From e8cf5ec9ff66c0ba3c04fd8fb6600ce817317ed8 Mon Sep 17 00:00:00 2001 From: Matteo Baccan Date: Fri, 31 May 2024 09:21:08 +0200 Subject: [PATCH] AIPositive --- slide/AI_Positive.md | 10 ++ "slide/AI_Realt\303\240.md" | 84 +++++++++++ slide/Ai_Reality.md | 175 ++++++++++++++++++++++ slide/img/ai-positive-Moneyball.jpeg | Bin 13847 -> 0 bytes slide/img/ai-positive-dr-mick-riviera.jpg | Bin 48614 -> 0 bytes slide/img/ai-positive-vipiteno.jpeg | Bin 0 -> 66957 bytes slide/img/ai-reality-Dwayne_Johnson.webp | Bin 152382 -> 25240 bytes slide/img/ai-reality-papa-col-piumino.jpg | Bin 0 -> 44295 bytes 8 files changed, 269 insertions(+) create mode 100644 "slide/AI_Realt\303\240.md" create mode 100644 slide/Ai_Reality.md delete mode 100644 slide/img/ai-positive-Moneyball.jpeg delete mode 100644 slide/img/ai-positive-dr-mick-riviera.jpg create mode 100644 slide/img/ai-positive-vipiteno.jpeg create mode 100644 slide/img/ai-reality-papa-col-piumino.jpg diff --git a/slide/AI_Positive.md b/slide/AI_Positive.md index 01c0dd2..a377c93 100644 --- a/slide/AI_Positive.md +++ b/slide/AI_Positive.md @@ -158,6 +158,16 @@ Deteniamo ancora il libero arbitrio, fino a quando la fiducia non sarà tale da --- +## Vipiteno + +Interruzione fantasma dell'A22 al Brennero, invasa Vipiteno: Molti stanno lasciando l'autostrada che però è libera + +![center width:600px](img/ai-positive-vipiteno.jpeg) + + + +--- + ## Il futuro Secondo l’ultimo report del World Economic Forum: **“Jobs of Tomorrow: Large Language Models and Jobs”**, le attività lavorative maggiormente sostituibili saranno quelle che hanno lavori ripetitivi: diff --git "a/slide/AI_Realt\303\240.md" "b/slide/AI_Realt\303\240.md" new file mode 100644 index 0000000..60d4c47 --- /dev/null +++ "b/slide/AI_Realt\303\240.md" @@ -0,0 +1,84 @@ +--- +theme: default +_class: lead +paginate: true +backgroundColor: #fff +backgroundImage: url('img/background.svg') +marp: true +footer: https://github.com/matteobaccan/CorsoAI ultimo aggiornamento del %date% %time% +--- + +# Il futuro delle AI + +Le AI cancelleranno la realtà? + +![bg right](img/matteo-baccan.jpg) + + + + + +--- + +## Come nascono queste slide + +Un Biden fake ha chiamato migliaia di persone: è stata una oscura società texana + +https://ainews.it/un-biden-fake-ha-chiamato-migliaia-di-persone-e-stata-una-oscura-societa-texana/ + + +Ancora cattive notizie legate ai #deepfake: azienda di Hong Kong perde 25 milioni di dollari + +https://www.youtube.com/watch?v=1oQo2CkEtjE + + +The Taylor Swift Album Leak’s Big AI Problem +When The Tortured Poets Department leaked, some Taylor Swift fans swore it must be AI. Expect that to be a common refrain. + +https://www.wired.com/story/the-taylor-swift-album-leaks-big-ai-problem/ + +--- + +## Chi sono? + +Matteo Baccan è un esperto software engineer con oltre 30 anni di esperienza nel campo dello sviluppo. Ha attraversato tutte le fasi storiche dell'evoluzione del software, comprendendo che la chiave non è solo scrivere prodotti funzionanti, ma mantenere coerenza e stabilità. La sua filosofia è quella di risolvere problemi concreti senza crearne di nuovi, lavorando in modo efficace e insegnando le buone pratiche per permettere ai team di progredire insieme. + +Matteo applica questa visione nella sua routine lavorativa quotidiana, occupandosi dello sviluppo di soluzioni tecniche mirate per soddisfare le esigenze dei clienti. + +Matteo è anche molto impegnato nella divulgazione tecnica. È docente all'Accademia di Belle Arti di Novara, dove insegna Web Design, Tecnologie Digitali e applicazioni di Intelligenza Artificiale oltre ad aver pubblicato corsi ed articoli su programmazione blockchain, smart contract e integrazione di AI nella produzione di siti web. + +--- diff --git a/slide/Ai_Reality.md b/slide/Ai_Reality.md new file mode 100644 index 0000000..9d87292 --- /dev/null +++ b/slide/Ai_Reality.md @@ -0,0 +1,175 @@ + + + +bbc full body capture of Dwayne Johnson at Jumanji Welcome to the Jungle, smiling, bald, athletic, strong, sunglasses, he is dressed as a zoo tourist guide, at jungle outdoors. extreme detail, digital art, 4k, ultra hd, hyperrealism, trending on Instagram. + + + +Impatto dell'IA sulla società (00:04 - 10:02) + +I modelli di IA possono contribuire al cambiamento climatico. + + I dati di addestramento utilizzano arte e libri senza consenso. + L'implementazione può discriminare contro alcune comunità. + +I grandi modelli linguistici hanno costi ambientali significativi. + + Bloom, un grande modello linguistico open source, ha emesso tonnellate di anidride carbonica durante l'addestramento. + Passare a un modello linguistico più grande emette più anidride carbonica per lo stesso compito. + +Strumenti per misurare e mitigare gli impatti dell'IA + +CodeCarbon stima il consumo di energia e le emissioni di carbonio durante l'addestramento dell'IA. + + Possono essere fatte scelte informate per scegliere modelli più sostenibili. + I modelli di IA possono essere implementati con energie rinnovabili per ridurre le emissioni. + +Spawning.ai ha creato "Have I Been Trained?" per aiutare artisti e autori a tracciare l'uso delle loro opere. + + Utilizzato come prova cruciale in una class action per violazione del copyright. + In collaborazione con Hugging Face per creare meccanismi di opt-in e opt-out per i set di dati. + +Affrontare i pregiudizi nell'IA + +I pregiudizi nell'IA possono portare a rappresentazioni di stereotipi e discriminazioni. + + I sistemi di riconoscimento facciale hanno mostrato pregiudizi contro le donne di colore. + Modelli prevenuti implementati nelle forze dell'ordine possono portare ad accuse false e ingiusto imprigionamento. + +Lo strumento Stable Bias Explorer esplora i pregiudizi nei modelli di generazione di immagini attraverso la lente delle professioni. + + Ha dimostrato una significativa rappresentazione di bianchezza e mascolinità nelle professioni. + Presentato a un evento ONU sui pregiudizi di genere come esempio di comprensione dell'IA. + +Importanza della trasparenza e degli strumenti + +L'IA dovrebbe rimanere accessibile per comprenderne il funzionamento e i limiti. + + Gli strumenti per misurare l'impatto dell'IA possono informare le decisioni di aziende e legislatori. + Gli utenti possono utilizzare le informazioni per scegliere modelli di IA affidabili. + +Progresso dell'IA (10:04 - 10:16) + +"L'IA sta progredendo rapidamente, ma non è un dato di fatto." + + Stiamo costruendo la strada mentre la percorriamo + Decisione collettiva sulla direzione + +Decision Making collettivo + +"Possiamo decidere collettivamente quale direzione prendere insieme." + + Importanza del decision making collettivo + Collaborazione per plasmare il futuro dell'IA + + +---------------- + +AI Is Dangerous, but Not for the Reasons You Think | Sasha Luccioni | TED + +https://www.youtube.com/watch?v=eXdVDhOGqoE + +Quindi sono stato un ricercatore di intelligenza artificiale per oltre un decennio. E un paio di mesi fa, ho ricevuto +l'email più strana della mia carriera. Uno sconosciuto mi ha scritto dicendo che il mio lavoro sull'AI metterà fine +all'umanità. Lo capisco, l'AI è così di moda in questo momento. (Risate) È sulla cresta dell'onda praticamente ogni +giorno, a volte per cose davvero interessanti come scoprire nuove molecole per la medicina o quel papa figo con il +piumino bianco. + +![center w:450px](img/ai-reality-papa-col-piumino.jpg) + + +Ma altre volte i titoli sono stati davvero cupi, come quel chatbot che ha detto a quel tizio che +dovrebbe divorziare da sua moglie o quell'app di pianificazione dei pasti AI che proponeva una ricetta accattivante a +base di gas cloro. E sullo sfondo, abbiamo sentito un sacco di discorsi su scenari apocalittici, rischi esistenziali e +la singolarità, con lettere scritte ed eventi organizzati per assicurarsi che non accada. Ora, sono un ricercatore che +studia gli impatti dell'AI sulla società, e non so cosa succederà tra 10 o 20 anni, e nessuno lo sa davvero. Ma quello +che so è che ci sono alcune cose abbastanza brutte che stanno accadendo ora, perché l'AI non esiste nel vuoto. Fa parte +della società e ha impatti sulle persone e sul pianeta. I modelli di AI possono contribuire al cambiamento climatico. I +loro dati di addestramento utilizzano arte e libri creati da artisti e autori senza il loro consenso. E il loro +dispiegamento può discriminare intere comunità. Ma dobbiamo iniziare a tracciarne gli impatti. Dobbiamo iniziare ad +essere trasparenti e rivelarli e creare strumenti in modo che le persone comprendano meglio l'AI, in modo che speriamo +le future generazioni di modelli di AI siano più affidabili, sostenibili, forse meno inclini a ucciderci, se è quello +che vi piace. Ma cominciamo con la sostenibilità, perché quella nuvola in cui vivono i modelli di AI è in realtà fatta +di metallo, plastica ed alimentata da enormi quantità di energia. E ogni volta che interroghi un modello di AI, comporta +un costo per il pianeta. + +L'anno scorso, ho fatto parte dell'iniziativa BigScience, che ha riunito un migliaio di ricercatori da tutto il mondo +per creare Bloom, il primo grande modello di linguaggio aperto, come ChatGPT, ma con un'enfasi sull'etica, la +trasparenza e il consenso. E lo studio che ho guidato che ha esaminato gli impatti ambientali di Bloom ha scoperto che +solo l'addestramento ha utilizzato tanta energia quanta ne consumano le case in un intero anno ed ha emesso tonnellate +di anidride carbonica, che equivale a guidare la propria auto cinque volte intorno al pianeta solo perché qualcuno possa +usare questo modello per raccontare una barzelletta sulla porta. E questo potrebbe non sembrare molto, ma altri modelli +di linguaggio di grandi dimensioni simili, come GPT-3, emettono molte volte di più anidride carbonica. Ma il fatto è che +le aziende tecnologiche non misurano queste cose. Non le divulgano. E quindi questo è probabilmente solo la punta +dell'iceberg, anche se è un iceberg che si sta sciogliendo. E negli ultimi anni abbiamo visto i modelli di AI aumentare +di dimensioni perché la tendenza attuale nell'AI è "più grande è meglio". Ma per favore non fatemi iniziare sul perché +sia così. In ogni caso, abbiamo visto i grandi modelli di linguaggio in particolare crescere di 10.000 volte in +dimensioni negli ultimi cinque anni. E ovviamente, anche i loro costi ambientali stanno aumentando. Il lavoro più +recente che ho guidato ha scoperto che passare da un modello più piccolo ed efficiente a un modello di linguaggio più +grande emette 30 volte più carbonio per lo stesso compito. Come raccontare quella barzelletta sulla porta. E mentre +stiamo mettendo questi modelli nei cellulari, motori di ricerca, frigoriferi intelligenti e altoparlanti, i costi +ambientali si stanno accumulando rapidamente. Quindi, invece di concentrarci su alcuni rischi esistenziali futuri, +parliamo degli impatti tangibili attuali e degli strumenti che possiamo creare per misurare e mitigare questi impatti. +Ho contribuito a creare CodeCarbon, uno strumento che funziona in parallelo con il codice di addestramento di AI che +stima la quantità di energia che consuma e la quantità di carbonio che emette. E utilizzare uno strumento del genere può +aiutarci a fare scelte informate, come scegliere un modello piuttosto che un altro perché è più sostenibile, o schierare +modelli di AI con energie rinnovabili che possono drasticamente ridurre le loro emissioni. Ma parliamo di altre cose +perché ci sono altri impatti dell'AI +oltre alla sostenibilità. Per esempio, è stato davvero difficile per artisti e autori dimostrare che il lavoro della +loro vita è stato utilizzato per addestrare modelli di AI senza il loro consenso. E se vuoi fare causa a qualcuno, di +solito hai bisogno di prove, giusto? Quindi Spawning.ai, un'organizzazione fondata da artisti, ha creato questo +strumento davvero figo chiamato "Have I Been Trained?". Ti permette di cercare in questi enormi set di dati per vedere +cosa hanno su di te. Lo ammetto, ero curioso. Ho cercato in LAION-B, che è questo enorme set di dati di immagini e +testi, per vedere se c'erano immagini di me lì dentro. Ora quelle prime due immagini, sono io da eventi in cui ho +parlato. Ma le altre immagini, nessuna di quelle sono io. Sono probabilmente di altre donne di nome Sasha che hanno +messo le loro fotografie su internet. E questo può probabilmente spiegare perché, quando interrogo un modello di +generazione di immagini per generare una fotografia di una donna di nome Sasha, più spesso che no ottengo immagini di +modelle in bikini. A volte hanno due braccia, a volte ne hanno tre, ma raramente hanno vestiti addosso. E mentre può +essere interessante per persone come te e me cercare in questi set di dati, per artisti come Karla Ortiz, questo +fornisce prove cruciali che il lavoro della sua vita, la sua arte, è stato utilizzato per addestrare modelli di AI senza +il suo consenso, e lei e due artisti hanno usato questo come prova per intentare una causa collettiva contro le aziende +di AI per violazione del diritto d'autore. E più recentemente - (Applausi) E più recentemente Spawning.ai si è associata +a Hugging Face, l'azienda in cui lavoro, per creare meccanismi di opt-in e opt-out per la creazione di questi set di +dati. Perché l'arte creata dagli umani non dovrebbe essere un buffet tutto-quello-che-puoi-mangiare per addestrare +modelli di linguaggio AI. (Applausi) L'ultima cosa di cui voglio parlare è il pregiudizio. Ne avrete probabilmente +sentito parlare molto. Formalmente, si verifica quando i modelli di AI codificano schemi e convinzioni che possono +rappresentare stereotipi o razzismo e sessismo. Una delle mie eroine, la dott.ssa Joy Buolamwini, ha +sperimentato questo in prima persona quando si è resa conto che i sistemi di AI non rilevavano nemmeno il suo viso a +meno che non indossasse una maschera di colore bianco. Scavando più a fondo, ha scoperto che i comuni sistemi di +riconoscimento facciale erano molto peggiori per le donne di colore rispetto agli uomini bianchi. E quando modelli +distorti come questi vengono dispiegati in ambito delle forze dell'ordine, questo può portare ad accuse false, persino a +detenzioni ingiuste, che abbiamo visto accadere a più persone negli ultimi mesi. Per esempio, Porcha Woodruff è stata +ingiustamente accusata di rapina a mano armata all'ottavo mese di gravidanza perché un sistema di AI l'ha identificata +erroneamente. Ma purtroppo, questi sistemi sono scatole nere, e persino i loro creatori non possono dire esattamente +perché funzionano in quel modo. E per esempio, per i sistemi di generazione di immagini, se vengono usati in contesti +come la generazione di una scheda segnaletica forense basata sulla descrizione di un colpevole, essi prendono tutti quei +pregiudizi e li rispediscono indietro per termini come "criminale pericoloso", "terrorista" o "membro di una gang", cosa +ovviamente super pericolosa quando questi strumenti vengono dispiegati nella società. E quindi per comprendere meglio +questi strumenti, ho creato questo strumento chiamato Stable Bias Explorer, che permette di esplorare il pregiudizio dei +modelli di generazione di immagini attraverso la lente delle professioni. Quindi cerca di immaginare uno scienziato +nella tua mente. Non guardarmi. Cosa vedi? Più o meno la stessa cosa, giusto? Uomini con occhiali e camici da +laboratorio. E nessuno di loro mi assomiglia. E il fatto è che abbiamo esaminato tutti questi diversi modelli di +generazione di immagini e abbiamo trovato più o meno la stessa cosa: una significativa rappresentazione di bianchezza e +mascolinità attraverso tutte le professioni che abbiamo osservato, anche se rispetto al mondo reale, secondo l'Ufficio +di Statistica del Lavoro degli Stati Uniti. Questi modelli mostrano gli avvocati come uomini, e i CEO come uomini, quasi +il 100% delle volte anche se sappiamo tutti che non sono tutti bianchi e maschi. E purtroppo, il mio strumento non è +stato ancora utilizzato +per scrivere leggi. Ma di recente l'ho presentato a un evento delle Nazioni Unite sui pregiudizi di genere come esempio +di come possiamo creare strumenti per persone di ogni estrazione sociale, anche per coloro che non sanno programmare, +per impegnarsi e comprendere meglio l'AI perché utilizziamo le professioni, ma puoi utilizzare qualsiasi termine che ti +interessa. E man mano che questi modelli vengono dispiegati, vengono intessuti nel tessuto stesso delle nostre società, +nei nostri cellulari, nei nostri feed sui social media, persino nei nostri sistemi giudiziari e nelle nostre economie +c'è l'AI. Ed è davvero importante che l'AI rimanga accessibile in modo che sappiamo come funziona e quando non funziona. +E non c'è una soluzione unica per cose davvero complesse come i pregiudizi, il diritto d'autore o il cambiamento +climatico. Ma creando strumenti per misurare l'impatto dell'AI, possiamo iniziare a farci un'idea di quanto siano gravi +e iniziare ad affrontarli man mano che andiamo avanti. Iniziare a creare guardrail per proteggere la società e il +pianeta. E una volta che avremo queste informazioni, le aziende potranno usarle per dire: "OK, sceglieremo questo +modello perché è più sostenibile, questo modello perché rispetta il diritto d'autore". I legislatori che hanno davvero +bisogno di informazioni per scrivere leggi, possono utilizzare questi strumenti per sviluppare nuovi meccanismi di +regolamentazione o governance per l'AI man mano che viene dispiegata nella società. E gli utenti come te e me possiamo +utilizzare queste informazioni per scegliere modelli di AI di cui ci possiamo fidare, che non ci rappresentino in modo +scorretto e che non facciano un uso improprio dei nostri dati. Ma cosa ho risposto a quell'email che diceva che il mio +lavoro distruggerà l'umanità? Ho detto che concentrarsi sui rischi esistenziali futuri dell'AI è una distrazione dagli +impatti attuali, molto tangibili, e dal lavoro che dovremmo fare ora, o anche ieri, per ridurre questi impatti. Perché +sì, l'AI si sta muovendo velocemente, ma non è un fatto compiuto. Stiamo costruendo la strada mentre la percorriamo, e +possiamo decidere collettivamente in quale direzione vogliamo andare insieme. \ No newline at end of file diff --git a/slide/img/ai-positive-Moneyball.jpeg b/slide/img/ai-positive-Moneyball.jpeg deleted file mode 100644 index e754025a45c62fea0cf65de20c5e4cf0c9dfbbef..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 13847 zcma*O2UJtd)<1kg6A=`oR}mi(5_<1~Qlz)gyCDM7r1xe)rHVl40V$z_bOHz>J)!rm z5CT#Kq=WL0&wKCt-n;Jo*7|m`&Y77#XU;jlnLV>-?|m+(FTVlQ8mj8500;yEYzaT$ zat?S1h~MQAGGd6 z_|F94OlSloEhnd^s+VPAl65)XH2*Km|G&x401Y|Ob>bpo5Enp110tpYU3LO2065#L};F2ze6a>#--Ws{+q3-EHc60Ys?#AiP?s)F9Bz^vhy%~(QKwm;G@i%#jWgP z=!W~r3cjNtxw-n$90yV~)_s@hD@VaO_{re245a8Uy)jnnvNsz(_uQu8lgLupNwoDs zfLM<`=BX!tMtThvaae~ym1QcOrT$3E)AH3y5t#S7@5Ni$w6`&^?jt-(E1l7O2_&Yh zP<|%73l#HQ1eW2F`lKke@l7MuUCS~!w3k(b23&u|Y^5Y7B6MTB0@Gi27dK_nEijJ)Duen zjY;%(uD6TC97|mAwH8a7pwvDIJk1y>0`<cQ&!L{Va@77^5 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