{ "version": "0fcb643019d8", "built_at": "2026-10-24T00:12:04.912Z", "buckets": [ { "id": "E1", "slug": "digital-ecosystem", "name": "Digital ecosystem", "kind": "evidence", "items": [ { "id": "E1.1", "name": "Connectivity", "question": "Can the intended audience get online reliably enough, often enough and at the speeds the use case needs?" }, { "id": "E1.2", "name": "Device access", "question": "How widespread is device ownership and use, and why; what kinds of devices are used?" }, { "id": "E1.3", "name": "Cost of use", "question": "Can they afford the device and data the use case requires, and what measures affect this (for example free data offers from mobile operators)?" }, { "id": "E1.4", "name": "Phone sharing and control", "question": "Who else uses or controls the phone, and what does that mean for meaningful engagement, privacy and safety?" }, { "id": "E1.5", "name": "Electricity", "question": "Can they charge and power a device often enough for the use case?" }, { "id": "E1.6", "name": "Online freedom and safety", "question": "Is there a history of shutdowns, platform blocking, censorship or surveillance that could affect the use case or put users at risk?" }, { "id": "E1.7", "name": "Laws and regulation", "question": "What laws, regulations or policies (data protection, AI policy and so on) may affect the use case?" } ], "url": "/digital-ecosystem", "md_url": "/digital-ecosystem.md", "items_count": 4 }, { "id": "E2", "slug": "ai-trust-norms", "name": "AI trust and norms", "kind": "evidence", "items": [ { "id": "E2.1", "name": "AI usage", "question": "Which AI tools, if any, does the audience use, how often and for what?" }, { "id": "E2.2", "name": "AI trust", "question": "How does the audience feel about AI and its outputs? Do they trust it enough, or too much, for this use case?" }, { "id": "E2.3", "name": "AI literacy", "question": "How much does the audience understand about AI, how it works, its risks and how to use it well?" }, { "id": "E2.4", "name": "AI acceptability", "question": "How does the audience feel about AI for this specific use case? How much will they share with an AI tool on this topic?" }, { "id": "E2.5", "name": "Social norms", "question": "How do influential people, organisations or institutions in the audience's life affect their likely use of AI?" } ], "url": "/ai-trust-norms", "md_url": "/ai-trust-norms.md", "items_count": 2 }, { "id": "E3", "slug": "language-literacy", "name": "Language and literacy", "kind": "evidence", "items": [ { "id": "E3.1", "name": "Preferred languages", "question": "Which languages does the audience prefer to write in, and to speak in?" }, { "id": "E3.2", "name": "Code-switching", "question": "In multilingual contexts, when, how and why does the audience mix languages?" }, { "id": "E3.3", "name": "Literacy", "question": "How well can the audience read and write, and how does that affect the use case?" }, { "id": "E3.4", "name": "Modality", "question": "Which ways of communicating (text, voice, voice notes, video) does the audience prefer and use comfortably?" }, { "id": "E3.5", "name": "Model performance", "question": "How well do the proposed language models perform in the audience's languages, code-switching and modalities?" } ], "url": "/language-literacy", "md_url": "/language-literacy.md", "items_count": 2 }, { "id": "E4", "slug": "data", "name": "Data", "kind": "evidence", "items": [ { "id": "E4.1", "name": "Content and knowledge base", "question": "Does validated, locally appropriate content exist for the model to draw on, in the languages needed, or must it be created?" }, { "id": "E4.2", "name": "Language data", "question": "If the main languages are poorly supported, does enough text or speech data exist to adapt models, especially for voice?" } ], "url": "/data", "md_url": "/data.md", "items_count": 0 }, { "id": "E5", "slug": "landscape", "name": "Competitor and actor landscape", "kind": "evidence", "items": [ { "id": "E5.1", "name": "Similar initiatives", "question": "Which local or international development organisations have built, or are building, a similar use case in the same context?" }, { "id": "E5.2", "name": "Content producers", "question": "Which brands, influencers, government bodies or NGOs already produce content on the topic? What do they do well, and where are the gaps?" } ], "url": "/landscape", "md_url": "/landscape.md", "items_count": 1 }, { "id": "E6", "slug": "evidence-benchmarks", "name": "Evidence and benchmarks", "kind": "evidence", "description": "Items not yet agreed. Pages here are candidate items.", "items": [], "url": "/evidence-benchmarks", "md_url": "/evidence-benchmarks.md", "items_count": 0 }, { "id": "E7", "slug": "risk-safety", "name": "Risk, safety and safeguarding", "kind": "evidence", "description": "Items not yet agreed. Pages here are candidate items.", "items": [], "url": "/risk-safety", "md_url": "/risk-safety.md", "items_count": 2 }, { "id": "E8", "slug": "problem-alternatives", "name": "Problem definition and AI alternatives", "kind": "evidence", "description": "Items not yet agreed. Pages here are candidate items.", "items": [], "url": "/problem-alternatives", "md_url": "/problem-alternatives.md", "items_count": 2 }, { "id": "E9", "slug": "enabling-environment", "name": "Enabling environment", "kind": "evidence", "description": "Items not yet agreed. Pages here are candidate items.", "items": [], "url": "/enabling-environment", "md_url": "/enabling-environment.md", "items_count": 1 }, { "id": "P1", "slug": "methods", "name": "Methods", "kind": "practice", "description": "Desk review, key informant interviews, focus groups, surveys, observation, diaries, cognitive interviewing, rapid assessments. One file per method, with when to use it and its limits", "items": [], "url": "/methods", "md_url": "/methods.md", "items_count": 0 }, { "id": "P2", "slug": "participation", "name": "Participation and co-design", "kind": "practice", "description": "Community involvement, participatory principles, co-design, power and consent, compensation of participants", "items": [], "url": "/participation", "md_url": "/participation.md", "items_count": 0 }, { "id": "P3", "slug": "research-ethics", "name": "Research ethics and data", "kind": "practice", "description": "Consent, privacy, data handling in research, safeguarding during fieldwork", "items": [], "url": "/research-ethics", "md_url": "/research-ethics.md", "items_count": 0 }, { "id": "P4", "slug": "funder-practice", "name": "Funder practice", "kind": "practice", "description": "What to ask for in proposals, how to right-size budgets and timelines, phased and flexible funding, go/no-go points, red flags in proposals", "items": [], "url": "/funder-practice", "md_url": "/funder-practice.md", "items_count": 0 }, { "id": "P5", "slug": "ai-assisted-research", "name": "Using AI in the research itself", "kind": "practice", "description": "The \"minimum viable research\" route with commercial or research AI tools (Perplexity, Elicit and so on), its caveats, and how to check AI output", "items": [], "url": "/ai-assisted-research", "md_url": "/ai-assisted-research.md", "items_count": 0 }, { "id": "P6", "slug": "foundations", "name": "Foundations", "kind": "practice", "description": "Definitions (formative vs design research, Level 0), principles, why it matters, the \"three users is not formative research\" type of misconception", "items": [], "url": "/foundations", "md_url": "/foundations.md", "items_count": 0 } ], "items": [ { "id": "kn-e1-1-connectivity", "title": "Connectivity", "bucket": "digital-ecosystem", "bucket_id": "E1", "item": "E1.1", "topic": null, "question": "Can the intended audience get online reliably enough, often enough and at the speeds the use case needs?", "type": "question", "audiences": [ "all" ], "evidence": "practitioner-consensus", "status": "draft", "reviewed_by": [], "updated": "2026-10-23", "summary": "Find out whether the intended users can get online where and when they would use the tool, and at the speed it needs. Connectivity means a person's own access to a mobile network or the internet. It has three parts: a network signal, a type of network fast enough for the use case (for example 2G, 3G or 4G), and a SIM card that still works. Coverage varies between countries, between towns and rural areas, and between groups such as women and men. Access can also fall as well as rise, with the seasons, after a drought or during political unrest.", "sources": [ { "id": "src-018", "pages": [ 26, 27, 28, 29 ] }, { "id": "src-011", "pages": [ 11 ] }, { "id": "src-032", "pages": [ 9, 10, 15, 16 ] }, { "id": "src-031", "pages": [ 8 ] }, { "id": "src-039", "pages": [ 51, 74, 79 ] }, { "id": "src-004", "pages": [ 17 ] }, { "id": "src-007", "pages": [ 30, 40, 41 ] }, { "id": "src-013", "pages": [ 13 ] }, { "id": "src-024", "pages": [ 6, 31 ] }, { "id": "src-038", "pages": [ 12 ] }, { "id": "src-014", "pages": [ 14 ] }, { "id": "src-005", "pages": [ 3 ] } ], "url": "/digital-ecosystem/connectivity", "md_url": "/digital-ecosystem/connectivity.md" }, { "id": "kn-e1-3-cost-of-use", "title": "Cost of use", "bucket": "digital-ecosystem", "bucket_id": "E1", "item": "E1.3", "topic": null, "question": "Can they afford the device and data the use case requires, and what measures affect this (for example free data offers from mobile operators)?", "type": "question", "audiences": [ "all" ], "evidence": "practitioner-consensus", "status": "draft", "reviewed_by": [], "updated": "2026-10-23", "summary": "Find out whether the intended users can pay for what the tool needs: the phone, its repairs, and the airtime, SMS or data to keep using it. For many people, and for women and girls in particular, the running cost of data can matter more than the price of the phone. A person may own a phone and a SIM and still be unable to use it because there is no credit on it. Cost is tied to who holds the money: women often have less money of their own, so others often pay for their phone and top-ups. Ask, too, what makes the tool cheaper or free to use, such as toll-free numbers or free short codes.", "sources": [ { "id": "src-018", "pages": [ 30, 31, 32, 33, 34 ] }, { "id": "src-020", "pages": [ 18, 60, 66 ] }, { "id": "src-012", "pages": [ 15, 16, 22 ] }, { "id": "src-037", "pages": [ 20 ] }, { "id": "src-015", "pages": [ 37 ] }, { "id": "src-003", "pages": [ 6 ] }, { "id": "src-016", "pages": [ 3 ] }, { "id": "src-038", "pages": [ 12, 17, 21, 22, 27 ] }, { "id": "src-004", "pages": [ 15, 20, 21, 34 ] }, { "id": "src-032", "pages": [ 6, 7, 9, 10 ] }, { "id": "src-039", "pages": [ 16, 37, 39, 74, 79 ] } ], "url": "/digital-ecosystem/cost-of-use", "md_url": "/digital-ecosystem/cost-of-use.md" }, { "id": "kn-e1-6-online-freedom-and-safety", "title": "Online freedom and safety", "bucket": "digital-ecosystem", "bucket_id": "E1", "item": "E1.6", "topic": null, "question": "Is there a history of shutdowns, platform blocking, censorship or surveillance that could affect the use case or put users at risk?", "type": "question", "audiences": [ "all" ], "evidence": "practitioner-consensus", "status": "draft", "reviewed_by": [], "updated": "2026-10-23", "summary": "Find out whether using the tool could expose people to state or non-state control of the internet, or to abuse online. This covers three things. First, whether governments or armed groups cut off networks or power, and when. Second, censorship and surveillance: who owns the networks and who can read what passes over them. Third, online abuse, especially technology-facilitated gender-based violence (TFGBV): harm done or made worse through digital tools, which falls mostly on women and girls. Laws on free speech and privacy matter, but they may not be upheld in practice.", "sources": [ { "id": "src-031", "pages": [ 4, 5, 6 ] }, { "id": "src-032", "pages": [ 11, 18 ] }, { "id": "src-011", "pages": [ 7, 8 ] }, { "id": "src-014", "pages": [ 14, 15, 16, 17, 18, 46 ] }, { "id": "src-019", "pages": [ 7 ] }, { "id": "src-037", "pages": [ 27, 38 ] }, { "id": "src-039", "pages": [ 21 ] }, { "id": "src-010", "pages": [ 10 ] } ], "url": "/digital-ecosystem/online-freedom-and-safety", "md_url": "/digital-ecosystem/online-freedom-and-safety.md" }, { "id": "kn-e1-7-laws-and-regulation", "title": "Laws and regulation", "bucket": "digital-ecosystem", "bucket_id": "E1", "item": "E1.7", "topic": null, "question": "What laws, regulations or policies (data protection, AI policy and so on) may affect the use case?", "type": "question", "audiences": [ "all" ], "evidence": "practitioner-consensus", "status": "draft", "reviewed_by": [], "updated": "2026-10-23", "summary": "Find out which laws, rules and policies apply to the AI tool in each country where it will be used. The main ones are data protection law, any AI-specific law or strategy, and sector rules such as those for health data or bulk messaging. Check national law, not only international frameworks such as the EU AI Act or GDPR (the EU's General Data Protection Regulation). These rules change quickly, so the answer needs checking again during the project.", "sources": [ { "id": "src-010", "pages": [ 3 ] }, { "id": "src-011", "pages": [ 7, 8, 12, 13 ] }, { "id": "src-012", "pages": [ 20, 22, 25 ] }, { "id": "src-013", "pages": [ 8, 9 ] }, { "id": "src-014", "pages": [ 38, 45, 46 ] }, { "id": "src-018", "pages": [ 22 ] }, { "id": "src-024", "pages": [ 6, 7, 90 ] }, { "id": "src-025", "pages": [ 18, 37 ] }, { "id": "src-028", "pages": [ 28, 29 ] }, { "id": "src-032", "pages": [ 10, 11, 21 ] }, { "id": "src-035", "pages": [ 6, 8, 9, 15 ] }, { "id": "src-037", "pages": [ 15, 16, 28, 29, 35, 36 ] }, { "id": "src-030", "pages": [ 21, 22 ] }, { "id": "src-031", "pages": [ 5, 6 ] }, { "id": "src-004", "pages": [ 14 ] }, { "id": "src-039", "pages": [ 43, 88 ] }, { "id": "src-001", "pages": [ 5 ] } ], "url": "/digital-ecosystem/laws-and-regulation", "md_url": "/digital-ecosystem/laws-and-regulation.md" }, { "id": "kn-e2-3-ai-literacy", "title": "AI literacy", "bucket": "ai-trust-norms", "bucket_id": "E2", "item": "E2.3", "topic": null, "question": "How much does the audience understand about AI, how it works, its risks and how to use it well?", "type": "question", "audiences": [ "all" ], "evidence": "practitioner-consensus", "status": "draft", "reviewed_by": [], "updated": "2026-10-23", "summary": "Find out what the intended users understand about AI: what it can and cannot do, that it can be wrong, and how to use it well for this task. The Digital Futures Lab playbook calls this critical AI literacy: an awareness of AI's strengths and limits, fitted to the user's needs and context. AI literacy rests on general digital skills, so find out those too. Many people in low-resource settings lack basic phone skills that designers take for granted. Some users do not realise they are talking to an AI rather than a person.", "sources": [ { "id": "src-028", "pages": [ 15, 44, 61, 62, 63, 64 ] }, { "id": "src-012", "pages": [ 8, 20, 24, 28 ] }, { "id": "src-013", "pages": [ 11, 13 ] }, { "id": "src-003", "pages": [ 7 ] }, { "id": "src-020", "pages": [ 7, 8, 9, 10, 11, 12, 18, 51, 57, 59, 65, 66 ] }, { "id": "src-021", "pages": [ 3, 4 ] }, { "id": "src-023", "pages": [ 1, 3 ] }, { "id": "src-019", "pages": [ 36, 39 ] }, { "id": "src-039", "pages": [ 39 ] } ], "url": "/ai-trust-norms/ai-literacy", "md_url": "/ai-trust-norms/ai-literacy.md" }, { "id": "kn-e2-5-social-norms", "title": "Social norms", "bucket": "ai-trust-norms", "bucket_id": "E2", "item": "E2.5", "topic": null, "question": "How do influential people, organisations or institutions in the audience's life affect their likely use of AI?", "type": "question", "audiences": [ "all" ], "evidence": "practitioner-consensus", "status": "draft", "reviewed_by": [], "updated": "2026-10-23", "summary": "Find out who shapes whether the intended users will try an AI tool, and what those people think about it. Social norms are the unwritten rules a group holds about what behaviour is acceptable. They cover what people believe others do and what they believe others approve of. The people who matter can be close family, such as husbands, parents and in-laws, or community figures such as teachers, health workers and religious leaders. Some of them act as gatekeepers: they can open or close a person's access to new information.", "sources": [ { "id": "src-026", "pages": [ 4, 6, 7, 8, 18 ] }, { "id": "src-022", "pages": [ 1, 2, 4, 5, 6, 7, 8 ] }, { "id": "src-003", "pages": [ 8, 10, 11 ] }, { "id": "src-016", "pages": [ 2, 3 ] }, { "id": "src-004", "pages": [ 13, 33 ] }, { "id": "src-039", "pages": [ 85 ] }, { "id": "src-015", "pages": [ 15, 37, 39 ] }, { "id": "src-028", "pages": [ 21, 22, 53, 54 ] }, { "id": "src-038", "pages": [ 19 ] }, { "id": "src-006", "pages": [ 36 ] }, { "id": "src-027", "pages": [ 34, 35 ] } ], "url": "/ai-trust-norms/social-norms", "md_url": "/ai-trust-norms/social-norms.md" }, { "id": "kn-e3-4-modality", "title": "Modality", "bucket": "language-literacy", "bucket_id": "E3", "item": "E3.4", "topic": null, "question": "Which ways of communicating (text, voice, voice notes, video) does the audience prefer and use comfortably?", "type": "question", "audiences": [ "all" ], "evidence": "practitioner-consensus", "status": "draft", "reviewed_by": [], "updated": "2026-10-23", "summary": "Find out how the intended users prefer to communicate, and which ways they can use with ease: typed text, voice calls, voice notes, images or video. Ask, too, where they get information today and through which channels, such as WhatsApp, radio or a trusted person. The answers differ between countries and within them, by town and countryside, gender, class and ethnic group. Voice channels work on basic phones and suit people who cannot read or are uneasy with text. Some people prefer to get information from a person rather than a tool.", "sources": [ { "id": "src-038", "pages": [ 17, 24 ] }, { "id": "src-039", "pages": [ 36, 37, 38, 85, 87 ] }, { "id": "src-015", "pages": [ 37, 38 ] }, { "id": "src-028", "pages": [ 23, 47 ] }, { "id": "src-020", "pages": [ 20, 28, 30, 31 ] }, { "id": "src-018", "pages": [ 18 ] }, { "id": "src-008", "pages": [ 11 ] }, { "id": "src-031", "pages": [ 2, 8 ] }, { "id": "src-037", "pages": [ 18 ] }, { "id": "src-006", "pages": [ 14, 24, 38 ] }, { "id": "src-027", "pages": [ 34, 35 ] }, { "id": "src-004", "pages": [ 13 ] } ], "url": "/language-literacy/modality", "md_url": "/language-literacy/modality.md" }, { "id": "kn-e3-5-model-performance", "title": "Model performance", "bucket": "language-literacy", "bucket_id": "E3", "item": "E3.5", "topic": null, "question": "How well do the proposed language models perform in the audience's languages, code-switching and modalities?", "type": "question", "audiences": [ "all" ], "evidence": "practitioner-consensus", "status": "draft", "reviewed_by": [], "updated": "2026-10-23", "summary": "Find out how well the AI models a project plans to use work in the users' own languages, in the way they mix languages, and in the modes they use, such as voice. Most language models work best in English and other widely written languages, and have mostly been used through typed text. Speech models are making voice tools more feasible, but many low-resource languages, often mainly spoken, are still poorly covered. A vendor's claim that a language is \"supported\" says little on its own. Ask for evidence of how quality differs between languages.", "sources": [ { "id": "src-008", "pages": [ 9, 11, 12, 25, 37, 38, 39, 40 ] }, { "id": "src-007", "pages": [ 35 ] }, { "id": "src-011", "pages": [ 9 ] }, { "id": "src-012", "pages": [ 10, 11, 17, 23, 24 ] }, { "id": "src-013", "pages": [ 10 ] }, { "id": "src-015", "pages": [ 19, 38 ] }, { "id": "src-028", "pages": [ 26, 40, 43, 44 ] }, { "id": "src-024", "pages": [ 82, 84, 87, 101 ] } ], "url": "/language-literacy/model-performance", "md_url": "/language-literacy/model-performance.md" }, { "id": "kn-e5-1-similar-initiatives", "title": "Similar initiatives", "bucket": "landscape", "bucket_id": "E5", "item": "E5.1", "topic": null, "question": "Which local or international development organisations have built, or are building, a similar use case in the same context?", "type": "question", "audiences": [ "all" ], "evidence": "practitioner-consensus", "status": "draft", "reviewed_by": [], "updated": "2026-10-17", "summary": "Find out who else has built, or is building, a tool for the same problem with the same kind of users in the same place. Look at local groups, international agencies, government and private firms, and at the applicant's own organisation. Include other donors funding the same issue, and government policies and sector strategies the tool should support. For each one, find out what they built, how it went and what they learned. Then decide whether the new project should reuse, join, partner with or step back from that work, rather than start from nothing.", "sources": [ { "id": "src-004", "pages": [ 10, 14 ] }, { "id": "src-039", "pages": [ 13, 16, 22, 40, 60 ] }, { "id": "src-012", "pages": [ 10, 11, 21 ] }, { "id": "src-037", "pages": [ 13 ] }, { "id": "src-030", "pages": [ 35, 37 ] }, { "id": "src-031", "pages": [ 9 ] }, { "id": "src-008", "pages": [ 5, 14 ] }, { "id": "src-010", "pages": [ 3, 4 ] }, { "id": "src-025", "pages": [ 18 ] }, { "id": "src-028", "pages": [ 20, 23, 25 ] }, { "id": "src-006", "pages": [ 36 ] }, { "id": "src-015", "pages": [ 10, 19, 23 ] }, { "id": "src-024", "pages": [ 29, 44, 63 ] } ], "url": "/landscape/similar-initiatives", "md_url": "/landscape/similar-initiatives.md" }, { "id": "kn-e7-bias-and-fairness", "title": "Bias and fairness", "bucket": "risk-safety", "bucket_id": "E7", "item": null, "topic": "bias-and-fairness", "question": "Will the tool work as well, and as safely, for women, poorer, older, rural and minority-language users as for others, and how will the team find out?", "type": "question", "audiences": [ "all" ], "evidence": "practitioner-consensus", "status": "draft", "reviewed_by": [], "updated": "2026-10-17", "summary": "Bias, here, means an AI tool treats some groups worse than others in a systematic way, often with no one intending it. Level 0 work should find out which groups the tool may serve badly, such as women, poorer, older, rural, disabled or minority-language users, and why. It should also say how the team will check performance for each of those groups, not only on average. A tool can be popular and cheap to run and still leave some groups further behind.", "sources": [ { "id": "src-001", "pages": [ 4, 6 ] }, { "id": "src-003", "pages": [ 9, 12 ] }, { "id": "src-007", "pages": [ 7 ] }, { "id": "src-011", "pages": [ 10 ] }, { "id": "src-013", "pages": [ 6, 10 ] }, { "id": "src-015", "pages": [ 14, 15, 31, 38, 44 ] }, { "id": "src-019", "pages": [ 9, 12 ] }, { "id": "src-024", "pages": [ 105, 126, 127, 128 ] }, { "id": "src-025", "pages": [ 7, 9, 18, 30, 33 ] }, { "id": "src-028", "pages": [ 8, 26, 40 ] }, { "id": "src-029", "pages": [ 9, 20, 21 ] }, { "id": "src-030", "pages": [ 31, 32 ] }, { "id": "src-035", "pages": [ 13, 15, 16 ] }, { "id": "src-036", "pages": [ 2 ] }, { "id": "src-037", "pages": [ 21 ] } ], "url": "/risk-safety/bias-and-fairness", "md_url": "/risk-safety/bias-and-fairness.md" }, { "id": "kn-e7-harm-and-risk", "title": "Harm scenarios and risk assessment", "bucket": "risk-safety", "bucket_id": "E7", "item": null, "topic": "harm-scenarios", "question": "What could go wrong for users and others if the tool is built, how likely and severe is each harm, and how will the team prevent and respond to it?", "type": "question", "audiences": [ "all" ], "evidence": "practitioner-consensus", "status": "draft", "reviewed_by": [], "updated": "2026-10-17", "summary": "Before an AI tool is built, the team should write down how it could hurt the people who use it and the people around them. For each harm, they should judge how likely it is and how bad it would be, then decide what they will do to prevent it and how they will respond if it happens anyway. Harms can be direct or indirect, and intended or accidental. They include false or unsafe advice, privacy breaches, fraud, violence enabled by technology, and effects on physical and mental health.", "sources": [ { "id": "src-001", "pages": [ 4, 5, 6 ] }, { "id": "src-003", "pages": [ 3, 5 ] }, { "id": "src-004", "pages": [ 13 ] }, { "id": "src-010", "pages": [ 10 ] }, { "id": "src-011", "pages": [ 9 ] }, { "id": "src-012", "pages": [ 15, 16, 17, 21 ] }, { "id": "src-013", "pages": [ 11, 15 ] }, { "id": "src-014", "pages": [ 12, 13, 27, 35, 40, 42, 45, 66 ] }, { "id": "src-015", "pages": [ 39, 45 ] }, { "id": "src-017", "pages": [ 1, 3, 5, 6 ] }, { "id": "src-019", "pages": [ 11, 12, 14, 21, 46, 47 ] }, { "id": "src-024", "pages": [ 1, 9, 55, 62, 71, 83, 85, 93, 135 ] }, { "id": "src-028", "pages": [ 22, 23, 24, 58 ] }, { "id": "src-029", "pages": [ 12, 13, 22, 23 ] }, { "id": "src-031", "pages": [ 2 ] }, { "id": "src-034", "pages": [ 3, 4 ] }, { "id": "src-035", "pages": [ 10, 11, 12, 14, 17 ] }, { "id": "src-037", "pages": [ 26, 27, 58 ] }, { "id": "src-038", "pages": [ 23, 25, 26 ] } ], "url": "/risk-safety/harm-and-risk", "md_url": "/risk-safety/harm-and-risk.md" }, { "id": "kn-e8-non-ai-alternatives", "title": "Non-AI alternatives", "bucket": "problem-alternatives", "bucket_id": "E8", "item": null, "topic": "non-ai-alternatives", "question": "Would a simpler, non-AI or non-digital option meet the need as well, and why is AI the better choice here?", "type": "question", "audiences": [ "all" ], "evidence": "practitioner-consensus", "status": "draft", "reviewed_by": [], "updated": "2026-10-23", "summary": "Before funding an AI tool, find out what else could meet the same need. Options include changing how work is done, a basic digital tool, more training, more staff, a policy change, or doing nothing new. A team should list these options with the benefits, limits and risks of each, and say with evidence why AI does better. If it cannot, the project may work as well or better without AI. The separate page on problem definition covers how to state the problem itself.", "sources": [ { "id": "src-001", "pages": [ 1 ] }, { "id": "src-004", "pages": [ 16 ] }, { "id": "src-006", "pages": [ 25, 29, 39 ] }, { "id": "src-007", "pages": [ 18 ] }, { "id": "src-012", "pages": [ 22, 24 ] }, { "id": "src-015", "pages": [ 20, 21, 22, 24, 43, 44 ] }, { "id": "src-016", "pages": [ 3 ] }, { "id": "src-024", "pages": [ 11, 38, 43, 62, 63, 135 ] }, { "id": "src-025", "pages": [ 18 ] }, { "id": "src-028", "pages": [ 13, 15, 18 ] }, { "id": "src-030", "pages": [ 6, 29, 30, 44 ] }, { "id": "src-032", "pages": [ 10 ] }, { "id": "src-035", "pages": [ 12 ] }, { "id": "src-038", "pages": [ 24, 28 ] }, { "id": "src-039", "pages": [ 29 ] } ], "url": "/problem-alternatives/non-ai-alternatives", "md_url": "/problem-alternatives/non-ai-alternatives.md" }, { "id": "kn-e8-problem-definition", "title": "Problem definition", "bucket": "problem-alternatives", "bucket_id": "E8", "item": null, "topic": "problem-definition", "question": "Is the problem clearly defined, with and by the people who have it, before any solution is chosen?", "type": "question", "audiences": [ "all" ], "evidence": "practitioner-consensus", "status": "draft", "reviewed_by": [], "updated": "2026-10-23", "summary": "Before anyone picks a tool, the team should be able to say what problem it is solving, for whom, and how they know. The problem should be one specific, observable difficulty in people's lives or work, not a broad aim such as \"better health\". The people who live with the problem should have helped name it, and should recognise the description. Only once the problem is clear does it make sense to ask whether AI, or any technology, has a part in solving it.", "sources": [ { "id": "src-004", "pages": [ 10, 27, 28 ] }, { "id": "src-006", "pages": [ 37, 38, 74 ] }, { "id": "src-007", "pages": [ 6, 10, 14, 15 ] }, { "id": "src-008", "pages": [ 13, 14 ] }, { "id": "src-012", "pages": [ 22 ] }, { "id": "src-015", "pages": [ 7, 16 ] }, { "id": "src-024", "pages": [ 62, 63, 74 ] }, { "id": "src-025", "pages": [ 37 ] }, { "id": "src-027", "pages": [ 18, 27, 31, 32, 36 ] }, { "id": "src-028", "pages": [ 14 ] }, { "id": "src-030", "pages": [ 10, 11, 12 ] }, { "id": "src-032", "pages": [ 6 ] }, { "id": "src-037", "pages": [ 13 ] }, { "id": "src-039", "pages": [ 13, 27, 28, 45 ] } ], "url": "/problem-alternatives/problem-definition", "md_url": "/problem-alternatives/problem-definition.md" }, { "id": "kn-e9-partner-capacity", "title": "Partner capacity", "bucket": "enabling-environment", "bucket_id": "E9", "item": null, "topic": "partner-capacity", "question": "Do the implementing partners have the skills, staff, systems and time to build, run and look after an AI tool responsibly?", "type": "question", "audiences": [ "all" ], "evidence": "practitioner-consensus", "status": "draft", "reviewed_by": [], "updated": "2026-10-17", "summary": "Find out whether the organisations that will build and run the tool can actually do it. That means the right mix of people, enough staff time, working equipment and power, and leaders who back the change. Look at the partner as it works in practice, not only at its organogram (a chart of who reports to whom). Check that the team understands the problem and the community as well as the technology. Running costs, maintenance and long-term sustainability are separate topics.", "sources": [ { "id": "src-006", "pages": [ 64 ] }, { "id": "src-007", "pages": [ 11 ] }, { "id": "src-012", "pages": [ 21, 23 ] }, { "id": "src-014", "pages": [ 62 ] }, { "id": "src-015", "pages": [ 33, 34 ] }, { "id": "src-024", "pages": [ 20, 22, 55, 66 ] }, { "id": "src-025", "pages": [ 10, 16 ] }, { "id": "src-027", "pages": [ 52, 56 ] }, { "id": "src-028", "pages": [ 24, 25, 66 ] }, { "id": "src-031", "pages": [ 3, 4 ] }, { "id": "src-032", "pages": [ 12, 19, 32 ] }, { "id": "src-034", "pages": [ 5 ] }, { "id": "src-037", "pages": [ 43, 49 ] }, { "id": "src-039", "pages": [ 40, 48, 54 ] }, { "id": "src-011", "pages": [ 5 ] }, { "id": "src-030", "pages": [ 33 ] } ], "url": "/enabling-environment/partner-capacity", "md_url": "/enabling-environment/partner-capacity.md" } ] }