Language AI Playbook
  • 1. Introduction
    • 1.1 How to use the partner playbook
    • 1.2 Chapter overviews
    • 1.3 Acknowledgements
  • 2. Overview of Language Technology
    • 2.1 Definition and uses of language technology
    • 2.2 How language technology helps with communication
    • 2.3 Areas where language technology can be used
    • 2.4 Key terminology and concepts
  • 3. Partner Opportunities
    • 3.1 Enabling Organizations with Language Technology
    • 3.2 Bridging the Technical Gap
    • 3.3 Dealing with language technology providers
  • 4. Identifying Impactful Use Cases
    • 4.1 Setting criteria to help choose the use case
    • 4.2 Conducting A Needs Assessment
    • 4.3 Evaluating What Can Be Done and What Works
  • 5 Communication and working together
    • 5.1 Communicating with Communities
    • 5.2 Communicating and working well with partners
  • 6. Language Technology Implementation
    • 6.1 Navigating the Language Technology Landscape
    • 6.2 Creating a Language-Specific Peculiarities (LSP) Document
    • 6.3 Open source data and models
    • 6.4 Assessing data and model maturity
      • 6.4.1 Assessing NLP Data Maturity
      • 6.4.2 Assessing NLP Model Maturity:
    • 6.5 Key Metrics for Evaluating Language Solutions
  • 7 Development and Deployment Guidelines
    • 7.1 Serving models through an API
    • 7.2 Machine translation
      • 7.2.1 Building your own MT models
      • 7.2.2 Deploying your own scalable Machine Translation API
      • 7.2.3 Evaluation and continuous improvement of machine translation
    • 7.3 Chatbots
      • 7.3.1 Overview of chatbot technologies and RASA framework
      • 7.3.2 Building data for a climate change resilience chatbot
      • 7.3.3 How to obtain multilinguality
      • 7.3.4 Components of a chatbot in deployment
      • 7.3.5 Deploying a RASA chatbot
      • 7.3.6 Channel integrations
        • 7.3.6.1 Facebook Messenger
        • 7.3.6.2 WhatsApp
        • 7.3.6.3 Telegram
      • 7.3.7 How to create effective NLU training data
      • 7.3.8 Evaluation and continuous improvement of chatbots
  • 8 Sources and further bibliography
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3. Partner Opportunities

Chapter 3 Overview: In this chapter, the playbook explores the numerous opportunities that language technology offers to organizations aiming to enhance efficiency and broaden their reach. By integrating language technology into their operations, organizations can utilize applications such as search engines and chatbots to provide information and amplify the voices of those they serve in accessible ways.

The chapter delves into several real-world examples of language technology applications developed by CLEAR Global, showcasing their impact across various sectors. These examples include TILES, a voice-enabled AI kiosk for climate resilience in rural areas; Kompas, an AI solution for crisis response in Ukraine; MT Rwanda, a machine translation initiative improving learning experiences; Shehu, a chatbot addressing COVID-19 queries in Nigeria; and a multilingual chatbot facilitating business registration in Kenya.

Additionally, the playbook highlights non-CLEAR Global examples like Me Bote na Conversa, a chatbot translating corporate terms in Brazil; and MAIA, a chatbot combatting gender-based harassment in Brazil. It also introduces UNICEF's U-Report Information Chatbot, fostering youth engagement.

The chapter emphasizes the importance of bridging the technical gap within organizations, providing principles and best practices for impactful solutions. It underscores the significance of a user-centered approach, well-defined use cases, and continuous user involvement.

Furthermore, the playbook guides organizations in engaging with language technology providers. It suggests considering factors such as expertise, collaborative attitude, resource availability, values alignment, past collaborations, communication skills, geographic considerations, size and scale, and network reach when selecting a partner. The playbook recommends appointing a dedicated team to ensure effective communication and collaboration between technical and non-technical teams, especially in the development of language technology solutions.

This section of the playbook requires little or no technical expertise and has been designed to be plain and concise with a focus on introducing language technology and how it can be integrated into programs, for organizations looking to use language AI for community engagement.

Language technology presents opportunities for organizations to enhance their efficiency and reach. By integrating language technology into their processes, organizations can use applications such as internet search engines, spoken language dialog systems (e.g., chatbots), and much more. With language technology, organizations can help many more of the people they serve get information or have their voices heard, in ways that are simple and accessible.

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