Kevin Desouza

From governance to execution in federal AI policy

Global artificial intelligence spending is forecasted to reach $2.5 trillion in 2026, according to one estimate, marking a 44% increase year-over-year. In 2027, spending is expected to reach $3.3 trillion, reflecting another 32% increase year-over-year.

Where does federal AI spending stand in 2026?

In July 2025, the Trump administration released its blueprint for artificial intelligence—America’s AI Action Plan—with a focus on deregulation and infrastructure investment to achieve “global AI dominance.” The plan represents a notable shift from previous, more cautious AI policies of the Biden era and emphasizes removing regulatory barriers and “ideological” bias in AI.

Why AI policy thrives in some states and fades in others

Discussions on artificial intelligence (AI) are occurring at all levels of government, including federal, state, and local, as each entity tries to understand, leverage, and protect from AI. In August 2025, Brookings identified the states leading and lagging on AI governance, along with the salience of different issues associated with the technology.

CrowdStrike and digital ecosystem transitivity

On July 19, 2024, a major global outage was caused by a faulty software update issued by CrowdStrike, a prominent cybersecurity firm.

What is the tone of the 2016 presidential campaign on Facebook?

The words and language used every day reveal who we are and what we want. They translate our internal thoughts and emotions to others as means of communication. In our previous posts, we analyzed candidates’ Facebook data to understand topics being discussed and how candidates interacted with the public. Here’s a discussion of the evolution of the leading Republican and Democratic candidates’ campaign on their Facebook pages since they announced their candidacy.

We have deepened our analysis to include linguistic cues to understand the personal and psychological attributes of commenters. Reactions, linguistic, and psychological indices of candidates’ commenters reveal interesting findings. Democrats’ commenters scored the highest scores in analytical and anxiety indices. Republicans’ commenters scored the highest scores on clout, authenticity, anger, and sadness indices. The value in understanding these commenter attributes is to shed light on the type of supporters each candidate attracts, campaign strategies that affect supporters of opposition (i.e. email controversy and tax returns) and lastly, which events trigger the commenters’ tone. This gives us a clue of what to expect going into the final period of the 2016 elections.