July 2023 - nexa - server-nexa.polito.it

Junk websites filled with AI-generated text are pulling in money from programmatic ads
by Alberto Cammozzo July 21, 2023

July 21, 2023

<https://www.technologyreview.com/2023/06/26/1075504/junk-websites-filled-wi…> More than 140 brands are advertising on low-quality content farm sites—and the problem is growing fast. People are using AI chatbots to fill junk websites with AI-generated text that attracts paying advertisers, according to a new report from the media research organization NewsGuard that was shared exclusively with MIT Technology Review. Over 140 major brands are paying for ads that end up on unreliable AI-written sites, likely without their knowledge. Ninety percent of the ads from major brands found on these AI-generated news sites were served by Google, though the company’s own policies prohibit sites from placing Google-served ads on pages that include “spammy automatically generated content.” The practice threatens to hasten the arrival of a glitchy, spammy internet that is overrun by AI-generated content, as well as wasting massive amounts of ad money. Most companies that advertise online automatically bid on spots to run those ads through a practice called “programmatic advertising.” Algorithms place ads on various websites according to complex calculations that optimize the number of eyeballs an ad might attract from the company’s target audience. As a result, big brands end up paying for ad placements on websites that they may have never heard of before, with little to no human oversight. To take advantage, content farms have sprung up where low-paid humans churn out low-quality content to attract ad revenue. These types of websites already have a name: “made for advertising” sites. They use tactics such as clickbait, autoplay videos, and pop-up ads to squeeze as much money as possible out of advertisers. In a recent survey, the Association of National Advertisers found that 21% of ad impressions in their sample went to made-for-advertising sites. The group estimated that around $13 billion is wasted globally on these sites each year. Now, generative AI offers a new way to automate the content farm process and spin up more junk sites with less effort, resulting in what NewsGuard calls “unreliable artificial intelligence–generated news websites.” One site flagged by NewsGuard produced more than 1,200 articles a day. Some of these new sites are more sophisticated and convincing than others, with AI-generated photos and bios of fake authors. And the problem is growing rapidly. NewsGuard, which evaluates the quality of websites across the internet, says it’s discovering around 25 new AI-generated sites each week. It’s found 217 of them in 13 languages since it started tracking the phenomenon in April. NewsGuard has a clever way to identify these junk AI-written websites. Because many of them are also created without human oversight, they are often riddled with error messages typical of generative AI systems. For example, one site called CountyLocalNews.com had messages like “Sorry, I cannot fulfill this prompt as it goes against ethical and moral principles … As an AI language model, it is my responsibility to provide factual and trustworthy information.” NewsGuard’s AI looks for these snippets of text on the websites, and then a human analyst reviews them. Making money from junk “It appears that programmatic advertising is the main revenue source for these AI-generated websites,” says Lorenzo Arvanitis, an analyst at NewGuard who has been tracking AI-generated web content. “We have identified hundreds of Fortune 500 companies and well-known, prominent brands that are advertising on these sites and that are unwittingly supporting it.” “This is not normal. This is not healthy.” MIT Technology Review looked at the list of almost 400 individual ads from over 140 major brands that NewsGuard identified on the AI-generated sites that served programmatic ads, which included companies from many different industries including finance, retail, auto, health care, and e-commerce. The average cost of a programmatic ad was $1.21 per thousand impressions as of January 2023, and brands often don’t review all the automatic placements of their advertisements, even though they cost money. Google’s programmatic ad product, called Google Ads, is the largest exchange and made $168 billion in advertising revenue last year. The company has come under criticism for serving ads on content farms in the past, even though its own policies prohibit sites from placing Google-served ads on pages with “spammy automatically generated content.” Around a quarter of the sites flagged by NewsGuard featured programmatic ads from major brands. Of the 393 ads from big brands found on AI-generated sites, 356 were served by Google. “We have strict policies that govern the type of content that can monetize on our platform,” Michael Aciman, a policy communications manager for Google, told MIT Technology Review in an email. “For example, we don’t allow ads to run alongside harmful content, spammy or low-value content, or content that’s been solely copied from other sites. When enforcing these policies, we focus on the quality of the content rather than how it was created, and we block or remove ads from serving if we detect violations.” Most ad exchanges and platforms already have policies against serving ads on content farms, yet they “do not appear to uniformly enforce these policies,” and “many of these ad exchanges continue to serve ads on [made-for-advertising] sites even if they appear to be in violation of … quality policies,” says Krzysztof Franaszek, founder of Adalytics, a digital forensics and ad verification company. Google said that the presence of AI-generated content on a page is not an inherent violation. “We also recognize that bad actors are always shifting their approach and may leverage technology, such as generative AI, to circumvent our policies and enforcement systems,” said Aciman. A new generation of misinformation sites NewsGuard says that most of the AI-generated sites are considered “low quality” but “do not spread misinformation.” But the economic dynamic of content farms already incentivizes the creation of clickbaity websites that are often riddled with junk and misinformation, and now that AIs can do the same thing on a bigger scale, it threatens to exacerbate the misinformation problem. For example, one AI-written site, MedicalOutline.com, had articles that spread harmful health misinformation with headlines like “Can lemon cure skin allergy?” “What are 5 natural remedies for ADHD?” and “How can you prevent cancer naturally?” According to NewsGuard, advertisements from nine major brands, including the bank Citigroup, the automaker Subaru, and the wellness company GNC, were placed on the site. Those ads were served via Google. Adalytics confirmed to MIT Technology Review that ads on Medical Outline appeared to be placed via Google as of June 24. We reached out to Medical Outline, Citigroup, Subaru, and GNC for comment over the weekend, but the brands have not yet replied. After MIT Technology Review flagged the ads on Medical Outline and other sites to Google, Aciman said Google had removed ads that were being served on many of the sites “due to pervasive policy violations.” The ads were still visible on Medical Outline as of June 25. “NewsGuard's findings shed light on the concerning relationship between Google, ad tech companies, and the emergence of a new generation of misinformation sites masquerading as news sites and content farms made possible by AI,” says Jack Brewster, the enterprise editor of NewsGuard. “The opaque nature of programmatic advertising has inadvertently turned major brands into unwitting supporters, unaware that their ad dollars indirectly fund these unreliable AI-generated sites." Related Story A high wire act looking down into their safety net. The nearest person has a inappropriate content flag in one hand. Catching bad content in the age of AI Why haven’t tech companies improved at content moderation? Franaszek says it’s still too early to tell how the AI-generated content will affect the programmatic advertising landscape. After all, in order for those sites to make money, they still need to attract humans to their content, and it’s currently not clear whether generative AI will make that easier. Some sites might draw in only a couple of thousand views each month, making just a few dollars. “The cost of content generation is likely less than 5% of the total cost of running a [made-for-advertising] site, and replacing low-cost foreign labor with an AI is unlikely to significantly change this situation,” says Franaszek. So far, there aren’t any easy solutions, especially given that advertising props up the entire economic model of the internet. “What is key to remember is that programmatic ads—and targeted ads more generally—are a fundamental enabler of the internet economy,” says Hodan Omaar, senior AI policy advisor at the Information Technology and Innovation Foundation, a think tank in Washington, DC. “If policymakers banned the use of these types of ad services, consumers would face a radically different internet: more ads that are less relevant, lower-quality online content and services, and more paywalls,” Omaar says. “Policy shouldn’t be focused on getting rid of programmatic ads altogether, but rather on how to ensure there are more robust mechanisms in place to catch the spread of misinformation, whether it be direct or indirect.”

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Re: [nexa] nexa Digest, Vol 171, Issue 53
by Giuseppe Attardi July 21, 2023

July 21, 2023

> On 19 Jul 2023, at 06:51, nexa-request(a)server-nexa.polito.it wrote: > > Date: Wed, 19 Jul 2023 12:05:12 +0200 > From: Fabio Alemagna <falemagn(a)gmail.com> > To: Guido Vetere <vetere.guido(a)gmail.com> > Cc: Daniela Tafani <daniela.tafani(a)unipi.it>, > "nexa(a)server-nexa.polito.it" <nexa(a)server-nexa.polito.it> > Subject: Re: [nexa] AI and antitrust in 10 minutes > Message-ID: > <CACGmXuPNy4Y9uFBdL7O=QsCYtNYE3hP5gLbg-QzUZW=fPr8qKA(a)mail.gmail.com> > Content-Type: text/plain; charset="UTF-8" > >> Il giorno mer 19 lug 2023 alle ore 10:44 Guido Vetere >> <vetere.guido(a)gmail.com> ha scritto: >> >> un piccolo commento a caldo dopo aver dato una scorsa a questo illuminante intervento >> noi diamo per scontato che i LLM non possano che essere ciò che oggi ci viene proposto dal dupolio Microsoft \ Google > > Non mi pare esista al momento un duopolio riguardo gli LLM: ne > esistono decine di completamente open source, prodotti un po' in tutto > il mondo. Dipende da cosa consideri Large. I veri LLM, quelli la cui dimensione consente l’apparire di emergent abilities, solo pochi si possono permettersi di costruirli. E le dimensiini dei LLM sono finora cresciute esponenzialmente. D’altra parte, non avrebbe senso che migliaia di ricercatori chiedessero di fermare lo sviluppo di LLM più potenti di GPT-4, se questa non fosse il percorso di sviluppo più promettente. I LM cosiddetti Open Source (ma non è di source che si parla, ma dei parametri del modello), sono circa un ordine di grandezza più piccoli di quelli più grandi. Questo si ripercuote sulle loro capacità. Non bisogna farsi illudere dalle dichiarazioni degli sviluppatori nel confronto con altri LLM. I confronti vengono fatti su task specifici, su cui quei modelli sono ottimizzati. Ma i LLM contengono una mole superiore di conoscenze, tali che possono essere utilizzati per altri task, solo col prompting, senza fare fine-tuning. E il fine-tuning di un modello da 60-80 miliardi di parametri richiede comunque un server con almeno 4 GPU (altrimenti non sta in memoria) e diversi giorni di calcolo. Il risultato è spesso inferiore a quello di un LLM. Lo so per esperienza diretta personale e di altri. Infine, non vorrei lasciare a quei pochi che se possono permettere, le scelte su come fare un LLM e dovermi limitare a quello che loro graziosamente, o pelosamente per conquistare quote di mercato, mettono a disposizione. Vorrei poter avere la libertà di esplorare anche nuove strade. Anche solo per fare, come dice Vetere, modelli per la mia lingua, o per un settore specifico (salute, energia), o per determinati punti di vista (politici, economici, sociali, personali). > Anche il Technology Innovation Institute dell'Arabia Saudita > ha rilasciato un LLM come Open Source: https://falconllm.tii.ae/ The model uses only 75 percent of GPT-3’s training compute, 40 percent of Chinchilla’s, and 80 percent of PaLM-62B’s Ossia, forse gli arabi hanno i soldi per pagarsi le risorse computazionali per costruirsi un loro LLM, ma difficile che ce li abbiano i ricercatori europei, quando i progetti europei su AI dispongono di un centinaio di milioni in tutto per dozzine di progetti triennali con dozzine di partner. Le risorse di calcolo per costruire GPT-3.5 sono stimate in 10^23 FLOPS per un costo di centinaia di milioni di $. Meta, per rilasciare i suoi modelli, ha costruito un Research Supercluster con 10.000 GPU Nvidia, che secondo Yann LeCun è già in overbooking. Musk, mentre chiede di fermare lo sviluppo di LLM, ha ordinato anche lui 10.000 GPU per X.AI. Le startup come Converse.AI e Anthropic AI, hanno raccolto finanziamenti da 1-3 miliardi$, principalmente per comprarsi le risorse di calcolo. Il massimo che abbiamo in Europa è Mistral, con 100 milioni di VC. — Beppe

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Authors call for AI companies to stop using their work without consent | Books | The Guardian
by Alberto Cammozzo July 20, 2023

July 20, 2023

<https://www.theguardian.com/books/2023/jul/20/authors-call-for-ai-companies…> Authors including Margaret Atwood, Viet Thanh Nguyen and Philip Pullman have signed a petition calling for artificial intelligence companies to stop using writers’ work without consent or credit. The open letter, which has been set up by the Authors Guild, America’s largest professional organisation for writers, is addressed to the CEOs of OpenAI, Alphabet, Meta, Stability AI, and IBM. It presents these generative AI leaders with three demands, asking that these companies: “Obtain permission for use of our copyrighted material”; “Compensate writers fairly for the past and ongoing use of our works”, and “Compensate writers fairly for the use of our works in AI output, whether or not the outputs are infringing under current law”. Maya Shanbhag Lang, president of the Authors Guild, said: “The output of AI will always be derivative in nature. AI regurgitates what it takes in, which is the work of human writers. It’s only fair that authors be compensated for having ‘fed’ AI and continuing to inform its evolution.” National book award-winning novelist Jonathan Franzen, My Sister’s Keeper author Jodi Picoult and nonfiction author and journalist Michael Pollan are among the letter’s nearly 8,000 signatories. “The Authors Guild is taking an important step to advance the rights of all Americans whose data and words and images are being exploited, for immense profit, without their consent”, said Franzen. “In other words, pretty much all Americans over the age of six.” The median writing-related income in 2022 for full-time writers in the US was just $23,330, according to the Authors Guild’s most recent income survey. “The advent of AI technology further exacerbates these challenges and will make it increasingly difficult, if not impossible, for writers – particularly those from underrepresented communities – to earn a living from the craft most spent years if not decades perfecting”, a statement from the Authors Guild read. “When writers have to give up their profession, it is a grave problem for all of us, not just the writers, because far fewer great books get written and published; and a free, democratic culture depends on a healthy, diverse ecosystem in which all views and voices are heard and ideas exchanged.” This petition is the latest in a series of steps taken by literary figures to combat the rising use of AI in the books sector. Earlier this month two North American authors, Mona Awad and Paul Tremblay, filed a lawsuit against OpenAI, claiming that the organisation breached copyright law. OpenAI is the company behind the tool ChatGPT, a chatbot that is “trained” by copying large swathes of text and extracting information from it. The suit filed on behalf of Awad and Tremblay argued that “ChatGPT generates summaries of plaintiffs’ copyrighted works – something only possible if ChatGPT was trained on plaintiffs’ copyrighted works”. This line of argument could be difficult to prove, as ChatGPT may work “exactly the same” if it had not ingested the books themselves, Andres Guadamuz, a reader in intellectual property law at the University of Sussex, told the Guardian at the time. This is because it may have been trained on non-copyrighted information such as internet users discussing the books. The UK’s leading industry body for writers, the Society of Authors (SoA) has backed both the legal action taken by Awad and Tremblay and this new petition by the Authors Guild. Nicola Solomon, chief executive of the SoA, said she and her colleagues “fully support” the open letter. “The principles of consent, credit and compensation are bedrocks of our intellectual property regime, and a critical part of every author’s ability to protect and make a living from their work.” But influencing AI developers is “only one part of the challenge here”, she added. “The race to build the next generation of systems is driven primarily by the profit motives of large corporations. It is opaque, unfettered and unregulated, while the ethical ramifications of AI systems are complex and crying out for scrutiny.” Solomon said the SoA is “working flat out on this - advising members and working closely with other creators’ unions (through the Creators’ Rights Alliance) and the British Copyright Council, as well as making sure we are part of conversations with industry, policy makers and technology companies to try to identify common ground and establish safeguards, regulation and compensation.” While the SoA does not currently have firm plans to publish its own open letter, it is something the team has discussed. At the moment, however, its focus is on continuing “to lobby in line with the recent report by the House of Lords, which urged government, in no uncertain terms, to protect IP and better fund and support the creative industries”, Solomon said. In June, the SoA published guidance for authors on how they can protect themselves and their work from being exploited by AI. In the same month the UK’s Publishers Association also announced it was setting up a taskforce to support the industry amid AI developments. This petition is not the first time the Authors Guild has taken tech companies to task. In 2005 the writers’ organisation filed a copyright infringement case against Google, claiming that the search engine’s scanning of millions of books “was a plain and brazen violation of copyright law”. In 2016, the long-running dispute came to an end when the US supreme court denied the Guild the right to appeal the ruling that Google’s scanning of books constituted “fair use”, and that “Google Books provide significant public benefits”.

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Artificial Intelligence, Persuasive Technology and Manipulation
by Stefano Faraoni July 20, 2023

July 20, 2023

Buongiorno a tutti, Leggo questa mailing list con estremo piacere da tempo, e oggi per la prima volta provo a contribuire. Il mio articolo "Persuasive Technology and computational manipulation: hypernudging out of mental self-determination" e' appena stato pubblicato da Frontiers on Artificial Intelligence, e spero possa farvi piacere leggerlo. https://www.frontiersin.org/articles/10.3389/frai.2023.1216340/full Parla di manipolazione computazionale, dark patterns e hypernudge, e della necessita' di riconoscere un nuovo diritto fondamentale, il diritto alla sovranita' cognitiva o autodeterminazione mentale. Un saluto a tutti. Stefano *Stefano Faraoni* *Founder and DirectorAvvocato Patrocinante in CassazioneAdjunct Professor in Legal English, University of TurinPGR in AI Law, University of York* *Lumen Legis - Law Firm* INTERNAZIONALE | CONTRACT LAW | IT LAW | DIRITTO CIVILE | DIRITTO PENALE *w*: lumenlegis.com *@*: stefano.faraoni(a)lumenlegis.com **** Riservatezza/Confidentiality **** In ottemperanza al Regolamento Europeo 679/2016 (GDPR) in materia di protezione dei dati personali, le informazioni contenute in questo messaggio sono strettamente riservate ed esclusivamente indirizzate al destinatario indicato (oppure alla persona responsabile di rimetterlo al destinatario). Vogliate tener presente che qualsiasi uso, riproduzione o divulgazione della informativa in esso contenuta è vietata. Nel caso in cui lo aveste ricevuto per errore, vi preghiamo di accettare le nostre scuse e di distruggerlo, informandoci immediatamente tramite l’indirizzo e-mail stefano.faraoni(a)lumenlegis.com / According to General Data Protection Regulation (GDPR) concerning privacy, if you are not the addressee (or responsible for delivery of the message to such person) you are hereby notified that any disclosure, reproduction, distribution or other dissemination or use of this communication is strictly prohibited. If you have received this message in error, please accept our apology and destroy any copies and delete it from your computer system, then inform us immediately sending a message to stefano.faraoni(a)lumenlegis.com

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AI and antitrust in 10 minutes
by Daniela Tafani July 20, 2023

July 20, 2023

Daron Acemoglu Thank you, Cristina, for that wonderful introduction and to you and Tommaso for inviting me. […] As Cristina said, I'm going to talk about something that's partly inspired by my book. AI and antitrust in 10 minutes. So that's a tall order especially if I try to blend in ideas from the book, so let me jump into it. I'm going to do 10 question and answers in 10 minutes, but since that's a very short time I'll just give you the answers. I'll let your imagination do the job of the what the questions might have been to which. These are the answers. - Yes, generative AI has great potential, so I am completely convinced that this is a very interesting technology that can bring lots of goods and has capabilities so we can build on that. But I think let's move forward. - And yes, I believe that monopoly is everywhere in the tech sector. So here, perhaps I differ from many IO economists, and I subscribe to the duck test. If something looks like a duck, walks like a duck, and quacks like a duck, it is a duck. So if you have companies that have reached sizes that have never been in human history, and that dominate a particular line of business, they are monopolies. So we have to grapple with that. And that means all sorts of regulatory tools have to be considered, including antitrust. So this is absolutely on target. - And yes, in my view this is getting worse with foundation models. Because there is a likelihood that we may go towards a duopoly. With Microsoft Open AI and Google as the two key players, even though open source and many other competitors are going to try to get into foundation models, but the current business model of foundation models is very resource intensive. So that raises the possibility, does not in any way creates a certainty, but it raises the possibility. These two companies and their models are going to be the dominant ones on which many others will have to build, raising all of the issues of vertical product creation and all sorts of other questions that are going to be central for policymakers and economists to grapple with. - But no, I actually don't think monopoly power leading to high prices is the main problem that we're dealing with. You know, of course, that is a problem. But if the only issue was that because the foundation models are controlled by, you know, Google and Microsoft, they’re going to charge higher prices, and as a result, the apps that are developed on them are going to be more expensive, that would be, of course a pity and it's something we can do something about, but it wouldn't be the end of the world. So we get many new apps. They cost a little bit more. We don't get quite the consumer surplus. Woe is us, but not the end of the world. The problem is the direction of innovation. The problem is that the current market structure is selecting a particular direction of innovation. And that has much more sweeping consequences. Taking the set of products and technologies as given and pricing them above marginal cost and thus losing some of the welfare triangle is not the main issue. There’s the potential for doing much greater damage. No, this is not because of existential risk. In fact, like Cristina was implying, when all of these tech leaders are talking about existential risk I see it as either a blind spot or a ploy for making us not worry about the bigger risks. The bigger risks in my mind are in the labour market. Most of us earn our living in the labour market, so what happens to jobs is the most important issue. And the current direction of AI looks like it is going to follow some of the trends we have seen with digital technologies before. Failing to create the complementarities which human workers and skills, and instead going much toward much more towards automation, hence generating inequality, potential job losses, especially for workers without very specialised skills such as those with postgraduate degree. - And no, it's not just economics. There is a real danger here that the current direction of generative AI could again continue existing trends that we saw in social media degrade political conversations. Increase the amount of misinformation and disinformation, with a much more powerful tool. Create a particular type of ecosystem in online forums where people are drawn on the basis of emotion rather than engagement. And hence generally act towards the exploitation of people in their capacities and duties as democratic citizen. It is this twin: Inequality and Elimination of good jobs in the labour market, as well as erosion of democratic capacity that I think are most problematic. - No, I am not a Luddite. So I am not saying that this is in the nature of technology, nor that we should oppose technological change. The issue here is that we are not along the right path. What's great about technology in general and generative AI in particular, that it's a very highly malleable type of technological platform or what some economic historians used to call general purpose technology, meaning that you can use it for creating many apps, many different types of sub technologies and many different directions are possible. It is not complete idle talk. When people used to talk about social media and other online tools creating new democratic spaces today, it looks like very naive. When people in the 2000s said oh, online communication and social media are going to democratise communication. But that potential was there, and that potential is much greater with AI. When some people in the tech industry talk about generative AI being useful to humans in terms of getting better information, performing better tasks so generative AI… actually, I think the great potential that I mentioned at the beginning is precisely in being a human complementary technology. The tragedy of our current age is that we have almost all information that is at least codified available in some form. But we do not have the processing power to decide which one we should retrieve, how we should interpret how we should process, and which types of information we should engage with in different forms. Generative AI has the capability to improve human interaction with information and hence generate a lot of tasks, not just for knowledge workers, but for electricians, for carpenters, for educators, for healthcare workers. So that possibility is there. - But no, we are not going in the right direction. So we do need a redirection of technological change. - And no. I don't think it is naive or unrealistic to think about the redirection of technological change. One view which is common among some economists and some tech leaders goes back to either to the view that technology somehow has a preordained path and we just have to follow it. No, I am denying that and I think history is quite a good guide on showing how malleable technology is. Goes back to a saying by Ferdinand de Lesseps of fame, from the Suez and the Panama Canal, which we discussed in this book where he said, don't worry, men of genius would arise and solve all problems. Who are today's men of genius. Maybe some Altman or Elon Musk. But no, I don't think we should trust them. So I think the direction of technology is malleable, but it's also a societal choice. - And yes, as Cristina was hinting, antitrust has a very important role in this. For two reasons. One, because if we want alternatives. They are not very likely to come from a duopolistic or highly oligopolistic structure, especially one further empowered by killer acquisitions and these companies being a block other types of technologies that do not fit well with their business model. So if we want more alternatives that go more in a human complementary direction or more pro democratic direction, or create a more open competitive environment, I think we have to use antitrust tools including potential breakup of the largest companies which are too big and one other reason is because this type of power comes with enormous social power. And by that social power, I mean economic power, and also general social power. Tech companies have an enormous sway on public opinion, which I think is associated with their mega profits. And again, I don't think that creates a healthy environment. - And no, finally, I don't think antitrust is the main tool as Cristina was also hinting in her introductory comment. I think antitrust is a very blunt tool and I think for the redirection of technology we need a suite of tools which should include exactly how data is used and accessed. We need a new interoperability type of approach as well as how do we compensate and how do we actually encourage more creation of creative data. We also need to provide explicit incentives, such as, for example, those that have been successful in the field of renewable technology, where we encourage more of the socially valuable types of technologies. And I think there are a number of tools for that and we may also need more tax policies to discourage the worst types of business models and create room for alternative business models. So I am actually quite favourable, although I think much more study is needed, to a digital ad tax that creates more openness for alternative business models based on things like Wikipedia or subscription models in the online space. - Finally, I think we also need to rethink other tools that we have, like fiscal tools that currently create a very asymmetric playing field between capital and labour and going back to the job market and labour market inequality issues. I think equating marginal tax rate between capital and labour are things that we should definitely revisit. Thank you. https://mailchi.mp/cepr/central-bank-communication-rpn-seminar-series-516707

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Re: [nexa] AI and antitrust in 10 minutes
by Giuseppe Attardi July 19, 2023

July 19, 2023

Magistrale. In particolare sono convinto della necessità di scoraggiare il business model dei servizi gratuiti finanziati con la pubblicità, introducendo una tassazione altamente progressiva dei ricavi pubblicitari, come propone il nobel Paul Romer. So I am actually quite favourable, […] to a digital ad tax that creates more openness for alternative business models based on things like Wikipedia or subscription models in the online space. — Beppe > On 19 Jul 2023, at 04:44, nexa-request(a)server-nexa.polito.it wrote: > > From: Daniela Tafani <daniela.tafani(a)unipi.it> > To: "nexa(a)server-nexa.polito.it" <nexa(a)server-nexa.polito.it> > Subject: [nexa] AI and antitrust in 10 minutes > Message-ID: <08789adc08254f80af9be9f171ad7521(a)unipi.it> > > Daron Acemoglu > Thank you, Cristina, for that wonderful introduction and to you and Tommaso for inviting me. […] > As Cristina said, I'm going to talk about something that's partly inspired by my book. AI and > antitrust in 10 minutes. So that's a tall order especially if I try to blend in ideas from the book, so > let me jump into it. I'm going to do 10 question and answers in 10 minutes, but since that's a very > short time I'll just give you the answers. I'll let your imagination do the job of the what the questions > might have been to which. These are the answers. > …

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Relazione Annuale 2023 - Autorità per le Garanzie nelle Comunicazioni (AGCOM)
by Luigi Scorca July 19, 2023

July 19, 2023

Si segnala la pubblicazione, in data odierna, della Relazione Annuale 2023 dell'Autorità per le Garanzie nelle Comunicazioni (AGCOM). https://www.agcom.it/documentazione/documento?p_p_auth=fLw7zRht&p_p_id=101_…

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“Emergence” isn’t an explanation, it’s a prayer. A critique of Emergentism in Artificial Intelligence
by Daniela Tafani July 19, 2023

July 19, 2023

“Emergence” isn’t an explanation, it’s a prayer A critique of Emergentism in Artificial Intelligence <https://ykulbashian.medium.com/?source=post_page-----ef239d3687bf----------…> [cardboarddreams] Emergence is the notion that in a complex system, the interactions of the whole may exhibit properties that are not present in the individual parts. It is most often applied to examples in physics and nature, such as the collective behaviours of ant colonies, the self-organizing principles of social groups, or the macro properties of molecules. In the last few decades, it has given rise to emergentist perspectives of human cognition<https://onlinelibrary.wiley.com/doi/10.1111/j.1756-8765.2010.01116.x>, and even of consciousness<https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7597170/>. These are based on the recognition that the complexities and mysteries of the human mind, being a part of nature, may be characterized as emergent phenomena. This approach has an intuitive appeal. It is supported by the superficial facts: the brain — the source of intelligence and consciousness— is most certainly a complex of interconnected neurons. Emergentist interpretations of human behaviour may also boast some recent wins—the proliferation of LLMs (e.g. ChatGPT) may be seen as one such success. This has reignited the discussion of whether emergence is the best way to frame intelligence. You may have noticed that the last paragraph switched between two subtly different uses of “emergence”. The first use was to describe an observed emergent property; consciousness, we have seen it, likely emerges out of neuronal interactions. The second was to use it as a hypothesis to predict the outcome of a complex, unknown system, with the hope that a desired property will emerge; e.g. intelligence will arise from the interactions of artificial neurons at scale. The latter example is the driving motivation behind the multi-million dollar Human Brain Project<https://en.wikipedia.org/wiki/Human_Brain_Project>. The project justifies its cost by leaning on evidence from observed instances of emergence. Doing so paints emergence as a theory; that is, existing observations can be used to justify future predictions. But emergence is not a theory. Emergence can only be ascribed to a phenomenon in retrospect, once you already know what has “emerged”. The higher-level properties that emerge are qualitatively different from those at the lower-level — otherwise it wouldn’t be “emergence”. So by necessity they could not have been predicted from the lower-level ones. The properties of “intelligence” could not have been logically foreseen from the properties of neurons unless you had already observed that property emerge in a similar substrate. And even then it’s just a guess that is likely to be wrong given the complexity of the interactions involved; small differences can easily invalidate the hypothesis. In both cases emergence gives no new information: when explaining existing examples it gives you no new insights about the processes except that they happen; and when predicting unknown behaviours it gives very poor guarantees that anything you expect to happen will do so. Emergence is only really valid as a general metaphysical classification of certain phenomena. It’s a metaphysical category, like “cause”, “effect” or “change”. Using the word when explaining cognition is not wrong per se, it just has no real meaning or explanatory force. It’s like having a theory of “thing-happened-ness” — it’s correct, but void of content. Take, for example, the following quotes from a review article on emergence: This process gives rise to an emergent tendency to facilitate perception of items consistent with the patterns of English orthography, without explicitly representing this knowledge in a system of rules, as in other approaches. … However, such modes of thought themselves might be viewed as emergent consequences of a lifetime of thought-structuring practice supported by culture and education. Emergence in Cognitive Science, McClelland<https://onlinelibrary.wiley.com/doi/10.1111/j.1756-8765.2010.01116.x> If you removed the word “emergent” from the above two sentences, would anything important change? Indeed any sentence that includes “emergent” would give the same information if you removed it; “it gives rise to emergent properties” means the same as “it gives rise to properties”, or “there is an emergent tendency” is not substantially different from “there is a tendency”. Adding “emergent” to any sentence doesn’t increase its useful information content.¹ Emergence has no information that fundamentally differentiates it from a “miracle”. If I were to say that applying transformers<https://arxiv.org/abs/1706.03762> to Neural Networks creates intelligence through a miracle, I would be ridiculed. Were I to say that they create intelligence through emergent interactions, suddenly they gain an air of scientific credibility — but what have I added to the conversation with the use of that word? What quantifiable scientific facts are entailed in the term “emergent”? There are none. In cognitive science, emergence is regularly used to “explain” the connection between two phenomena, when it is otherwise complex and difficult to predict: e.g. how neuronal firing gives rise to consciousness, or transformers to the appearance of language comprehension. Where there may be a connection, but nothing more is known or can be proved, emergence is a placeholder that fills the gap. The word gives weight and gravitas to what is essentially a blank space. Despite emergence contributing nothing of substance to the discussion, as a concept it admittedly has a compelling intuitive appeal. There is a wonderful feeling about the notion of emergence. It does seem to be adding something valuable, as if you’ve discovered a magical ingredient by which you can explain mysterious phenomena. That’s the reason it continues to be popular, and gets inserted into scientific discussions. It convinces the listener that something has been explained with scientific rigour when all we’ve done is to say “it’s complicated”. Besides the good feeling, however, emergence is void of any explanatory power. And so it has no scientific value in a predictive capacity. You can’t use it to say anything about what an unknown system will do; only what you hope it will do. When applied to pie-in-the-sky AI futurism, emergence has become synonymous with “I’m sure the system will work itself out”. It indicates that the author has a feeling that a complex system will align at some point, but no clear sense of how, why, or when. Insofar as intelligence does manifest in a specific instance, “emergence” doesn’t tell us anything interesting about how it happened. And insofar as intelligence hasn’t yet manifested, emergence doesn’t tell us when it will or what direction to take to get there. In the field of AI development, emergence is invoked whenever someone encounters a phenomenon in the human mind and has no idea how to even start explaining it (e.g. art, socialization, empathy, transcendental aesthetics, DnD, etc). If said researcher already has a working theory of AI, this realization is disheartening. So they look deeper into the matter, find some point of overlap between the existing theory and the missing behaviour, and assume that with enough time and complexity the missing pieces will emerge. Emergence is attractive in such cases because it puts the author’s mind at ease, by making it seem like they have a viable mechanism that only needs more time to be vindicated. It placates their inner watchdog, the one that demands concrete, scientific explanations. Emergence, being related to complexity and superficially validated by experiments such as Conway’s Game of Life, is enough to lull that watchdog back to sleep. This justifies continuing to ignore any shortcomings in a theoretical model, and persisting on the current path. Like the proverbial man who searches for his lost keys under the lamplight, because that is where the light is, he hopes that with enough persistence his keys will “emerge”. The only other alternative is to admit failure, and to give up any hope of accomplishing what you want within this lifetime. Scientists, it seems, can have superstitions too. And emergence has a powerful narcotic effect: it feels so reasonable and credible on a gut level². There are many factors that prevent a given researcher from investigating emergence too deeply and realizing that it lacks any substance. First, there appears to be a lot of external evidence to back it up in the natural world. This, as was pointed out, equivocates between retrospective and prospective uses of the term, and so legitimate uses are being conscripted to justify the illegitimate ones. Secondly, the fact that emergence exclusively concerns itself with intractably complex systems means anything behind its curtain by definition can’t be studied. So it conveniently excludes itself from exactly that analysis which would reveal it to be hollow. In the end emergence isn’t an explanation; it’s an observation combined with a recognition of ignorance. Wherever emergence shows up there is an implicit acceptance that everyone involved is at a loss for how to approach the topic. It’s not that properties like intelligence won’t emerge from neural activity, it’s that emergence is a placeholder that justifies and promotes a lack of interest in exploring the details behind the connection. It discourages investigation. By invoking the term, we are merely thanking the nature gods for granting us this emergent property (aka property), and trying not to examine their gifts too profanely or with ingratitude. This impulse is understandable, since we don’t think we’ll discover an answer if we were to dig in. But we shouldn’t allow our insecurities to masquerade as science, or else they may become ingrained to the extent that they are difficult to uproot. A false answer stands in the way of a true one. ¹ This used to say ‘You can remove “emergent” from any sentence and it would mean the same thing’, but that has caused some confusion, so to clarify: the word “emergent” when used as an adjective doesn’t add new or useful information; you won’t know any more about the subject than you did before. ² A self-aware researcher should notice if they have a strong intuitive or emotional reason for holding on to the idea. If you ever feel that emergence is so self-evident that it can never be disproved, that should give you pause — perhaps you have strayed outside the bounds of scientific inquiry and into metaphysical expositions. Not that there’s anything wrong with the latter… https://ykulbashian.medium.com/emergence-isnt-an-explanation-it-s-a-prayer-…

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Re: [nexa] AI and antitrust in 10 minutes
by Giuseppe Attardi July 19, 2023

July 19, 2023

> On 19 Jul 2023, at 07:21, nexa-request(a)server-nexa.polito.it wrote: > > Date: Wed, 19 Jul 2023 13:17:32 +0200 > From: Fabio Alemagna <falemagn(a)gmail.com> > To: Guido Vetere <vetere.guido(a)gmail.com> > Cc: Daniela Tafani <daniela.tafani(a)unipi.it>, > "nexa(a)server-nexa.polito.it" <nexa(a)server-nexa.polito.it> > Subject: Re: [nexa] AI and antitrust in 10 minutes > Message-ID: > <CACGmXuO94NnbKmRO3zqqazLNWOcOFry3=p-MFocTjodu1PmcLw(a)mail.gmail.com> > Content-Type: text/plain; charset="utf-8" > >> Il giorno mer 19 lug 2023 alle ore 12:51 Guido Vetere >> <vetere.guido(a)gmail.com> ha scritto: >> >> per quel poco che ho studiato la questione del cross-lingual transfer learning, la cosa riguarda il trasferimento da lingue con molte risorse (leggi: inglese) a lingue con scarse risorse >> c'è tutta una questione di relativismo culturale nella quale ora non è il caso di addentrarsi, ma in tutti i casi vale il discorso del downsizing: è difficile - per dire - che sia necessario trasferire qualcosa di urdu in italiano, quindi basterebbero coppie inglese-x > > Se la produzione letteraria in un dato linguaggio è scarsa, viene da > sé che il contributo ai parametri del modello sarà anch'esso "scarso". > Non vedo dunque il problema. Non è detto, ci sono tecniche di ribilanciamento. — Beppe

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DPA norvegese blocca trattamento di Meta
by Stefano Quintarelli July 19, 2023

July 19, 2023

The Norwegian Data Protection Authority imposes a ban on Meta carrying out behavioural advertising based on the surveillance and profiling of users in Norway. The ban will initially apply until October … In December last year, the Irish Data Protection Commission issued a decision on behalf of all data protection authorities across the EEA which established that Meta has conducted illegal behavioural advertising. Since then, Meta has made certain changes, but a fresh decision from the Court of Justice of the European Union (curia.europa.eu) has stated that Meta’s behavioural advertising still does not comply with the law. Therefore, the Norwegian Data Protection Authority is now taking action by imposing a temporary ban. https://www.datatilsynet.no/en/news/aktuelle-nyheter-2023/temporary-ban-of-…

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