- nexa - server-nexa.polito.it

CCC Hacker Camp 2023 - Ultimi slot di partecipazione disponibili
by Fabio Pietrosanti (Lists) June 26, 2023

June 26, 2023

Buongiorno a tutti, come di consueto come Inclusive Hacker Framework organizziamo la Italian Hacker Embassy, raduno di Hacker Italiani presso l'hacker camp internazionale CCC CAMP che si terrà in Germania. Per chi volesse fare una mistica esperienza di partecipazione a 5 giorni di convegni, talk e workshop, in campeggio (con anche area "family village" per chi viene con i bambini) alla intersezione di tecnologia, qui le informazioni https://events.ccc.de/camp/2023/infos/ . Sono rimasti ultimi 22 biglietti per il CCC CAMP 2023 e ITALIAN HACKER EMBASSY dal 15 al 19 Agosto in Germania. Da acquistare entro Giovedì 29 Giugno, dopodiché non sarà possibile averne più e le vendite da parte del CCC sono già chiuse: https://pretix.eu/italianhackersembassy/ccc2023/ Fabio

1 0

MEMENTO | 107° Nexa Lunch Seminar | 28 giugno 2023, ore 13.00
by Nexa Media June 26, 2023

June 26, 2023

Gentilissime, gentilissimi, Vi ricordiamo che *mercoledì 28 giugno*, dalle ore 13.00 alle ore 14.00, si terrà il *107° Nexa Lunch Seminar* con un incontro dal titolo: /*"Deepfake e il c.d. "revenge porn": catastrofe annunciata... o immunità di gregge?"*/. Ospiti dell'incontro: *Marco Viola* (Università Roma Tre) e *Cristina Voto* (Università di Torino). _L'incontro si terrà IN PRESENZA e ONLINE._ _SEDE FISICA_ dell'incontro: Centro Nexa su Internet e Società, Politecnico di Torino, Via Boggio 65/a, Torino (1° piano). Per accedere alla sala si raccomanda di suonare al citofono *Portineria* e di seguire le indicazioni segnalate dai cartelli lungo il percorso. QUI <https://nexa.polito.it/contatti> maggiori informazioni su come raggiungerci. _STANZA VIRTUALE _dell'incontro: https://didattica.polito.it/VClass/NexaEvent Per maggiori dettagli è possibile consultare la pagina web dell'evento: https://nexa.polito.it/lunch-107 Cordiali saluti, -- Anita Botta Communication Manager Nexa Center for Internet & Society Politecnico di Torino – DAUIN Corso Duca degli Abruzzi, 24 - 10129 Torino web: https://nexa.polito.it/ mail: anita.botta(a)polito.it tel: 011 090 7219

1 0

Il giro del mondo (in 80 milioni di micro-tasks)
by Antonio Casilli June 25, 2023

June 25, 2023

Segnalo questo mio articolo in italiano uscito oggi. Il Manifesto 25.06.2023 https://ilmanifesto.it/intelligenza-artificiale-lesercito-dei-precari Intelligenza artificiale, l’esercito dei precari Anticipazioni. Un testo del sociologo che interverrà oggi alla giornata di dibattito presso il Monk di Roma dal titolo «C’è vita oltre il lavoro», organizzata da Tlon Antonio Casilli Angelica, giovane donna di 27 anni, vive a Tambaú, a nord della megalopoli di San Paolo. Il suo lavoro: “addestrare” robot aspirapolvere, piccoli elettrodomestici dotati di telecamere intelligenti che riconoscono e evitano ostacoli. Anche i più inattesi, come gli escrementi degli animali domestici. Angelica è retribuita per scattare foto delle deiezioni del suo cane. Le sue foto, etichettate e catalogate, vengono pagate solo pochi reais su una delle 54 piattaforme di micro-lavoro attive in Brasile. L'esempio di Angelica è tratto dal rapporto "Micro-lavoro in Brasile. I lavoratori dietro l'IA?" pubblicato il 19 giugno 2023 dal centro LATRAPS (Brasile), in collaborazione con il mio gruppo di ricerca DiPLab (Francia). Per anni, con i miei colleghi e studenti ho condotto inchieste come questa in 19 paesi in Europa, Africa e America Latina. Alla domanda: "Dove viene prodotta l'intelligenza artificiale?”, oggi noi diamo una risposta originale: non nella Silicon Valley o in grandi centri tecnologici dei paesi del Nord. I dati, ingredienti fondamentali dell'IA, vengono prodotti nei paesi emergenti e in via di sviluppo. Foto, video e testi sono filtrati ed arricchiti dai lavoratori delle piattaforme internazionali come la famigerata Mechanical Turk di Amazon, che li paga a cottimo per realizzare piccoli progetti online che durano appena qualche minuto: trascrivere, registrare, taggare, moderare, ecc. Ci sono anche altre grandi imprese quasi sconosciute come Appen o Telus, e piattaforme più piccole come la russa 2captcha e l'africana Sama. Nel gennaio scorso, Sama è stata oggetto di rivelazioni da parte della rivista Time, la quale ha scoperto che centinaia dei suoi micro-lavoratori in Kenia hanno "addestrato" ChatGPT. L’azienda produttrice della nota IA generativa ha ammesso di averne reclutati altri in India, Turchia, e nelle Filippine. La mappa globale che emerge dalle nostre ricerche attesta la costituzione di un vero e proprio un esercito industriale composto principalmente da persone tra i 20 e i 30 anni (ma anche quarantenni e pensionati nei paesi del Nord). In alcuni paesi, la maggioranza è costituita da donne con figli a carico che accettano di essere pagate meno di due euro all'ora. Anche nel Sud globale, questi salari non sono sufficienti per una vita dignitosa. Il fenomeno è strettamente legato alla disoccupazione e all'economia informale. I micro-lavoratori hanno regolarmente un livello di istruzione superiore alla media del loro paese, ma non riescono ad accedere al mercato del lavoro e guadagnano realizzando “micro-task”, ovvero brevi progetti retribuiti pochi centesimi. In America Latina, il paese con la più alta proporzione di micro-lavoratori rispetto alla popolazione attiva è in realtà il Venezuela, che da oltre dieci anni affronta una grave crisi politica ed economica. I lavoratori venezuelani sulle piattaforme si specializzano nell'annotazione di immagini per veicoli autonomi, e nel riconoscimento facciale e vocale. Si tratta di micro-task ancora più brevi e semplici del normale. Il motivo è tecnico. In Venezuela, i computer sono obsoleti e, nonostante l'elettricità gratuita, i blackout sono frequenti. Qui i micro-lavoratori guadagnano meno rispetto ad altri paesi, il che li rende molto ricercati da aziende sviluppatrici di IA che si trovano negli Stati Uniti, Canada e Germania. In Venezuela, l'arte di arrangiarsi è diventata un paradigma. Intere famiglie e caseggiati si organizzano, condividendo computer e smartphone o utilizzando account comuni. In Africa, è il Madagascar che attira aziende tecnologiche occidentali grazie a zone franche con agevolazioni fiscali. I clienti, soprattutto francesi, esternalizzano la moderazione di contenuti, la digitalizzazione di documenti e la registrazioni di messaggi per l’IA vocale. Il micro-lavoro attira giovani istruiti che lo considerano come un punto di ingresso nel mercato dell’impiego. Tuttavia, i magri guadagni (attorno a 100 euro al mese) non permettono di vivere nella capitale o nelle città turistiche della costa. E i lavoratori, presi in questa trappola della povertà, non possono lavorare a distanza, in zone rurali dove la connessione internet è instabile o costosa. Anche in altri paesi come Argentina ed Egitto, emergono piattaforme di lavoro legate ai dati. In alcuni, questa attività avviene nelle "click farms", dove si possono acquistare follower o like per aumentare il proprio traffico su piattaforme come YouTube e Instagram. Questa attività è in un'area di ambiguità legale, ma contribuisce allo sviluppo dell'IA, influenzando algoritmi e creando lavoro a basso salario. Per alcuni lavoratori, questi task rappresentano la loro principale fonte di reddito. Il micro-lavoro solleva questioni importanti. La prima riguarda la crescente precarietà globale del lavoro. La gig economy e le aziende come Uber o Glovo avevano già generato conflitti contro lo sfruttamento e rischi per i lavoratori. Le piattaforme di micro-lavoro a distanza hanno effetti analoghi, ma coinvolgono una popolazione dieci volte più ampia e dispersa a livello mondiale. I lavoratori dell'IA accettano incarichi frammentati, spesso pagati a cottimo, senza sicurezza occupazionale a lungo termine. Questo fenomeno evidenzia l'insicurezza e la svalutazione crescenti del lavoro. Le possibili implicazioni sociali ed economiche sono enormi. Per non parlare di quelle tecnologiche, se l’IA si rivelasse sempre più prodotta artigianalmente in paesi del Sud. -- Antonio A. Casilli Professor, Telecom Paris | Institut Polytechnique de Paris Member, Interdisciplinary Institute for Innovation (CNRS) Associate Member, LACI-LAP (EHESS) Associate researcher, Weizenbaum-Institut, Berlin Member, Scholarly council UCLA Center for Critical Internet Inquiry (C2i2) Faculty Fellow, Nexa Center for Internet & Society *We respect your right to disconnect. My workflow efficiency accounts for this email send time. Taking action or responding outside of office hours is not mandatory*

1 0

Techno-Narcissism | No Mercy / No Malice
by Alberto Cammozzo June 25, 2023

June 25, 2023

<https://www.profgalloway.com/techno-narcissism/> Scott Galloway@profgalloway I’m at Founders Forum in the Cotswolds … which they assure me is somewhere outside of London. There are a lot of Teslas and recycled Mason jars as … we’re making the world a better place. As at any gathering of the tech elite in 2023, the content could best be described as AI and the Seven Dwarves. The youth and vision toggles between inspiring moments and bouts of techno-narcissism. It’s understandable. If you tell a thirtysomething male he is Jesus Christ, he’s inclined to believe you. The tech innovator class has an Achilles tendon that runs from their heels to their necks: They believe their press. Making a dent in the universe is so aughts. Today, membership in the Soho House of tech requires you to birth the leverage point that will alter the universe. Jack Dorsey brought low-cost credit card transactions to millions of small vendors. But he’s still not our personal Jesus, so he renamed his company Block and pushed into crypto, because bitcoin would bring “world peace.” Side note: If anybody knows @jack’s brand of edibles, Whatsapp me. Elon Musk made a great electric car, then a better rocket … and recently appointed himself Noah to shepherd humanity to an interplanetary future. When techno-narcissism meets technology that is genuinely disruptive (vs. crypto or a headset), the hype cycle makes the jump to lightspeed. Late last year, OpenAI’s ChatGPT reached 1 million users in five days. Six months later, Congress asked its CEO if his product was going to destroy humanity. In contrast, it took Facebook 10 months to get to a million users, and it was 14 years before the CEO was hauled before Congress for damaging humanity. The claims are extreme, positive and negative: Solutionists pen think pieces on “Why AI Will Save the World,” while catastrophists warn us of “the risks of extinction.” These are two covers of the same song: techno-narcissism. It’s exhausting. But AI is a huge breakthrough, and the stakes are genuinely high. Existential Egos It’s notable today that many of the outspoken prophets of AI doom are the same people who birthed AI. Specifically, taking up all the oxygen in the AI conversation with dystopian visions of sentient AI eliminating humanity isn’t helpful. It only serves the interests of the developers of nonsentient AI, in several ways. At the simplest level, it gets attention. If you are a semifamous computer engineer who aspires to be more famous, nothing beats telling every reporter in earshot: “I’ve invented something that could destroy the world.” Partisans complain about the media’s left or right bias, but the real bias is toward spectacle. If it bleeds it leads, and nothing bleeds like the end of the world with a tortured genius at the center of the plot. Land Grab AI fearmongering is also a business strategy for the incumbents, who’d like the government to suppress nascent competition. OpenAI CEO Sam Altman told Congress we need an entire new federal agency to scrutinize AI models, and said he’d be happy to help them define what kinds of companies and products should get licenses (i.e., compete with OpenAI). “Licensing regimes are the death of competition in most places they operate,” says antitrust scholar and former White House senior adviser Tim Wu (total gangster). Similar to cheap capital and regulatory capture, catastrophism is an attempt to commit infanticide on emerging competition. Real Risks Granted, we should not ignore the dangers of AI, but the real risks are the existing incentives and amorality in tech and our ongoing inability to regulate it. The techno-catastrophists want to create a narrative that the shit coming down the pike is not the result of their actions, but the inevitable cost of progress. Just as the devil’s trick was convincing us he didn’t exist, the technologist’s sleight of hand is to absolve himself of guilt for the damage the next generation of tech leaders will levy on society [...]

1 0

Presentazione libro "L’autore artificiale Creatività e proprietà intellettuale nell'era dell'AI"
by Diego Giorio June 23, 2023

June 23, 2023

Un cordiale saluto a tutti i nexiani. Segnalo questo evento che si terrà mercoledì prossimo a Torino, ad ingresso libero Buona giornata e buon fine settimana a tutti D.

1 0

Benedetto Ponti, “Attività amministrativa e trattamento dei dati personali. Gli standard di legalità tra tutela e funzionalità”
by J.C. DE MARTIN June 22, 2023

June 22, 2023

Buonasera, segnalo con piacere il libro del collega e amico Benedetto Ponti dal titolo: “Attività amministrativa e trattamento dei dati personali. Gli standard di legalità tra tutela e funzionalità” (Franco Angeli). Il volume è pubblicato in open access: https://www.francoangeli.it/Libro/Attivit%C3%A0-amministrativa-e-trattament… juan carlos

2 1

Registrazione della conferenza di Richard Stallman
by Daniela Tafani June 22, 2023

June 22, 2023

Buongiorno. La registrazione della conferenza di Richard Stallman del 7 giugno scorso, "Working for the public. Universities, software and freedom", è disponibile qui https://www.garr.tv/stream/64849cf80622c181f0d9288a e qui: https://www.gnu.org/audio-video/philosophy-recordings#rms-202306070 Un saluto, Daniela

1 0

PedagoGPT
by Daniela Tafani June 22, 2023

June 22, 2023

La costruzione di un'infrastruttura include l'addestramento degli utenti ad usarla, a ritenerla utile, ad averne bisogno. Un intero apparato di corsi gratuiti abituerà gli utenti, fin da piccoli, ad utilizzare la cosiddetta "IA generativa" integrata in ogni programma: non serve Orwell, per prevedere gli effetti di generatori di testo che ci suggeriscano, in ogni istante della giornata, cosa comprare, cosa scrivere, cosa pensare, proprio mentre stiamo scrivendo o pensando. PedagoGPT<https://codeactsineducation.wordpress.com/2023/06/10/pedagogpt/> June 10, 2023<https://codeactsineducation.wordpress.com/2023/06/10/pedagogpt/> by Ben Williamson<https://codeactsineducation.wordpress.com/author/benwilliamson2013/> New educational courses are being produced to train people to use generative AI and make it familiar across industries and everyday life. Artificial intelligence might be top of the tech hype pinnacle<https://www.gartner.co.uk/en/articles/what-is-new-in-artificial-intelligenc…> right now, but maintaining its momentum requires turning short-term novelty into long term patterns and habits of use. A recent proliferation of educational courses to train users in generative AI, like image and text generators, is intended to do just that. The pedagogical apparatus being built to support AI will extend its applications into a vast array of industries, sectors, and everyday practices. The range of generative AI developments over the past year has been astonishing. What appeared to be technically impressive but socially, politically and ethically problematic<https://rse.org.uk/resources/resource/blog/the-socio-ethical-challenges-of-…> products like ChatGPT and Stable Diffusion only last year are fast being translated into a kind of infrastructure for everyday life and work. AI is being integrated into search engines<https://blogs.bing.com/search/march_2023/Confirmed-the-new-Bing-runs-on-Ope…> and all manner of other platforms<https://technative.io/the-api-key-rush-how-generative-ai-is-revolutionising…>, seemingly as a substrate for how people access and create knowledge, information and culture. Depending on your perspective, AI is either going to be enormously disruptive and transformative<https://www.accenture.com/us-en/insights/technology/generative-ai-summary> for businesses, or enormously damaging<https://nymag.com/intelligencer/article/ai-artificial-intelligence-chatbots…> for societies. The tech entrepreneurs responsible for building AI are themselves calling for long-term regulatory efforts to forestall the “existential risks”<https://www.salon.com/2023/06/11/ai-and-the-of-human-extinction-what-are-th…> of AI, while others argue that AI and other algorithmic systems are already causing considerable harms and dangers<https://www.thenation.com/article/economy/artificial-intelligence-silicon-v…> that could be addressed in the immediate present<https://thesociologicalreview.org/magazine/june-2023/artificial-intelligenc…>. Governments and political leaders<https://www.ft.com/content/6cc8a0f3-f2fc-4470-a881-8763451b47ea>, seemingly wooed by AI leaders like OpenAI’s Sam Altman, have begun calling for regulatory action to ensure “AI safety” while paving the way for the benefits that AI is supposed to promise. Safeguarding AI from too much regulation in order to enable innovation, while speculating about the far-out problems it could usher in rather than addressing contemporary problems, has become the preferred industry and government approach. Besides efforts to shape and choreograph regulation, however, the other problem for AI leaders and their advocates is to maintain the rapid growth of AI beyond its recent ascent up the curve of the hype cycle. And to do that requires maintaining and growing the user base for AI. While millions have played with the likes of image generators DALL-E and Midjourney or text generators such as ChatGPT over recent months, prolonged uptake and use into the future may be less certain. The business aim of AI companies after all isn’t to provide “toys” for people to play with, but to embed their AI tools, or more accurately AI infrastructure<https://www.wired.co.uk/article/digital-infrastructure-politics-government>, into a huge variety of industries, organizations, and everyday activities. Achieving that means educating users, ranging from enterprise leaders, IT managers and software developers, to public sector workers, NGOs, journalists, lawyers, healthcare staff, to families, children, and far more. This is where a new apparatus of pedagogical interventions to train users in AI has appeared. Let’s call it the PedagoGPT complex. The PedagoGPT complex consists of online courses that are intended to train everyone from beginners to advanced machine learning engineers in how to use and deploy generative AI. Mundane as that may seem, if we understand AI to be becoming an active infrastructural presence in an array of everyday technologies and practices, then new AI courses can be understood as accustoming and socializing populations into such infrastructures. As colleagues and I have previously suggested, tech companies create training schemes to operate as “habituation programs”<https://www.researchgate.net/publication/361934307_Amazon_and_the_New_Globa…> that tether business practices and personal desires to the affordances of their infrastructures. An infrastructure isn’t just the technology; it depends for its enactment on willing and habitual users. The PedagoGPT complex Surveying the PedagoGPT complex reveals a large number of players. A simple search for “generative AI” on ClassCentral, which is like a MoneySuperMarket service for online courses, returns more than 8,600 courses<https://www.classcentral.com/search?q=generative%20ai>. Many of them are available on online learning platforms like Coursera, Udemy, Udacity or FutureLearn, or are posted on YouTube as basic tutorials by independent entrepreneurial individuals. While many of these courses are only tagged “generative AI” to generate hits, the search surfaces something of the extent to which AI has become a key focus for training courses at a massive scale and scope. But the PedagoGPT complex is dominated by major industry players. One is Andrew Ng, the former co-founder of online learning platform Coursera, who in 2017 established DeepLearning.A<https://www.deeplearning.ai/about/>I “to fill a need for world-class AI education.” Ng, who is a key ally and advocate of OpenAI, launched a series of generative AI short courses<https://www.deeplearning.ai/short-courses/> on DeepLearning.AI in spring 2023. The courses were developed in partnership with OpenAI and are co-taught by OpenAI staff, and focus on topics like “ Building Systems With The ChatGPT API” and “ChatGPT Prompt Engineering for Developers”, where users learn how to use a large language model (LLM) to build “new and powerful applications” and “effectively utilize LLMs”. The short courses, then, are explicitly intended to advance OpenAI infrastructure into business environments through training-up new AI engineers and accustoming them to ChatGPT. Amazon has a relatively long history of running training programs to habituate workers to the AWS infrastructure<https://codeactsineducation.wordpress.com/2022/07/12/how-amazon-operates-in…> through its AWS Educate program. It too has begun offering training guidance and advice<https://aws.amazon.com/blogs/enterprise-strategy/how-technology-leaders-can…> for enterprise leaders on generative AI, partially through its “Machine Learning University” scheme. This is in support of the major announcements<https://aws.amazon.com/blogs/machine-learning/announcing-new-tools-for-buil…> made by AWS about its LLMs in April 2023. Similarly, Microsoft has set up an online course<https://learn.microsoft.com/en-us/training/modules/explore-azure-openai/> called “Introduction to Azure OpenAI Service” to support the integration of OpenAI’s services in its enterprise platforms, as part of a pathway of courses called “Microsoft Azure AI Fundamentals: Get started with artificial intelligence”. The Azure OpenAI course consists of short blocks of text that can be completed in just a few minutes, including a “module” on “OpenAI’s access and responsible AI policies” that takes 3 minutes to complete. Google, meanwhile, has launched a series<https://www.cloudskillsboost.google/course_templates/536> of “Generative AI Fundamentals” courses, including “Introduction to Generative AI”, “Introduction to Large Language Models” and “Introduction to Responsible AI courses”, that can be completed for free online. These courses require no prerequisites and are targeted at the general public. Google claims that “By passing the final quiz, you’ll demonstrate your understanding of foundational concepts in generative AI” and earn a digital skills badge. Other courses to introduce AI are also being taken into schools. Writing in the New York Times<https://www.nytimes.com/2023/06/08/business/ai-literacy-schools-amazon-alex…>, Natasha Singer reported on an “Amazon-sponsored lesson in artificial intelligence” taking place in public schools and an “MIT initiative on ‘responsible AI’ whose donors include Amazon, Google and Microsoft”. Singer noted in particular that the Amazon course introduced schoolchildren to building Alexa applications, while Amazon had just received a huge multimillion dollar fine for illegally collecting and storing masses of child data from Alexa devices. Nonetheless, “the one-hour Amazon-led workshop did not touch on the company’s data practices”. Public platform pedagogies The PedagoGPT complex of generative AI courses appears to be growing fast. It represents an expanding educational enterprise to habituate users from schoolchildren to SMEs, big business and civil society organizations alike to the promises of AI. PedagoGPT seeks to tether personal desires to AI providers, and to train organizations to integrate AI infrastructure into their products and working practices. Emerging AI courses are a form of public pedagogy that plays out on online learning platforms like DeepLearning.AI, MOOCs or corporate training spaces. They are explicitly user-friendly, but their intention is often to make the user friendly. Making the user friendly<https://www.tandfonline.com/doi/abs/10.1080/17508487.2020.1727544>, as Radhika Gorur and Joyeeta Dey have put it, means that platforms impose particular desires on a range of distributed actors, in the hopes that those actors respond amenably to its overtures. PedagoGPT programmes aspire to make users friendly to generative AI at mass scale, to see their business aims, knowledge work, or cultural experiences seem inextricable from what generative AI can offer. These public pedagogies are intended to synchronize users’ desires with AI. In these ways, PedagoGPT training programmes might also help concentrate the power of tech businesses<https://ainowinstitute.org/wp-content/uploads/2023/04/AI-Now-2023-Landscape…> like OpenAI, AWS, Google, Microsoft and others. An informal range of friendly ambassadors to generative AI helps extend the messaging and the branding through YouTube tutorials and the like. Increasing numbers of leaders, developers, and other workers will be familiarized with AI and habituated to everyday usage in ways that are aimed at establishing big tech operations in everyday routines, just as enterprise software, digital platforms and web applications have been routinized already. Educating users is a strategy for increasing the network effects and hyperscalability of AI-based platforms too, all intended to ensure long-term investor infusions of finance and growing valuations. More broadly, PedagoGPT synchronizes neatly with governmental enthusiasm for STEM (science, technology, engineering and maths) as primary educational aims and aspirations. It is little wonder that global leaders simultaneously extol the potential of both AI and STEM: they are both central to economic and geopolitical ambitions. Steve Rolf and Seth Schindler have recently written on the ways state aims are now tied to digital platforms<https://journals.sagepub.com/doi/10.1177/0308518X221146545> in a synthesis they call “state platform capitalism”. AI and STEM are integral to state platform capitalism and the geopolitical contests and rivalries it signifies. What has been termed “AI Nationalism”<https://www.ianhogarth.com/blog/2018/6/13/ai-nationalism> relies on a steady STEM pipeline of users who can operationalize AI. While users are made friendly to AI, then, AI isn’t always being put to friendly use. Finally, PedagoGPT raises the questions of how users are introduced to questions of ethics and responsibility. One might argue, for example, that an emphasis on STEM-based approaches further marginalizes the social sciences, arts and humanities in approaches to AI<https://www.adalovelaceinstitute.org/blog/role-arts-humanities-thinking-art…>, when these are the very subject areas where such debates are most advanced. Existing PedagoGPT courses reference ethics and responsibility, but often in limited form – for example, Microsoft’s Azure OpenAI Service course defers to Transparency Reports. Likewise, recent calls for “AI literacy”<https://www.edweek.org/technology/ai-literacy-explained/2023/05>, often promoted by industry and computer science figures, tend to prioritize skills for using generative AI. Here, ethics are addressed as personal responsibilities, based on an assumption that AI will be beneficial with the right “guardrails”<https://www.unesco.org/en/articles/unesco-supports-g7-leaders-calling-ai-gu…> for use and application. It’s possible to speculate, perhaps, that ethics in public and enterprise AI training might become synonymous with so-called “AI Safety”<https://www.wired.com/story/effective-altruism-artificial-intelligence-sam-…>, a particular approach informed by tech industry enthusiasm for “longtermist”<https://www.radicalphilosophy.com/commentary/the-toxic-ideology-of-longterm…> thinking and its concerns over “existential risk” rather than the immediate impacts of AI. Yet generative AI itself poses a well-reported wide range of immediate problems<https://iapp.org/news/a/epic-publishes-report-on-generative-ai-harms/>, from the generation of false information and reproduction of biases and discrimination, to the automation of occupational tasks, to the environmental impacts of data processing. These contemporary problems with AI itself may remain out of the purview of ethics in PedagoGPT programs, while ideas of AI literacy framed by industry-based risk and safety concerns could be scripted into PedagoGPT curricula. It seems likely that PedagoGPT courses will continue proliferating in the months and years to come. Who takes such courses, what content they contain, and how they affect everyday practices of living and working with AI remain open questions. But as AI becomes increasingly infrastructural, these courses will play a key role in habituating users, making them friendly to AI, and synchronizing everyday routines and desires to giant commercial business aspirations. https://codeactsineducation.wordpress.com/2023/06/10/pedagogpt/

1 0

NO alla guida autonoma fai-da-te sulle strade
by Marco Fioretti June 22, 2023

June 22, 2023

Buongiorno a tutti, tempo fa qui si discuteva di se e come dovrebbe essere permesso di modificare il software delle auto. Ieri ho incontrato un caso estremo della stessa pratica, cioe' guida autonoma fai-da-te con lo smartphone, e mi e' venuto questo: https://mfioretti.substack.com/p/no-diy-driverless-hacking-on-public-roads (https://mfioretti.substack.com/p/no-diy-driverless-hacking-on-public-roads) Marco

3 5

Chi addestra l'intelligenza artificiale in Brasile? (nuovo rapporto #DiPLab/LATRAPS)
by Antonio Casilli June 21, 2023

June 21, 2023

Dear all, siamo lieti di annunciare la pubblicazione del nostro ultimo rapporto, intitolato " Microlavoro in Brasile. Chi sono i lavoratori dietro l'intelligenza artificiale?" [Microtrabalho no Brasil: quem são os trabalhadores por trás da inteligência artificial?], che fa luce sul panorama emergente del lavoro di addestramento all'intelligenza artificiale sulle piattaforme brasiliane. Scarica il rapporto in 🇬🇧 e in 🇧🇷 qui: https://diplab.eu/?p=2833 Questo studio è il risultato di una collaborazione tra il centro di ricerca LATRAPS (Laboratório de Trabalho, Saúde e Processos de Subjetivação dell'Università statale di Minas Gerais, Brasile), coordinato da Matheus Viana Braz, e il programma di ricerca DiPLab (Digital Platform Labor dell'Institut Polytechnique de Paris, Francia), co-fondato da Paola Tubaro e dal sottoscritto. Il rapporto esamina le caratteristiche dei micro-lavoratori in Brasile, rivelando una tendenza che vede le donne giovani e altamente qualificate dominare questo settore, dove sono sostanzialmente sottopagate. Il microlavoro è legato alla disoccupazione: Il 33,5% di loro non ha un altro lavoro retribuito e guadagna appena 1,80 dollari all'ora. Il rapporto sottolinea anche l'importanza delle supply chain globali di dati, che collegano le case e i cybercafé brasiliani ai data center internazionali. Rendendo visibili queste interconnessioni, lo studio intende contribuire al dibattito sulla regolamentazione dell'IA e del lavoro su piattaforma, garantendo l'equità per tutte le parti interessate. Se leggete il portoghese, potete anche dare un'occhiata al reportage che The Intercept ha dedicato al nostro rapporto: "Revolta, impotência, tristeza Brasileiros ganham frações de centavos para melhorar sua inteligência artificial". https://www.intercept.com.br/2023/06/19/brasileiros-ganham-fracoes-de-centa… Buona lettura, Per #DiPLab Antonio Casilli -- Antonio A. Casilli Professor, Telecom Paris | Institut Polytechnique de Paris Member, Interdisciplinary Institute for Innovation (CNRS) Associate Member, LACI-LAP (EHESS) Associate researcher, Weizenbaum-Institut, Berlin Member, Scholarly council UCLA Center for Critical Internet Inquiry (C2i2) Faculty Fellow, Nexa Center for Internet & Society *We respect your right to disconnect. My workflow efficiency accounts for this email send time. Taking action or responding outside of office hours is not mandatory*

1 0