Via Slashdot: “The potential threat of bosses attempting to replace human workers with AI agents is just one of many compounding reasons people are critical of generative AI…” writes Wired, arguing that there’s an AI backlash that “keeps growing strong.” “The pushback from the creative community ramped up during the 2023 Hollywood writer’s strike, and continued to accelerate through the current wave of copyright lawsuits brought by publishers, creatives, and Hollywood studios.” And “Right now, the general vibe aligns even more with the side of impacted workers.” “I think there is a new sort of ambient animosity towards the AI systems,” says Brian Merchant, former WIRED contributor and author of Blood in the Machine, a book about the Luddites rebelling against worker-replacing technology. “AI companies have speedrun the Silicon Valley trajectory.” Before ChatGPT’s release, around 38 percent of US adults were more concerned than excited about increased AI usage in daily life, according to the Pew Research Center. The number shot up to 52 percent by late 2023, as the public reacted to the speedy spread of generative AI. The level of concern has hovered around that same threshold ever since… [F]rustration over AI’s steady creep has breached the container of social media and started manifesting more in the real world. Parents I talk to are concerned about AI use impacting their child’s mental health. Couples are worried about chatbot addictions driving a wedge in their relationships. Rural communities are incensed that the newly built data centers required to power these AI tools are kept humming by generators that burn fossil fuels, polluting their air, water, and soil. As a whole, the benefits of AI seem esoteric and underwhelming while the harms feel transformative and immediate. Unlike the dawn of the internet where democratized access to information empowered everyday people in unique, surprising ways, the generative AI era has been defined by half-baked software releases and threats of AI replacing human workers, especially for recent college graduates looking to find entry-level work. “Our innovation ecosystem in the 20th century was about making opportunities for human flourishing more accessible,” says Shannon Vallor, a technology philosopher at the Edinburgh Futures Institute and author of The AI Mirror, a book about reclaiming human agency from algorithms. “Now, we have an era of innovation where the greatest opportunities the technology creates are for those already enjoying a disproportionate share of strengths and resources.” The impacts of generative AI on the workforce are another core issue that critics are organizing around. “Workers are more intuitive than a lot of the pundit class gives them credit for,” says Merchant. “They know this has been a naked attempt to get rid of people.”
The article suggests “the next major shift in public opinion” is likely “when broad swaths of workers feel further threatened,” and organize in response…

Goldman Sachs Launches AI Assistant Firmwide, With 10,000 Employees Already Using It (reuters.com) – Via Slashdot – Goldman Sachs has officially rolled out a generative AI assistant across the company to enhance productivity, with around 10,000 employees already using it for tasks like summarizing documents and data analysis. Reuters reports: With the AI tool’s official company-wide launch, Goldman joins a long list of big banks already leveraging the technology to shape their operations in a targeted manner and help employees in day-to-day tasks. […] The GS AI assistant will help Goldman employees in “summarizing complex documents and drafting initial content to performing data analysis,” according to the internal memo. “While the official line is that AI frees up employees for ‘higher-value work,’ the real-world consequence is a reduced need for human labor,” notes Gizmodo in their reporting. A banker told Gizmodo that because their AI system now processes 85% of all client responses for margin calls, “the operations team avoided hiring 30 new people.” Gizmodo asks pointedly: “If one AI tool is replacing the need for 30 back-office staff in one corner of one bank, what happens when the entire industry scales that up?”

NGOs/IGOs:

BIS.org: Financial stability implications of artificial intelligence – Executive Summary – FSI Executive Summaries | 26 June 2025. PDF full text – The growing use of artificial intelligence (AI) by financial institutions is attracting closer regulatory scrutiny, including from a financial stability perspective. This expansion is driven by supply side factors, such as advances in large language models (LLMs), deep learning techniques, access to more unstructured data sources and increasing computational power, as well as demand side factors such as opportunities to reduce costs and the desire to stay competitive. Against this backdrop, the Financial Stability Board (FSB) report The Financial Stability Implications of Artificial Intelligence, published in November 2024, provides of stocktake of industry and regulatory/supervisory AI use cases and identifies potential implications for financial stability. Drivers of AI use cases in the financial sector – The report identified supply and demand side factors (summarised in the diagram and table below), noting that the former currently play a bigger role due to recent technological advancements.

AI for Risk-Based Supervision: Another Nice to Have Tool or a Game-Changer (Washington, DC: World Bank, 2025-02-27) Dohotaru, Matei; Prisacaru, Marin; Shin, Ji Ho; Palta, Yasemin. Regardless of the individual perspectives on Artificial Intelligence (AI), it can transform the personal and professional lives at an unprecedented pace. It will also impact one of the most regulated and supervised industries in the world…. The remarkable advancement of AI in recent years, both in terms of performance and accessibility, promises to revolutionize numerous industries, including the financial sector. The benefits of AI for financial sector supervision extend beyond the automation.

IMF – Working Papers Demystifying Trade Patterns In A Fragmenting World – June 27, 2025 – Schulze, Tatjana ; Xin, Weining – So-called “connector” countries have been argued to benefit from the US-China trade tensions, given their rising share in US imports. This paper draws an important distinction between trade reallocation—countries increase domestic production to substitute for declining Chinese exports to the US—and trade rerouting—countries serve as one-stop place for transshipment of Chinese exports to the US. Leveraging granular data on trade and FDI flows and global input-output linkages, focusing on six Asian countries, we first document that the connector role of these countries may reflect their growing domestic markets and Chinese supply chain reconfiguration, beyond trade rerouting from China to the US. We then zoom in on value-added components and deploy a synthetic control approach to disentangle trade reallocation from trade rerouting. While the evidence remains elusive for five of the six countries, Vietnam appears to have benefited from trade reallocation, with increased domestic content in its exports to the US in strategic sectors, instead of facilitating significant transshipment of Chinese exports to the US. Such domestic production expansion also helped increase domestic content in Vietnam’s exports to the rest of the world, and may be partly due to Chinese firms relocating to Vietnam through greenfield FDI. Despite potential short-term gains, trade reallocation increases connector countries’ vulnerability to geoeconomic fragmentation with losses to all countries in the long run.

Soto, Paul E. (2025). “Research in Commotion: Measuring AI Research and Development through Conference Call Transcripts,” Finance and Economics Discussion Series 2025-011. Washington: Board of Governors of the Federal Reserve System, https://doi.org/10.17016/FEDS.2025.011

Adams, Jonathan, Min Fang, Zheng Liu, and Yajie Wang. 2025. “The Rise of AI Pricing: Trends, Driving Forces, and Implications for Firm Performance.” Federal Reserve Bank of San Francisco Working Paper 2024-33. https://doi.org/10.24148/wp2024-33. We document key stylized facts about the time-series trends and cross-sectional distributions AI pricing and study its implications for firm performance, both on average and in response to monetary policy shocks. We use the online job postings data from Lightcast to measure the adoption of AI pricing. We infer that a firm is adopting AI pricing if it posts a job that requires AI-related skills and contains the keyword “pricing.” At the aggregate level, the share of AI pricing jobs in all pricing jobs has increased more than tenfold since 2010. The rise of AI pricing jobs has been broad-based, spreading across more industries than other types of AI jobs. At the firm level, larger and more productive firms are more likely to adopt AI pricing. Firms that adopted AI pricing experienced faster growth in sales, employment, assets, and markups, and their stock returns are also more responsive to high-frequency monetary policy surprises than non-adopters. We show that these empirical observations can be rationalized by a simple model where a monopolist firm with incomplete information about its demand function invests in AI pricing to acquire information.

Speech by Governor Barr on artificial intelligence and banking Board of Governors of the Federal Reserve System at Federal Reserve Bank of San Francisco. San Francisco, California. April 4, 2025. Today, I’d like to speak about responsible innovation in the context of generative artificial intelligence (Gen AI) in banking and how bank–fintech partnerships may accelerate the integration of the technology and banking. Earlier this year, I laid out two scenarios for Gen AI adoption—an incremental scenario where the technology primarily augments what humans do today, and a transformative scenario where we extend human capabilities with far-reaching consequences. Of course, these are hypotheticals, and elements of both scenarios will likely come to pass. But in either scenario, we should anticipate widespread productivity gains, particularly for banking.