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As an alternative approach, I tested whether large language models (LLMs) could provide more realistic estimates by simulating compliance scenarios in the final section of this post. I prompted ChatGPT, Claude, and Grok to act as compliance officers at companies subject to new CCPA provisions and a Bureau of Industry and Security (BIS) rule, asking each to estimate hours needed for first-year implementation and ongoing compliance.

The big takeaways:

* For California's risk assessment regulation, Claude and Grok project 400-580 hours will be needed for the first-year of compliance (vs. the official 120 hours) and 150-240 hours thereafter (vs. the official 18-36 hours annually). ChatGPT estimates the time at 90-250 hours initially and 40-150 hours for each additional year.

* For the automated decision-making provision of the CCPA, Claude and Grok project 450-730 hours for first-year compliance, far exceeding the official 360-hour estimate. While ChatGPT suggests lower initial costs (80-300 hours), all three LLMs predict significantly higher ongoing annual costs than official projections.

* For the BIS reporting rule, Claude projects 1,140 hours for first-year compliance (3x the official estimate of 333 hours), while ChatGPT estimates 280 hours and Grok projects 380 hours. All three LLMs agree ongoing compliance will require substantial resources.

In short, the LLMs consistently predicted much higher compliance costs than the official sources, suggesting a systematic underestimation.

> By the 2000s, it was common to split the semiconductor industry into three categories. “Logic” refers to the processors that run smartphones, computers, and servers. “Memory” refers to DRAM, which provides the short-term memory com puters need to operate, and flash, also called NAND, which remembers data over time. The third category of chips is more diffuse, including analog chips like sensors that convert visual or audio signals into digital data, radio frequency chips that communicate with cell phone networks, and semiconductors that manage how devices use e lectricity.

That’s the idea actually.

I would also look into this: https://www.washingtonpost.com/technology/2022/07/13/ftc-lin.... I often disagree with Commissioner Wilson but she has a point. The entire agency has shifted due to Chair Khan.

Public squares have always been styled as places where the general public would gather to share and exchange ideas, discuss politics, and engage in debate. This is not what is happening online. The Pew Research Center's survey of social media users found that only 9 percent of those online say they often discuss, comment, or post about politics. Most people are uncomfortable discussing politics, including in online arenas.

Both these polls add depth to a well-understood trend: People live a lot of their lives online—yet they still rarely engage in politics there. Only the politically active are going online to talk politics. The rest of us are going there to watch, like spectators at a coliseum.

All of that being said, SaaS and remote work tools should reduce the cost of transactions in the firm, which means expanded control of capital and more productive monitoring systems. In effect this means that the company can coordinate restrictions on output, monitor agents, and curb the costs imposed by the agents on the firm.

Theory is ambiguous when it comes to markups, what the company charges versus the price that consumers pay. This might go up or go down. There is a lot of current debate on this. But the theory does suggest that markets should get more monopolized.

Let me know if you need more. This is one of my research foci.

The basic idea is this. You know Canada has certain demographics. A part of the population is male and female, of a certain age, of a certain income, etc. You ask everyone in your survey those questions, as well as the things you want to understand, and then you can use some techniques to match your survey to the rest of the country. From here, then you can estimate what the entire country thinks about given just the survey.

As one can imagine, the process of matching called undersampling/oversampling matters a lot in practice.