December 2019 - nexa - server-nexa.polito.it

Re: [nexa] esperimento https://amazon.tracking.exposed - verificare se le DSAR sono complete

by Luigi Scorca

Grazie, leggo con vivo interesse. C'è nulla su come un algoritmo assegna eventuali servizi di consegna attraverso una piattaforma crowdsourced? Grazie Il sab 7 dic 2019, 10:39 Claudio Agosti <claudio.agosti(a)hermescenter.org> ha scritto: > Buongiorno Nexa, > > Sono stato invitato un paio di mesi fa, a partecipare ad una trasmissione > (Petrolio, Rai2, episodio del 6 Dicembre) su Amazon. > > Quindi, abbiamo modificato la tecnologia alla base di > facebook.tracking.exposed e di youtube.tracking.exposed per analizzare > l'algoritmo di Amazon. > > Questo report abbastanza breve spiega la nostra investigazione: > > https://github.com/tracking-exposed/presentation/blob/master/amazon.trackin… > > Studiando i risultati personalizzati, abbiamo giocato con le funzioni di > amazon per verificare quali variabili influissero nella macchina di > profilazione, e secondo noi, alcuni dati che dovrebbero essere sotto il > nostro controllo (perché personali) sono usati nella profilazione, senza > che ci siano comunicato. > > se avete riflessioni in merito, mi piacerebbe parlarne con voi. > > * p.s. dal subject, DSAR, sta per Data Subject Access Request > > Cordialmente, > Claudio > _______________________________________________ > nexa mailing list > nexa(a)server-nexa.polito.it > https://server-nexa.polito.it/cgi-bin/mailman/listinfo/nexa >

Dec. 7, 2019

esperimento https://amazon.tracking.exposed - verificare se le DSAR sono complete

by Claudio Agosti

Buongiorno Nexa, Sono stato invitato un paio di mesi fa, a partecipare ad una trasmissione (Petrolio, Rai2, episodio del 6 Dicembre) su Amazon. Quindi, abbiamo modificato la tecnologia alla base di facebook.tracking.exposed e di youtube.tracking.exposed per analizzare l'algoritmo di Amazon. Questo report abbastanza breve spiega la nostra investigazione: https://github.com/tracking-exposed/presentation/blob/master/amazon.trackin… Studiando i risultati personalizzati, abbiamo giocato con le funzioni di amazon per verificare quali variabili influissero nella macchina di profilazione, e secondo noi, alcuni dati che dovrebbero essere sotto il nostro controllo (perché personali) sono usati nella profilazione, senza che ci siano comunicato. se avete riflessioni in merito, mi piacerebbe parlarne con voi. * p.s. dal subject, DSAR, sta per Data Subject Access Request Cordialmente, Claudio

Dec. 7, 2019

Inside the hate factory: how Facebook fuels far-right profit | Australia news | The Guardian

by Alberto Cammozzo

<https://www.theguardian.com/australia-news/2019/dec/06/inside-the-hate-fact…> [...] A Guardian investigation can reveal those messages were part of a covert plot to control some of Facebook’s largest far-right pages, including one linked to a rightwing terror group, and create a commercial enterprise that harvests Islamophobic hate for profit. This group is now using its 21-page network to churn out more than 1,000 coordinated faked news posts per week to more than 1 million followers, funnelling audiences to a cluster of 10 ad-heavy websites and milking the traffic for profit. The posts stoke deep hatred of Islam across the western world and influence politics in Australia, Canada, the UK and the US by amplifying far-right parties such as Australia’s One Nation and vilifying Muslim politicians such as the London mayor, Sadiq Khan, and the US congresswoman Ilhan Omar. The network has also targeted leftwing politicians at critical points in national election campaigns. It posted false stories claiming the UK Labour leader, Jeremy Corbyn, said Jews were “the source of global terrorism” and accused the Canadian prime minister, Justin Trudeau, of allowing “Isis to invade Canada”. The revelations show Facebook has failed to stop clandestine actors from using its platform to run coordinated disinformation and hate campaigns. The network has operated with relative impunity even since Mark Zuckerberg’s apology to the US Senate following the Cambridge Analytica and Russian interference scandals. When the Guardian notified Facebook of its investigation, the company removed several pages and accounts “that appeared to be financially motivated”, a spokesperson said in a statement. “These pages and accounts violated our policy against spam and fake accounts by posting clickbait content to drive people to off-platform sites,” the spokesperson said. “We don’t allow people to misrepresent themselves on Facebook and we’ve updated our inauthentic behaviour policy to further improve our ability to counter new tactics.” But this comes too late for some of the network’s victims. Australia’s first female Muslim senator, Mehreen Faruqi, felt the full force of the network in August last year, when 10 of its pages launched coordinated posts inciting their 546,000 followers to attack her for speaking in parliament against racism. The posts prompted what Faruqi described as a “horrific feeding frenzy of racism, fake news and hate”, soliciting vile comments like “put your burka on – and shut the fuck up!”, “deport the whining bitch” and “Revoke citizenship and Deport”. Faruqi said the network represented a “new level of far-right organisation and coordination”, and she places the blame squarely on social media companies. “By allowing racist and misleading posts, social media giants like Facebook … are profiteering from the proliferation of hate speech and abuse,” Faruqi said. “Facebook could do much more and shut these pages down but so long as they continue to profit from the reach and engagement, they don’t seem to be interested in decisive action.” A spokesperson for Facebook told the Guardian: “Nobody can advocate or advertise hate or violence on Facebook and we remove any violations as soon as we become aware.” It begins with a single post, curated by Israel-based administrators. The post typically has an attention-grabbing headline and links to an article that mimics the style of a legitimate news story. It employs a blend of distorted news and total fabrication to paint Muslims as sharia-imposing terrorists and child abusers, whose existence poses a threat to white culture and western civilisation. It is then published almost simultaneously to the network’s 21 Facebook pages, which have a combined 1 million followers across the globe. The content is so predictable that even Devito once complained to his Israeli counterpart. “I told her flat out, ‘you’re a one-trick pony’,” he said. “It’s Islam, Islam, Islam, Islam and more Islam. Like, enough with the Islam already, we get it.” Interactive The Guardian conducted an analysis to confirm the extent of coordination across the network, checking where posts were identical in content and similar in publication time across different pages. The network published 5,695 coordinated posts at its height in October 2019, receiving 846,424 likes, shares or comments in that month alone. In total, the network has published at least 165,000 posts and attracted 14.3 million likes, shares or comments. The content is amplified further by other far-right Facebook pages, including those run by the rightwing UK Independence party (Ukip), who share it organically. The posts link back to one of 10 near-identical websites masquerading as news sites with generic titles like “The Politics Online” and “Free Press Front”. Ad-heavy and poorly designed, the websites feature “stories” that usually combine slabs of copied text intermingled with unsourced opinion and graphic imagery. The Guardian worked with researchers from Queensland University of Technology’s digital media research centre, who conducted an analysis of the order in which identical posts appeared across the 21 Facebook pages. Their analysis indicates a single entity is coordinating the publication of content across the Facebook pages, likely using automatic scheduling software, and that a single entity controls the websites that receive traffic from the posts. “It’s very obvious looking at the websites, the way that they’re structured, the way that they’re sharing design and code, and the way they share Google site IDs, that they’re all interconnected with each other,” said QUT professor Axel Bruns, one of Australia’s leading internet researchers. “They’re just cheap sites to set up, cheap sites to run … It’s not very sophisticated and it’s just brute force, to push all this stuff out.” Bruns and his colleagues believe the motivation is commercial, and that hatred, division and political influence may be byproducts of the pursuit of profit. “Here’s a bunch of people who – they’re not stupid but they’re highly prone to clicking on content that reflects their already held beliefs, especially content that is highly emotive and contains polarising and extreme material,” said Timothy Graham, a senior lecturer on social network analysis at QUT. “These people are great for business. If you get them to come to your website, they’re not going to [look closely at] the content, they’re going to click through and keep [sharing] it. They’re the perfect foot soldiers.” ‘You’re the one profiting’ The network wasn’t always so extensive. The delivery of coordinated content began in 2016 through just a few pages in Israel and the US. Unique v duplicated content within a network of far-right Facebook pages >From 2018 onwards, the network began approaching the administrators of large, pre-existing Facebook pages across Australia, Austria, Canada, the US and the UK, promising content that would help grow their audiences. In March 2018, the network gained access to a Canadian pro-Israel page dubbed Never Again Canada, which has 232,000 followers. A previous BuzzFeed News investigation into Never Again Canada showed it was regularly sharing content about the Jewish Defence League, an FBI-designated rightwing terror group, and coordinating content with other pages. Coordinated content posting by far-right Facebook pages, by target country The network reached its peak in October this year with coordination across 21 pages. Each time a local page-owner agrees to let one of the Israeli administrators in, they become unwitting though not necessarily unwilling participants in the globally coordinated distribution of online hate. Some page-owners, like Villereal, who runs Pissed off Deplorables, had no idea their new Israeli counterparts were making money from the following they had built. “It’s a little disheartening to sit here and think I’ve been doing this for two years and I haven’t made a dime, and I allowed someone to come in who’s built the little back channel but they’re going to use my clientele to make money,” he said. “You know, it’s like I own the store, I built it and everything like that, and you’re the one profiting.” Those behind the network went to great lengths to hide their identities, concealing personal information from websites and using different Facebook profiles when contacting the owners of existing far-right pages. But by following a trail of digital breadcrumbs, the Guardian’s investigation traced the network back to a key player: a man going by the username Ariel1238a. [...]

Dec. 6, 2019

Crack down on genomic surveillance

by Alberto Cammozzo

<https://www.nature.com/articles/d41586-019-03687-x> Across the world, DNA databases that could be used for state-level surveillance are steadily growing. The most striking case is in China. Here police are using a national DNA database along with other kinds of surveillance data, such as from video cameras and facial scanners, to monitor the minority Muslim Uyghur population in the western province of Xinjiang. Concerns about the potential downsides of governments being able to interrogate people’s DNA have been voiced since the early 2000s1 by activist groups, such as the non-profit organization GeneWatch UK, and some geneticists (myself included). Partly thanks to such debate, legislation and best practices have emerged in many countries around the use of DNA profiling in law enforcement2. (In profiling, several regions across the genome, each consisting of tens of nucleotides, are sequenced to identify a person or their relatives.) Now the stakes are higher for two reasons. First, as technology gets cheaper, many countries might want to build massive DNA databases. Second, DNA-profiling technology can be used in conjunction with other tools for biometric identification — and alongside the analysis of many other types of personal data, including an individual’s posting behaviour on social networks. Last year, the Chinese firm Forensic Genomics International (FGI) announced that it was storing the DNA profiles of more than 100,000 people from across China (FGI, known as Shenzhen Huada Forensic Technology in China, is a subsidiary of the BGI, the world’s largest genome-research organization). It made the information available to the individuals through WeChat, China’s equivalent of WhatsApp, using an app accessed by facial recognition. A pregnant woman and other migrants are apprehended by a Border Patrol agent With stringent safeguards and oversight, it is legitimate for law-enforcement agencies to use DNA-profiling technology. But these uses can easily creep towards human-rights abuses. In October this year, the US Department of Homeland Security announced that it would authorize the mandatory collection of DNA samples from immigrants in federal custody at the US border, including children and those applying for asylum at legal ports of entry. The resulting DNA profiles will be available through a database called CODIS (Combined DNA Index System), which includes the profiles of convicted offenders and individuals arrested for serious offences. Such treatment could reinforce debunked claims that immigrants are more prone to criminal behaviour than the general population. A much broader array of stakeholders must engage with the problems that DNA databases present. In particular, governments, policymakers and legislators should tighten regulation and reduce the likelihood of corporations aiding potential human-rights abuses by selling DNA-profiling technology to bad actors — knowingly or negligently. Researchers working on biometric identification technologies should consider more deeply how their inventions could be used. And editors, reviewers and publishers must do more to ensure that published research on biometric identification has been done in an ethical way. [...]

Dec. 5, 2019

To decarbonize we must decomputerize: why we need a Luddite revolution | Technology | The Guardian

by Alberto Cammozzo

<https://www.theguardian.com/technology/2019/sep/17/tech-climate-change-ludd…> Big tech claims AI and digitization will bring a better future. But putting computers everywhere is bad for people and the planet @bentarnoff Last modified on Wed 2 Oct 2019 20.42 BST Our built environment is becoming one big computer. “Smartness” is coming to saturate our stores, workplaces, homes, cities. As we go about our daily lives, data is made, stored, analyzed and used to make algorithmic inferences about us that in turn structure our experience of the world. Computation encircles us as a layer, dense and interconnected. If our parents and our grandparents lived with computers, we live inside them. A growing chorus of activists, journalists and scholars are calling attention to the dangers of digital enclosure. Employers are using algorithmic tools to surveil and control workers. Cops are using algorithmic tools to surveil and control communities of color. And there is no shortage of dystopian possibilities on the horizon: landlords evicting tenants with “smart locks”, health insurers charging higher premiums because your Fitbit says you don’t exercise enough. Digitization doesn’t just pose a risk to people, however. It also poses a risk to the planet. July was the hottest month on record. Large chunks of the Arctic are melting. In India, more than half a billion people face water shortages. Putting computation everywhere directly contributes to this crisis. Digitization is a climate disaster: if corporations and governments succeed in making vastly more of our world into data, there will be less of a world left for us to live in. To understand the relationship between data and climate, the best place to start is machine learning (ML). Billions of dollars are being spent on researching, developing, and deploying ML because major breakthroughs in the past decade have made it a powerful tool for pattern recognition, whether analyzing faces or predicting consumer preferences. ML “learns” by training on large quantities of data. Computers are stupid: babies know what a face is within the first few months of being alive. For a computer to know what a face is, it must learn by looking at millions of pictures of faces. Digitization is a climate disaster: if corporations and governments succeed in making vastly more of our world into data, there will be less of a world left for us to live in This is a demanding process. It takes place inside the data centers we call the cloud, and much of the electricity that powers the cloud is generated by burning fossil fuels. As a result, ML has a large carbon footprint. In a recent paper that made waves in the ML community, a team at the University of Massachusetts, Amherst, found that training a model for natural-language processing – the field that helps “virtual assistants” like Alexa understand what you’re saying – can emit as much as 626,155lb of carbon dioxide. That’s about the same amount produced by flying roundtrip between New York and Beijing 125 times. Training models isn’t the only way ML contributes to the cooking of our planet. It has also stimulated a hunger for data that is probably the single biggest driver of the digitization of everything. Corporations and governments now have an incentive to acquire as much data as possible, because that data, with the help of ML, might yield valuable patterns. It might tell them who to fire, who to arrest, when to perform maintenance on a machine or how to promote a new product. One of the best ways to make more data is to put small connected computers everywhere: Cisco predicts there will be 28.5bn networked devices by 2022. Aside from the energy required to manufacture and maintain those devices, the data they produce will live in the carbon-intensive cloud. Data centers currently consume 200 terawatt hours per year – roughly the same amount as South Africa. Anders Andrae, a widely cited researcher at Huawei, tells me that number is likely to grow 4-5 times by 2030. This would put the cloud on par with Japan, the fourth-biggest energy consumer on the planet. What can be done to curb the carbon costs of data? Greenpeace has long pushed cloud providers to switch to renewable energy sources and improve efficiency. These efforts have seen some success: the use of renewables by data centers has grown substantially. Meanwhile, efficiency gains from better techniques and bigger economies of scale have moderated the cloud’s power consumption in recent years. When it comes to ML, a group of researchers are calling for a more energy-conscious approach, which they call “Green AI”. These are encouraging trends, and tech workers themselves are likely to play a key role in advancing them: Amazon employees have been organizing for a climate plan since late last year, and they recently announced a global walkout for 20 September. Among their demands is for the company to commit to zero emissions by 2030 and to stop selling cloud services to fossil fuel companies. But it’s clear that confronting the climate crisis will require something more radical than just making data greener. That’s why we should put another tactic on the table: making less data. We should reject the assumption that our built environment must become one big computer. We should erect barriers against the spread of “smartness” into all of the spaces of our lives. To decarbonize, we need to decomputerize. This proposal will no doubt be met with charges of Luddism. Good: Luddism is a label to embrace. The Luddites were heroic figures and acute technological thinkers. They smashed textile machinery in 19th-century England because they had the capacity to perceive technology “in the present tense”, in the words of the historian David F Noble. They didn’t wait patiently for the glorious future promised by the gospel of progress. They saw what certain machines were doing to them in the present tense – endangering their livelihoods – and dismantled them. We are often sold a similar bill of goods: big tech companies talk incessantly about how “AI” and digitization will bring a better future. In the present tense, however, putting computers everywhere is bad for most people. It enables advertisers, employers and cops to exercise more control over us – in addition to helping heat the planet. Fortunately, there are latter-day Luddites working to stem the tide. Community groups like the Stop LAPD Spying Coalition are organizing to shut down algorithmic policing programs. A growing campaign to ban the government use of facial recognition software has won important victories in San Francisco and Somerville, Massachusetts, while workers at Amazon are calling for the company to stop selling such software to law enforcement. And in the streets of Hong Kong, protesters are developing techniques for evading the algorithmic gaze, using lasers to confuse facial recognition cameras and cutting down “smart” lamp-posts equipped with monitoring devices. These are just a few possible sources of inspiration for a broader movement for decomputerization, one that pursues social and ecological goals simultaneously. The premise of the Green New Deal is that we can make society greener and more equitable at the same time – that we can democratize as we decarbonize. We should apply the same logic to our digital sphere. Preventing a local police department from constructing an ML-powered panopticon is a matter of algorithmic, social and climate justice. As they used to say in the 1960s: one struggle, many fronts. For such a struggle to be successful, however, resistance is not enough. We also need a vision of the future we want. Again, the history of the Luddites can be helpful. In 1812, a group of Yorkshire Luddites sent a factory owner a letter promising continued action until “the House of Commons passes an Act to put down all Machinery hurtful to Commonality”. Following their example, we might derive a simple Luddite principle for democratizing technology: we should destroy machinery hurtful to the common good and build machinery helpful to it. What matters is not only how much data a service collects, but what imprint that service leaves upon the world – and thus whether it should be performed at all What does this mean in practice? It’s hard to think of anything more hurtful to our common life than heating large portions of the planet beyond habitable levels. Privacy advocates have long called for companies to restrict their collection of data to the minimum necessary to perform a service – a principle now enshrined in the GDPR, the EU’s omnibus data regulation. A 21st-century Luddism should embrace this principle but go further. What matters is not only how much data a service collects, but what imprint that service leaves upon the world – and thus whether it should be performed at all. Decomputerization doesn’t mean no computers. It means that not all spheres of life should be rendered into data and computed upon. Ubiquitous “smartness” largely serves to enrich and empower the few at the expense of the many, while inflicting ecological harm that will threaten the survival and flourishing of billions of people. Precisely which computational activities should be preserved in a less computerized world is a matter for those billions of people themselves to decide. The question of whether a particular machine hurts or helps the common good can only be answered by the commons itself. It can only be answered collectively, through the experiment and argument of democracy. The zero-carbon commonwealth of the future must empower people to decide not just how technologies are built and implemented, but whether they’re built and implemented. Progress is an abstraction that has done a lot of damage over the centuries. Luddism urges us to consider: progress towards what and progress for whom? Sometimes a technology shouldn’t exist. Sometimes the best thing to do with a machine is to break it.

Dec. 5, 2019

Uber’s “Academic Research” Program: How to Use Famous Economists to Spread Corporate Narratives -

by J.C. DE MARTIN

Uber’s “Academic Research” Program: How to Use Famous Economists to Spread Corporate Narratives Posted on December 5, 2019 by Hubert Horan Uber’s employees co-authored academic papers with brand name scholars that were then used to back the company’s PR and lobbying strategy. Published in respected journals, those articles are based on proprietary data and non-replicable analysis. Moreover, they all don’t discuss the subsidies that make it possible for Uber to pursue market dominance despite its endless losses. https://promarket.org/ubers-academic-research-program-how-to-use-famous-eco… (Sent from my wireless device; please excuse brevity and typos (if any))

Dec. 5, 2019

‘Short window’ to stop AI taking control of society, warns ex-Google employee

by J.C. DE MARTIN

Short window’ to stop AI taking control of society, warns ex-Google employee Meredith Whittaker warns we are becoming lab animals in a giant tech experiment https://www.irishtimes.com/business/technology/short-window-to-stop-ai-taki… (Sent from my wireless device; please excuse brevity and typos (if any))

Dec. 5, 2019

Optimal solid state neurons

by Giacomo Tesio

Scusate, ho dimenticato di aggiungere l'oggetto della mail... Giacomo On 05/12/2019, Giacomo Tesio <giacomo(a)tesio.it> wrote: > Bioelectronic medicine is driving the need for neuromorphic > microcircuits that integrate raw nervous stimuli and respond > identically to biological neurons. However, designing such circuits > remains a challenge. Here we estimate the parameters of highly > nonlinear conductance models and derive the ab initio equations of > intracellular currents and membrane voltages embodied in analog > solid-state electronics. By configuring individual ion channels of > solid-state neurons with parameters estimated from large-scale > assimilation of electrophysiological recordings, we successfully > transfer the complete dynamics of hippocampal and respiratory neurons > in silico. The solid-state neurons are found to respond nearly > identically to biological neurons under stimulation by a wide range of > current injection protocols. The optimization of nonlinear models > demonstrates a powerful method for programming analog electronic > circuits. This approach offers a route for repairing diseased > biocircuits and emulating their function with biomedical implants that > can adapt to biofeedback. > > Continua su https://www.nature.com/articles/s41467-019-13177-3 > > Ne scrive anche Enrica Battifoglia per Ansa: > http://www.ansa.it/canale_scienza_tecnica/notizie/biotech/2019/12/04/-primo… > > Certamente un ambito di ricerca enormemente interessante dal punto di > vista medico, che magari fra qualche decennio porterà ad una forte > mitigazione dei sintomi delle malattie neurodegenerative. > > Eppure apre anche a scenari inquietanti. > > > Giacomo >

Dec. 5, 2019

(no subject)

by Giacomo Tesio

Bioelectronic medicine is driving the need for neuromorphic microcircuits that integrate raw nervous stimuli and respond identically to biological neurons. However, designing such circuits remains a challenge. Here we estimate the parameters of highly nonlinear conductance models and derive the ab initio equations of intracellular currents and membrane voltages embodied in analog solid-state electronics. By configuring individual ion channels of solid-state neurons with parameters estimated from large-scale assimilation of electrophysiological recordings, we successfully transfer the complete dynamics of hippocampal and respiratory neurons in silico. The solid-state neurons are found to respond nearly identically to biological neurons under stimulation by a wide range of current injection protocols. The optimization of nonlinear models demonstrates a powerful method for programming analog electronic circuits. This approach offers a route for repairing diseased biocircuits and emulating their function with biomedical implants that can adapt to biofeedback. Continua su https://www.nature.com/articles/s41467-019-13177-3 Ne scrive anche Enrica Battifoglia per Ansa: http://www.ansa.it/canale_scienza_tecnica/notizie/biotech/2019/12/04/-primo… Certamente un ambito di ricerca enormemente interessante dal punto di vista medico, che magari fra qualche decennio porterà ad una forte mitigazione dei sintomi delle malattie neurodegenerative. Eppure apre anche a scenari inquietanti. Giacomo

Dec. 5, 2019

Re: [nexa] The future internet regulation - Aral Balkan at the European Parliament - With Slides - La Quadrature du Net

by Giovanni Biscuolo

"J.C. DE MARTIN" <demartin(a)polito.it> writes: > Circa 17’ molto ben spesi: > > https://video.lqdn.fr/videos/watch/861c07f7-7e9b-4e64-9765-cf1de592c8a0 \O/ ...dico solo che a 13:33 sulla frase "It is up to you, it is your responsibility" qui è partita la ola :-)... aka "se non lo sapevate, ora sapetelo!" grazie infinite per la segnalazione! vi prego colleghi iscritti: diffondete (ci sono anche i sottotitoli in italiano) [...] saluti, Giovanni -- Giovanni Biscuolo Xelera IT Infrastructures

Dec. 4, 2019