The unveiling of OpenAI’s GPT-4o and Google’s Project Astra marks a paradigm shift: artificial intelligence that not only understands words but reads emotional nuance from tone and gesture. From Tehran, where the Persian press has covered these developments with fascination, the technology is described as heralding an era of “emotional AI” — machines capable of empathy, or at least its simulation. This leap, however, has landed unevenly across societies.

In the United States, the public’s ambivalence toward AI was on vivid display during graduation season. At Glendale Community College in Arizona, students revolted when an AI-generated commencement speech was revealed, drowning out the automation with boos. Contrast that with the reception for Apple cofounder Steve Wozniak at Grand Valley State University, where his quip that graduates possess “actual intelligence” — a play on the acronym AI — drew laughter and applause. The divergence underscores a deeper unease: trust in the technology remains fragile, contingent on who delivers the message.

That unease extends to the classroom. A rising proposition, debated in educational circles and amplified by Silicon Valley commentators, argues that majoring in computer science may become obsolete as AI automates coding. Philosophy, with its emphasis on critical thinking and ethics, is touted as an alternative. Yet such claims are premature, as the technology’s rapid advance — including the development of AI girlfriends and the disappointment of filmmaker Paul Schrader when his own creation “dumped” him — reveals more about human longing than about the robustness of AI.

Viewed from Washington, the economic implications are equally unsettling. Companies pursuing AI-driven layoffs may find the strategy backfiring, as the promised returns on investment remain elusive. Nvidia’s CEO Jensen Huang has warned that China already has all the chips it needs, despite US sanctions, injecting a geopolitical dimension into the narrative. As AI evolves from a tool into a companion, the questions it raises — about education, employment, and emotional connection — demand answers that no algorithm can yet provide.