99 Problems

[AI is worried about tariffs too.]

Problem #1 “Tariff Rollercoaster“

Currently, AI is facing several problems. Last week, the U.S. took a ride on the “tariff rollercoaster” as President Trump’s tariff policy went into effect. Here are some of the ups and downs:

  1. Trump Administration announces double-digit tariff rates for dozens of countries. (April 9)

  2. Trump administration backs down from April 9 announcement and issues a 90-day pause on most countries.

  3. Trump administration increases the rate for China to 145%, up from 20%, citing China’s lack of respect for World Markets. (April 10)

  4. China increases tariffs on U.S. imports to 125% (April 11)

  5. Trump Administration announces there is no tariff exception for electronics, including semiconductors, phones, and laptops. (April 13)

The recent volatility is due to uncertainty in the international supply chain. As a result, international trade is suffering, causing global markets to take a hit. President Trump’s reasoning suggests that the tariffs will aid American manufacturing and generate $6 trillion. Economists estimate a more modest $3 trillion. Between tariffs and market uncertainty, many industries are doing all they can to navigate the waters. The AI industry is no different. On Sunday, President Trump emphasized that phones, computers, and other popular electronic items will still be hit by tariffs. This includes the Nintendo Switch 2 (sorry gamers), and possibly semiconductors, a vital component of AI development. For context, the majority of U.S. semiconductors stem from imports. According to President Trump, the ‘whole electronic supply chain’ is under investigation, which could spell billions in losses for several industries:

  • Data Center Construction

  • Automotive & Aerospace Sectors

  • Integrated Device Manufacturers & Consumer Electronics

Problem #2 Environmental Concerns “The Foundation”

Leaving the recent trade fiasco aside momentarily, AI’s development has been put under question given the large amount of water and electricity needed to train AI’s large language models (LLMs). AI opponents have stated for all AI’s benefits, there is a considerable concern for national water supplies and electrical grids. For context, Deloitte has recently forecasted that global data electrical usage will increase from 536 TwH to 1,065 TwH by 20230 - enough to supply electricity to over 28 million households. Moreover, water usage for AI training has also been a serious problem. In 2022, Microsoft, Google, and Meta collectively used $580 billion gallons of water to cool AI servers. These environmental factors are forcing several projects to accommodate increasing demands.    

Problem #3 Regulations & #4 Labor “The L curve”

As the problems for AI pile up, the Trump administration is attempting to manage two of the biggest challenges: regulations and labor. Recently, the Office of Management and Budget (OMB) released two memos that reverse Biden-era safeguards: (1) allowing for the acquisition of AI products, and (2) mandating consumer rights and transparency. In the memo, the Director of OMB states,  “Agencies must adopt a forward-leaning and pro-innovation approach that takes advantage of this technology to help shape the future of government operations.” 

Federal agencies are tasked with developing strategies to achieve enterprise-wide solutions within six months. However, these same agencies also must learn on the job as they determine what specific AI performance outcomes they need. AI development takes time and collaboration, which the U.S. has not utilized as well as our trading partners. Subsequently, the current administration has a renewed focus on policies that will improve the mass adoption of AI tools and services. Federal Agencies will have to assess AI’s features and how they coincide with the specific agency’s needs. Federal agencies also have to deploy these technologies precisely to ensure that US research and development strategies are competitive globally. This means getting technical. 

This dilemma leads to the next problem for AI-labor. Despite recent growth in AI-related careers, the majority of Americans are still apprehensive about using AI, let alone learning it. Growth in the AI labor market requires one of two things: (a) a technical understanding; (b) the adoption of AI tools in daily life. The former is seeing a surge in demand that is difficult to keep up with, while the latter is not moving as quickly.

The Pew Research Center issued a report acknowledging that 52% of U.S. workers are worried about the future impact of AI use in the workplace. Even more concerning, 63% of U.S. workers say they don’t use AI much or at all in their jobs. These stats, in addition to the mass federal government firings and reallocation of the workforce, speak to a large class of Americans who are not prepared to help build AI. And yet, growth is not one of AI’s problems. 

________Part 1__________

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