Artificial intelligence (AI) has driven many information and communication technology (ICT) breakthroughs. Nonetheless, the scope of ICT systems has expanded far beyond AI since the Turing test proposal. Critically, recent AI regulation proposals adopt AI definitions affecting ICT techniques, approaches, and systems that are not AI. In some cases, even works from mathematics, statistics, and engineering would be affected. Worryingly, AI misdefinitions are observed from Western societies to the Global South. In this paper, we propose a framework to score how \textit{validated as appropriately-defined for regulation} (VADER) an AI definition is. Our online, publicly-available VADER framework scores the coverage of premises that should underlie AI definitions for regulation, which aim to (i) reproduce principles observed in other successful technology regulations, and (ii) include all AI techniques and approaches while excluding non-AI works. Regarding the latter, our score is based on a dataset of representative AI, non-AI ICT, and non-ICT examples. We demonstrate our contribution by reviewing the AI regulation proposals of key players, namely the United States, United Kingdom, European Union, and Brazil. Importantly, none of the proposals assessed achieve the appropriateness score, ranging from a revision need to a concrete risk to ICT systems and works from other fields.

It's been almost one year since the European Commission unveiled the draft for what may well be one of the most influential legal frameworks in the world: the EU AI Act. According to the Mozilla Foundation, the framework is still work in progress, and now is the time to actively engage in the effort to shape its direction. Mozilla Foundation's stated mission is to work to ensure the internet remains a public resource that is open and accessible to everyone. Since 2019, Mozilla Foundation has focused a significant portion of its internet health movement-building programs on AI. We met with Mozilla Foundation's Executive Director Mark Surman and Senior Policy Researcher Maximilian Gahntz to discuss Mozilla's focus and stance on AI, key facts about the EU AI Act and how it will work in practice, as well as Mozilla's recommendations for improving it, and ways for everyone be involved in the process.

Deploying machine learning models in a repeatable, scalable manner requires an understanding that the algorithms and techniques that underpin models are rapidly evolving and are managed differently than traditional software development tools. With significant advances happening in the open-source community, the tools, techniques and algorithms that your data scientists use today to solve business problems will undoubtedly change very soon. Of course, not all change is good, and in many situations, implementing techniques and approaches that aren't understood can lead to catastrophic failures. Here are some guiding principles to ensure your company increases its chance of being successful in its machine learning practices. Maslow's hammer talks of a cognitive bias that involves using a familiar tool: "If all I have is a hammer, every problem looks like a nail."

Procedural generation is a growing trend in game development. It allows developers to create games that are bigger and more dynamic, giving the games a higher level of replayability. Procedural generation isn't just one technique, it's a collection of techniques and approaches that are used together to create dynamic systems and objects. C is the industry-standard programming language to write computer games. It's at the heart of most engines, and is incredibly powerful.

Artificial intelligence (AI) is an umbrella term that covers a variety of techniques and approaches that make it possible for machines to learn, adjust and act with intelligence comparable to the natural intelligence of humans. AI plays an ever-increasing role in enterprise solutions. Unlike robotics, which automate manual tasks, AI automates computing tasks. That's especially valuable given the large and diverse data sets most organizations use today. While the human role in enterprise solutions will never disappear, it's foolish to argue against the advantage of AI-augmented humans.