53 Matching Annotations
  1. Last 7 days
    1. The integration also connects to Upwork's AI agent Uma, which helps automate parts of the hiring and execution process once a project is underway.

      AI正在从单一工具演变为完整的工作生态系统,这种从招聘到执行的自动化整合展示了AI如何重塑整个工作流程。这不仅提高了效率,也可能导致传统中介角色的消失,同时创造了新的AI服务市场,值得深入思考这种转变对不同行业的影响。

    1. A surprising number of people are now employed as model trainers, feeding their human expertise to automated systems.

      这一观察揭示了AI发展中一个令人深思的悖论:人类专家正在训练AI系统来取代自己的工作。这种'自我替代'的劳动力模式可能是前所未有的,它不仅改变了就业结构,还提出了关于知识传承、专业价值定义的深刻问题。这种趋势可能加速某些领域的专业知识流失,同时创造新的权力动态。

  2. Nov 2024
    1. Desmond, Matthew. Poverty, by America. 1st ed. New York: Crown, 2023. https://amzn.to/40Aqzlp

      Annotation URL: urn:x-pdf:eefd847a2a1723651d1d863de5153292

      Alternate annotation link: https://jonudell.info/h/facet/?user=chrisaldrich&max=100&exactTagSearch=true&expanded=true&url=urn%3Ax-pdf%3Aeefd847a2a1723651d1d863de5153292

  3. Apr 2023
    1. Why do we devalue education? Is it such a commodity now that its transmission value is worth pennies on the dollar?

      Is Government requirement and support for education part of what causes the devaluation of the "educational market"? If so, how would one decouple this process to increase the wages of educators? Is a capitalistic version the best way to go, or is it better to socialize it further and inject more money into it versus other choices?

      Major nationwide strike forming minimum wage with variances for local consumer indices and city/state costs of living? Something which would drive competition for child care and teaching spaces? Wages that would push up the social value of education? Create a market for competition for teachers at the local level as well as between areas?

  4. Jan 2021
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  10. Oct 2019
    1. We live in an age of paradox. Systems using artificial intelligence match or surpass human level performance in more and more domains, leveraging rapid advances in other technologies and driving soaring stock prices. Yet measured productivity growth has fallen in half over the past decade, and real income has stagnated since the late 1990s for a majority of Americans. Brynjolfsson, Rock, and Syverson describe four potential explanations for this clash of expectations and statistics: false hopes, mismeasurement, redistribution, and implementation lags. While a case can be made for each explanation, the researchers argue that lags are likely to be the biggest reason for paradox. The most impressive capabilities of AI, particularly those based on machine learning, have not yet diffused widely. More importantly, like other general purpose technologies, their full effects won't be realized until waves of complementary innovations are developed and implemented. The adjustment costs, organizational changes and new skills needed for successful AI can be modeled as a kind of intangible capital. A portion of the value of this intangible capital is already reflected in the market value of firms. However, most national statistics will fail to capture the full benefits of the new technologies and some may even have the wrong sign

      This is for anyone who is looking deep in economics of artificial intelligence or is doing a project on AI with respect to economics. This paper entails how AI might effect our economy and change the way we think about work. the predictions and facts which are stated here are really impressive like how people 30 years from now will be lively with government employment where everyone will get equal amount of payment.