Computer science/engineering grads had an employment advantage (see chart) that, since ChatGPT's release, has disappeared. Is A.I. to blame? Here's what the data say and what new grads (or anyone!) can do about it:
THE EMPLOYMENT LANDSCAPE
• NY Fed: unemployment for recent computer-science grads (22-27) sits at 7.0%, and computer engineering at 7.8% (roughly on par with fine arts and anthropology grads!)
• Compare that to ~5.8% for recent grads overall and ~4% for the whole US workforce.
• Eighteen-year-olds are voting with their feet: US undergrad CS enrolment fell 11% in 2025; computer programming fell a stunning 26%.
• Demand is shrinking too: Handshake postings are down ~50% from their 2022 peak, and Revelio Labs data suggest entry-level software and data-analysis postings have dropped as much as 67%.
IS A.I. TO BLAME?
• "Yes" camp: A 2025 Stanford University study found employment for 22-25-year-olds in A.I.-exposed jobs dropped 13% since 2022, while older workers held steady. The Dallas Fed replicated it... and the decline comes from juniors never being hired, not layoffs.
• "Not so fast" camp: Google economists found posting declines were just as steep for senior workers and predate ChatGPT. A Fed study of 1M+ firms found "null effects." Their take: high interest rates and a post-pandemic hangover, with A.I. as a convenient scapegoat.
WHAT YOU CAN DO:
1. Stop competing on raw code. The human edge is now system design, architecture and deciding what to build in the first place.
2. Pick a domain. "A.I. engineer" is a common résumé; "A.I. engineer who worked alongside a hospital team for two summer internships" is a short list.
3. Build a public portfolio. Substantive GitHub repos and a Kaggle project beat CVs sent into the void.
4. Get fluent with agentic tooling, e.g., RAG, model evaluation, multi-agent orchestration. PwC found A.I.-skilled workers earn a 56% wage premium (!!!)
5. Lean on your network. Referrals and warm intros are crushing mass (often GenAI-produced) applications in this market.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
Filtering by Tag: #education
AI in the Classroom: How a Top Elementary School Is Doing It Right, with Principal Traci Walker Griffith
Long overdue episode today on how A.I. can support children's education. Hard to imagine a better guest than Traci Walker Griffith, principal of a K-8 school that has used innovations like A.I. to become Boston's #1 school.
In this episode, we discuss:
How Traci transformed The Eliot School from an underperforming school on the closure list into the highest-performing school in Boston.
How kids as young as four at the Elliott work with robots and coding tools like Kibo and Scratch Junior, learning that the quality of their input determines the quality of their output ("garbage in, garbage out").
How, for younger students in kindergarten through fourth grade, teachers use A.I. behind the scenes.
How students in grades five through eight interact with A.I. directly, enabling them to build metacognition and critical-thinking skills.
Her concrete guidance for schools (or parents!) considering incorporating A.I. into pedagogy.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.