Although social media companies are in many ways villains that have not done nearly enough to protect children on their platforms, they nonetheless should not be held liable based on claims that they are creating addictive and harmful online environments. Last week, a trial began in Los Angeles Superior Court in a lawsuit brought by a woman, referred to in documents as Kaley G.M., against tech giants YouTube and Instagram. (TikTok previously settled with her).
Mr Jones said offenders are collaborating and co-ordinating their activities on the dark web and using the open web as a discovery platform to identify and abuse vulnerable children. (Getty Images) We were dealing with in the region of 500-800 arrests a few years ago, and we are now dealing with 1,000 arrests and 1,200 (child) safeguards every month. To maintain that means a 24/7 effort by the NCA and colleagues in policing, and that gives you a feel for how the threat has grown.
Today's eLearning solutions use algorithms for many things, including recommendations for courses, tags for skills, scores for completions, heat maps, and metrics for engagement levels. Anyone interested in eLearning sees learning in new ways; all of those ways are measurable, sortable, and optimizable. We seem to have come a long way in terms of learning. Through data-driven learning, one can increase efficiency, personalize learning, and scale it up.
How do we discover new music? It used to be mostly through friends, record stores, and radio. Now, friends, some radio stations, and music platforms still play a role. Spotify's annual wrap-up is an ideal time to see what new music has reached our ears. The European Union is funding a project to audit algorithmic music discovery because it believes there may be bias and a lack of transparency in this process.
It is clean and complete. It captures almost everything I have watched over the last decade, with the exception of a couple of hours of viewing on flights or in hotel rooms. Normally, the algorithm serves up a menu of options that includes something that will satisfy me. And that's the thing about algorithms: They are tuned to normality. They make predictions based on statistical likelihoods, past behavior, and expectations about the continuation of trends.
On the same day Meta showcased its latest , Brandy Roberts stood outside its headquarters mourning her daughter Englyn - who was just 14 when she died after watching a "how-to" suicide video on Instagram. Brandy wasn't there as an activist. She was there as a grieving mother demanding answers. Inside, Mark Zuckerberg fumbled through of glitchy smart glasses and AI tools. Outside, grieving families demanded accountability. Meta's silence spoke volumes: Growth over grief, product over protection, optics over safety.
It's become a bit of an inevitability: I'll be scrolling social media at night, as one does, when I stumble upon a drama-filled reel about someone going through a divorce. Then the algorithm does its thing and, before I know it, I'm being served countless #DivorceTok videos. It doesn't matter that I'm happily married - I can't seem to scroll past one of these reels without staying tuned in until the end. Many of my friends report being served (and watching) the same things. Which begs the question: Why are happily married people obsessed with watching breakup content?
When it comes to Scala interviews, the trick isn't just solving problems - it's solving them the Scala way.Interviewers are often less interested in whether you can code something and more curious about how you think, use language features, and write clean functional code. In this article, I'll walk through three interview-style Scala questions. Each question is designed to test a different dimension of your Scala skill set - from string manipulation to functional collections and stack-based problem solving.
