Large language models display a peculiar form of inconsistency: they "know" the correct answer but fail to act on it. In human philosophy, this tension between global judgment and local impulse is called akrasia, or weakness of will. We propose akrasia as a foundational concept for analyzing inconsistency and goal drift in agentic AI systems. To operationalize it, we introduce a preliminary version of the Akrasia Benchmark, currently a structured set of prompting conditions (Baseline [B], Synonym [S], Temporal [T], and Temptation [X]) that measures when a model's local response contradicts its own prior commitments. The benchmark enables quantitative comparison of "self-control" across model families, decoding strategies, and temptation types. Beyond single-model evaluation, we outline how micro-level akrasia may compound into macro-level instability in multi-agent systems that may be interpreted as "scheming" or deliberate misalignment. By reframing inconsistency as weakness of will, this work connects agentic behavior to classical theories of agency and provides an empirical bridge between philosophy, psychology, and the emerging science of agentic AI.

Whether you're a student, a journalist, or a business professional, knowing how to do high-quality research and writing using trustworthy data and sources, without giving in to the temptation of AI or ChatGPT, is a skill worth developing. As I detail in my book Writing That Gets Noticed, locating credible databases and sources and accurately vetting information can be the difference between turning a story around quickly or getting stuck with outdated information. Since I had written about getting pregnant in my forties, I knew that as long as I updated my facts and figures, and included supportive and relevant peer-reviewed research, I could pull off this story. The story ran later that day, and it led to other assignments. Here are some tips I've learned that you should consider mastering before you turn to automated tools like generative AI to handle your writing work for you.

In a world of shifting, new technologies, how do we stay connected with one another? That's one of the questions at the heart of "Rachels Don't Run," a short film directed by the French American filmmaker Joanny Causse. The film takes place entirely in an empty office, late at night, some time in the near future. Leah (Sera Barbieri), a customer-support agent for an A.I.-companionship company called Iris, sits alone at a sparingly lit desk, monitoring calls and dealing with frustrated clients. She helps them navigate the high-tech service and fields feedback about Svetlana, Siobhan, and Rachel--a few of the various personas of artificial-intelligence companions that Iris provides.

Students at the University of Texas at Austin tell Fox News whether they know or have heard of fellow students using ChatGPT to complete class assignments. AUSTIN, Texas – A majority of college students who spoke with Fox News said they knew or had heard of fellow pupils using ChatGPT for class assignments. "Unfortunately, yes," Riley, an economics major, told Fox News. "I definitely have heard of a couple of people using it for certain things," Piper, a STEM major, said. Recent advances in artificial intelligence technologies, including ChatGPT and Google's Bard, have ignited plagiarism concerns across American schools.

As constantly and rapidly changes, many businesses find themselves unable to keep up with the advances. The reality is that digitalization promises to change the way that businesses operate, and a 2019 McKinsey Digital Quotient survey found that 93 percent of executives believe that taking advantage of digital technology is essential for accomplishing strategic goals. Digitization brings new opportunities, improves processes, expands production and many other benefits. Leaders need to work to develop the right systems, structures, and expertise to welcome digitization with open arms. Digital transformation is defined as "cultural, organizational, and operation change of an organization, industry, or ecosystem through the smart integration of digital technologies, processes, and competencies."

If your work puts you in regular contact with technology vendors, you'll have heard terms such as artificial intelligence (AI), machine learning (ML), natural language processing and computer vision before. You'll have heard that AI/ML is the future, that the boundaries of these technologies are constantly being pushed and broadened, and that AI/ML will play an integral role in shaping this tech-forward era's most successful business models. As a technology leader, I've heard all these claims and more. To say that AI/ML will play an increasingly impactful role in business is no overstatement. According to a recent Forbes article, the machine learning market is poised to more than quadruple in the coming years.

The result of the development of an application is of high and demonstrable value to the organization. The more concrete the benefits can be, the easier it is to justify the application. Be prepared to sacrifice technical elegance for utility. There is a considerable temptation by those who have read the more optimistic stories about AI to assume that it can do things beyond the capability of a skilled human. Yielding to such temptation is sure to be a disaster!

The contest between China and America, the world's two superpowers, has many dimensions, from skirmishes over steel quotas to squabbles over student visas. Both countries are investing large sums in militarised artificial intelligence (ai), from autonomous robots to software that gives generals rapid tactical advice in the heat of battle. China frets that America has an edge thanks to the breakthroughs of Western companies, such as their successes in sophisticated strategy games. America fears that China's autocrats have free access to copious data and can enlist local tech firms on national service. Neither side wants to fall behind.

THE CONTEST between China and America, the world's two superpowers, has many dimensions, from skirmishes over steel quotas to squabbles over student visas. Both countries are investing large sums in militarised artificial intelligence (AI), from autonomous robots to software that gives generals rapid tactical advice in the heat of battle. China frets that America has an edge thanks to the breakthroughs of Western companies, such as their successes in sophisticated strategy games. America fears that China's autocrats have free access to copious data and can enlist local tech firms on national service. Neither side wants to fall behind.

AI procedures are changing and optimizing more and more areas of the economy and society. Especially deep neural networks are characterized by an enormous efficiency and are able to solve various tasks in an intelligent way, which until now has only been possible by humans. Examples are the classification of films according to content, playing poker on a superhuman level or creating deceptively real looking faces. However, it is all too easy to forget that artificial intelligence is fundamentally different from natural intelligence. While the latter inherently uses "worldviews", the former is ultimately based on the highly complex interpolation of countless data. Data are therefore the prerequisite for any AI.