📰 Key Summary

ASE 3711’s ground station equipment demand for low-earth-orbit satellites is driving a more upbeat earnings call outlook, with the market expecting Q4 revenue momentum to continue, though the summary lacks concrete guidance figures — so we’re focusing on the AI Economy news here.

Here’s the translation:

Google is expanding its AI and economy research team, bringing on several heavyweight economists. The move follows shortly after Google’s earlier release of “AI & Economy ATLAS v1.0,” an interactive open platform designed to track how people are actually using Google’s AI tools at work and in daily life. Google says that simply observing adoption patterns is just a starting point — understanding the structural shifts AI brings to work, business, and everyday life requires a cross-disciplinary approach that combines granular data with rigorous economic research.

The newly recruited academic advisors include Philippe Aghion, the 2025 Nobel laureate in Economics and chair professor at INSEAD and the Collège de France, who will apply his pioneering research on innovation-driven growth and “creative destruction” theory to modeling AI’s impact on the economy’s long-term trajectory. He’ll be joined on the advisory panel by fellow Nobel laureate Michael Spence and Cambridge scholar Diane Coyle. Ajay Agrawal, a professor at the University of Toronto’s Rotman School of Management, is joining as a visiting scholar and will work with MIT economics department chair David Autor, focusing on the economics of AI and scientific discovery, as well as AI and robotics.

In addition, Anu Madgavkar, former partner at the McKinsey Global Institute (MGI), has been named research program director. She’s spent the past two decades focused on global research into labor markets and technology adoption, and will now lead Google’s empirical research into global AI diffusion and small business ecosystems, among other areas. The research program centers on four core areas: the future of work, productivity and economic growth, the speed of global technology diffusion, and AI’s impact on scientific discovery. See the original article for full details.

💬 JudyAI Lab Perspective

Google expanding its AI and economy research team by bringing on several heavyweight economists is worth paying attention to — not just because of who’s on the list, but because Google is formally treating “AI’s impact on the economy” as a discipline that requires long-term investment.

From an AI builder’s perspective, this reflects a shift: the industry has mostly framed AI in terms of “is the tool useful” or “what’s the adoption rate,” but Google bringing in macroeconomists like Philippe Aghion (creative destruction theory), Michael Spence, and David Autor signals that major platforms now recognize usage data alone can’t answer the real structural questions — how AI reshapes work patterns, the trajectory of productivity growth, and the pace of technology diffusion. This “data + theoretical framework” dual-track approach is a reminder for anyone building AI products or doing AI research: usage growth alone doesn’t give you the full picture — you also need a framework that can explain causal mechanisms to anticipate what comes next.

Actionable takeaway for readers: when following this kind of cross-disciplinary research, don’t just look at the conclusions — pay attention to which economic framework they’re using to interpret the data. That’s more valuable than the headline of the report.

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