July 2024 - nexa - server-nexa.polito.it

La tragedia dell'istruzione digitale (was Re: Didattica a distanza...)

by 380°

Buongiorno, merita un applauso questa: «tessere le lodi del Titanic perché è importante saper nuotare» :-) voglio fare il pignolo e sottolineare l'ovvio, ovvero che la contrapposizione non è tra "istruzione digitale" vs "istruzione analogica" ma tra "didattica in presenza" e "didattica a distanza (cioè _mediata_ attraverso sistemi software... di sorveglianza)" è "la distanza" l'elemento _mortifero_ del discorso, contrapposta a "la vicinanza" che è l'elemento _vitale_ che ci _definisce_ come umani "Enrico Nardelli" <nardelli(a)mat.uniroma2.it> writes: > Beh, ci sono gli articoli "marchettari" più che marchettari nel caso in oggetto sono cialtroni, avendo rimpiazzato "one-to-one online tutoring" con "didattica a distanza", che a _tutti_ richiama alla mente le lezioni remote di intere classi via videocall et al di epoca COVID e non quello che realmente è: ripetizioni a distanza con UNA persona dedicata dall'altra parte della videochiamata :-O non sono "semplici" marchette, è manipolazione della (pseudo)scienza per far apparire reale ciò che si vuol far credere a chi si limita a leggere i titoli e i sottotitoli, senza capire _perché_ - su quali basi - si sostengono determinate tesi > e poi c'è la realtà già, la realtà... costa Troppa Fatica™ restare ancorati alla realtà > https://www.startmag.it/innovazione/la-tragedia-istruzione-digitale-ovvero-… «La tragedia dell'istruzione digitale ovvero la rivincita di Platone» bellissimo articolo grazie! un "bagno nella realtà" che farebbe bene a tutti ma che interessa _letteralmente_ a quattro gatti, mentre i "padroni delle notizie" lo ignorano spudoratamente, perché il loro _compito_ è /altro/ nell'articolo Enrico non fa riferimento a eventuali ricerche sulla percezione/valutazione della c.d. "istruzione digitale" (didattica a distanza?) da parte di studenti e genitori, cercherò nel rapporto UNESCO perché questo aspetto mi interessa aggiungo stralci per fini archivistici: --8<---------------cut here---------------start------------->8--- 6 Luglio 2024 07:11 No, non si tratta della situazione di cui si lamentano quelli (troppi, purtroppo) che sostengono che gli insegnanti italiani siano indietro perché « [ignorano le potenzialità delle tecnologie digitali]». È invece la rivincita di quelli che, sottolineando la centralità dell'elemento umano nei processi educativi, hanno sempre ribadito che nell'istruzione non è un elemento davvero essenziale avere, ad esempio, un tablet per ogni studente o reti superveloci nell'intero edificio scolastico, mentre lo è avere insegnanti ben preparati e ben pagati, con un ruolo sociale riconosciuto e difeso. In un mio recente intervento ho ricordato come gli [aspetti relazionali del rapporto tra docente e studente] siano fondamentali per il successo del processo educativo. Si tratta di una riflessione elaborata da Platone nei suoi Dialoghi, [...] A questo punto abbiamo una certificazione autorevole che chi ha ragione tra queste due posizioni sono gli scettici dell'uso della tecnologia digitale nelle scuole e non gli entusiasti. Si tratta del recente rapporto UNESCO [An Ed-Tech Tragedy?] (= Una tragedia per l'istruzione digitale?), di cui, chissà perché, non mi pare si sia parlato molto sui grandi giornali d'opinione [...] Invece, man mano che le soluzioni digitali venivano dispiegate come mezzo primario per erogare l'istruzione obbligatoria, ci si è accorti delle conseguenze dannose e non volute risultanti dalla transizione da un'educazione in presenza basata sulla scuola come luogo fisico ad un insegnamento a distanza supportato dalla tecnologia. [...] Una dipendenza senza precedenti del sistema educativo dalla tecnologia si è tradotta in esclusione, disuguaglianza sconcertante, danni involontari e modelli di apprendimento che antepongono le macchine e il profitto alle persone. Il semplice elenco dei capitoli della sezione del rapporto che analizza tali guasti ( /“Act II: From Promises to Reality”/) (= Atto 2°: dalle promesse alla realtà) è sufficiente a far capire la portata del disastro compiuto: • la maggior parte degli allievi è rimasta indietro; • le disuguaglianze sono aumentate; • gli allievi si sono impegnati di meno, hanno raggiunto risultati inferiori, e hanno abbandonato l'istruzione obbligatoria; • l'istruzione è stata affossata e impoverita; • l'immersione nella tecnologia è stata dannosa per la salute; • i costi ambientali sono aumentati; • il settore privato ha rafforzato il controllo sull'istruzione pubblica; • una sorveglianza senza precedenti si è diffusa nel settore dell'istruzione. [...] Il documento prosegue discutendo quali alternative avrebbero dovuto essere considerate, dal tenere le scuole aperte all'uso di soluzioni non tecnologiche. La parte finale del rapporto fornisce alcune raccomandazioni per l'uso futuro della tecnologia digitale nel mondo dell'istruzione, che si auspica più rispettoso della componente umana, tra cui vale la pena sottolineare l'indicazione che sostiene che l'apprendimento in presenza ha la priorità su altre modalità e quella che sottolinea la necessità di difendere l'istruzione dalla diminuzione delle opportunità di usufruirne in modo libero, accessibile e disponibile, diminuzione che è conseguenza della tecnologia digitale. Appunto, “la rivincita di Platone”. /(I lettori interessati potranno dialogare con l'autore, a partire dal terzo giorno successivo alla pubblicazione, [su questo blog interdisciplinare])/ [ignorano le potenzialità delle tecnologie digitali] <https://www.tecnicadellascuola.it/professori-noiosi-e-privi-di-cultura-digi…> [aspetti relazionali del rapporto tra docente e studente] <https://link-and-think.blogspot.com/2024/01/il-ciclone-chatgpt-e-la-scuola-…> [An Ed-Tech Tragedy?] <https://www.unesco.org/en/digital-education/ed-tech-tragedy> [su questo blog interdisciplinare] <https://link-and-think.blogspot.com/> --8<---------------cut here---------------end--------------->8--- saluti, 380° -- 380° (Giovanni Biscuolo public alter ego) «Noi, incompetenti come siamo, non abbiamo alcun titolo per suggerire alcunché» Disinformation flourishes because many people care deeply about injustice but very few check the facts. Ask me about <https://stallmansupport.org>.

July 7, 2024

Meet Mercy and Anita – the African workers driving the AI revolution, for just over a dollar an hour | Artificial intelligence (AI) | The Guardian

by Alberto Cammozzo

<https://www.theguardian.com/technology/article/2024/jul/06/mercy-anita-afri…> Mercy craned forward, took a deep breath and loaded another task on her computer. One after another, disturbing images and videos appeared on her screen. As a Meta content moderator working at an outsourced office in Nairobi, Mercy was expected to action one “ticket” every 55 seconds during her 10-hour shift. This particular video was of a fatal car crash. Someone had filmed the scene and uploaded it to Facebook, where it had been flagged by a user. Mercy’s job was to determine whether it had breached any of the company’s guidelines that prohibit particularly violent or graphic content. She looked closer at the video as the person filming zoomed in on the crash. She began to recognise one of the faces on the screen just before it snapped into focus: the victim was her grandfather. Mercy pushed her chair back and ran towards the exit, past rows of colleagues who looked on in concern. She was crying. Outside, she started calling relatives. There was disbelief – nobody else had heard the news yet. Her supervisor came out to comfort her, but also to remind her that she would need to return to her desk if she wanted to make her targets for the day. She could have a day off tomorrow in light of the incident – but given that she was already at work, he pointed out, she may as well finish her shift. New tickets appeared on the screen: her grandfather again, the same crash over and over. Not only the same video shared by others, but new videos from different angles. Pictures of the car; pictures of the dead; descriptions of the scene. She began to recognise everything now. Her neighbourhood, around sunset, only a couple of hours ago – a familiar street she had walked along many times. Four people had died. Her shift seemed endless. We spoke with dozens of workers just like Mercy at three data annotation and content moderation centres run by one company across Kenya and Uganda. Content moderators are the workers who trawl, manually, through social media posts to remove toxic content and flag violations of the company’s policies. Data annotators label data with relevant tags to make it legible for use by computer algorithms. Behind the scenes, these two types of “data work” make our digital lives possible. Mercy’s story was a particularly upsetting case, but by no means extraordinary. The demands of the job are intense. “Physically you are tired, mentally you are tired, you are like a walking zombie,” said one data worker who had migrated from Nigeria for the job. Shifts are long and workers are expected to meet stringent performance targets based on their speed and accuracy. Mercy’s job also requires close attention – content moderators can’t just zone out, because they have to correctly tag videos according to strict criteria. Videos need to be examined to find the highest violation as defined by Meta’s policies. Violence and incitement, for instance, are a higher violation than simple bullying and harassment – so it isn’t enough to identify a single violation and then stop. You have to watch the whole thing, in case it gets worse. “The most disturbing thing was not just the violence,” another moderator told us, “it was the sexually explicit and disturbing content.” Moderators witness suicides, torture and rape “almost every day”, commented the same moderator; “you normalise things that are just not normal.” Workers in these moderation centres are continually bombarded with graphic images and videos, and given no time to process what they are witnessing. They’re expected to action between 500 and 1,000 tickets a day. Many reported never feeling the same again: the job had made an indelible mark on their lives. The consequences can be devastating. “Most of us are damaged psychologically, some have attempted suicide … some of our spouses have left us and we can’t get them back,” commented one moderator who had been let go by the company. “The company policies were even more strenuous than the job itself,” remarked another. Workers at one of the content moderation centres we visited were left crying and shaking after witnessing beheading videos, and were told by management that at some point during the week they could have a 30-minute break to see a “wellness counsellor” – a colleague who had no formal training as a psychologist. Workers who ran away from their desks in response to what they’d seen were told they had committed a violation of the company’s policy because they hadn’t remembered to enter the right code on their computer indicating they were either “idle” or on a “bathroom break” – meaning their productivity scores could be marked down accordingly. The stories were endless: “I collapsed in the office”; “I went into a severe depression”; “I had to go to hospital”; “they had no concern for our wellbeing”. Workers told us that management was understood to monitor hospital records to verify whether an employee had taken a legitimate sick day – but never to wish them better, or out of genuine concern for their health. Job security at this particular company is minimal – the majority of workers we interviewed were on rolling one- or three-month contracts, which could disappear as soon as the client’s work was complete. They worked in rows of up to a hundred on production floors in a darkened building, part of a giant business park on the outskirts of Nairobi. Their employer was a client of Meta’s, a prominent business process outsourcing (BPO) company with headquarters in San Francisco and delivery centres in east Africa where insecure and low-income work could be distributed to local employees of the firm. Many of the workers, like Mercy herself, had once lived in the nearby Kibera slum – the largest urban slum in Africa – and were hired under the premise that the company was helping disadvantaged workers into formal employment. The reality is that many of these workers are too terrified to question management for fear of losing their jobs. Workers reported that those who complain are told to shut up and reminded that they could easily be replaced. While many of the moderators we spoke to were Kenyan, some had migrated from other African countries to work for the BPO and assist Meta in moderating other African languages. A number of these workers spoke about being identifiable on the street as foreigners, which added to their sense of being vulnerable to harassment and abuse from the Kenyan police. Police harassment wasn’t the only danger they faced. One woman we interviewed described how members of a “liberation front” in a neighbouring African country found names and pictures of Meta moderators and posted them online with menacing threats, because they disagreed with moderation decisions that had been made. These workers were terrified, of course, and went to the BPO with the pictures. The company informed them they would see about enhancing security at the production facilities; aside from that, they said, there was nothing else they could do – the workers should just “stay safe”. Most of us can hope never to experience the inhumane working conditions endured by Mercy and her colleagues. But data work of this kind is performed by millions of workers in different circumstances and locations around the world. At this particular centre, some of the working conditions changed after our research was conducted. However large companies such as Meta tend to have multiple outsourced providers of moderation services who compete for the most profitable contracts from the company. This data work is essential for the functioning of the everyday products and services we use – from social media apps to chatbots and new automated technologies. It’s a precondition for their very existence – were it not for content moderators constantly scanning posts in the background, social networks would be immediately flooded with violent and explicit material. Without data annotators creating datasets that can teach AI the difference between a traffic light and a street sign, autonomous vehicles would not be allowed on our roads. And without workers training machine learning algorithms, we would not have AI tools such as ChatGPT. One such worker we spoke to, Anita, worked for a BPO in Gulu, the largest city in northern Uganda. Anita has been working on a project for an autonomous vehicle company. Her job is to review hour after hour of footage of drivers at the wheel. She’s looking for any visual evidence of a lapse in concentration, or something resembling a “sleep state”. This assists the manufacturer in constructing an “in-cabin behaviour monitoring system” based on the driver’s facial expressions and eye movements. Sitting at a computer and concentrating on this footage for hours at a time is draining. Sometimes, Anita feels the boredom as a physical force, pushing her down in her chair and closing her eyelids. But she has to stay alert, just like the drivers on her screen. In return for 45 hours of intense, stressful work a week – possibly with unpaid overtime on top – annotators can expect to earn in the region of 800,000 Ugandan shillings a month, a little over US$200 or approximately $1.16 per hour. On the production floor, hundreds of data annotators sit in silence, lined up at rows of desks. The setup will be instantly familiar to anyone who’s worked at a call centre – the system of management is much the same. The light is dimmed in an attempt to reduce the eye strain that results from nine hours of intense concentration. The workers’ screens flicker with a constant stream of images and videos requiring annotation. Like Anita, workers are trained to identify elements of the image in response to client specifications: they may, for example, draw polygons around different objects, from traffic lights to stop signs and human faces. Every aspect of Anita and her fellow annotators’ working lives is digitally monitored and recorded. From the moment they use the biometric scanners to enter the secure facilities, to the extensive network of CCTV cameras, workers are closely surveilled. Every second of their shift must be accounted for according to the efficiency-monitoring software on their computer. Some workers we spoke to even believe managers cultivate a network of informers among the staff to make sure that attempts to form a trade union don’t sneak under the radar. Working constantly, for hours on end, is physically and psychologically draining. It offers little opportunity for self-direction; the tasks are reduced to their simplest form to maximise the efficiency and productivity of the workers. Annotators are disciplined into performing the same routine actions over and over again at top speed. As a result, they experience a curious combination of complete boredom and suffocating anxiety at the same time. This is the reality at the coalface of the AI revolution: people working under oppressive surveillance at furious intensity just to keep their jobs and support their families. When we think about the world of AI development our minds might naturally turn to engineers working in sleek, air-conditioned offices in Silicon Valley. What most people don’t realise is that roughly 80% of the time spent on training AI consists of annotating datasets. Frontier technologies such as autonomous vehicles, machines for nanosurgery and drones are all being developed in places like Gulu. As tech commentator Phil Jones puts it: “In reality, the magic of machine learning is the grind of data labelling.” This is where the really time-consuming and laborious work takes place. There is a booming global marketplace for data annotation, which was estimated to be worth $2.22bn in 2022 and is expected to grow at around 30% each year until it reaches over $17bn in 2030. As AI tools are taken up in retail, healthcare and manufacturing – to name just a few sectors that are being transformed – the demand for well-curated data will increase by the day. The majority of workers in the global south work in the informal jobs sector. Photograph: Yannick Tylle/Getty Images Today’s tech companies can use their wealth and power to exploit a deep division in how the digital labour of AI work is distributed across the globe. The majority of workers in countries in the global south work in the informal sector. Unemployment rates remain staggeringly high and well-paid jobs with employment protections remain elusive for many. Vulnerable workers in these contexts are not only likely to work for lower wages; they will also be less ready to demand better working conditions, because they know how easily they can be replaced. The process of outsourcing work to the global south is popular with businesses not because it provides much-needed economic opportunities for the less well off, but because it provides a clear route to a more tightly disciplined workforce, higher efficiency and lower costs. By using AI products we are directly inserting ourselves into the lives of workers dispersed across the globe. We are connected whether we like it or not. Just as drinking a cup of coffee implicates the coffee drinker in a global production network from bean to cup, we should all understand how using a search engine, a chatbot – or even something as simple as a smart robot vacuum – sets in motion global flows of data and capital that connect workers, organisations and consumers in every corner of the planet. Many tech companies therefore do what they can to hide the reality of how their products are actually made. They present a vision of shining, sleek, autonomous machines – computers searching through large quantities of data, teaching themselves as they go – rather than the reality of the poorly paid and gruelling human labour that both trains them and is managed by them. Back in Gulu, Anita has just arrived home from work. She sits outside with her children in plastic chairs under her mango tree. She’s tired. Her eyes start to close as the sun falls below the horizon. The children go to bed, and she will not be long after them. She needs to rest before her 5am start tomorrow, when she will be annotating again. Nobody ever leaves the BPO willingly – there’s nothing else to do. She sees her ex-colleagues when she’s on her way to work, hawking vegetables on the market or trying to sell popcorn by the side of the road. If there were other opportunities, people would seize them. She just has to keep her head down, hit her targets, and make sure that whatever happens, she doesn’t get laid off. Maybe another project will come in; maybe she could change to a new workflow. That would be a relief, something a bit different. Maybe labelling streets, drawing outlines around signs and trying to work out what it would be like to live at the other end of the lens, in a country with big illuminated petrol signs and green grass lawns. This is an edited extract from Feeding the Machine: The Hidden Human Labour Powering AI, by James Muldoon, Mark Graham and Callum Cant (Canongate £20). To support the Guardian and Observer, order your copy from guardianbookshop.com. Delivery charges may apply

July 7, 2024

Meet Mercy and Anita – the African workers driving the AI revolution, for just over a dollar an hour | Artificial intelligence (AI) | The Guardian

by Alberto Cammozzo

<https://www.theguardian.com/technology/article/2024/jul/06/mercy-anita-afri…> Mercy craned forward, took a deep breath and loaded another task on her computer. One after another, disturbing images and videos appeared on her screen. As a Meta content moderator working at an outsourced office in Nairobi, Mercy was expected to action one “ticket” every 55 seconds during her 10-hour shift. This particular video was of a fatal car crash. Someone had filmed the scene and uploaded it to Facebook, where it had been flagged by a user. Mercy’s job was to determine whether it had breached any of the company’s guidelines that prohibit particularly violent or graphic content. She looked closer at the video as the person filming zoomed in on the crash. She began to recognise one of the faces on the screen just before it snapped into focus: the victim was her grandfather. Mercy pushed her chair back and ran towards the exit, past rows of colleagues who looked on in concern. She was crying. Outside, she started calling relatives. There was disbelief – nobody else had heard the news yet. Her supervisor came out to comfort her, but also to remind her that she would need to return to her desk if she wanted to make her targets for the day. She could have a day off tomorrow in light of the incident – but given that she was already at work, he pointed out, she may as well finish her shift. New tickets appeared on the screen: her grandfather again, the same crash over and over. Not only the same video shared by others, but new videos from different angles. Pictures of the car; pictures of the dead; descriptions of the scene. She began to recognise everything now. Her neighbourhood, around sunset, only a couple of hours ago – a familiar street she had walked along many times. Four people had died. Her shift seemed endless. We spoke with dozens of workers just like Mercy at three data annotation and content moderation centres run by one company across Kenya and Uganda. Content moderators are the workers who trawl, manually, through social media posts to remove toxic content and flag violations of the company’s policies. Data annotators label data with relevant tags to make it legible for use by computer algorithms. Behind the scenes, these two types of “data work” make our digital lives possible. Mercy’s story was a particularly upsetting case, but by no means extraordinary. The demands of the job are intense. “Physically you are tired, mentally you are tired, you are like a walking zombie,” said one data worker who had migrated from Nigeria for the job. Shifts are long and workers are expected to meet stringent performance targets based on their speed and accuracy. Mercy’s job also requires close attention – content moderators can’t just zone out, because they have to correctly tag videos according to strict criteria. Videos need to be examined to find the highest violation as defined by Meta’s policies. Violence and incitement, for instance, are a higher violation than simple bullying and harassment – so it isn’t enough to identify a single violation and then stop. You have to watch the whole thing, in case it gets worse. “The most disturbing thing was not just the violence,” another moderator told us, “it was the sexually explicit and disturbing content.” Moderators witness suicides, torture and rape “almost every day”, commented the same moderator; “you normalise things that are just not normal.” Workers in these moderation centres are continually bombarded with graphic images and videos, and given no time to process what they are witnessing. They’re expected to action between 500 and 1,000 tickets a day. Many reported never feeling the same again: the job had made an indelible mark on their lives. The consequences can be devastating. “Most of us are damaged psychologically, some have attempted suicide … some of our spouses have left us and we can’t get them back,” commented one moderator who had been let go by the company. “The company policies were even more strenuous than the job itself,” remarked another. Workers at one of the content moderation centres we visited were left crying and shaking after witnessing beheading videos, and were told by management that at some point during the week they could have a 30-minute break to see a “wellness counsellor” – a colleague who had no formal training as a psychologist. Workers who ran away from their desks in response to what they’d seen were told they had committed a violation of the company’s policy because they hadn’t remembered to enter the right code on their computer indicating they were either “idle” or on a “bathroom break” – meaning their productivity scores could be marked down accordingly. The stories were endless: “I collapsed in the office”; “I went into a severe depression”; “I had to go to hospital”; “they had no concern for our wellbeing”. Workers told us that management was understood to monitor hospital records to verify whether an employee had taken a legitimate sick day – but never to wish them better, or out of genuine concern for their health. Job security at this particular company is minimal – the majority of workers we interviewed were on rolling one- or three-month contracts, which could disappear as soon as the client’s work was complete. They worked in rows of up to a hundred on production floors in a darkened building, part of a giant business park on the outskirts of Nairobi. Their employer was a client of Meta’s, a prominent business process outsourcing (BPO) company with headquarters in San Francisco and delivery centres in east Africa where insecure and low-income work could be distributed to local employees of the firm. Many of the workers, like Mercy herself, had once lived in the nearby Kibera slum – the largest urban slum in Africa – and were hired under the premise that the company was helping disadvantaged workers into formal employment. The reality is that many of these workers are too terrified to question management for fear of losing their jobs. Workers reported that those who complain are told to shut up and reminded that they could easily be replaced. While many of the moderators we spoke to were Kenyan, some had migrated from other African countries to work for the BPO and assist Meta in moderating other African languages. A number of these workers spoke about being identifiable on the street as foreigners, which added to their sense of being vulnerable to harassment and abuse from the Kenyan police. Police harassment wasn’t the only danger they faced. One woman we interviewed described how members of a “liberation front” in a neighbouring African country found names and pictures of Meta moderators and posted them online with menacing threats, because they disagreed with moderation decisions that had been made. These workers were terrified, of course, and went to the BPO with the pictures. The company informed them they would see about enhancing security at the production facilities; aside from that, they said, there was nothing else they could do – the workers should just “stay safe”. Most of us can hope never to experience the inhumane working conditions endured by Mercy and her colleagues. But data work of this kind is performed by millions of workers in different circumstances and locations around the world. At this particular centre, some of the working conditions changed after our research was conducted. However large companies such as Meta tend to have multiple outsourced providers of moderation services who compete for the most profitable contracts from the company. This data work is essential for the functioning of the everyday products and services we use – from social media apps to chatbots and new automated technologies. It’s a precondition for their very existence – were it not for content moderators constantly scanning posts in the background, social networks would be immediately flooded with violent and explicit material. Without data annotators creating datasets that can teach AI the difference between a traffic light and a street sign, autonomous vehicles would not be allowed on our roads. And without workers training machine learning algorithms, we would not have AI tools such as ChatGPT. One such worker we spoke to, Anita, worked for a BPO in Gulu, the largest city in northern Uganda. Anita has been working on a project for an autonomous vehicle company. Her job is to review hour after hour of footage of drivers at the wheel. She’s looking for any visual evidence of a lapse in concentration, or something resembling a “sleep state”. This assists the manufacturer in constructing an “in-cabin behaviour monitoring system” based on the driver’s facial expressions and eye movements. Sitting at a computer and concentrating on this footage for hours at a time is draining. Sometimes, Anita feels the boredom as a physical force, pushing her down in her chair and closing her eyelids. But she has to stay alert, just like the drivers on her screen. In return for 45 hours of intense, stressful work a week – possibly with unpaid overtime on top – annotators can expect to earn in the region of 800,000 Ugandan shillings a month, a little over US$200 or approximately $1.16 per hour. On the production floor, hundreds of data annotators sit in silence, lined up at rows of desks. The setup will be instantly familiar to anyone who’s worked at a call centre – the system of management is much the same. The light is dimmed in an attempt to reduce the eye strain that results from nine hours of intense concentration. The workers’ screens flicker with a constant stream of images and videos requiring annotation. Like Anita, workers are trained to identify elements of the image in response to client specifications: they may, for example, draw polygons around different objects, from traffic lights to stop signs and human faces. Every aspect of Anita and her fellow annotators’ working lives is digitally monitored and recorded. From the moment they use the biometric scanners to enter the secure facilities, to the extensive network of CCTV cameras, workers are closely surveilled. Every second of their shift must be accounted for according to the efficiency-monitoring software on their computer. Some workers we spoke to even believe managers cultivate a network of informers among the staff to make sure that attempts to form a trade union don’t sneak under the radar. Working constantly, for hours on end, is physically and psychologically draining. It offers little opportunity for self-direction; the tasks are reduced to their simplest form to maximise the efficiency and productivity of the workers. Annotators are disciplined into performing the same routine actions over and over again at top speed. As a result, they experience a curious combination of complete boredom and suffocating anxiety at the same time. This is the reality at the coalface of the AI revolution: people working under oppressive surveillance at furious intensity just to keep their jobs and support their families. When we think about the world of AI development our minds might naturally turn to engineers working in sleek, air-conditioned offices in Silicon Valley. What most people don’t realise is that roughly 80% of the time spent on training AI consists of annotating datasets. Frontier technologies such as autonomous vehicles, machines for nanosurgery and drones are all being developed in places like Gulu. As tech commentator Phil Jones puts it: “In reality, the magic of machine learning is the grind of data labelling.” This is where the really time-consuming and laborious work takes place. There is a booming global marketplace for data annotation, which was estimated to be worth $2.22bn in 2022 and is expected to grow at around 30% each year until it reaches over $17bn in 2030. As AI tools are taken up in retail, healthcare and manufacturing – to name just a few sectors that are being transformed – the demand for well-curated data will increase by the day. The majority of workers in the global south work in the informal jobs sector. Photograph: Yannick Tylle/Getty Images Today’s tech companies can use their wealth and power to exploit a deep division in how the digital labour of AI work is distributed across the globe. The majority of workers in countries in the global south work in the informal sector. Unemployment rates remain staggeringly high and well-paid jobs with employment protections remain elusive for many. Vulnerable workers in these contexts are not only likely to work for lower wages; they will also be less ready to demand better working conditions, because they know how easily they can be replaced. The process of outsourcing work to the global south is popular with businesses not because it provides much-needed economic opportunities for the less well off, but because it provides a clear route to a more tightly disciplined workforce, higher efficiency and lower costs. By using AI products we are directly inserting ourselves into the lives of workers dispersed across the globe. We are connected whether we like it or not. Just as drinking a cup of coffee implicates the coffee drinker in a global production network from bean to cup, we should all understand how using a search engine, a chatbot – or even something as simple as a smart robot vacuum – sets in motion global flows of data and capital that connect workers, organisations and consumers in every corner of the planet. Many tech companies therefore do what they can to hide the reality of how their products are actually made. They present a vision of shining, sleek, autonomous machines – computers searching through large quantities of data, teaching themselves as they go – rather than the reality of the poorly paid and gruelling human labour that both trains them and is managed by them. Back in Gulu, Anita has just arrived home from work. She sits outside with her children in plastic chairs under her mango tree. She’s tired. Her eyes start to close as the sun falls below the horizon. The children go to bed, and she will not be long after them. She needs to rest before her 5am start tomorrow, when she will be annotating again. Nobody ever leaves the BPO willingly – there’s nothing else to do. She sees her ex-colleagues when she’s on her way to work, hawking vegetables on the market or trying to sell popcorn by the side of the road. If there were other opportunities, people would seize them. She just has to keep her head down, hit her targets, and make sure that whatever happens, she doesn’t get laid off. Maybe another project will come in; maybe she could change to a new workflow. That would be a relief, something a bit different. Maybe labelling streets, drawing outlines around signs and trying to work out what it would be like to live at the other end of the lens, in a country with big illuminated petrol signs and green grass lawns. This is an edited extract from Feeding the Machine: The Hidden Human Labour Powering AI, by James Muldoon, Mark Graham and Callum Cant (Canongate £20). To support the Guardian and Observer, order your copy from guardianbookshop.com. Delivery charges may apply

July 6, 2024

Re: [nexa] Didattica a distanza, l’84% degli studenti è più sicuro e con voti migliori.

by Enrico Nardelli

Beh, ci sono gli articoli "marchettari" e poi c'è la realtà https://www.startmag.it/innovazione/la-tragedia-istruzione-digitale-ovvero-… Ciao, Enrico ------ Messaggio originale ------ Da "380° via nexa" <nexa(a)server-nexa.polito.it> A nexa(a)server-nexa.polito.it Data 03/07/2024 18:44:39 Oggetto [nexa] Didattica a distanza, l’84% degli studenti è più sicuro e con voti migliori. >Buongiorno, > >https://www.orizzontescuola.it/didattica-a-distanza-l84-degli-studenti-e-pi… > >--8<---------------cut here---------------start------------->8--- > >Ricerca GoStudent: “I più piccoli traggono maggiori benefici dalle >lezioni da remoto” > >La didattica a distanza, conseguenza del Covid-19 e del lockdown, ha >lasciato un segno inaspettato sugli studenti: l’84% di loro si sente più >sicuro e meno impacciato a seguire le lezioni attraverso lo schermo di >un computer, nella propria cameretta. > >È quanto emerge da una ricerca condotta da GoStudent, piattaforma di >tutoring e ripetizioni online, che ha chiesto un feedback a bambini e >ragazzi dai 6 ai 18 anni sulle lezioni online. > >Le risposte provenienti da diversi paesi europei, tra cui l’Italia, >hanno rivelato che la maggioranza degli studenti ha visto aumentare la >propria fiducia grazie alle lezioni da remoto, con conseguenti >miglioramenti nei voti scolastici. I risultati migliori sono stati >ottenuti dagli studenti della scuola primaria, che hanno iniziato il >loro percorso scolastico durante la pandemia. > >Il 77% degli intervistati si dichiara inoltre più a proprio agio in un >mondo digitale, confermando un fenomeno ormai diffuso. Tuttavia, scuole >e famiglie stanno cercando di monitorare l’utilizzo degli strumenti >digitali per evitare che i ragazzi cadano in trappole del web, come le >pericolose “challenge”. > >“L’apprendimento personalizzato, se sostenuto e affrontato come una >collaborazione, aumenta significativamente la fiducia degli studenti e >il rendimento accademico”, spiega Felix Ohswald, CEO e co-fondatore di >GoStudent. “Il fatto che più di tre studenti su quattro abbiano >sperimentato un sostanziale aumento della fiducia in se stessi >attraverso il tutoring personalizzato è una potente testimonianza >dell’impatto del supporto educativo individuale”. > >La ricerca sottolinea l’importanza di un approccio personalizzato >all’apprendimento, che tenga conto delle esigenze individuali di ciascun >studente e che sfrutti le potenzialità offerte dagli strumenti digitali, >pur mantenendo un’attenzione costante al benessere e alla sicurezza dei >ragazzi. > >--8<---------------cut here---------------end--------------->8--- > > >-- >380° (Giovanni Biscuolo public alter ego) > >«Noi, incompetenti come siamo, > non abbiamo alcun titolo per suggerire alcunché» > >Disinformation flourishes because many people care deeply about injustice >but very few check the facts. Ask me about <https://stallmansupport.org>. -- EN https://www.hoepli.it/libro/la-rivoluzione-informatica/9788896069516.html ====================================================== Prof. Enrico Nardelli Past President di "Informatics Europe" Direttore del Laboratorio Nazionale "Informatica e Scuola" del CINI Dipartimento di Matematica - Universit� di Roma "Tor Vergata" Via della Ricerca Scientifica snc - 00133 Roma home page: https://www.mat.uniroma2.it/~nardelli blog: https://link-and-think.blogspot.it/ tel: +39 06 7259.4204 fax: +39 06 7259.4699 mobile: +39 335 590.2331 e-mail: nardelli(a)mat.uniroma2.it online meeting: https://blue.meet.garr.it/b/enr-y7f-t0q-ont ====================================================== --

July 6, 2024

Multiple nations enact mysterious export controls on quantum computers

by Fabio Alemagna

> > *Identical wording placing limits on the export of quantum computers has > appeared in regulations across the globe. There doesn't seem to be any > scientific reason for the controls, and all can be traced to secret > international discussions* *Secret* international discussions have resulted in governments across the > world imposing *identical* export controls on quantum computers, while > *refusing* to disclose the scientific rationale behind the regulations. > Although quantum computers theoretically have the potential to threaten > national security by breaking encryption techniques, even the most advanced > quantum computers currently in public existence are too small and too > error-prone to achieve this, rendering the bans seemingly pointless. > The UK is one of the countries that has prohibited the export of > <https://www.newscientist.com/article/2431853-uk-ban-on-quantum-computer-exp…> quantum > computers with 34 or more quantum bits, or qubits, and error rates below a > certain threshold. The intention seems to be to restrict machines of a > certain capability, but the UK government hasn’t explicitly said this. A *New > Scientist* *freedom of information request* for a rationale behind these > numbers *was turned down on the grounds of national security*. https://www.newscientist.com/article/2436023-multiple-nations-enact-mysteri…

July 5, 2024

[OT] Re: Didattica a distanza, l’84% degli studenti è più sicuro e con voti migliori.

by 380°

Buongiorno, colgo l'occasione offerta dal "per rendersene conto" per scrivere un _clamoroso_ off-topic, perché ovviamente sono un _tuttologo_ :-D Stefano Borroni Barale <s.barale(a)erentil.net> writes: > giovedì 4 luglio 2024 14:08, Andrea Trentini <andrea.trentini(a)unimi.it> ha scritto: > >> stiamo creando tanti Hikikomori... non so in che tipo di "patologia" verrebbero inseriti quelli che si sentono più sicuri a seguire le lezioni a distanza, ma mi piacerebbe tantissimo sentire da loro _da cosa_ si sentirebbero più scuri e perché d'altro canto mi domando se quel 84% del campione di ragazzi ha risposto seriamente o tanto per gioco... o per _prendersi gioco_ della "ricerca": voglio davvero vederli socializzare senza avere "contatto fisico" a scuola, ROTFL! ...a meno che stiano /sognando/ la scuola come un "grande campo educativo invernale", contrapposto a quelli estivi, assieme ai genitori che non sanno dove lasciare i figli mentre sono al lavoro. la cosa sicura è che: > Ma per rendersene conto bisogna frequentare le classi di una scuola > reale, già: /frequentare/ e non /pontificare/, /reale/ e non /virtuale/... roba tosta! :-) io introdurrei anche _frequentissimi_ scambi lavorativi tra docenti dei vari livelli scolastici e universitari, perché _questa_ specializzazione, questo _scollamento_, anzi questo tipo di "concorrenza", fa _schifo_, pena, pietà e rabbia: https://www.tecnicadellascuola.it/test-dingresso-universita-anticipati-110-… «Test d’ingresso università anticipati, 110 docenti: “Sono logici, e a quel punto cosa importa a un 18enne di studiare Dante?”» se vogliamo davvero parlare di disagio _sociale_ a scuola, o meglio della _ospedalizzazione burocraticizzata_ della scuola, perché non analizzare la serie storica E la distribuzione territoriale delle _certificazioni_ di alunni DSA e BSA? https://www.miur.gov.it/documents/20182/6891182/Focus+sugli+alunni+con+Dist… «I principali dati relativi agli alunni con DSA» la serie storica è a pag. 17: guardate voi. La _normativa_ scolastica relatica a DSA (e successivamente BSA) è stata introdotta nel 2010 e le diagnosi sono in aumento progressivo quasi lineare da allora. e quello è _solo_ per i DSA, non riesco a trovare "al volo" un report analogo per i BSA ah scusate: - disabilità: https://www.miur.gov.it/web/guest/disabilita - DSA: Disturbo Specifico dell'Apprendimento (https://www.miur.gov.it/web/guest/disturbi-specifici-dell-apprendimento-dsa-) - BSA: Bisogni Educativi Speciali (https://www.miur.gov.it/altri-bisogni-educativi-speciali-bes-) non illudiamoci poi manco di striscio di poter parlare di _pedagogia_, cosa che evidentemente è ritenuta superflua da "quelli che GoStudent è il futuro!" (e "la classe sparirà"): https://www.tecnicadellascuola.it/uno-studente-su-due-ha-dimenticato-lonlin… «Uno studente su due ha dimenticato l’online: report di GoStudent sul futuro dell’istruzione» ah, ovviamente sempre secondo il TOT% del _genitori_, che notoriamente sono molto _equilibrati_ quando si tratta del rapporto con la scuola e con i docenti, vero? ...ma stiamo divagando, qui non possiamo parlare di scuola :-) torniamo "a bomba" all'oggetto: la "notizia"... > non il mondo lisergico da cui scrivono i moderni Candide di > Orizzonte Scuola. Da tempo non è fonte affidabile di notizie sul mondo > scolastico. SBB Io ho fornito l'URL della notizia da Orizzontescuola perché quello "originale" di Repubblica era dietro paywall qualche giorno fa: https://www.repubblica.it/italia/2024/07/02/news/il_covid_e_la_didattica_a_… Repubblica è fonte affidabile di notizie sul mondo scolastico? ...ma SOPRATTUTTO: dove /divolo/ è la "ricerca" GoStudent citata nella "notizia"?!? qualcosa di più dice questo articolo (11 Giu 2024): https://askanews.it/2024/06/11/voti-migliori-e-piu-fiducia-in-se-stessi-uno… --8<---------------cut here---------------start------------->8--- Voti migliori e più fiducia in sé stessi: uno studio rivela i benefici della didattica online L’84% degli studenti in Italia ha migliorato i propri risultati a scuola [...] Lo rivela una ricerca condotta da Tricia Thrasher, Director of Research di Immerse piattaforma specializzata nell’apprendimento tramite realtà virtuale, che ha analizzato le risposte di circa 500 studenti in Italia fornite dalla piattaforma di apprendimento online GoStudent. Gli alunni coinvolti hanno ricevuto supporto per lo più in materie come matematica, scienze, inglese e altre lingue straniere. --8<---------------cut here---------------end--------------->8--- facendo un lavoro di "incrocio semantico" tra le traduzioni IT delle citazioni della Thrasher e di Oshwald sono confidente al 99.9% che la "ricerca" alla quale fanno riferimento molte notizie (senza MAI fornire un link, tacciloro) sia quella citata in questa press relaase di GoStudent: https://www.gostudent.org/en/press-releases/new-study-confirms-one-to-one-o… «New Study Confirms One-to-One Online Tutoring Drives Significant Grade Improvement and Boosts Student Confidence» --8<---------------cut here---------------start------------->8--- - Independent study finds three in four students increase their performance by up to three grades with personalised tutoring - 90% of students who improved their grades also reported increased confidence, meaning preparedness for exams - Performance in mathematics showed significant improvements, with 80% improving grades by up to three levels after 12 months of consistent tutoring --8<---------------cut here---------------end--------------->8--- ATTENZIONE: prego notare con _estrema_ cura che "one-to-one online tutoring" del titolo della press release sopra è "magicamente" diventato "didattica a distanza" in quello delle "notizie generaliste"... e stiamo parlando _solo_ del titolo. Leggete la "press release" per "approfondimenti". Per tornare solo brevemente al "rendersene conto", faccio sommessamente notare che per migliorare la qualità delle lezioni (e NON le ripetizioni che esistono da secoli) basterebbe evitare le "classi pollaio" di 30 ragazzi... l'ideale sarebbe una classe di 10 persone. ROTFL, pensando alle risorse _umane_ E _logistiche_ su cui possono contare le scuole (che da quello che /percepisco/ sono sempre più "integrate" da quelle che i genitori spendono per le ripetizioni one-to-one ai figli: ci sono statistiche in merito?!? Ci sono "report"? :-O ). Ma torniamo alla "notizia". La cosa divertente è che il link «The full study is available for download HERE (https://www.gostudent.org/en-gb/gostudent.org/tutoring-effectiveness)» risponde con un bel errore 404 (page not found) ma con sofisticatissime tecniche sono riuscito a correggere l'URL in https://www.gostudent.org/en-gb/tutoring-effectiveness/ ...che punta al "full report": https://a.storyblok.com/f/192322/x/9f26afe17d/en-proof-of-concept.pdf quindi: è una "notizia" o è uno spot pubblicitario? quindi: è scienza o sono solo _stronzate_ (anche senza "IA")? quelli che scrivono in _quei_ termini sono interessati a un dibattito pubblico serio (a 360°) o solo a fare _becera_ propaganda, specie quando c'è di mezzo "il digitale" o "l'online"? saluti, 380° -- 380° (Giovanni Biscuolo public alter ego) «Noi, incompetenti come siamo, non abbiamo alcun titolo per suggerire alcunché» Disinformation flourishes because many people care deeply about injustice but very few check the facts. Ask me about <https://stallmansupport.org>.

July 5, 2024

Re: [nexa] Didattica a distanza, l’84% degli studenti è più sicuro e con voti migliori.

by Michele Pinassi

Esatto. a quanto pare da alcune recenti indagini ( https://www.agendadigitale.eu/cultura-digitale/hikikomori-il-fenomeno-cresc…) una media città di provincia in Italia (66.000 individui) vivono una situazione di isolamento sociale, quasi tuti concentrati nella c.d Gen Z, i "nativi digitali". Purtroppo la mia personalissima opinione è che la Scuola Italiana ha serie difficoltà a restare al passo con i tempi, puntando ancora e soprattutto con la verifica delle nozioni e non della formazione dell'individuo in quanto tale. Formazione che si compone anche di capacità relazionali, comunicative, comportamentali che si formano in società e nelle relazioni tra pari, come avviene nelle aule scolastiche "fisiche". Va benissimo la didattica a distanza, ma non prima che l'individuo si sia socialmente formato IMHO. Just my 2 cent. Michele Il giorno gio 4 lug 2024 alle ore 14:08 Andrea Trentini < andrea.trentini(a)unimi.it> ha scritto: > stiamo creando tanti Hikikomori... > > > On 03/07/2024 18:44, 380° via nexa wrote: > > Buongiorno, > > > https://www.orizzontescuola.it/didattica-a-distanza-l84-degli-studenti-e-pi… > > > > -- > Andrea Trentini ⠠⠵ > http://atrent.it > public key ID: 0xA7A91E3B > Dip.to di Informatica > Università degli Studi di Milano > > -- Michele Pinassi Ufficio Esercizio e tecnologie - Università degli Studi di Siena tel: 0577.(23)5000 - helpdesk(a)unisi.it PGP/GPG key fingerprint 6EC4 9905 84F5 1537 9AB6 33E7 14FC 37E5 3C24 B98E

July 5, 2024

Can the climate survive the insatiable energy demands of the AI arms race? | Technology sector | The Guardian

by Alberto Cammozzo

<https://www.theguardian.com/business/article/2024/jul/04/can-the-climate-su…> Can the climate survive the insatiable energy demands of the AI arms race? New computing infrastructure means big tech is likely to miss emissions targets but they can’t afford to get left behind in a winner takes all market Dan Milmo, Alex Hern and Jillian Ambrose The artificial intelligence boom has driven big tech share prices to fresh highs, but at the cost of the sector’s climate aspirations. Google admitted on Tuesday that the technology is threatening its environmental targets after revealing that datacentres, a key piece of AI infrastructure, had helped increase its greenhouse gas emissions by 48% since 2019. It said “significant uncertainty” around reaching its target of net zero emissions by 2030 – reducing the overall amount of CO2 emissions it is responsible for to zero – included “the uncertainty around the future environmental impact of AI, which is complex and difficult to predict”. It follows Microsoft, the biggest financial backer of ChatGPT developer OpenAI, admitting that its 2030 net zero “moonshot” might not succeed owing to its AI strategy. So will tech be able to bring down AI’s environmental cost, or will the industry plough on regardless because the prize of supremacy is so great? Why does AI pose a threat to tech companies’ green goals? Datacentres are a core component of training and operating AI models such as Google’s Gemini or OpenAI’s GPT-4. They contain the sophisticated computing equipment, or servers, that crunch through the vast reams of data underpinning AI systems. They require large amounts of electricity to run, which generates CO2 depending on the energy source, as well as creating “embedded” CO2 from the cost of manufacturing and transporting the necessary equipment. According to the International Energy Agency, total electricity consumption from datacentres could double from 2022 levels to 1,000 TWh (terawatt hours) in 2026, equivalent to the energy demand of Japan, while research firm SemiAnalysis calculates that AI will result in datacentres using 4.5% of global energy generation by 2030. Water usage is significant too, with one study estimating that AI could account for up to 6.6bn cubic metres of water use by 2027 – nearly two-thirds of England’s annual consumption. What do experts say about the environmental impact? A recent UK government-backed report on AI safety said that the carbon intensity of the energy source used by tech firms is “a key variable” in working out the environmental cost of the technology. It adds, however, that a “significant portion” of AI model training still relies on fossil fuel-powered energy. Indeed, tech firms are hoovering up renewable energy contracts in an attempt to meet their environmental goals. Amazon, for instance, is the world’s largest corporate purchaser of renewable energy. Some experts argue, though, that this pushes other energy users into fossil fuels because there is not enough clean energy to go round. “Energy consumption is not just growing, but Google is also struggling to meet this increased demand from sustainable energy sources,” says Alex de Vries, the founder of Digiconomist, a website monitoring the environmental impact of new technologies. Is there enough renewable energy to go round? Global governments plan to triple the world’s renewable energy resources by the end of the decade to cut consumption of fossil fuels in line with climate targets. But the ambitious pledge, agreed at last year’s COP28 climate talks, is already in doubt and experts fear that a sharp increase in energy demand from AI datacentres may push it further out of reach. The IEA, the world’s energy watchdog, has warned that even though global renewable energy capacity grew by the fastest pace recorded in the past 20 years in 2023, the world may only double its renewable energy by 2030 under current government plans. The answer to AI’s energy appetite may be for tech companies to invest more heavily in building new renewable energy projects to meet their growing power demand. How soon can we build new renewable energy projects? Onshore renewable energy projects such as wind and solar farms are relatively fast to build – they can take less than six months to develop. However, sluggish planning rules in many developed countries alongside a global logjam in connecting new projects to the power grid could add years to the process. Offshore windfarms and hydro power schemes face similar challenges in addition to construction times of between two and five years. This has raised concerns over whether renewable energy can keep pace with the expansion of AI. Major tech companies have already tapped a third of US nuclear power plants to supply low-carbon electricity to their datacentres, according to the Wall Street Journal. But without investing in new power sources these deals would divert low-carbon electricity away from other users leading to more fossil fuel consumption to meet overall demand. Will AI’s demand for electricity grow for ever? Normal rules of supply and demand would suggest that, as AI uses more electricity, the cost of energy rises and the industry is forced to economise. But the unique nature of the industry means that the largest companies in the world may instead decide to plough through spikes in the cost of electricity, burning billions of dollars as a result. The largest and most expensive datacentres in the AI sector are those used to train “frontier” AI, systems such as GPT-4o and Claude 3.5 which are more powerful and capable than any other. The leader in the field has changed over the years, but OpenAI is generally near the top, battling for position with Anthropic, maker of Claude, and Google’s Gemini. Already, the “frontier” competition is thought to be “winner takes all”, with very little stopping customers from jumping to the latest leader. That means that if one business spends $100m on a training run for a new AI system, its competitors have to decide to spend even more themselves or drop out of the race entirely. Worse, the race for so-called “AGI”, AI systems that are capable of doing anything a person can do, means that it could be worth spending hundreds of billions of dollars on a single training run – if doing so led your company to monopolise a technology that could, as OpenAI says, “elevate humanity”. Won’t AI firms learn to use less electricity? Every month, there are new breakthroughs in AI technology that enables companies to do more with less. In March 2022, for instance, a DeepMind project called Chinchilla showed researchers how to train frontier AI models using radically less computing power, by changing the ratio between the amount of training data and the size of the resulting model. But that didn’t result in the same AI systems using less electricity; instead, it resulted in the same amount of electricity being used to make even better AI systems. In economics, that phenomenon is known as “Jevons’ paradox”, after the economist who noted that the improvement of the steam engine by James Watt, which allowed for much less coal to be used, instead led to a huge increase in the amount of the fossil fuel burned in England. As the price of steam power plummeted following Watt’s invention, new uses were discovered that wouldn’t have been worthwhile when power was expensive.

July 5, 2024

Re: [nexa] Didattica a distanza, l’84% degli studenti è più sicuro e con voti migliori.

by Stefano Borroni Barale

Buonasera! giovedì 4 luglio 2024 18:11, Damiano Verzulli <damiano(a)verzulli.it> ha scritto: > temo di *NON* riuscire a *NON* apparire antipatico, saccente, presuntuoso.... > > Cio' premesso, *SU QUESTA LISTA*, scelgo di scriverlo ugualmente: Non rilevo questi difetti nell'intervento, semmai quel tipo di pessimismo che rischia di produrre il "danno collaterale" dell'attesa di qualche intervento salvifico da parte della Legge, dello Stato, dell'Europa o altra Entità Superiore. Quindi, premesso che il mio intervento era più che altro volto a promuovere l'abbandono della lettura di certe testate online che diffondono fuffa e depressione, qualcosa quest'anno s'è fatto, collettivamente, sia col sindacato che in contesti assai più improbabili (cito un messaggio di Karlessi del febbraio '24): > al momento siamo giunti al paradosso di tenere corsi di pedagogia hacker, tramite > scuola futura (PNNR), su Google Meet perché così vuole la procedura... no comment. > chissà che nelle prossime edizioni non riusciamo a passare a BBB, hackerando in > qualche modo la procedure :P E, verso Maggio, abbiamo in effetti hackerato la procedura 😂 Domani, a Entità Superiori piacendo (per restare in tema), vado a discutere una certa sperimentazione. Se son rose... Poi si scrive articoli e post, si parla coi colleghi di varie scuole, davanti a un caffè. Facciamo la differenza? A livello globale direi tanto quanto il numero di scuole coinvolte comparate con le 8254 scuole d'Italia (22/8254 = 2,6 per mille), ma che si perda o che si vinca posso garantire che almeno: - non avremo perso tempo chiusi in casa a piangere sul software versato - ci saremo divertiti a giocare questa partita, in squadra con chi ci andava a genio Io mi diverto ancora, nonostante sia ormai parecchio "vintage" (come dice mia figlia). Quindi, il pessimismo lo tengo in caldo per tempi migliori, che adesso c'è da spicciare un paio di tecnologie GAFAM. 😉 Buon weekend, Stefano

July 4, 2024

Re: [nexa] Didattica a distanza, l’84% degli studenti è più sicuro e con voti migliori.

by Andrea Trentini

On 04/07/2024 18:11, Damiano Verzulli wrote: > temo di *NON* riuscire a *NON* apparire antipatico, saccente, presuntuoso.... perché?!? a me sembra che (sotto) dici cose supercondivisibili, non ti interpreto come tale > Cio' premesso, *SU QUESTA LISTA*, scelgo di scriverlo ugualmente: > ... > *NON* ditemi/diteci di quali problemi "soffre" la scuola (mi riferisco a quelli ICT). A tutti noi > (me incluso) sono chiari. A chi piu', a chi meno... ma, ripeto, QUI, sono chiari. > > ....cosi' come a molti di noi è chiaro che --alla scala di noi "singoli", tecnici-ICT-esperti > inclusi-- il tema *NON* ammette una soluzione (nessuno di noi, singolarmente, è capace di ottenere > risultati anche dell'ordine di epsilon, sia con approcci trancianti, sia con approcci diplomatici - > lo scrivo da genitori di due figli ancora coinvolti nella scuola dell'obbligo). anche su scala un po' maggiore, non vedo tendenze auspicabili > Se abbiamo ancora capacita' di CPU, spendiamola per proporre qualcosa (non so "cosa"; non ne ho > proprio idea) che faccia rifletterci con l'obiettivo di provare a migliorare il mondo che verra'... > Io mi rifiuto di credere che, alla scala NEXA, non si riesca a fare nulla... nel mio piccolo cerco di abbassare il `gap interattivo` che si "alza" di solito tra studenti e docenti... (i.e. rispondo *rapidamente* alle mail o su telegram, non mi offendo se mi danno del "tu", ecc.) ma cose più "ad ampio respiro" le ho abbandonate dopo che tanti anni fa venni deriso (da un collega, durante un Consiglio di Dipartimento) quando proposi di istituire/organizzare dei brevi corsi di Public Speaking per i nostri studenti già allora (MOLTO prima della pandemia) largamente incapaci di esprimersi in pubblico: "non sono cose da informatici!" fu il senso della sua risposta. -- Andrea Trentini ⠠⠵ http://atrent.it public key ID: 0xA7A91E3B Dip.to di Informatica Università degli Studi di Milano

July 4, 2024