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"I started to feel that propaganda had fundamentally changed. The types of actors who could create it and spread it had shifted, and the impact it was having on our society was quite significant, but we weren't using the word. We were using words like "misinformation" or "disinformation", which seemed to be misdiagnoses of the problem. And so I wanted to write a book that asked, in this media ecosystem, what does propaganda look like?"

"This election is the first time we face the danger of post-ChatGPT AI in a high-stakes sociopolitical scenario. That is new. Bots pass the Turing test (which means they write and speak indistinguishably from real people). They're also more persuasive. Image and video generators can make realistic faces, which people use mostly to make jokes but also to plant doubt. We will eventually adapt to perception-altering algorithms but for now, they're a big unsolved problem. Here are five ways the bad guys can weaponize AI to influence the US democratic election."

"Jobhunters flood recruiters with AI-generated CVs About half of applicants are using tools such as ChatGPT to help write cover letters but, without editing, the language is 'clunky'"

"Writing in the journal Science, Summerfield and colleagues from Google DeepMind report how they built the "Habermas Machine" - an AI system named after the German philosopher Jürgen Habermas. The system works by taking written views of individuals within a group and using them to generate a set of group statements designed to be acceptable to all. Group members can then rate these statements, a process that not only trains the system but allows the statement with the greatest endorsement to be selected."

""An emotionally intelligent human does not usually claim they can accurately put a label on everything everyone says and tell you this person is currently feeling 80% angry, 18% fearful, and 2% sad," says Edward B Kang, an assistant professor at New York University writing about the intersection of AI and sound. "In fact, that sounds to me like the opposite of what an emotionally intelligent person would say." Adding to this is the notorious problem of AI bias. "Your algorithms are only as good as the training material," Barrett says. "And if your training material is biased in some way, then you are enshrining that bias in code.""

"Recent experiments suggest AI peer reviews tend to be surprisingly good, with 82.4% of scientists finding AI peer reviews more useful than at least some of the human reviews they received from on a paper, and other work suggests AI is reasonably good at spotting errors, though not as good as humans, yet. Regardless of how good AI gets, the scientific publishing system was not made to support AI writers writing to AI reviews for AI opinions for papers later summarized by AI. The system is going to break."

"'Fredbot' is one example of a technology known as chatbots of the dead, chatbots designed to speak in the voice of specific deceased people. Other examples are plentiful: in 2016, Eugenia Kuyda built a chatbot from the text messages of her friend Roman Mazurenko, who was killed in a traffic accident. The first Roman Bot, like Fredbot, was selective, but later versions were generative, meaning they generated novel responses that reflected Mazurenko's voice. In 2020, the musician and artist Laurie Anderson used a corpus of writing and lyrics from her late husband, Velvet Underground's co-founder Lou Reed, to create a generative program she interacted with as a creative collaborator. And in 2021, the journalist James Vlahos launched HereAfter AI, an app anyone can use to create interactive chatbots, called 'life story avatars', that are based on loved ones' memories. Today, enterprises in the business of 'reinventing remembrance' abound: Life Story AI, Project Infinite Life, Project December - the list goes on."

"In the short term, generative AI will replace a lot of people because productivity increases while demand stays the same due to inertia. In the long term, the creation of new jobs compensates for the loss of old ones, resulting in a net positive outcome for humans who leave behind jobs no one wants to do. The most important aspect of any technological revolution is the transition from before to after. Timing and location matters: older people have a harder time reinventing themselves into a new trade or craft. Poor people and poor countries have less margin to react to a wave of unemployment. Digital automation is quicker and more aggressive than physical automation because it bypasses logistical constraints-while ChatGPT can be infinitely cloned, a metallic robot cannot. Writing and painting won't die because people care about the human factor first and foremost; there are already a lot of books we can't possibly read in one lifetime so we select them as a function of who's the author. Even if you hate OpenAI and ChatGPT for being responsible for the lack of job postings, I recommend you ally with them for now; learn to use ChatGPT before it's too late to keep your options open. Companies are choosing to reduce costs over increasing output because the sectors where generative AI is useful can't artificially increase demand in parallel to productivity. (Who needs more online content?) Our generation is reasonably angry at generative AI and will bravely fight it. Still, our offspring-and theirs-will be grateful for a transformed world whose painful transformation they didn't have to endure. Certifiable human-made creative output will reduce its quantity but multiply its value in the next years because demand specific for it will grow; automation can mimic 99% of what we do but never reaches 100%. The maxim "AI won't take your job, a person using AI will; yes, you using AI will replace yourself not using it" applies more in the long term than the

"This is a broader pattern we're seeing across other fields where LLMs are being deployed. Whether it's coding, writing, design, law, or medicine, the most effective AI users are people who already have deep domain expertise. Expertise isn't obsolete; it's more important than ever-because the value isn't just in producing outputs quickly. It's in being able to vet, steer, and improve those outputs. The future of computer science education isn't about teaching less. It's about teaching differently. We still need students who can understand how software works at a fundamental level. But we also need to train them to collaborate with AI-to become fluent in prompting, reviewing, debugging, and refining AI-generated outputs. Mastering this hybrid skillset will be critical not just for engineers, but for anyone hoping to thrive in a world where knowledge work is increasingly AI-augmented. Practically speaking, AI could dramatically lower the barrier to entry for students. When I was in high school, it would take months (if not years) of training in CS before you could create a game or app that was genuinely cool to people that aren't inherently curious and nerdy."

"When employees at meta started developing their flagship AI model, Llama 3, they faced a simple ethical question. The program would need to be trained on a huge amount of high-quality writing to be competitive with products such as ChatGPT, and acquiring all of that text legally could take time. Should they just pirate it instead?"

"computer programs can accelerate discovery in the sciences faster than scientists can, if the computer is trained to behave like one"

"These experiments in computational creativity are enabled by the dramatic advances in deep learning over the past decade. Deep learning has several key advantages for creative pursuits. For starters, it's extremely flexible, and it's relatively easy to train deep-learning systems (which we call models) to take on a wide variety of tasks."

"Commentary: Our emails are getting more impolite and that might be a problem Although some choose to dive into their content immediately, starting your emails with an opening greeting could raise the chances of them being read, says the Financial Times' Pilita Clark."

"The combination of ChatGPT with its Wolfram plug-in just scored 96% in a UK Maths A-level paper, the exam taken at the end of school, as a crucial metric for university entrance. (That compares to 43% for ChatGPT alone). If this doesn't shock you, it should. Maths A-level (like its equivalent in many other countries) is held up as the required and essential qualification for much of our populations-the way to be prepared for our upcoming AI age. And yet, here it is, done by those very AIs, better than most of our students."

"The reported ownership of LLM group's essays in the interviews was low. The Search Engine group had strong ownership, but lesser than the Brain-only group. The LLM group also fell behind in their ability to quote from the essays they wrote just minutes prior. As the educational impact of LLM use only begins to settle with the general population, in this preliminary study we demonstrate the pressing matter to explore further any potential changes in learning skills based on the results of our study. "