Seeking resources on A.I. and machine learning
Dear AoIRists, I am researching artificial intelligence and machine learning within the framework of digital culture studies and philosophy of technoscience. Right now, I am looking for articles that reflect current developments in AI & ML programming that are suitable for non-STEM experts. Specifically, I am interested in pieces that illuminate the ways in which generalization and inductive/abductive reasoning are essential to algorithms that effectively “predict” the future. However, more wide-ranging, introductory pieces would also be helpful for me. I am familiar with the work of Pedro Domingos, but do not know of many other sources that suit my needs. Any recommendations would be very welcome. Thank you in advance! Best, Emma -- *Emma Stamm* *PhD Student, ASPECT Virginia Tech <https://liberalarts.vt.edu/departments-and-schools/alliance-for-social-political-ethical-and-cultural-thought.html>* *o-culus.com <http://o-culus.com> | @turing_tests*
Hi Emma and All, I've been compiling an "AI for social scientists" list as a Google Doc. Editing is set to public so feel free to add! It's currently organized reverse chronologically and has lots of room to grow. https://docs.google.com/document/d/1xAQlNqpoK8TUoB21i4XVze1zxkvgcKe06evTfdqd... [https://lh3.googleusercontent.com/ctAthH-HY-83A1XyPMxgu5yYr8_ahLAHoC1ksfl2fi1PSlis4jlqTsKOJV3s1jmR3h8dQQ=w1200-h630-p]<https://docs.google.com/document/d/1xAQlNqpoK8TUoB21i4XVze1zxkvgcKe06evTfdqd7BA/edit?usp=sharing> AI Reading List<https://docs.google.com/document/d/1xAQlNqpoK8TUoB21i4XVze1zxkvgcKe06evTfdqd7BA/edit?usp=sharing> docs.google.com AI Readings for Social Scientists Dillon Reisman, Jason Schultz, Kate Crawford, Meredith Whittaker. 2018 “AI Now Algorithmic Impact Assessments” https://ainowinstitute.org/aiareport2018.pdf Eubanks, Virginia. 2018. “Automating Inequality” https://us.macmillan.com/automatinginequality/virginiaeu... Best, Jenny Jenny L. Davis Lecturer, School of Sociology The Australian National University Co-Editor: Cyborgology<https://thesocietypages.org/cyborgology/> <https://twitter.com/Jenny_L_Davis> Twitter: @Jenny_L_Davis<https://twitter.com/Jenny_L_Davis> ________________________________ From: Air-L <air-l-bounces@listserv.aoir.org> on behalf of Emma Stamm <stamm@vt.edu> Sent: Wednesday, July 25, 2018 7:17:46 AM To: aoir list Subject: [Air-L] Seeking resources on A.I. and machine learning Dear AoIRists, I am researching artificial intelligence and machine learning within the framework of digital culture studies and philosophy of technoscience. Right now, I am looking for articles that reflect current developments in AI & ML programming that are suitable for non-STEM experts. Specifically, I am interested in pieces that illuminate the ways in which generalization and inductive/abductive reasoning are essential to algorithms that effectively “predict” the future. However, more wide-ranging, introductory pieces would also be helpful for me. I am familiar with the work of Pedro Domingos, but do not know of many other sources that suit my needs. Any recommendations would be very welcome. Thank you in advance! Best, Emma -- *Emma Stamm* *PhD Student, ASPECT Virginia Tech <https://liberalarts.vt.edu/departments-and-schools/alliance-for-social-political-ethical-and-cultural-thought.html>* *o-culus.com <http://o-culus.com> | @turing_tests* _______________________________________________ The Air-L@listserv.aoir.org mailing list is provided by the Association of Internet Researchers http://aoir.org Subscribe, change options or unsubscribe at: http://listserv.aoir.org/listinfo.cgi/air-l-aoir.org Join the Association of Internet Researchers: http://www.aoir.org/
A good overview as part of a course syllabus: AI Methodology - Theoretical aspects– Mathematical formalizations, properties, algorithms - Engineering aspects– The act of building (useful) machines - Empirical science– Experiments https://www.cs.cornell.edu/courses/cs4700/2013fa/slides/CS4700-Intro_part2_v... On Tue, Jul 24, 2018 at 11:12 PM, Jenny Davis <jennifer.davis@anu.edu.au> wrote:
Hi Emma and All,
I've been compiling an "AI for social scientists" list as a Google Doc. Editing is set to public so feel free to add! It's currently organized reverse chronologically and has lots of room to grow.
https://docs.google.com/document/d/1xAQlNqpoK8TUoB21i4XVze1zxkvgc Ke06evTfdqd7BA/edit?usp=sharing
[https://lh3.googleusercontent.com/ctAthH-HY-83A1XyPMxgu5yYr8_ ahLAHoC1ksfl2fi1PSlis4jlqTsKOJV3s1jmR3h8dQQ=w1200-h630-p]<ht tps://docs.google.com/document/d/1xAQlNqpoK8TUoB21i4XVze1zxkvgc Ke06evTfdqd7BA/edit?usp=sharing>
AI Reading List<https://docs.google.com/document/d/ 1xAQlNqpoK8TUoB21i4XVze1zxkvgcKe06evTfdqd7BA/edit?usp=sharing> docs.google.com AI Readings for Social Scientists Dillon Reisman, Jason Schultz, Kate Crawford, Meredith Whittaker. 2018 “AI Now Algorithmic Impact Assessments” https://ainowinstitute.org/aiareport2018.pdf Eubanks, Virginia. 2018. “Automating Inequality” https://us.macmillan.com/automatinginequality/ virginiaeu...
Best,
Jenny
Jenny L. Davis
Lecturer, School of Sociology
The Australian National University
Co-Editor: Cyborgology<https://thesocietypages.org/cyborgology/> < https://twitter.com/Jenny_L_Davis>
Twitter: @Jenny_L_Davis<https://twitter.com/Jenny_L_Davis>
________________________________ From: Air-L <air-l-bounces@listserv.aoir.org> on behalf of Emma Stamm < stamm@vt.edu> Sent: Wednesday, July 25, 2018 7:17:46 AM To: aoir list Subject: [Air-L] Seeking resources on A.I. and machine learning
Dear AoIRists,
I am researching artificial intelligence and machine learning within the framework of digital culture studies and philosophy of technoscience. Right now, I am looking for articles that reflect current developments in AI & ML programming that are suitable for non-STEM experts. Specifically, I am interested in pieces that illuminate the ways in which generalization and inductive/abductive reasoning are essential to algorithms that effectively “predict” the future. However, more wide-ranging, introductory pieces would also be helpful for me.
I am familiar with the work of Pedro Domingos, but do not know of many other sources that suit my needs. Any recommendations would be very welcome.
Thank you in advance!
Best,
Emma
-- *Emma Stamm* *PhD Student, ASPECT Virginia Tech <https://liberalarts.vt.edu/departments-and-schools/ alliance-for-social-political-ethical-and-cultural-thought.html>* *o-culus.com <http://o-culus.com> | @turing_tests* _______________________________________________ The Air-L@listserv.aoir.org mailing list is provided by the Association of Internet Researchers http://aoir.org Subscribe, change options or unsubscribe at: http://listserv.aoir.org/ listinfo.cgi/air-l-aoir.org
Join the Association of Internet Researchers: http://www.aoir.org/ _______________________________________________ The Air-L@listserv.aoir.org mailing list is provided by the Association of Internet Researchers http://aoir.org Subscribe, change options or unsubscribe at: http://listserv.aoir.org/ listinfo.cgi/air-l-aoir.org
Join the Association of Internet Researchers: http://www.aoir.org/
https://www.fatml.org/ On Tue, Jul 24, 2018 at 5:17 PM, Emma Stamm <stamm@vt.edu> wrote:
Dear AoIRists,
I am researching artificial intelligence and machine learning within the framework of digital culture studies and philosophy of technoscience. Right now, I am looking for articles that reflect current developments in AI & ML programming that are suitable for non-STEM experts. Specifically, I am interested in pieces that illuminate the ways in which generalization and inductive/abductive reasoning are essential to algorithms that effectively “predict” the future. However, more wide-ranging, introductory pieces would also be helpful for me.
I am familiar with the work of Pedro Domingos, but do not know of many other sources that suit my needs. Any recommendations would be very welcome.
Thank you in advance!
Best,
Emma
-- *Emma Stamm* *PhD Student, ASPECT Virginia Tech <https://liberalarts.vt.edu/departments-and-schools/ alliance-for-social-political-ethical-and-cultural-thought.html>* *o-culus.com <http://o-culus.com> | @turing_tests* _______________________________________________ The Air-L@listserv.aoir.org mailing list is provided by the Association of Internet Researchers http://aoir.org Subscribe, change options or unsubscribe at: http://listserv.aoir.org/ listinfo.cgi/air-l-aoir.org
Join the Association of Internet Researchers: http://www.aoir.org/
-- *Tracey P. Lauriault* Assistant Professor Critical Media Studies and Big Data Communication Studies School of Journalism and Communication Suite 4110, River Building Carleton University 1125 Colonel By Drive Ottawa (ON) K1S 5B6 1-613-520-2600 x7443 Tracey.Lauriault@Carleton.ca @TraceyLauriault Skype: Tracey.P.Lauriault https://carleton.ca/sjc/people-archives/lauriault-tracey/
Thanks all for sharing these! Jenny, is it ok to add to this list? I’m working on a piece now and have found some articles that would fit in nicely. Also, given the sorts of materials reflected in the materials already exchanged, I hope some of you might like to become part of the Center for Race and Digital Studies, link below. Best, — Shaka McGlotten (they/he) Associate Professor, Media Studies Coordinator, Gender Studies & Global Black Studies Center for Critical Race and Digital Studies<https://criticalracedigitalstudies.com/> On Jul 25, 2018, at 5:20 PM, Tracey P. Lauriault <tlauriau@gmail.com<mailto:tlauriau@gmail.com>> wrote: https://www.fatml.org/ On Tue, Jul 24, 2018 at 5:17 PM, Emma Stamm <stamm@vt.edu> wrote: Dear AoIRists, I am researching artificial intelligence and machine learning within the framework of digital culture studies and philosophy of technoscience. Right now, I am looking for articles that reflect current developments in AI & ML programming that are suitable for non-STEM experts. Specifically, I am interested in pieces that illuminate the ways in which generalization and inductive/abductive reasoning are essential to algorithms that effectively “predict” the future. However, more wide-ranging, introductory pieces would also be helpful for me. I am familiar with the work of Pedro Domingos, but do not know of many other sources that suit my needs. Any recommendations would be very welcome. Thank you in advance! Best, Emma -- *Emma Stamm* *PhD Student, ASPECT Virginia Tech <https://liberalarts.vt.edu/departments-and-schools/ alliance-for-social-political-ethical-and-cultural-thought.html>* *o-culus.com <http://o-culus.com> | @turing_tests* _______________________________________________ The Air-L@listserv.aoir.org mailing list is provided by the Association of Internet Researchers http://aoir.org Subscribe, change options or unsubscribe at: http://listserv.aoir.org/ listinfo.cgi/air-l-aoir.org Join the Association of Internet Researchers: http://www.aoir.org/ -- *Tracey P. Lauriault* Assistant Professor Critical Media Studies and Big Data Communication Studies School of Journalism and Communication Suite 4110, River Building Carleton University 1125 Colonel By Drive Ottawa (ON) K1S 5B6 1-613-520-2600 x7443 Tracey.Lauriault@Carleton.ca @TraceyLauriault Skype: Tracey.P.Lauriault https://carleton.ca/sjc/people-archives/lauriault-tracey/ _______________________________________________ The Air-L@listserv.aoir.org mailing list is provided by the Association of Internet Researchers http://aoir.org Subscribe, change options or unsubscribe at: http://listserv.aoir.org/listinfo.cgi/air-l-aoir.org Join the Association of Internet Researchers: http://www.aoir.org/
Hi everyone, This is such a wonderful collection of resources here! I'd like to add to the list Adrian Mackenzie's *Machine Learners* <https://mitpress.mit.edu/books/machine-learners>. Also of interest may be Matteo Pasquinelli's work <http://www.glass-bead.org/article/machines-that-morph-logic/?lang=enview>. Finally, if anyone wishes to start to get at the technical implementations or the pedagogical approaches to ML in Computer Sciencey circles, Andrew Ng's course here <https://www.coursera.org/learn/machine-learning> is the go-to for a number of people, so the introduction there may be of limited use. Cheers/ranjodh On Fri, 27 Jul 2018 at 09:45 Mcglotten, Shaka <shaka.mcglotten@purchase.edu> wrote:
Thanks all for sharing these! Jenny, is it ok to add to this list? I’m working on a piece now and have found some articles that would fit in nicely.
Also, given the sorts of materials reflected in the materials already exchanged, I hope some of you might like to become part of the Center for Race and Digital Studies, link below.
Best, — Shaka McGlotten (they/he) Associate Professor, Media Studies Coordinator, Gender Studies & Global Black Studies
Center for Critical Race and Digital Studies< https://criticalracedigitalstudies.com/>
On Jul 25, 2018, at 5:20 PM, Tracey P. Lauriault <tlauriau@gmail.com <mailto:tlauriau@gmail.com>> wrote:
On Tue, Jul 24, 2018 at 5:17 PM, Emma Stamm <stamm@vt.edu> wrote:
Dear AoIRists,
I am researching artificial intelligence and machine learning within the framework of digital culture studies and philosophy of technoscience. Right now, I am looking for articles that reflect current developments in AI & ML programming that are suitable for non-STEM experts. Specifically, I am interested in pieces that illuminate the ways in which generalization and inductive/abductive reasoning are essential to algorithms that effectively “predict” the future. However, more wide-ranging, introductory pieces would also be helpful for me.
I am familiar with the work of Pedro Domingos, but do not know of many other sources that suit my needs. Any recommendations would be very welcome.
Thank you in advance!
Best,
Emma
-- *Emma Stamm* *PhD Student, ASPECT Virginia Tech <https://liberalarts.vt.edu/departments-and-schools/ alliance-for-social-political-ethical-and-cultural-thought.html>* *o-culus.com <http://o-culus.com> | @turing_tests* _______________________________________________ The Air-L@listserv.aoir.org mailing list is provided by the Association of Internet Researchers http://aoir.org Subscribe, change options or unsubscribe at: http://listserv.aoir.org/ listinfo.cgi/air-l-aoir.org
Join the Association of Internet Researchers: http://www.aoir.org/
-- *Tracey P. Lauriault*
Assistant Professor Critical Media Studies and Big Data Communication Studies School of Journalism and Communication Suite 4110, River Building Carleton University 1125 Colonel By Drive Ottawa (ON) K1S 5B6
1-613-520-2600 x7443 <(613)%20520-2600> Tracey.Lauriault@Carleton.ca @TraceyLauriault Skype: Tracey.P.Lauriault https://carleton.ca/sjc/people-archives/lauriault-tracey/ _______________________________________________ The Air-L@listserv.aoir.org mailing list is provided by the Association of Internet Researchers http://aoir.org Subscribe, change options or unsubscribe at: http://listserv.aoir.org/listinfo.cgi/air-l-aoir.org
Join the Association of Internet Researchers: http://www.aoir.org/
_______________________________________________ The Air-L@listserv.aoir.org mailing list is provided by the Association of Internet Researchers http://aoir.org Subscribe, change options or unsubscribe at: http://listserv.aoir.org/listinfo.cgi/air-l-aoir.org
Join the Association of Internet Researchers: http://www.aoir.org/
-- Ranjodh Singh Dhaliwal https://www.ranjodhdhaliwal.com/ PhD Candidate in English with an emphasis in Science and Technology Studies, UC Davis. Sent from a cellphone. Please excuse any typos.
Hi Shaka and All, Yes, please do add to the list! I want it to be a collaboration and community resource. Best, Jenny Jenny L. Davis Lecturer, School of Sociology The Australian National University Co-Editor: Cyborgology<https://thesocietypages.org/cyborgology/> <https://twitter.com/Jenny_L_Davis> Twitter: @Jenny_L_Davis<https://twitter.com/Jenny_L_Davis> ________________________________ From: Mcglotten, Shaka <shaka.mcglotten@purchase.edu> Sent: Friday, July 27, 2018 5:45:19 PM To: aoir list Cc: Emma Stamm; Tracey P. Lauriault; Jenny Davis Subject: Re: [Air-L] Seeking resources on A.I. and machine learning Thanks all for sharing these! Jenny, is it ok to add to this list? I’m working on a piece now and have found some articles that would fit in nicely. Also, given the sorts of materials reflected in the materials already exchanged, I hope some of you might like to become part of the Center for Race and Digital Studies, link below. Best, — Shaka McGlotten (they/he) Associate Professor, Media Studies Coordinator, Gender Studies & Global Black Studies Center for Critical Race and Digital Studies<https://criticalracedigitalstudies.com/> On Jul 25, 2018, at 5:20 PM, Tracey P. Lauriault <tlauriau@gmail.com<mailto:tlauriau@gmail.com>> wrote: https://www.fatml.org/ On Tue, Jul 24, 2018 at 5:17 PM, Emma Stamm <stamm@vt.edu> wrote: Dear AoIRists, I am researching artificial intelligence and machine learning within the framework of digital culture studies and philosophy of technoscience. Right now, I am looking for articles that reflect current developments in AI & ML programming that are suitable for non-STEM experts. Specifically, I am interested in pieces that illuminate the ways in which generalization and inductive/abductive reasoning are essential to algorithms that effectively “predict” the future. However, more wide-ranging, introductory pieces would also be helpful for me. I am familiar with the work of Pedro Domingos, but do not know of many other sources that suit my needs. Any recommendations would be very welcome. Thank you in advance! Best, Emma -- *Emma Stamm* *PhD Student, ASPECT Virginia Tech <https://liberalarts.vt.edu/departments-and-schools/ alliance-for-social-political-ethical-and-cultural-thought.html>* *o-culus.com <http://o-culus.com> | @turing_tests* _______________________________________________ The Air-L@listserv.aoir.org mailing list is provided by the Association of Internet Researchers http://aoir.org Subscribe, change options or unsubscribe at: http://listserv.aoir.org/ listinfo.cgi/air-l-aoir.org Join the Association of Internet Researchers: http://www.aoir.org/ -- *Tracey P. Lauriault* Assistant Professor Critical Media Studies and Big Data Communication Studies School of Journalism and Communication Suite 4110, River Building Carleton University 1125 Colonel By Drive Ottawa (ON) K1S 5B6 1-613-520-2600 x7443 Tracey.Lauriault@Carleton.ca @TraceyLauriault Skype: Tracey.P.Lauriault https://carleton.ca/sjc/people-archives/lauriault-tracey/ _______________________________________________ The Air-L@listserv.aoir.org mailing list is provided by the Association of Internet Researchers http://aoir.org Subscribe, change options or unsubscribe at: http://listserv.aoir.org/listinfo.cgi/air-l-aoir.org Join the Association of Internet Researchers: http://www.aoir.org/
Another list that I am maintaining, from the perspectives of cultural + software studies + artistic practices, also with technical parts where source code is available (from the perspective of beginner). http://softwarestudies.projects.cavi.au.dk/index.php/Machine_Learning_Experi... /winnie -- /* Winnie Soon - artist-researcher Assistant Professor @ PIT Research Centre, Aarhus University, Denmark <http://pit.au.dk> www.siusoon.net <http://www.siusoon.com> */ On 24 July 2018 at 23:17, Emma Stamm <stamm@vt.edu> wrote:
Dear AoIRists,
I am researching artificial intelligence and machine learning within the framework of digital culture studies and philosophy of technoscience. Right now, I am looking for articles that reflect current developments in AI & ML programming that are suitable for non-STEM experts. Specifically, I am interested in pieces that illuminate the ways in which generalization and inductive/abductive reasoning are essential to algorithms that effectively “predict” the future. However, more wide-ranging, introductory pieces would also be helpful for me.
I am familiar with the work of Pedro Domingos, but do not know of many other sources that suit my needs. Any recommendations would be very welcome.
Thank you in advance!
Best,
Emma
-- *Emma Stamm* *PhD Student, ASPECT Virginia Tech <https://liberalarts.vt.edu/departments-and-schools/ alliance-for-social-political-ethical-and-cultural-thought.html>* *o-culus.com <http://o-culus.com> | @turing_tests* _______________________________________________ The Air-L@listserv.aoir.org mailing list is provided by the Association of Internet Researchers http://aoir.org Subscribe, change options or unsubscribe at: http://listserv.aoir.org/ listinfo.cgi/air-l-aoir.org
Join the Association of Internet Researchers: http://www.aoir.org/
Hi! I gave a talk about AI and the future of work at NESTA Future Fest Forward a few weeks ago, see the video here https://www.nesta.org.uk/event/futurefest-forward-ai-and-future-work/ if that's of any use Phoebe Dr Phoebe V Moore Personal email pvm.doc@gmail.com Work email pm358@le.ac.uk <p.moore@mdx.ac.uk> Twitter @phoebemoore Biolog http://phoebevmoore.wordpress.com/ On 1 August 2018 at 11:21, // Winnie Soon <siusoon@gmail.com> wrote:
Another list that I am maintaining, from the perspectives of cultural + software studies + artistic practices, also with technical parts where source code is available (from the perspective of beginner).
http://softwarestudies.projects.cavi.au.dk/index.php/ Machine_Learning_Experiments
/winnie
-- /* Winnie Soon - artist-researcher Assistant Professor @ PIT Research Centre, Aarhus University, Denmark <http://pit.au.dk> www.siusoon.net <http://www.siusoon.com> */
On 24 July 2018 at 23:17, Emma Stamm <stamm@vt.edu> wrote:
Dear AoIRists,
I am researching artificial intelligence and machine learning within the framework of digital culture studies and philosophy of technoscience. Right now, I am looking for articles that reflect current developments in AI & ML programming that are suitable for non-STEM experts. Specifically, I am interested in pieces that illuminate the ways in which generalization and inductive/abductive reasoning are essential to algorithms that effectively “predict” the future. However, more wide-ranging, introductory pieces would also be helpful for me.
I am familiar with the work of Pedro Domingos, but do not know of many other sources that suit my needs. Any recommendations would be very welcome.
Thank you in advance!
Best,
Emma
-- *Emma Stamm* *PhD Student, ASPECT Virginia Tech <https://liberalarts.vt.edu/departments-and-schools/ alliance-for-social-political-ethical-and-cultural-thought.html>* *o-culus.com <http://o-culus.com> | @turing_tests* _______________________________________________ The Air-L@listserv.aoir.org mailing list is provided by the Association of Internet Researchers http://aoir.org Subscribe, change options or unsubscribe at: http://listserv.aoir.org/ listinfo.cgi/air-l-aoir.org
Join the Association of Internet Researchers: http://www.aoir.org/
The Air-L@listserv.aoir.org mailing list is provided by the Association of Internet Researchers http://aoir.org Subscribe, change options or unsubscribe at: http://listserv.aoir.org/ listinfo.cgi/air-l-aoir.org
Join the Association of Internet Researchers: http://www.aoir.org/
participants (8)
-
// Winnie Soon -
Emma Stamm -
Jenny Davis -
Ken Latta -
Mcglotten, Shaka -
Phoebe Moore -
Ranjodh Singh Dhaliwal -
Tracey P. Lauriault