology, like many other digital technologies, shorten attention spans? How can it be ensured that algorithms like this do not leave out critical information?
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- 2 min
- azfamily.com
- 2018
Facial recognition technology has found a new application: reuniting dogs with their owners. A simple machine learning algorithm takes a photo of a dog and crawls through a database of photos of dogs in shelters in hopes of finding a match.
- azfamily.com
- 2018
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- 2 min
- azfamily.com
- 2018
Facial recognition technology now used in Phoenix area to locate lost dogs
Facial recognition technology has found a new application: reuniting dogs with their owners. A simple machine learning algorithm takes a photo of a dog and crawls through a database of photos of dogs in shelters in hopes of finding a match.
How could this beneficial use of recognition technology find even broader use?
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- 20 min
- MIT Press
- 2018
Lilith, a contract laborer, ends up in a dangerous situation when the self-driving ship she rides malfunctions. Kyleen, a human who has undergone a human-editing networking process called “meshing,” is able to control a proxy robot via a brain-computer interface to help Lilith get to her destination safely.
- MIT Press
- 2018
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- 20 min
- MIT Press
- 2018
Robotic Proxies and Telepresence: “Different Seas” by Alastair Reynolds
Lilith, a contract laborer, ends up in a dangerous situation when the self-driving ship she rides malfunctions. Kyleen, a human who has undergone a human-editing networking process called “meshing,” is able to control a proxy robot via a brain-computer interface to help Lilith get to her destination safely.
How can robotic proxies be helpful to people in danger? Who should be allowed or certified to operate these, in theory? How might these be implicated in inequitable class structures, as outlined in the story? Should humans be networked with machines, and would this really be to the ultimate benefit of humanity?
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- 3 min
- TechCrunch
- 2021
This article presents several case studies of technologies introduced at CES which are specifically designed to help elderly people continue to live independently, mostly using smartphones and internets of things to monitor both the home environment and the physical health of the occupant.
- TechCrunch
- 2021
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- 3 min
- TechCrunch
- 2021
Startups at CES showed how tech can help elderly people and their caregivers
This article presents several case studies of technologies introduced at CES which are specifically designed to help elderly people continue to live independently, mostly using smartphones and internets of things to monitor both the home environment and the physical health of the occupant.
What implications do these technologies have for the agency of the senior citizens which they are meant to monitor? Does close surveillance truly equate to increased independence? Are there any other downsides or tradeoffs to these technologies?
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- 7 min
- VentureBeat
- 2021
New research and code was released in early 2021 to demonstrate that the training data for Natural Language Processing algorithms is not as robust as it could be. The project, Robustness Gym, allows researchers and computer scientists to approach training data with more scrutiny, organizing this data and testing the results of preliminary runs through the algorithm to see what can be improved upon and how.
- VentureBeat
- 2021
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- 7 min
- VentureBeat
- 2021
Salesforce researchers release framework to test NLP model robustness
New research and code was released in early 2021 to demonstrate that the training data for Natural Language Processing algorithms is not as robust as it could be. The project, Robustness Gym, allows researchers and computer scientists to approach training data with more scrutiny, organizing this data and testing the results of preliminary runs through the algorithm to see what can be improved upon and how.
What does “robustness” in a natural language processing algorithm mean to you? Should machines always be taught to automatically associate certain words or terms? What are the consequences of large corporations not using the most robust training data for their NLP algorithms?