The adoption of generative AI technologies is swiftly expanding. Services employing both linguistic and mul-timodal models are evolving, offering users increasingly precise responses. Consequently, human reliance on these technologies is expected to grow rapidly. With the premise that people will be impacted by the output of AI, we explored approaches to help AI output produce better results. Initially, we evaluated how contemporary AI services competitively meet user needs, then examined society's depiction as mirrored by Large Language Models (LLMs). We did a query experiment, querying about social conventions in various countries and eliciting a one-word response. We compared the LLMs' value judgments with public data and suggested an model of decision-making in value-conflicting scenarios which could be adopted for future machine value judgments. This paper advocates for a practical approach to using AI as a tool for investigating other remote worlds. This re-search has significance in implicitly rejecting the notion of AI making value judgments and instead arguing a more critical perspective on the environment that defers judgmental capabilities to individuals. We anticipate this study will empower anyone, regardless of their capacity, to receive safe and accurate value judgment-based out-puts effectively.

I was challenged by the editors here at Work: Reimagined to imagine what a corporation might look like in 2050. My immediate response was to think'that's a long ways off.' But on the other hand, it does take an incredibly long time to make foundational changes in society, except when major disruptions occur, as with the rise of the Internet over the past few decades, or the Black Death, when over 100 million people died, leading to the shifts in power that ultimately sparked the Renaissance. So I am resorting to a futurist sleight-of-hand to get to an answer in several steps. I can't just scramble to the roof of the house to see out over the horizon: First, I have to build a ladder to climb up to the roof.

In October 2016, "Westworld" topped the charts as the most-watched premiere season of an HBO original series ever. In the series, a science fiction thriller written and directed by novelist Michael Crichton based on a 1973 film of the same name, Anthony Hopkins takes on the role of Dr Ford, who creates a futuristic western-themed amusement park populated by android hosts to cater human guests, with Evan Rachel Wood playing the role of Dolores, the oldest android host working in the park. Further to the great script and the impressive casting, the success of the series is also undoubtedly linked to its timing. Just one year ago, Lee Sedol, 18-time world Go-board game champion, was beaten by DeepMind's AlphaGo, which was a monumental breakthrough of Artificial Intelligence (AI). Even before the AlphaGo's victory over Lee Sedol, there was growing interest in the potential and risks of humanoid robots and of AI, led by the likes of Stephen Hawking and Elon Musk.

It's 3/14, also known as Pi Day – a mathematics holiday to celebrate the irrational, transcendental number we learned in school, for the most part, to calculate the circumference or area of circles. While there are a number of fulfilling Pi(e) related activities you can indulge in, from feasting on scrumptious pies to chasing down the value of Pi (good luck!), it is also an apt moment to turn attention to where children across the world stand in mathematics achievement and other learning outcomes. While countries have made impressive gains in access to education, a recurring theme is that not nearly enough learning is happening. The 2018 World Development Report (WDR) takes on the learning crisis and its possible underlying factors. The report also takes stock of a growing evidence base to identify key principles and effective interventions to improve learning, challenges in taking successful interventions to scale, and strategies to overcome those challenges.

There is so much doom and gloom associated with robots and jobs it is time to add some common sense to the misunderstandings created by so called experts opinions about robots and jobs – thankfully authors from the OECD may have added some clarity to the debate -- 'finding that on average, across the 21 OECD countries, '9% of jobs rather than 47%, as proposed by Frey and Osborne face a high automatibility.' Capitalism, the term for our global'free' markets, is a uniquely future-oriented economic system in which people invest, make innovations, apply for patents, and in other ways bet on the future. Behind all of this we find the hallmark of humanity, which is our creative intelligence. It is intelligence that drives these investments and innovations, and intelligence that forges within many of us an intense curiosity of what the future may hold. It is also intelligence that forges in others an anxiety over what the future holds. For many the future is no longer a promise but a threat!