Any statement regarding the potential benefits and/or hazards of AI tends to be automatically very divisive and controversial as the world tries to figure out what the technology means to them, and how to make the most money off it in the process. Either meaning Artificial Inference or Artificial Intelligence depending on who you ask, AI has seen itself used mostly as a way to ‘assist’ people. Whether in the form of a chat client to answer casual questions, or to generate articles, images and code, its proponents claim that it’ll make workers more efficient and remove tedium.

In a recent paper published by researchers at Microsoft and Carnegie Mellon University (CMU) the findings from a survey are however that the effect is mostly negative. The general conclusion is that by forcing people to rely on external tools for basic tasks, they become less capable and prepared of doing such things themselves, should the need arise. A related example is provided by Emanuel Maiberg in his commentary on this study when he notes how simple things like memorizing phone numbers and routes within a city are deemed irrelevant, but what if you end up without a working smartphone?

Does so-called generative AI (GAI) turn workers into monkeys who mindlessly regurgitate whatever falls out of the Magic Machine, or is there true potential for removing tedium and increasing productivity?

The Survey

In this survey, 319 knowledge workers were asked about how they use GAI in their job and how they perceive GAI usage. They were asked how they evaluate the output from tools like ChatGPT and DALL-E, as well as how confident they were about completing these same tasks without GAI. Specifically there were two research questions:

1. When and how do knowledge workers know that they are performing critical thinking when using GAI?
2. When and why do they perceive increased/decreased need for critical thinking due to GAI?

Obviously, the main thing to define here is the term ‘critical thinking‘. In the survey’s context of creating products like code, marketing material and similar that has to be assessed for correctness and applicability (i.e. meeting the requirements), critical thinking mostly means reading the GAI-produced text, analyzing a generated image and testing generated code for correctness prior to signing off on it.

The first research question was often answered by those partaking in a way that suggests that critical thought was inversely correlated with how trivial the task was thought to be, and directly correlated to the potential negative repercussions of flaws. Another potential issue appeared here where some participants indicated accepting GAI responses which were outside that person’s domain knowledge, yet often lacking the means or motivation to verify claims.

The second question got a bit more of a diverse response, mostly depending on the kind of usage scenario. Although many participants indicated a reduced need for critical thinking, it was generally noted that GAI responses cannot be trusted and have to be verified, edited and often adjusted with more queries to the GAI system.
Distribution of perceived effort when using a GAI tool. (Credit: Hao-Ping Lee et al., 2025)
Of note is that this is about the participant’s perception, not about any objective measure of efficiency or accuracy. An important factor the study authors identify is that of self-confidence, with less self-confidence resulting in the person relying more on the GAI to be correct. Considering that text generated by a GAI is well-known to do the LLM equivalent of begging the question, alongside a healthy dose of bull excrement disguised as forceful confidence and bluster, this is not a good combination.

It is this reduced self-confidence and corresponding increase in trust in the AI that also reduces critical thinking. Effectively, the less the workers know about the topic, and/or the less they care about verifying the GAI tool output, the worse the outcome is likely to be. On top of this comes that the use of GAI tools tends to shift the worker’s activity from information gathering to information verification, as well as from problem-solving to AI-output integration. Effectively the knowledge worker thus becomes more of a GAI quality assurance worker.

Essentially Automation

Baltic Aviation Academy Airbus B737 Full Flight Simulator (FFS) in Vilnius (Credit: Baltic Aviation Academy)
The thing about GAI and its potential impacts on the human workforce is that these concerns are not nearly as new as some may think it is. In the field of commercial aviation, for example, there has been a strong push for many decades now to increase the level of automation. Over this timespan we have seen airplanes change from purely manual flying to today’s glass cockpits, with autopilots, integrated checklists and the ability to land autonomously if given an ILS beacon to lock onto.

While this managed to shrink the required crew to fly an airplane by dropping positions such as the flight engineer, it changed the task load of the pilots from actively flying the airplane to monitoring the autopilot for most of the flight. The disastrous outcome of this arrangement became clear in June of 2009 when Air France Flight 447 (AF447) suffered blocked pitot tubes due to ice formation while over the Atlantic Ocean. When the autopilot subsequently disconnected, the airplane was in a stable configuration, yet within a few minutes the pilot flying had managed to put the airplane into a fatal stall.

Ultimately the AF447 accident report concluded that the crew had not been properly trained to deal with a situation like this, leading to them not identifying the root cause (i.e. blocked pitot tubes) and making inappropriate control inputs. Along with the poor training, issues such as the misleading stopping and restarting of the stall alarm and unclear indication of inconsistent airspeed readings (due to the pitot tubes) helped to turn an opportunity for clear, critical thinking into complete chaos and bewilderment.

The bitter lesson from AF447 was that as good as automation can be, as long as you have a human in the loop, you should always train that human to be ready to replace said automation when it (inevitably) fails. While not all situations are as critical as flying a commercial airliner, the same warnings about preparedness and complacency apply in any situation where automation of any type is added.

Not Intelligence

A nice way to summarize GAI is perhaps that they’re complex tools that can be very useful but at the same time are dumber than a brick. Since these are based around probability models which essentially extrapolate from the input query, there is no reasoning or understanding involved. The intelligence bit is the one ingredient that still has to be provided by the human intelligence that sits in front of the computer. Whether it’s analyzing a generated image to see that it does in fact show the requested things, criticizing a generated text for style and accuracy, or scrutinizing generated code for accuracy and lack of bugs, these are purely human tasks without substitution.

We have seen in the past few years how relying on GAI tends to get into trouble, ranging from lawyers who don’t bother to validate (fake) cited cases in a generated legal text, to programmers who end up with 41% more bugs courtesy of generated code. Of course in the latter case we have seen enough criticisms of e.g. Microsoft’s GitHub Copilot back when it first launched to be anything but surprised.

In this context this recent survey isn’t too surprising. Although GAI tools are just that, like any tool you have to properly understand them to use them safely. Since we know at this point that accuracy isn’t their strong suit, that chat bots like ChatGPT in particular have been programmed to be pleasant and eager to please at the cost of their (already low) accuracy, and that GAI generated images tend to be full of (hilarious) glitches, the one conclusion one should not draw here is that it is fine to rely on GAI.

Before ChatGPT and kin, we programmers would use forums and sites like StackOverflow to copy code snippets for. This was a habit which would introduce many fledging programmers to the old adage of ‘trust, but verify’. If you cannot blindly trust a bit of complicated looking code pilfered from StackOverflow or GitHub, why would you roll with whatever ChatGPT or GitHub Copilot churns out?

hackaday.com/2025/02/13/why-ai…

There are a wide range of typing tutors out there that will educate you in the glorious skill of touch-typing. Many just focus on the basics, ranking you on accuracy and speed. However, there’s a nifty little online tutor that can help you with one skill specifically—it’s aim is to teach you to use the Shift keys “properly.”

The tutor is the work of [KaarelP2rtel]. The unnamed tool is intended to guide you into instinctively using both the left and right Shift keys as you type. Many typers default to using one or the other. This can lead to fumbles and slowdown when one hand is trying to hit both the Shift key and a letter.

[KaarelP2rtel]’s belief is that the “correct” method is to press the Shift key with the opposite hand to the one typing the letter, and this typing tutor enforces that practice. You must type repeated capitalized words one after the other, and you’ll only progress quickly if you’re hitting the opposite Shift key each time. Unconventional keyboardists fear not—you can convert the tool to work with Dvorak or Colemak layouts if necessary.

Is this a crucial tool for the fast typist? The jury’s out on that one. It’s entirely possible to hit in excess of 120 wpm without this technique for most normal passages of text, using dynamic finger reassignments when hitting Shift with the same hand. Still, the diligent may find it a useful upgrade to their existing typing abilities.

Source code is on GitHub for the curious. Notably, it’s a very small website that weighs in at just a few kilobytes; it would be a rather fitting part of the Small Web, which we’ve explored before!

hackaday.com/2025/02/13/tiny-t…

di Leonhard Dobusch

Testo originale:
moment.at/story/apple-google-m…

Distribuito con licenza Creative Commons BY 4.0

Quando autocrati come Donald Trump prendono il potere, le istituzioni, le aziende e le organizzazioni della società civile non possono semplicemente continuare come prima. Quello in cui Google e Apple sbagliano, l'organizzazione no-profit Wikipedia riesce a fare meglio. Un commento di Leonhard Dobusch.

Il nome che da 500 anni viene dato al mare tra la costa meridionale degli Stati Uniti, il Messico e Cuba sembra essere uno dei problemi più importanti degli Stati Uniti. O almeno, così si potrebbe pensare. Perché uno dei primi atti di Donald Trump nel suo secondo mandato è stato quello di rinominarlo. Con un decreto, ha fatto rinominare il “Golfo del Messico” in “Golfo d'America”, secondo l'interpretazione ufficiale del governo statunitense.

Google e Apple rinominano il Golfo del Messico

In primo luogo, la “cambio di nome” è ovviamente un atto altamente simbolico che risponde a riflessi nazionalistici. Fa parte della strategia Flood-the-zone-with-shit-Strategie (Inonda il campo di merda) della nuova destra di Trump & Co. Ma è più di uno stupido scherzo, più di un semplice simbolo. Il cambio di nome costringe gli altri a relazionarsi con Trump.

Questo pone un problema ai produttori di mappe mondiali. Il mare deve essere chiamato come Trump lo immagina o come il resto del mondo e la maggioranza delle persone lo conoscono da secoli? I giganti della tecnologia statunitensi, Google e Apple, hanno deciso: si allineano ai rispettivi governi del paese - in questo caso anche a Trump. Negli Stati Uniti, questo è l'unico nome che utilizzano nei loro servizi di mappe. Ma nella versione in lingua tedesca di Google Maps, il “Golfo del Messico” è stato recentemente etichettato anche come “Golfo d'America”.

La propaganda autocratica non è normale

Quanto più assurda è l’azione di autocrati come Trump, tanto più forte è se gli altri potenti coinvolti si comportano come se questo fosse normale, come se si trattasse di faccende quotidiane. Questo è esattamente ciò che hanno fatto Google e Apple. Lutz Mache, responsabile degli affari governativi e delle politiche pubbliche di Google, ha risposto alle critiche sull’immsdiato cambio di nome di Google Maps: “In questo caso viene rispettata la legge in vigore. Nulla di più, nulla di meno”.

Inoltre, Mache ha citato una dichiarazione ufficiale (naturalmente su X-Twitter, dove se no?) in cui Google fa riferimento alla “prassi di lunga data” di adottare i cambiamenti di nome se sono stati modificati in fonti governative ufficiali (negli Stati Uniti si tratta del “Geographic Names Information System” (GNIS)). Può darsi che sia così, ma tale consuetudine non è una legge. E finché il GNIS non è stato usato impropriamente per la propaganda nazionalistica del governo, non è stato un problema.

Ma se i politici autoritari abusano delle istituzioni statali per scopi propagandistici, allora anche l'abitudine di continuare a fidarsi ciecamente di queste istituzioni deve essere messa in discussione.

Senza resistenza, gli autocrati vanno sempre più lontano

Questo è importante perché tutto ciò che funziona senza resistenza è visto dagli autocrati come un invito a mettere una marcia in più. È così anche in questo caso: un deputato repubblicano ha presentato una mozione per rinominare la Groenlandia “Red, White and Blueland”.

Ci sono certamente delle alternative a questa reazione. Wikipedia, ad esempio, non solo è più resistente alla disinformazione rispetto alle piattaforme orientate al profitto, ma anche agli interventi propagandistici delle forze autoritarie.

Wikipedia è più resistente

Nella Wikipedia in lingua inglese, il “Golfo del Messico” viene ancora chiamato così. Il motivo è da ricercare nelle convenzioni di denominazione di Wikipedia: ciò che conta è il modo in cui ci si riferisce prevalentemente a un luogo, non come qualcuno pensa che debba essere chiamato.

È quindi giunto il momento che Google riconsideri la sua “prassi consolidata”. Perché non adottare semplicemente i termini geografici di Wikipedia? In ogni caso, il tempo del “Business as usual” è finito. Questa non è un’esercitazione.

Leonhard Dobusch è docente di Organizzazione all’università di Innsbruck, cofondatore di Momentum-Institut e Momentum-Magazin.
@Leonido
#GAFAM #mappe #USA #Trump #Wikipedia #imperialismo #traduzioni
@Informa Pirata

"Se non è prassi comune consultare i bambini sulla loro vita, allora, nelle poche occasioni in cui li consultiamo, non dovremmo essere troppo sorpresi di sentirci dire “non lo so”. La generazione del sapere e la capacità di articolare questo sapere sono sicuramente il prodotto di processi interattivi."

connessioni.cmtf.it/le-scuole-…

Le scuole come comunità di riconoscimento. Una conversazione con Michael White (parte 2)

di Christopher McLean Traduzione di Enrico Valtellina

^{Connessioni Web}

In all likelihood, asteroid 2024 YR4 will slip silently past the Earth. Based on the data we have so far, there’s an estimated chance of only 2.1% to 2.3% that it will collide with the planet on December 22nd, 2032. Under normal circumstances, if somebody told you there was a roughly 98% chance of something not happening, you probably wouldn’t give it a second thought. There’s certainly a case to be made that you should feel that way in regards to this particular event — frankly, it’s a lot more likely that some other terrible thing is going to happen to you in the next eight years than it is an asteroid is going to ruin your Christmas party.

That being said, when you consider the scale of the cosmos, a 2+% chance of getting hit is enough to raise some eyebrows. After all, it’s the highest likelihood of an asteroid impact that we’re currently aware of. It’s also troubling that the number has only gone up as further observations of 2024 YR4’s obit have been made; a few weeks ago, the impact probability was just 1%. Accordingly, NASA has recently announced they’ll be making time in the James Webb Space Telescope’s busy scientific schedule to observe the asteroid next month.

So keeping in mind that we’re still talking about an event that’s statistically unlikely to actually occur, let’s take a look at what we know about 2024 YR4, and how further study and analysis can give us a better idea of what kind of threat we’re dealing with.

An Unexpected Visitor

Officially, 2024 YR4 was discovered on December 27th, 2004 by the Asteroid Terrestrial-impact Last Alert System (ATLAS), but by that time we had already dodged a potential impact. It turns out that the asteroid had come within 828,800 kilometers (515,000 miles), or around two times the distance from the Earth to the Moon, on December 25th without anyone realizing.
2024 YR4’s Orbit (Gray)
All of the observations of the asteroid made since its discovery have therefore been made while the object is moving away from the planet and back into deep space. This is a less than ideal situation when you consider that the asteroid is estimated to be between 40 to 90 meters (130 to 300 ft) in diameter.

With each passing day, it becomes more difficult to track and resolve 2024 YR4, and it’s currently estimated that observing it with ground-based telescopes will no longer be possible beyond April.

That is, until 2028. As you might have put together by now, 2024 YR4 is in such an orbit that it comes within close proximity of Earth every four years. If current orbital projections hold true, during the summer of 2028, the asteroid will be close enough again that we can observe it on the way towards us.

That will include a fly-by of Earth in early December before it swings back out of range. Hopefully by that time we’ll have collected enough data to know whether or not we’ll need to brace for impact the next time it swings by our neighborhood.

Deflect, or Evacuate?

As far as potentially dangerous Near Earth Objects (NEOs) go, 2024 YR4 is about as ideal as they get. While it did sneak up on us in 2024, now we know it’s on a fairly predictable schedule and there’s enough time that we could actually do something about it if the chance of impact gets high enough to take it more seriously. In 2028, we’ve even got a chance to deflect it as it zooms past Earth.

That would have been science fiction a few years ago, but after NASA’s successful DART demonstration mission, we now know it’s possible to significantly alter the orbit of an asteroid simply by ramming a spacecraft into it at high velocity. The target asteroid in that test was much larger than 2024 YR4, with a diameter of 177 meters (581 ft). Yet the head-on impact of the 500 kg (1,100 lb) DART spacecraft was able to slow it down enough to make a noticeable change in its orbit.

Given how close 2024 YR4 would be passing by Earth, it’s not hard to imagine that a spacecraft with several times the mass of DART could be put on a collision course with the asteroid in 2028. Even if such an impact would not be enough to entirely prevent a collision with 2024 YR4, if applied carefully, it could certainly be sufficient to move the calculated point of impact.
Potential 2032 Impact Corridor
But would such a mission even be necessary? Current estimates put around half of the potential impact points for 2024 YR4 over the ocean. Even where the path of the asteroid does cross over land, most of it is sparsely populated. The biggest risks to human life would be in Nigeria and India, but the chances of a direct hit over either area is particularly remote, especially given the estimated blast radius of 50 km (31 miles).

Unless updated orbital data for 2024 YR4 indicates that it’s going to directly impact one of these densely populated areas, the most cost effective approach may be to simply move as many people out of the impact area as possible. While an evacuation of this scale would still be a monumental task, we’d at least have several years to implement the plan.

Bringing Out the Big Guns

While the chances are still excellent that 2024 YR4 will zip harmlessly past our Blue Marble in 2032, it’s not outside the realm of possibility that some big decisions might need to be made in the next few years. So how do we figure out how large of a threat this asteroid really is before it’s too late?

That’s where advanced space-bound observatories like the James Webb Space Telescope (JWST) come in. While our instruments on Earth soon won’t be able to see 2024 YR4, the JWST will not only be able to keep its gaze on the asteroid for longer, but the infrared observatory is uniquely suited for capturing critical data about its size and shape.

Up to this point, the size of 2024 YR4 has been estimated based on its visible appearance, but that can be misleading. It could be that only part of the asteroid is reflective, which would give the impression that its smaller than it actually is. But the JWST doesn’t rely on visible light, and instead can use its IR instruments to detect the heat being given off by the asteroid’s rocky surface.

With definitive data about the asteroid’s size, shape, and rotation, astronomers will be able to better model how 2024 YR4 is moving through space. That’s going to be key to figuring out whether or not that 2.3% chance of impact is going to go up or down — and if it does go up, will help narrow down exactly where the asteroid is likely to hit.

hackaday.com/2025/02/13/nasa-t…

Di Michael White conosciamo il contributo a un modo di lavorare insieme ai bambini rendendoli protagonisti o, per dirla con la metafora narrativa, narratori in prima persona.
Qui parla a lungo di situazioni di “abuso tra pari”, o, come usiamo dire abitualmente, comportamenti di bullismo.

connessioni.cmtf.it/le-scuole-…

Le scuole come comunità di riconoscimento. Una conversazione con Michael White (parte 1)

di Christopher McLean Traduzione di Enrico Valtellina

^{Connessioni Web}

- Fernando Pessoa – Poesia di Álvaro de Campos – Adelphi 1993 - 6€
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- Pier Paolo Pasolini – La nuova gioventù – Einaudi 1981 - 8€
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- Sandro Penna – Poesie – Garzanti 1973 - 9€
- Umberto Piersanti – I luoghi persi – Einaudi 1994 - 9€
- Wislawa Szymborska – La fine e l’inizio – Scheiwiller 1997 - 8€
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- Abbas Kiarostami – Un lupo in agguato. Poesie – Einaudi 2003 - 9€

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