Q: What does AI access for low-income students mean and why is it called the new digital divide? A: It refers to the widening gap between wealthy schools that rapidly adopt AI tools and teacher training and underfunded districts that lack devices, broadband, and AI training. The result is a new digital divide where students who need the most support have the least opportunity to practice and build AI-related skills. Q: What are the main reasons underfunded schools fall behind in AI adoption? A: Funding and infrastructure gaps force Title I schools to prioritize basics like safe buildings, buses, and staff, leaving little for refreshed devices, software, or reliable broadband. Teachers in under-resourced schools also lack time, pay, and coaching for AI training, and Big Tech pilots tend to favor wealthier districts. Q: What specific AI skills does the guide say students should learn? A: The guide separates AI literacy—understanding AI’s purpose, functions, ethics, bias, privacy, and limits—from AI competency—practical tasks like prompting chatbots to gather and synthesize information, summarizing texts, turning data into charts, and drafting and testing code. It recommends starting early with guided use and pairing AI work with hand-based writing and math to build judgment. Q: What practical steps can schools take now to improve AI access for low-income students? A: Schools can provide 1:1 devices, filtered broadband, and student accounts, invest in teacher training, planning time, and micro-credentials, and set clear classroom rules for AI use and citation. They can also use free or low-cost tools, create short weekly AI practice stations and student AI coach programs, and measure impact by tracking attendance and assignment quality rather than only test scores. Q: What policy changes does the guide recommend to make AI access for low-income students more equitable? A: The guide urges prioritizing Title I districts for devices, broadband, and coaching, adopting statewide standards for AI literacy and competency, and tying grants to documented training and student practice. It also recommends privacy protections, expanded rural access via hotspots and community Wi‑Fi, and vendor contracts that include long-term support for high-need districts. Q: How can community organizations and companies help close the AI divide? A: Libraries, nonprofits, and youth centers can run evening labs and weekend clubs while high schools match students with local businesses to solve practical problems. Companies can commit to multi-year partnerships that provide mentors, paid internships, and donated seats or credits to turn practice into pathways. Q: What guardrails should educators teach students when they use AI? A: Students should always verify AI outputs against two trusted sources, show their work by submitting prompts and drafts, and explicitly check for bias and privacy risks. Teachers should review students’ reasoning, set rules about when AI use is allowed, and require citation of AI-generated material. Q: What does success look like if AI access for low-income students improves? A: Success means every student can explain what AI is good at and bad at, plan an essay with AI and then write and cite independently, and analyze small datasets while explaining each step, with teachers receiving ongoing coaching and sharing short usable lessons. Over time, gaps in course completion, graduation, and internships should shrink year over year.