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AI does not guarantee trial success, as challenges such as finding the right patients, obtaining consent, and drug manufacturing/distribution remain. Additionally, the need for humans to verify the work of AI agents could offset some of the time savings.

AI agents could be used to track the diversity of the trial population to ensure treatments work for a broad population, and they can enable researchers to understand the safety and effectiveness of a drug earlier, allowing researchers to focus on more strategic work.

Medable officials suggest that AI agents could become standard features of some clinical trials in three to five years, functioning similarly to self-driving cars to handle record-keeping for new drug approval applications.

Ken Getz, the executive director of the Tufts center, stated that deploying the agent led to efficiencies such as accelerating enrollment in the trial, reducing the number of on-site visits, and locking in the data.

AI could potentially help aggregate and better analyze more real-time data feeds to help policymakers make better decisions.

The task force was appointed to improve the quality and timeliness of real economic signals that inform the Federal Reserve's policy judgments.

The members appointed to the task force include Harvard economics professor Raj Chetty, former Walmart CEO Doug McMillon, and University of Chicago economics professor emeritus Kevin Murphy.

Fed Chair Kevin Warsh has appointed a data task force to improve the quality and timeliness of real economic signals that inform the Federal Reserve's policy judgments.

As of the report, Warsh has been at the helm for 10 weeks, leading a 112-year-old institution with a $6.7 trillion balance sheet. While he is pushing for a paradigm shift through AI and structural changes, the Fed is currently still using its standard toolkit of adjusting the federal funds rate target range based on government economic statistics to combat inflation.

Warsh has raised the possibility of cutting the number of monetary policy meetings from eight per year to six. The logic is that this would allow each meeting to incorporate two months of inflation and employment data rather than just one, and provide officials more bandwidth for other responsibilities like bank regulation and payments systems.

The press conference led to a market blowup where markets sold off, partly because Warsh was vague regarding the possibility of raising interest rates to combat inflation. The sell-off was likely exacerbated by traders unwinding positions bet on a rate hike and outsized moves in the thinly traded market for long-term Treasury bonds.

Before taking office, Warsh built AI bots named "Milton" and "Tobin" that ingested the collected works of 20th-century economists Milton Friedman and James Tobin to provide insights on contemporary economic questions.