#facct — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #facct, aggregated by home.social.
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The Netherlands: the police quietly stop using CAS (the Crime Anticipation System), a country-wide predictive policing system.
‘Ten years ago, The Netherlands introduced a national police system that used data and algorithms to predict crime rates in neighbourhoods. It never worked properly, and warnings about bias had been raised for years.’
‘Politie stapte in stilte af van algoritme dat kans op misdaad in buurten zou voorspellen’
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New paper, open access.
‘If Deceptive Patterns are the problem, are Fair Patterns the solution?’
By Tim de Jonge, Hanna Schraffenberger, Jorrit Geels, Jaap-Henk Hoepman, Marie-Sophie Simon & me.
https://dl.acm.org/doi/10.1145/3715275.3732199
#law #tech #design #darkpatterns #facct #deceptivepatterns #manipulation #privacy
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How to use FaCCT (ACM Conference on Fairness, Accountability, and Transparency) template for journals requiring use of #LaTeX templates
https://github.com/Zettlr/Zettlr#:Rr9ab:
Guidelines for the conference will link to the ACM proceedings guide, as #FaCCT is an Association for Computing Machinery #ACM conference.
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Who do I know here who's going to #FAccT #FAccT2025 in Athens? #Fairness
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Call for Papers, AIMMES 2025: AI fairness and bias Measurements, Mitigation, Explanation Strategies
https://ai-fairness-cluster.zohobackstage.com/AIFairnessClusterConference2025#/sponsors?lang=en
#law #computerscience #facct #bias #discrimination #ai #tech #academia -
The preprint of our #recsys2024 LBR paper on "Understanding Fairnesss in Recommender Systems: A Healthcare Perspective" is now available at https://alansaid.com/publications/2024-kecki-fairness/
#recsys #fairness #facct -
The preprint of our #recsys2024 LBR paper on "Understanding Fairnesss in Recommender Systems: A Healthcare Perspective" is now available at https://alansaid.com/publications/2024-kecki-fairness/
#recsys #fairness #facct -
Nina Baranowska, @philipphacker, Alessandro Fabris & I published a new pre-print:
'Non-discrimination law in Europe: a primer for non-lawyers'
We have tried to write it in such a ways that non-lawyers can follow the text. We hope we succeeded a bit :)
If you have suggestions to improve the paper, we would love to hear them!
That's the fun thing of a pre-print: we can still amend things.
https://arxiv.org/abs/2404.08519
#ai #tech #bias #discrimination #facct #humanrights #law #gdpr #aiact
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#SIMswap hijacking #phone numbers in #eSIM attacks
Russian #cybersecurity firm #FACCT reports that #SIM swappers in the country and worldwide have been taking advantage of this shift to eSIMs to hijack phone numbers and bypass protections to access bank accounts. Now, attackers breach a user's mobile account with stolen, brute-forced, or leaked credentials and initiate porting the victim's number to another device on their own.
https://www.bleepingcomputer.com/news/security/sim-swappers-hijacking-phone-numbers-in-esim-attacks/ -
📬 eSIM-Hack ermöglicht Übernahme fremder Kontos
#Cyberangriffe #Mobilfunk #DmitryDudkov #eSIMKartenHack #eSIMSwapping #FACCT #Haftung #SIMKarte https://sc.tarnkappe.info/a3a874 -
"Going back to #FAccT, I should mention that, in browsing recent papers, it seems that many participants are willing to ask not just the how-to-build-it-better question, but the should-we-build-it question. This line distinguishes discourse that power will have no problem with and discourse that will be painted as radical, regressive, and inappropriate" https://web.cs.ucdavis.edu/~rogaway/papers/crisis/crisis.pdf
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Russian Authorities Arrest SugarLocker Operator in Connection with Global Cyberattacks https://thecyberexpress.com/sugarlocker-member-arrest-in-cybercrime/ #SugarLockerransomwaregroup #SugarLockermemberarrest #RussianLawEnforcement #TheCyberExpress #FirewallDaily #HackingNews #FACCT #RaaS
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Russian Authorities Arrest SugarLocker Operator in Connection with Global Cyberattacks https://thecyberexpress.com/sugarlocker-member-arrest-in-cybercrime/ #SugarLockerransomwaregroup #SugarLockermemberarrest #RussianLawEnforcement #TheCyberExpress #FirewallDaily #HackingNews #FACCT #RaaS
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What are the key concepts a 2 hours long lecture on #FAccT / #FATE in #recsys should cover? (pointers to papers appreciated). The lecture will be part of our #cogsci program, specifically in a course on influence in in digital society (https://kursplaner.gu.se/english/tig119.pdf)
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A few days ago, Mattias Rost and I sat down to continue our conversation on #HumancenteredArtificialIntelligencel Tune in!
https://hci.social/@hcai/111533010650426890 #ArtificialIntelligence #hcai #facct #fate #hci #ai -
A few days ago, Mattias Rost and I sat down to continue our conversation on #HumancenteredArtificialIntelligencel Tune in!
https://hci.social/@hcai/111533010650426890 #ArtificialIntelligence #hcai #facct #fate #hci #ai -
A few days ago, Mattias Rost and I sat down to continue our conversation on #HumancenteredArtificialIntelligencel Tune in!
https://hci.social/@hcai/111533010650426890 #ArtificialIntelligence #hcai #facct #fate #hci #ai -
'Uber still dragging its feet on algorithmic transparency, Dutch court finds'
In a legal battle about the GDPR's right to an explanation.Reporting by @riptari
2 months ago, but I mention it anyway in case you missed it.
https://techcrunch.com/2023/10/05/uber-slow-on-algo-transparency/
#ai #tech #law #ai #facct #gdpr #eu #Netherlands
https://techcrunch.com/2023/10/05/uber-slow-on-algo-transparency/?guccounter=1 -
Racism and Technology Center, newsletter
https://racismandtechnology.center/tag/newsletter-38/
#tech #ai #bias #discrimination #racism #facct #law #politics -
If, like most people, you don’t speak Dutch: here is a blog post in English in which we make similar points:
Using sensitive data to prevent AI-driven discrimination: Does the EU GDPR need a new exception?
https://iapp.org/news/a/using-sensitive-data-to-prevent-ai-discrimination-does-the-eu-gdpr-need-a-new-exception/
#AI #FAccT #bias #discrimination #tech #gdpr #privacy #data #dataprotection #datascience #machinelearning #aiact #law -
Nieuwe blog post door Marvin van Bekkum & mij:
Mag je gevoelige gegevens verwerken om discriminatie door AI tegen te gaan, en waarom (niet)?https://ibestuur.nl/artikel/gevoelige-gegevens-verwerken-om-discriminatie-door-ai-tegen-te-gaan/
#AI #FAccT #bias #discrimination #tech #gdpr #privacy #data #dataprotection #datascience #machinelearning #aiact #avg
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Russian Cybersecurity Executive Arrested for Alleged Role in 2012 Megahacks https://krebsonsecurity.com/2023/06/russian-cybersecurity-executive-arrested-for-alleged-role-in-2012-megahacks/ #FightAgainstCybercrimeTechnologies #U.S.Securities&ExchangeCommission #OleksandrVitalyevichIeremenko #Ne'er-Do-WellNews #U.S.SecretService #YevgeniyNikulin #DmitryVolkov #OlegTolstikh #IlyaSachkov #ArkadyBukh #Formspring #Group-IB #LinkedIn #Dropbox #Lamarez #FACCT #Zl0m
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The gradient of generative AI release: important #facct paper by @irenesolaiman https://dl.acm.org/doi/10.1145/3593013.3593981
(we came across it while finishing the proofs for our #cui2023 paper on a related topic — just in time to include it)
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The gradient of generative AI release: important #facct paper by @irenesolaiman https://dl.acm.org/doi/10.1145/3593013.3593981
(we came across it while finishing the proofs for our #cui2023 paper on a related topic — just in time to include it)
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The gradient of generative AI release: important #facct paper by @irenesolaiman https://dl.acm.org/doi/10.1145/3593013.3593981
(we came across it while finishing the proofs for our #cui2023 paper on a related topic — just in time to include it)
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The gradient of generative AI release: important #facct paper by @irenesolaiman https://dl.acm.org/doi/10.1145/3593013.3593981
(we came across it while finishing the proofs for our #cui2023 paper on a related topic — just in time to include it)
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The gradient of generative AI release: important #facct paper by @irenesolaiman https://dl.acm.org/doi/10.1145/3593013.3593981
(we came across it while finishing the proofs for our #cui2023 paper on a related topic — just in time to include it)
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FAccT: We identify harms in tech, but often the workers building this tech *don't have _power_ to fix these harms*. #FAccT2023
This questions FAccT theories of change.
At 2:30pm in W196BC in the "Workplace" session, join me+Derrick Zhen for our paper:
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In a Theory of Change panel at
@FAccTConference #FAccT 1) advocate to abolish harmful tech, or 2) participate in its development to reduce harm.IoT microphones mandatorially installed in CMU offices & the story of when I unplugged them, is instructive:
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"Even the most impressive #AIchatbots require thousands of human work hours to behave in a way their creators want them to, and even then they do it unreliably. The work can be brutal and upsetting, as we will hear this week when the ACM Conference on #Fairness, #Accountability, and #Transparency (#FAccT) gets underway. It’s a conference that brings together research on things I like to write about, such as how to make #AISystems more #accountable and #ethical." https://www.technologyreview.com/2023/06/13/1074560/we-are-all-ais-free-data-workers/
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1/3
Absolutely thrilled that our paper on Regulating ChatGPT and other Large Generative AI Models was accepted at ACM #FAccT, perhaps the leading conference and publication on AI Law and Ethics. This is joint work w/ Andreas Engel and Marco Mauer. Many thanks to all the persons and audiences who provided great feedback on the paper!Link to the paper: https://arxiv.org/abs/2302.02337
Link to the conference: https://facctconference.org/
#chatgpt #gpt4 #law #itrecht #itlaw #ml #ki #ai #aiact #dsa #facct2023
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#introduction and news
I guess it's time for an introduction. I'm a research scientist at Google based in Montréal where I work on the design and evaluation of machine learning systems, especially search and recommender systems and their broader societal effects.
#recsys #sigir #machinelearning #hcai #facct @facct @recsys
and...
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#introduction and news
I guess it's time for an introduction. I'm a research scientist at Google based in Montréal where I work on the design and evaluation of machine learning systems, especially search and recommender systems and their broader societal effects.
#recsys #sigir #machinelearning #hcai #facct @facct @recsys
and...
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#introduction and news
I guess it's time for an introduction. I'm a research scientist at Google based in Montréal where I work on the design and evaluation of machine learning systems, especially search and recommender systems and their broader societal effects.
#recsys #sigir #machinelearning #hcai #facct @facct @recsys
and...
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Further to the last boosted post about the lawsuit against GitHub Copilot – https://fediscience.org/@riedl/109282064359790093
This case connects with something I’m thinking about in connection with AI image generators like DALL•E, but it shows that this issue generalizes to any case of AI trained on data scraped from the web. There’s a presumption in AI development that data of any kind that one finds on the public web is free for the taking. They treat those data as, in effect, unclaimed natural resources, the sort of thing that John Locke argued is yours once your labour improves or builds upon it to produce something new.
But this is false on its face. First, as decolonial thinkers have pointed out, no natural resources are “unclaimed”—what explorers found and declared to be terra nullius actually belonged to indigenous communities. Data on the web are no different: they don't just exist there waiting to be exploited; they belong to real people on the other side of the network. The resource-extraction mindset of AI development based on data scraped from the web is modelled after the plunder and pillage of colonization.
Second, and building on this, as the lawsuit against GitHub Copilot argues, these data are the intellectual property of their creators. Code uploaded to GitHub is rarely released into the public domain; it is often libre or open source, and where no licence is included the presumption should be that it is protected by copyright. The lawsuit alleges that coders’ intellectual property rights have been infringed by the developers who used their code to train Copilot, because the terms of the various copyright licences have not been respected.
Third, even if the lawsuit and similar legal arguments don't succeed, there’s an ethical argument about intellectual property that does. This brings us back to Locke: recall that he argues that things produced by your labour are yours by right. This argument has been used to justify intellectual property rights as well as physical property rights: the products of your labour belong to you, so long as what you transformed with your labour wasn’t itself stolen. This goes for both the labour of the body and the labour of the mind—creative and intellectual labour, such as that which goes into writing code or painting digital images. But Locke's argument is set up so that it doesn't depend on any particular legal framework of property rights, intellectual or otherwise. His account of labour and property is set in the state of nature, where there is no government or law to enforce anyone’s rights.
So the ethical point stands regardless of whether the lawsuit against Github Copilot succeeds or fails. Using code or images or whatever kind of data you can download from the web and encode for training AI, without seeking permission from the creators or respecting the terms under which they licensed their work, is theft. And, it is not just theft of intellectual and creative property: it’s theft of labour and plunder of goods that the colonialist mindset frames as unowned.
There are plenty of unanswered questions here of course but I'm interested to hear what folks think of this argument. I'm currently working on writing it up as a paper, maybe for @facct. Am I missing anything? What objections do I need to answer?
Here’s the announcement of the lawsuit against GitHub Copilot: https://githubcopilotlitigation.com/
#aiEthics #ethicsOfComputing #artificialIntelligence #AI #ethics #philosophy #facct #responsibleComputing #techEthics #computerEthics #computerScience
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Further to the last boosted post about the lawsuit against GitHub Copilot – https://fediscience.org/@riedl/109282064359790093
This case connects with something I’m thinking about in connection with AI image generators like DALL•E, but it shows that this issue generalizes to any case of AI trained on data scraped from the web. There’s a presumption in AI development that data of any kind that one finds on the public web is free for the taking. They treat those data as, in effect, unclaimed natural resources, the sort of thing that John Locke argued is yours once your labour improves or builds upon it to produce something new.
But this is false on its face. First, as decolonial thinkers have pointed out, no natural resources are “unclaimed”—what explorers found and declared to be terra nullius actually belonged to indigenous communities. Data on the web are no different: they don't just exist there waiting to be exploited; they belong to real people on the other side of the network. The resource-extraction mindset of AI development based on data scraped from the web is modelled after the plunder and pillage of colonization.
Second, and building on this, as the lawsuit against GitHub Copilot argues, these data are the intellectual property of their creators. Code uploaded to GitHub is rarely released into the public domain; it is often libre or open source, and where no licence is included the presumption should be that it is protected by copyright. The lawsuit alleges that coders’ intellectual property rights have been infringed by the developers who used their code to train Copilot, because the terms of the various copyright licences have not been respected.
Third, even if the lawsuit and similar legal arguments don't succeed, there’s an ethical argument about intellectual property that does. This brings us back to Locke: recall that he argues that things produced by your labour are yours by right. This argument has been used to justify intellectual property rights as well as physical property rights: the products of your labour belong to you, so long as what you transformed with your labour wasn’t itself stolen. This goes for both the labour of the body and the labour of the mind—creative and intellectual labour, such as that which goes into writing code or painting digital images. But Locke's argument is set up so that it doesn't depend on any particular legal framework of property rights, intellectual or otherwise. His account of labour and property is set in the state of nature, where there is no government or law to enforce anyone’s rights.
So the ethical point stands regardless of whether the lawsuit against Github Copilot succeeds or fails. Using code or images or whatever kind of data you can download from the web and encode for training AI, without seeking permission from the creators or respecting the terms under which they licensed their work, is theft. And, it is not just theft of intellectual and creative property: it’s theft of labour and plunder of goods that the colonialist mindset frames as unowned.
There are plenty of unanswered questions here of course but I'm interested to hear what folks think of this argument. I'm currently working on writing it up as a paper, maybe for @facct. Am I missing anything? What objections do I need to answer?
Here’s the announcement of the lawsuit against GitHub Copilot: https://githubcopilotlitigation.com/
#aiEthics #ethicsOfComputing #artificialIntelligence #AI #ethics #philosophy #facct #responsibleComputing #techEthics #computerEthics #computerScience
-
Further to the last boosted post about the lawsuit against GitHub Copilot – https://fediscience.org/@riedl/109282064359790093
This case connects with something I’m thinking about in connection with AI image generators like DALL•E, but it shows that this issue generalizes to any case of AI trained on data scraped from the web. There’s a presumption in AI development that data of any kind that one finds on the public web is free for the taking. They treat those data as, in effect, unclaimed natural resources, the sort of thing that John Locke argued is yours once your labour improves or builds upon it to produce something new.
But this is false on its face. First, as decolonial thinkers have pointed out, no natural resources are “unclaimed”—what explorers found and declared to be terra nullius actually belonged to indigenous communities. Data on the web are no different: they don't just exist there waiting to be exploited; they belong to real people on the other side of the network. The resource-extraction mindset of AI development based on data scraped from the web is modelled after the plunder and pillage of colonization.
Second, and building on this, as the lawsuit against GitHub Copilot argues, these data are the intellectual property of their creators. Code uploaded to GitHub is rarely released into the public domain; it is often libre or open source, and where no licence is included the presumption should be that it is protected by copyright. The lawsuit alleges that coders’ intellectual property rights have been infringed by the developers who used their code to train Copilot, because the terms of the various copyright licences have not been respected.
Third, even if the lawsuit and similar legal arguments don't succeed, there’s an ethical argument about intellectual property that does. This brings us back to Locke: recall that he argues that things produced by your labour are yours by right. This argument has been used to justify intellectual property rights as well as physical property rights: the products of your labour belong to you, so long as what you transformed with your labour wasn’t itself stolen. This goes for both the labour of the body and the labour of the mind—creative and intellectual labour, such as that which goes into writing code or painting digital images. But Locke's argument is set up so that it doesn't depend on any particular legal framework of property rights, intellectual or otherwise. His account of labour and property is set in the state of nature, where there is no government or law to enforce anyone’s rights.
So the ethical point stands regardless of whether the lawsuit against Github Copilot succeeds or fails. Using code or images or whatever kind of data you can download from the web and encode for training AI, without seeking permission from the creators or respecting the terms under which they licensed their work, is theft. And, it is not just theft of intellectual and creative property: it’s theft of labour and plunder of goods that the colonialist mindset frames as unowned.
There are plenty of unanswered questions here of course but I'm interested to hear what folks think of this argument. I'm currently working on writing it up as a paper, maybe for @facct. Am I missing anything? What objections do I need to answer?
Here’s the announcement of the lawsuit against GitHub Copilot: https://githubcopilotlitigation.com/
#aiEthics #ethicsOfComputing #artificialIntelligence #AI #ethics #philosophy #facct #responsibleComputing #techEthics #computerEthics #computerScience
-
Further to the last boosted post about the lawsuit against GitHub Copilot – https://fediscience.org/@riedl/109282064359790093
This case connects with something I’m thinking about in connection with AI image generators like DALL•E, but it shows that this issue generalizes to any case of AI trained on data scraped from the web. There’s a presumption in AI development that data of any kind that one finds on the public web is free for the taking. They treat those data as, in effect, unclaimed natural resources, the sort of thing that John Locke argued is yours once your labour improves or builds upon it to produce something new.
But this is false on its face. First, as decolonial thinkers have pointed out, no natural resources are “unclaimed”—what explorers found and declared to be terra nullius actually belonged to indigenous communities. Data on the web are no different: they don't just exist there waiting to be exploited; they belong to real people on the other side of the network. The resource-extraction mindset of AI development based on data scraped from the web is modelled after the plunder and pillage of colonization.
Second, and building on this, as the lawsuit against GitHub Copilot argues, these data are the intellectual property of their creators. Code uploaded to GitHub is rarely released into the public domain; it is often libre or open source, and where no licence is included the presumption should be that it is protected by copyright. The lawsuit alleges that coders’ intellectual property rights have been infringed by the developers who used their code to train Copilot, because the terms of the various copyright licences have not been respected.
Third, even if the lawsuit and similar legal arguments don't succeed, there’s an ethical argument about intellectual property that does. This brings us back to Locke: recall that he argues that things produced by your labour are yours by right. This argument has been used to justify intellectual property rights as well as physical property rights: the products of your labour belong to you, so long as what you transformed with your labour wasn’t itself stolen. This goes for both the labour of the body and the labour of the mind—creative and intellectual labour, such as that which goes into writing code or painting digital images. But Locke's argument is set up so that it doesn't depend on any particular legal framework of property rights, intellectual or otherwise. His account of labour and property is set in the state of nature, where there is no government or law to enforce anyone’s rights.
So the ethical point stands regardless of whether the lawsuit against Github Copilot succeeds or fails. Using code or images or whatever kind of data you can download from the web and encode for training AI, without seeking permission from the creators or respecting the terms under which they licensed their work, is theft. And, it is not just theft of intellectual and creative property: it’s theft of labour and plunder of goods that the colonialist mindset frames as unowned.
There are plenty of unanswered questions here of course but I'm interested to hear what folks think of this argument. I'm currently working on writing it up as a paper, maybe for @facct. Am I missing anything? What objections do I need to answer?
Here’s the announcement of the lawsuit against GitHub Copilot: https://githubcopilotlitigation.com/
#aiEthics #ethicsOfComputing #artificialIntelligence #AI #ethics #philosophy #facct #responsibleComputing #techEthics #computerEthics #computerScience