User:Alexander Roidl/bookscanning: Difference between revisions
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* generating new data | * generating new data | ||
(endless data generation) | (endless data generation) | ||
* what data is selected? | |||
* how to find sth. in that data (analysis)? | |||
* FILTERS | |||
=bubbles= | =bubbles= | ||
| Line 55: | Line 58: | ||
* books become searchable and more connected | * books become searchable and more connected | ||
* quantitative method (counting women vs. counting men) | * quantitative method (counting women vs. counting men) | ||
=Feedback= | |||
* scanned material to train an algorithm > a chatbot trained on the books that are scanned > ref to Google Books (and to failed twitterbot) | |||
** always limited resources as input | |||
* What happens if you train this chat bot on a book, not on social media material | |||
Connecting to the reader | |||
* What is lost, what is gained by scanning | |||
* forensic materiality to more performative materiality | |||
* "Not enough data" as a mantra to promise that the algorithm gets better | |||
* The scanner as a mediator to use other types of data | |||
> fembot | |||
https://www.nytimes.com/2018/02/04/arts/fembot-poppy-lil-miquela-kylie-jenner.html | |||
http://soulellis.com/ book on chatbots by artists and designers | |||
Enron company, the Enron dataset https://www.cs.cmu.edu/~enron/ | |||
datasets that are used often also shape the language, a standardized way to assess 'natural' language | |||
leaked data used for machine learning | |||
Sam Lavigne and Tega Brain: The Good Life | |||
https://www.newmuseum.org/calendar/view/1258/the-making-of-natural-language (there is also a video recording of the event) | |||
http://publicdomainday.constantvzw.org/ the death of the author | |||
The Bot Opera http://video.constantvzw.org/PublicDomainDay2015/NEWNOVA.webm | |||
2015 edition: http://publicdomainday.constantvzw.org/#1943 | |||
Train chatbot on dataset | |||
-> extremist references | |||
-> introduction on | |||
=the database / data-usage= | |||
how does the data influence the algorithm? | |||
where data for algorithms is coming from | |||
-> books / internet | |||
-> training AI | |||
how is the data being selected? | |||
-> you can not see the data in the background | |||
-> you do not know what Google uses its data for | |||
==Feedback Steve== | |||
* Protocol by Alexander Gallaway (how interface is organized) | |||
* Software takes command (serve interests of several groups) | |||
* Sorting Things Out | |||
* Literacy and its consequences | |||
==Related Texts== | |||
Sorted by importance | |||
* Lev Manovich – The database | |||
* http://adanewmedia.org/blog/2015/11/01/issue8-masters/ | |||
* http://adanewmedia.org/blog/2016/05/01/issue9-hoffmann-and-bloom/ | |||
* webs of feminist knowledge | |||
* https://www.wired.com/2010/02/ff_google_algorithm/ | |||
==Femenist methodologies== | |||
=Sources= | =Sources= | ||
| Line 74: | Line 149: | ||
Article on Roger Chartier and the past & Future of books | Article on Roger Chartier and the past & Future of books | ||
http://www.booksandideas.net/The-Book-Its-Past-Its-Future.html | http://www.booksandideas.net/The-Book-Its-Past-Its-Future.html | ||
Data selection of AI bots | |||
https://www.newmuseum.org/exhibitions/view/sam-lavigne-and-tega-brain-the-good-life | |||
https://www.cs.cmu.edu/~enron/ | |||
Fembot | |||
https://www.nytimes.com/2018/02/04/arts/fembot-poppy-lil-miquela-kylie-jenner.html | |||
Latest revision as of 14:25, 7 February 2018
transformative processes
- transforming knowledge
- creating new file
- creating new »content«
- new possibilities of processing (OCR, analysis…)
- revealing information layers (printing technique)
- turning an analog medium into a digital file
- change of object, color, pages, reading flow
- Kantian model of the book (object, that’s sellable & knowledge)
- Chartier
- display is changing
- reproducing the reproduced (Walter Benjamin -> next level)
scanning as a tool
- creating graphics / visuals out of scanned pages
-> draw an image from a scanned book pages -> AI? drawing images / abstract / concrete / emotion
- missuse -> new unexpected results
big data
- generating new data
(endless data generation)
- what data is selected?
- how to find sth. in that data (analysis)?
- FILTERS
bubbles
- we live within a given framework
- selection of texts leads to an opinion
- filter
- idea: chatbot trained only from scanned book pages
- sherry turkle?
light-sensitive color
- print with light-sensitive color
-> see nothing / image when scanned or -> see the text when scanned, but it disappears after scanning
More
Access to…
- digitale books
- analog books
- who has access / who hasn't and why?
- how easy is access (com. digital / analog)
Adding/Deleting/Altering information of existing books
- (piracy - connected to anonymous )
Feminist Methodologies
How digitization is changing the view on sexism/feminism
- books become searchable and more connected
- quantitative method (counting women vs. counting men)
Feedback
- scanned material to train an algorithm > a chatbot trained on the books that are scanned > ref to Google Books (and to failed twitterbot)
- always limited resources as input
- What happens if you train this chat bot on a book, not on social media material
Connecting to the reader
- What is lost, what is gained by scanning
- forensic materiality to more performative materiality
- "Not enough data" as a mantra to promise that the algorithm gets better
- The scanner as a mediator to use other types of data
> fembot https://www.nytimes.com/2018/02/04/arts/fembot-poppy-lil-miquela-kylie-jenner.html
http://soulellis.com/ book on chatbots by artists and designers
Enron company, the Enron dataset https://www.cs.cmu.edu/~enron/ datasets that are used often also shape the language, a standardized way to assess 'natural' language leaked data used for machine learning Sam Lavigne and Tega Brain: The Good Life https://www.newmuseum.org/calendar/view/1258/the-making-of-natural-language (there is also a video recording of the event)
http://publicdomainday.constantvzw.org/ the death of the author The Bot Opera http://video.constantvzw.org/PublicDomainDay2015/NEWNOVA.webm 2015 edition: http://publicdomainday.constantvzw.org/#1943
Train chatbot on dataset -> extremist references -> introduction on
the database / data-usage
how does the data influence the algorithm?
where data for algorithms is coming from -> books / internet -> training AI
how is the data being selected?
-> you can not see the data in the background
-> you do not know what Google uses its data for
Feedback Steve
- Protocol by Alexander Gallaway (how interface is organized)
- Software takes command (serve interests of several groups)
- Sorting Things Out
- Literacy and its consequences
Related Texts
Sorted by importance
- Lev Manovich – The database
- http://adanewmedia.org/blog/2015/11/01/issue8-masters/
- http://adanewmedia.org/blog/2016/05/01/issue9-hoffmann-and-bloom/
- webs of feminist knowledge
- https://www.wired.com/2010/02/ff_google_algorithm/
Femenist methodologies
Sources
The Mass Digitization of Books: http://www.kcoyle.net/jal-32-6.html
https://en.wikipedia.org/wiki/Roger_Chartier
Discussion on Googles Book Scanning http://www.firstmonday.org/article/view/2101/2037
NYT article on Google’s bookscanning & bookscanning in general http://www.nytimes.com/2006/05/14/magazine/14publishing.html
(Video) What is a book by Roger Chartier http://mediasitemob1.mediagroup.ubc.ca/Mediasite/Play/b7ff39a973534d4c9583fcd935ee2c581d
Article on Roger Chartier and the past & Future of books http://www.booksandideas.net/The-Book-Its-Past-Its-Future.html
Data selection of AI bots https://www.newmuseum.org/exhibitions/view/sam-lavigne-and-tega-brain-the-good-life
https://www.cs.cmu.edu/~enron/
Fembot https://www.nytimes.com/2018/02/04/arts/fembot-poppy-lil-miquela-kylie-jenner.html