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  • Faethm by Pearson
    Faethm by Pearson Your Guide to the Future Workforce Join leading companies across the globe using Faethm AI to make strategic workforce decisions for the future
  • Faethm by Pearson
    In 2021, Faethm joined Pearson, creating the world’s first truly end-to-end future of work company and accelerating our mission to prepare every worker, everywhere, for the future of work Our market-leading data, insights and AI capabilities will power the next generation of Pearson’s lifelong learning products to meet the rapidly changing
  • Announcing Pearsons Acquisition of Faethm
    “We are delighted to be accelerating our mission and impact with Pearson,” says Michael Priddis, Faethm Chief Executive Officer “Integrating AI-driven insights from the world’s most sophisticated future of work platform with the world’s learning company will propel the pace of upskilling and reskilling for any organisation, enabling
  • Strategic Workforce Planning - Faethm
    Faethm fuels the Six B’s of talent acquisition and talent management across your workforce Borrow Bring in short-term talent for fixed-term projects to transfer skills and ideas
  • Customer Success Stories - Faethm
    Woolworths Faethm by Pearson helped Woolworths Group analyze tech impacts, plan its workforce growth, plan its workforce growth, and establish a Future of Work Fund for reskilling, creating 838+ tech roles amid automation
  • Introduction to the Technology Taxonomy - Faethm
    The Faethm Technology Taxonomy is a human-centred classification of technology, comprising sixteen technology classes that are categorised by four fields of AI How the taxonomy was developed To develop the taxonomy, Faethm first identified the human abilities that are required to perform work and used these to construct a grouping of
  • Faethm by Pearson
    Deliver effective outcomes Inform policy decisions with integrated economic, technological, and workforce predictive data
  • How does Faethm determine prediction accuracy?
    However, Faethm’s prediction accuracy is high in both precision and recall, a measure of evaluating performance and efficacy of data science models, scoring at 95% This has been tested against real world job automation scenarios and data Faethm also estimates a confidence interval of 3 8%
  • Impact of Generative AI and Large Language Models (LLMs . . . - Faethm
    Understanding the Faethm Technology Taxonomy The Faethm Technology Taxonomy is a human-centered classification of technology We identified human abilities required for work and used these to construct a comprehensive taxonomy of technologies that could disrupt or enhance one or more of these abilities
  • Beyond the Basics: Exploring the Meaning Impact of Skill Proficiency
    Skill proficiency frameworks enable organizations with deeper insights and improved workforce adaptability These frameworks improve hiring, optimize talent development and inform strategic workforce planning by providing a common language and a clear structure for understanding skills and skill lev





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