AI Access Proposal
You have spent this module studying real problems: concentrated AI development, the digital divide, global inequities in access, biased systems, uneven benefits, governance gaps, and approaches to improvement. Now it is your turn. A proposal is not a wish list — it is a structured plan. Real policy proposals, nonprofit pitches, and company initiatives all have the same basic anatomy: they identify a specific problem, argue for a solution, explain who will do what, anticipate objections, and describe how success would be measured.
What Makes a Strong Proposal
The strongest proposals are specific rather than vague. A proposal to improve AI access for everyone is not actionable. A proposal to require that public school districts in underserved areas receive free access to AI tutoring platforms, funded through state education technology budgets, with annual audits of student outcome data broken down by demographic group, is specific, actionable, and measurable. Proposals are persuasive when they are grounded in evidence. The facts and patterns you have studied in this module — about the digital divide, about data labeling labor, about facial recognition error rates, about language representation in AI models — are your evidence base. Use them. Strong proposals acknowledge trade-offs. Every solution has costs, limitations, or unintended consequences. A proposal that pretends its approach is cost-free and without downside is not credible. Naming the trade-offs and explaining why the benefits outweigh them is more persuasive than ignoring them.
Your proposal can be any type that appeals to you. A government policy (requiring something by law or funding it through a budget). A nonprofit initiative (a program a civil society organization could run). A company commitment (a practice a tech company should adopt voluntarily or be required to adopt). A community project (something a school, library, or local organization could launch). An international agreement (something countries could commit to together). Each type has different actors, mechanisms, and timelines.
Your proposal joins a real global conversation. Existing efforts include: the Alliance for Affordable Internet advocating for lower data costs in developing countries; Masakhane, a grassroots NLP research community building AI tools for African languages; Mozilla Foundation's work on open and trustworthy AI; the OECD AI Principles adopted by dozens of governments; and municipal campaigns that have successfully banned facial recognition in cities like San Francisco, Portland, and Boston. You are not starting from zero.
Your Proposal
AI Access Proposal
- Your task is to write a structured proposal to widen fair access to AI or address an AI equity problem you have studied in this module.
- SECTION 1 — THE PROBLEM (2-3 sentences)
- Identify a specific AI equity problem you want to address. Be precise: name who is affected, what harm they experience, and why it matters. Use at least one fact or example from this module.
- SECTION 2 — YOUR SOLUTION (3-4 sentences)
- Describe your proposed solution clearly. What type of proposal is it — policy, nonprofit initiative, company commitment, community project, or international agreement? Who are the main actors? What would they do?
- SECTION 3 — WHY IT WOULD WORK (2-3 sentences)
- Explain the mechanism: how does your solution actually address the problem you described? What evidence or examples from this module support your reasoning?
- SECTION 4 — WHO DOES WHAT (use a list)
- List at least three different actors (government body, company, community organization, educator, etc.) and describe the specific role each plays in making your proposal succeed.
- SECTION 5 — TRADE-OFFS AND OBJECTIONS (2-3 sentences)
- Identify at least one significant limitation, cost, or unintended consequence of your proposal. Then explain why you believe the benefits outweigh this trade-off.
- SECTION 6 — MEASURING SUCCESS (2 sentences)
- Describe two concrete, measurable indicators you would use to know whether your proposal is working after three years.
- SECTION 7 — YOUR PITCH (1-2 sentences)
- Write the most compelling short summary of your proposal — the version you would use to convince a decision-maker in sixty seconds.
Peer Review and Reflection
Once you have written your proposal, exchange it with a classmate. Your job as a reviewer is not just to say what you liked — it is to be a constructive critic who makes the proposal stronger. Ask: Is the problem specific enough? Is the solution clearly described? Are the trade-offs addressed honestly? Are the success measures actually measurable? After receiving feedback, spend five minutes revising the weakest part of your proposal based on the input you received. Revision is not failure — it is how real proposals get better.
Why is a proposal that says it will 'improve AI access for everyone' considered weak compared to one with specific targets and mechanisms?
Why should a strong proposal acknowledge the trade-offs and limitations of its own solution?