AI, università, lezioni ed esami.
I have a colleague who has completely embraced A.I. My understanding is that his course is much harder than it used to be, but students are allowed to use A.I. during exams. I see the motivation—A.I. is supposed to enhance our skills/productivity, so students should be expected to produce more—but I don’t want to create a situation where students are helplessly dependent on A.I. because they don’t have a solid grasp of the fundamentals.
AI come l’autocorrezione del nostro telefono.
I’ll say that the computing speed of today’s devices is fast enough to trick some people into thinking that such devices are doing more than just performing calculations. But this ‘understanding’ and ‘learning’ and ‘communicating’ are just a faster and sometimes more efficient autocorrect. Yes, the autocorrect you have on your phones and tablets and personal computers.
When you’re typing a message and you see your phone’s OS correctly suggesting the next word after the one you’re typing, that’s not intelligence. The phone doesn’t ‘get’ you. The phone doesn’t ‘know’ you. The system is making a prediction by calculating probabilities. The data sample it’s using for this prediction is everything you’ve typed on the phone since you bought it.
È una questione di calcolo, di computazione:
By the way, Large Language Models don’t even see those as words, but numbers, tokens.
It wasn’t artificial intelligence, it was computers that computed. It’s always been computers computing. We have more refined tools today, but that’s it.
Con l’AI stiamo assistendo all’ennesimo giro dello stesso ciclo: accesso facile, poi un nuovo soffitto sopra chi sa usarlo davvero.
Design tools followed the same arc. Figma lowered the floor of UI design — suddenly, anyone could open a canvas and move elements around. Design systems lowered it again. Templates lowered it further. Each step made the starting point more accessible. And each step produced a new professional layer above it — people who understood not just where the buttons were, but what they were actually for.
Sull’idea che "ciò che si vede è ciò che esiste".
The boom and recognition of information design, though, has not improved significantly the public understanding of design and data, of their specific qualities. Particularly, the implications of their constructed and interpretive – and potentially misleading – nature have received little attention. The assumption that “what you see is what is there” has remained dominant. Practitioners, for their part, have done little to shake it, generally aligning – implicitly or explicitly – with the idea that data and design are objective and transparent, and mostly focusing, in their discussion of information design, on usability or formal issues (Hall, 2011).
Sulle istruzioni agli agenti AI
Collaborative steering doesn't mean dumping every possible bit of design or development context into agent instructions. It's being precise about what matters because with AI agents today, the more you pile in, the less useful it gets.
And that's where expertise kicks in. Knowing the three to five things that actually matter, in what order, and how they need to be done, is the value add. It's the part you can't fake by playing a role you never trained for. And it's the part worth encoding for everyone else.
Un estratto di un intervento di Michael Bierut a Design Indaba dal titolo "How to Think Like a Designer".
No one secretly wants a new logo. They all want someone else's logo, or they want their old logo back.
(L’estratto viene da Daily Designer, un progetto di Arun Venkatesan, dove si raccolgono cose dette da noti e famosi designer.)
I CEO alle prese con il vibe-coding.
“Why don’t we just do what I did here?” is demoralizing. I get why you’re frustrated. Nothing seems to get done, regardless of all these wondrous advancements in AI. It trivializes all the actual work that needs to get done to produce something real and reliable. It dismisses people’s expertise and skills. You also don’t look good—you even look just a little worse.
Tra le tante cose che un browser riesce a intercettare del dispositivo che stai utilizzando c’è anche il livello di batteria.
Your browser kept your battery level back. Firefox removed this API entirely in 2016, after researchers proved it could be used to track a visitor across websites without cookies, without consent. The API still exists in the specification. It was simply hidden — from you, and from any page that might ask after it.
Anil Dash sulla NASA che usa ancora Flickr come archivio pubblico per le sue immagini.
The beautiful thing about communities and platforms like Flickr is that they remind us that not everything on the internet has to be ephemeral, not everything on the web has to be hyper-commercial. Sometimes a bunch of decent people can do a good thing for the right reasons, and the result of that work can persevere for decades.
Il design delle piattaforme può indirizzare il nostro uso di esse, ma se siamo frustrati ci passiamo più tempo. Se abbiamo impegni e passioni facciamo altro. Ma per avere impegni e passioni dobbiamo avere il tempo e le risorse culturali, economiche e sociali per coltivarle.
Viviamo in una condizione di stress persistente — lavorativo, economico, esistenziale — che il capitalismo contemporaneo produce quotidianamente e per la quale cerchiamo sollievo momentaneo nello scrolling, esattamente come le generazioni precedenti cercavano sollievo nella televisione spazzatura. Il design della piattaforma conta, certo, ma conta meno delle condizioni materiali di vita.
Your inability to focus isn’t a moral failing. It’s a design problem. You’re trying to think in environments built to prevent thinking. You’re trying to sustain attention in spaces engineered to shatter it. You’re fighting algorithms explicitly optimised to keep you scrolling, not learning.
The solution isn’t discipline. It’s architecture. Build different defaults. Create different spaces. Establish different rhythms. Make depth as easy as distraction currently is. Make thinking feel as natural as scrolling currently does.
Sul “mestiere” e sul design.
No knowledge I possess about design—the incorporeal understanding that makes what I create better than an off-the-shelf template or something done by someone without my experience—is made irrelevant by AI. Nor is it contradicted by my use of AI tools.
Structure still communicates before content. Visual hierarchy still guides attention. Negative space still creates rhythm. These principles don’t vanish because I’m working through AI rather than directly manipulating pixels.
The craft migrates to a different level of abstraction. But it remains craft.
Riflessioni sul graphic design, e non solo, di Silvio Lorusso.
The promise of simplification is to maintain, or even increase, semantic depth through synthesis. When synthesis is missing, what you get is blandness.
L’articolo di presentazione del nuovo font della fonderia Mass-Driver, MD UI.
When we think about reading, we tend to picture books, or magazines, or business reports. Blocks of text, traversed from beginning to end. There’s another kind of reading, though, one which I think we do much more often without really noticing it.
It’s a kind of instantaneous scanning of a word or two at a time: the hour on a smartwatch, or the label on microwave dial, or the URL in your web browser. I like to call this interfacing, because it’s less about digesting information (or experiencing the text) than about interacting with your immediate surroundings. You don’t think of it as reading at all — it just happens.
Il futuro della programmazione, in questo interessante articolo del New York Times.
But if coders are more upbeat, it's because their encounters with A.I. are diametrically opposite to what's happening in many other occupations, says Anil Dash, a friend of mine who is a longtime programmer and tech executive. "The reason that tech generally — and coders in particular — see L.L.M.s differently than everyone else is that in the creative disciplines, L.L.M.s take away the most soulful human parts of the work and leave the drudgery to you," Dash says. "And in coding, L.L.M.s take away the drudgery and leave the human, soulful parts to you."
Il paradosso di Jevons, quando qualcosa costa meno farlo, ne facciamo di più. E paghiamo meno chi lo fa.
When something gets cheaper to do, we don't just pocket the savings — we do more of it. Though it could also be that these software jobs won't pay as well as in the past, because, of course, the jobs aren't as hard as they used to be. Acquiring the skills isn't as challenging.