AI Research Memo

Antitrust breakups miss the real battleground: AI assistants, not blue links Prioritize interoperability and open defaults to keep markets contestable Track assistant-led discovery, not just search share, to safeguard users and educators

Trusted news wins when fakes surge Make “proof” visible—provenance, corrections, and methods—not just better detectors Adopt open standards and clear labels so platforms, schools, and publishers turn credibility into a product feature

AI excels on known paths, so schools must shift beyond procedure Assessments should reward framing and defense under uncertainty This prepares students for judgment in an AI-driven world Every era has its pivotal moment.

Europe’s schools rely on foreign AI infrastructure, creating vulnerability A neutral European stack with local compute and governance can secure continuity This ensures resilient, interoperable education under global tensions

AI doesn’t make students “dumber”; low-rigor, answer-only tasks do Redesign assessments for visible thinking—cold starts, source triads, error analysis, brief oral defenses Legalize guided AI use, keep phones out of instruction, and run quick A/B pilots to prove impact

AI scans simplify elections but risk bias Clear rules and provenance reduce errors With oversight, even losers can trust them The largest election year ever recorded coincides with the most persuasive media techn

AI prices reflect scarce compute and network effects, not just hype Educators must teach market dynamics and govern AI use Turn volatility into lasting learning gains In a time historically dominate

Judge AI use by proportion, not yes/no Require disclosure and provenance to prove human lead Apply thresholds (≤20%, 20–50%, >50%) to grade and govern Sixty-two percent of people say they would like their favorite artw

The real risk isn’t the LLM’s words but the agent’s actions with your credentials Malicious images, pages, or files can hijack agents and trigger privileged workflows Treat agents as superusers: least privilege, gated tools, full logs, and human checks

AI lowers entry barriers, raises mastery standards Novices gain most; experts move to oversight and design Education must deliver operator training and governance mastery A quiet result from a very loud technology

AI use is ubiquitous; current assessments reward fluency over thinking Grade process, add brief vivas, and require transparent AI-use disclosure Train teachers, ensure equity, and track outcomes to make AI a partner Eig

AI accelerates information cascades, turning rumors into rapid bank runs Stability now hinges on dampening synchronized behavior, not just capital buffers Build rumor-aware stress tests, fast disclosures, and drill-based curricula

U.S.

AI translation reshapes the labor market, eroding low-skill roles while rewarding domain expertise Education must shift toward “language plus” skills—pairing translation with data, law, or health Policy should teach students to work with machines, not against them

AI and robotics remain narrow tools, excelling only in tightly defined tasks Human versatility—handling exceptions, combining roles, and adapting to context—remains the decisive advantage Education policy must prioritize training for this versatility, turning automation into complement rather than substitute

Search behaves like reinforcement learning, rewarding confirmation Narrow queries and clicks shrink exposure at scale Break the loop with IV-style ranking and teach students to triangulate queries

Student well-being is falling fast AI chatbots are spreading quickly Without safeguards, risks will escalate

AI’s IMO gold isn’t AGI Deploy it as an instrumented calculator Require refusal metrics and proof logs <

LLMs are not conscious, only probabilistic parrota They often mislead through errors, biases, and manipulations Education must use them as tools, never as advisors