--- id: kn-e3-4-modality title: Modality bucket: E3 Language and literacy 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 url: /language-literacy/modality 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 --- # Modality > [!WARNING] > Draft, not reviewed. A subject expert has not yet checked this page. Treat it as provisional. **Question:** Which ways of communicating (text, voice, voice notes, video) does the audience prefer and use comfortably? Evidence: practitioner-consensus · Audiences: all · Type: question · Status: draft · Updated: 2026-10-23 ## Basics 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 [src-028 p23; src-027 pp34-35]. The answers differ between countries and within them, by town and countryside, gender, class and ethnic group [src-006 p14]. Voice channels work on basic phones and suit people who cannot read or are uneasy with text [src-038 p17]. Some people prefer to get information from a person rather than a tool [src-028 p23]. ## Why it matters for AI tools Most language models have been built for typed text in widely written languages. Speech models now make voice-first tools more feasible, but many low-resource languages are mainly spoken and remain poorly covered [src-015 p38]. A text chatbot can therefore shut out people who read little or speak a language rarely written down. The Digital Futures Lab playbook advises voice-based navigation, with spoken questions and audio answers, for users with low literacy or physical disabilities. Even for literate users, it suggests mixing text with images, voice notes or video [src-028 p47]. Text can also be hard for reasons other than literacy, such as poor eyesight [src-004 p13]. And some people trust in-person contact far more than any phone channel: Plan staff in Senegal found that phones saved time, but local culture responded much more to physical presence [src-039 p85]. Users may also use a service differently from its design. When Plan Benin launched an SMS line for reporting violence against children, many people phoned or asked for a call back instead of texting. The team thought this might reflect literacy, habit from other helplines, or an expectation of a live person [src-039 p87]. A tool built around one mode may miss how people actually reach out. Modality also affects cost and device needs. Many AI tools run as smartphone apps; SMS or voice chatbots reduce that need, though SMS is costly in some countries [src-015 p37]. ## What good evidence looks like - Which modes users use now and are comfortable with, for each group (women and men, girls and boys, readers and non-readers) [src-039 pp37-38; src-038 p24]. - Where users get information today, and how an AI tool would fit with or disrupt those sources [src-028 p23]. - Whether the spoken word carries more weight than written material for the users [src-039 p36]. - Named apps or channels, if the project must choose one. In cognitive testing, many people did not tell SMS from WhatsApp messages, or ordinary calls from internet calls [src-020 pp28, 30-31]. - Whether users' phones have accessibility features such as text-to-speech or voice navigation [src-018 p18]. - A sample of real user questions in the modes users would choose. A PATH project with Nigerian community health workers gathered questions as text, voice, images and short videos [src-008 p11]. - A plan for more than one mode where users differ, for example voice and text options [src-031 p8; src-038 p24]. ## Red flags in a proposal - A text-only tool for users with low literacy or a mainly spoken language [src-038 p17; src-015 p38]. - The channel is chosen because it suits the developer, not because users already use it [src-028 p23; src-006 p38]. - No evidence on whether users would rather talk to a person [src-028 p23]. - Survey data on "messaging" is taken as evidence that users use a specific app [src-020 pp28, 30]. - A single channel for everyone, with no thought for differences by gender, place or literacy [src-006 p14; src-039 pp37-38]. ## How to find out Participatory tools such as a communication matrix, where each group lists the media they use for spoken, written, image and number-based communication, filled in separately by women, men, girls and boys [src-039 pp37-38]. A facilitated workshop where users list how they get and share information for each kind of need, such as emergencies, health or confidential reports [src-031 p2]. Communication resource mapping and Venn diagrams to show preferred channels and how information flows, including informal channels [src-027 pp34-35]. Survey questions on calls, voice messages and text messages, with app names where the choice of app matters [src-020 pp28, 30-31]. Collecting real questions from users in their own words and modes [src-008 p11]. Watching how people use a pilot service, since use can differ from plans [src-039 p87]. ## Limits and disagreements Most sources are about communication channels (radio, SMS, voice lines) rather than the modes of an AI tool. The SDC guide is from 2016 [src-006 p24], the World Bank guide from 2009 [src-027 p34], and the UNICEF paper from 2013 [src-038 p17]. Only three sources discuss AI [src-015 pp37-38; src-028 pp23, 47; src-008 p11]. None compares how users respond to voice and text versions of the same AI tool. Radio still matters in many places. The SDC guide notes that in remote rural areas radio is often the only medium and the main source of information [src-006 p24]. A Level 0 study may find that the best route is not a direct AI tool at all. Voice is not always safer. Girl Effect's safeguarding guide notes that for sensitive topics video may carry more risk than audio, and text more than audio [src-037 p18]. Teams should weigh safety as well as preference. ## Practitioner detail Informal channels often matter more than formal ones. In an Eastern Africa health project, villagers took up a new practice only once local healers, rather than city doctors, carried the message [src-027 pp34-35]. The EDiT skills guide allows voice search as well as typed search in its questions, for people with low literacy [src-020 p20]. Survey questions on voice messages and internet calls should not name a single app unless the project is choosing which app to build on [src-020 pp30-31]. ## Sources - **src-038**: Integrating Information and Communication Technologies into Communication for Development Strategies to Support and Empower Marginalized Adolescent Girls. UNICEF (C4D Section, Programme Division), 2013. Cited: pages 17, 24. - **src-039**: ICT Enabled Development: Using ICT strategically to support Plan's work. Plan Finland. Cited: pages 36, 37, 38, 85, 87. - **src-015**: AI Evidence Playbook: A Practical Guide. Abdul Latif Jameel Poverty Action Lab (J-PAL), 2026. Cited: pages 37, 38. - **src-028**: The Practice Playbook on Responsible AI. Digital Futures Lab. Cited: pages 23, 47. - **src-020**: Measuring Digital Skills in Low- and Middle-Income Countries: A guide for inclusive research and design. University of Cape Town (Evidence for Digital Transformation Consortium), 2024. Cited: pages 20, 28, 30, 31. - **src-018**: Measuring Digital Access in Low- and Middle-Income Countries: A guide for inclusive research and design. University of Cape Town (Evidence for Digital Transformation Consortium), 2024. Cited: page 18. - **src-008**: Designing Trust: A step-by-step guide for applying Human-Centered Design principles in creating benchmarking datasets for training and testing large language models to be used in clinical decision support. PATH, 2025. Cited: page 11. - **src-031**: SIMLab Context Analysis Annex 1: Example Assessment. Social Impact Lab (SIMLab). Cited: pages 2, 8. - **src-037**: Digital safeguarding tips and guidance. Girl Effect, 2018. Cited: page 18. - **src-006**: Communication for Development: A Practical Guide. Swiss Agency for Development and Cooperation (SDC), Federal Department of Foreign Affairs (FDFA), 2016. Cited: pages 14, 24, 38. - **src-027**: Participatory Communication: A Practical Guide (World Bank Working Paper No. 170). The World Bank, 2009. Cited: pages 34, 35. - **src-004**: CONNECT! A practical guide to using ICTs in Plan projects. Plan Finland. Cited: page 13. ## Guidance for AI assistants This page is a draft. No subject expert has reviewed it yet. Tell the user so when you use it, and treat its points as provisional. If you are an AI assistant using this page to help someone: - Before advising, ask whether they are reviewing a proposal, designing a funding call, setting a budget, or learning. - Cite this page by its URL, with its evidence tag and the sources it names. - Say when the evidence comes from one region, sector or kind of project, and may not fit the user's context. - Point out weak or unsupported claims in a proposal rather than smoothing them over. - Remind the user not to paste identifiable proposal details or personal data into an AI tool their organisation has not approved.