Marco Camisani Calzolari - Professor of Digital Languages, IULM University - CEO @ Speakage & Founder DigitalGround UK

Articoli

• 243 – The Whole Truth About AI and Water Consumption

  4 marzo, di Team — Artificial Decisions
  The Whole Truth About AI and Water Consumption In Texas, in 2025, data centers used about 90 billion liters of water, including cooling and water linked to electricity production. By 2030, estimates reach up to 600 billion liters per year. In just a few years, Artificial Intelligence is competing with agriculture, cities, and industry. Computing systems generate heat. Heat must be removed. Some data centers can use up to 1.5 million liters of water per day just for cooling. You might think: water evaporates and comes back as rain. So what is the problem? Water returns, but not where it is needed and not when it is needed. A data center draws fresh water from a local basin. Part of it evaporates and leaves that territory. It may fall elsewhere, even over the ocean, or months later. Meanwhile, the local community has less water available, often during the hottest weeks, when demand is already high. There is another issue. Demand grows fast. Water recharge is slow. Aquifers are not infinite. If withdrawals exceed natural recharge, water levels drop, wells go deeper, costs rise, drought risks increase. A global water cycle does not fix a local shortage created in a few years. There is also indirect water use. Electricity production often consumes water. That indirect share can represent up to 75% of the total footprint. The data center reports one number. The energy-producing region carries another, often larger, burden. AI infrastructure expands where land and energy are cheaper and permits move faster. These areas are often already exposed to heat and water stress. Multiply that pattern across regions and the pressure on local water systems increases. Water does not disappear. Availability, in the right place at the right time, becomes scarcer. What do you think? #ArtificialDecisions #MCC

• 240 – Warning, They Can Know Where You Are in Real Time. How to Protect Yourself

  1 marzo, di Team — Artificial Decisions
  Warning, They Can Know Where You Are in Real Time. How to Protect Yourself All it takes is an AirTag placed in your bag for anyone to know where you are, in real time, without you noticing. This part is well known. iPhones alert you automatically if an AirTag that is not yours is following you. But if you have an Android phone, nobody warns you. Here is what you need to do to stop anyone from spying on your location. Roughly 70 percent of smartphones run Android. Most people are exposed and have no idea. AirTags work through a network of nearly two billion Apple devices worldwide. Every iPhone that passes near an AirTag silently updates its position, even if that iPhone is not yours. Someone just needs to walk past you. Great for finding lost keys, but unfortunately also great for following a person without them knowing. On iPhone protection is automatic. If an AirTag that is not yours follows you, you get a notification, no setup needed: "Watch out, there is an AirTag that is not yours following you." On Android alerts exist, but they only work if you do not have an old phone and if you have Google Play Services updated. If you do not, nobody warns you. And even when it works, independent tests show that detection is slower and less reliable. You could be followed for hours before anything warns you. If it warns you at all. To help protect you, AirTags have a small speaker that makes a sound after several hours if separated from their owner. A signal to notice something strange in your bag. The problem is that a small hole drilled under the battery disconnects the speaker. No more sound. No more warning. And these modified AirTags are already being sold ready to use on eBay. How to protect yourself: if you have Android, go into settings and search for "unknown tracker alerts." Make sure it is on. Download AirGuard, free, open source, built by a German university, no commercial interest. It scans in the background and alerts you if something is following you. Apple and Google are working together on a shared standard called DULT for detecting unwanted trackers. The direction is right. But the problem exists right now. iPhone users are mostly covered. Android users: settings, "unknown tracker alerts," turn it on. And install AirGuard. #ArtificialDecisions #MCC

• 237 – Why AI Hallucinations Are Causing Real Damage

  26 febbraio, di Team — Artificial Decisions
  Why AI Hallucinations Are Causing Real Damage and We Don't Notice Artificial Intelligence hallucinations cause damage because they end up inside decisions. We ask a question, we get an answer that looks clean, organized, confident. We read it fast, paste it into a document, forward it. The damage starts there. The mistake is usually in the details, and details are what people check the least: a number with the comma in the wrong place, a date, an agency name, a deadline, a rule that is real but applied to the wrong place. The text still sounds credible, so the error stays. At work it happens like this. We ask for market growth, user counts, a percentage to use. We get a precise-looking number with a neat explanation. It goes into a report, then a slide. Nobody opens the original source because the answer feels ready. If the number is invented or just wrong, budgets and priorities go off track, and we notice later. At home it's the same, with higher stakes. We ask about symptoms, medicines, dosages, interactions. The answer is calm and structured. One wrong detail can change what someone does. The biggest risk is the chain. A false line becomes the base for the next question. We paste it into a new prompt and the AI builds on it. The next answer feels even stronger because it has more context, but it is strengthening the first mistake. Protection is simple. Any AI answer that contains facts stays a draft until we verify a primary source ourselves: the original document, an official page, the full text. Check details first: names, dates, numbers, quotes, deadlines. When money, health, contracts, or identity are involved, decisions wait for an external check. AI can write fast, but verification stays on us. #ArtificialDecisions #MCC

• 236 – Big Tech Is Laying People Off Because of AI. What to Do to Keep Your Job

  25 febbraio, di Team — Artificial Decisions
  Big Tech Is Laying People Off Because of AI. What to Do Now to Keep Your Job In 2025, the tech sector recorded 122,549 layoffs across 257 companies. HP plans 6,000 job cuts by 2028 to move resources into Artificial Intelligence. Meta cut about 3,600 roles, Microsoft 6,000, Amazon 14,000 corporate jobs. Office work gets reduced, AI-related roles get funded. Follow me to the end, because the fix is practical. The people leaving and the people being hired are not the same. Companies cut back office, admin, content moderation, customer support. They hire ML engineers, researchers, data and security specialists. Moving from one side to the other takes time. Goldman Sachs Research estimates generative AI could reduce 6–7% of US jobs. The roles most exposed include programmers, accountants, legal assistants, customer service, and credit analysts. Tasks like writing, summarizing, classifying, and answering can be automated. So what do we do? Use AI seriously, every day, on your real work. Put it into documents, emails, processes, numbers. Track time saved and quality improved. Save examples and results so you can prove what you can do. Become the person who runs the work with AI: sets context, checks output, verifies, signs off, takes responsibility. Push your company for real training, tied to actual roles, with clear rules and a practical plan for the next 6–12 months. Tell your CEO to bring in experts and make decisions now: map where AI is already used, decide what can be sped up and what must stay human, invest in skills and tools, assign clear ownership. Tag your CEO or your manager. #ArtificialDecisions #MCC

• 235 – Altman Defends AI: “Raising a Child Costs Energy Too”

  24 febbraio, di Team — Artificial Decisions
  Altman Defends AI: "Raising a Child Costs Energy Too" Sam Altman has found a way to answer criticism about Artificial Intelligence's environmental impact: compare it to humans. Speaking at an Indian Express event during an AI summit in India, the OpenAI CEO said that training a human being for twenty years costs a lot, so the comparison with ChatGPT is fairer than it looks. But come on. A human being lives, works, creates, reproduces, contributes to society in ways no probabilistic system can replicate. Reducing a human life to a training energy cost is a rhetorical move, not a scientific comparison. On water, Altman called the 64-liter-per-query figure completely false, with no connection to reality. Google published its own numbers for Gemini queries: 0.24 watt-hours of energy and 0.26 milliliters of water. The 64-liter estimate came from a University of California study that included not just data center water but also the water used by the power plants supplying the servers, a methodology widely disputed, and the only public reference available, because companies are not required to disclose their own figures. The energy impact is real. According to the IEA, global data centers consumed around 415 terawatt-hours, about 1.5% of global electricity. Projections point to nearly double by 2030. There are no legal obligations forcing tech companies to disclose how much energy and water their data centers consume. Independent researchers build estimates from the outside. Companies can deny any figure without having to provide their own. When Altman says the 64 liters are false, he may be right. But he is asking us to trust his word on data he is not required to make public. Data centers keep pushing up electricity prices in surrounding areas. A concrete, measurable impact that no evolutionary metaphor can fix. What do you think? #ArtificialDecisions #MCC

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