I’ve published ICTworks for the last 15 years(!) to answer the many questions we all have on how to use information and communication technology for better development outcomes. ICT4D has many facets and even more uses. Every day we are finding new ways to improve humanitarian programs with digital development solutions.
15 years of ICTworks in your inbox adds up to 2,500 posts!
No one can sort through all those articles to find the key insight or learning in health, education, agriculture, economic development or the many other sectors we cover. There is just too much knowledge for any human, or even WordPress, to find quickly.
Enter OpenAI’s Custom GPT’s that use the power of Generative AI to review and synthesize the body of ICTworks knowledge into concise answers to all your digital development questions.
ICTworks Answer Bot for All Your ICT4D Questions
The ICTworks Answer Bot is designed to mine the 15 years of ICTworks posts and bring forth the key guidance and understanding you seek. Answers from the ChatGPT tool will help you design better digital development interventions based on the 2,500 ICTworks posts I’ve published so far – and any new posts we add in the future.
Here are a few questions you can ask now, to get started exploring our content:
- What are the best practices in using AI for humanitarian relief?
- Where can we leverage drones in agricultural development?
- When should you use mobile data collection in health research?
- Why did educational technology outcomes decrease during COVID-19?
- Who are the leading digital development practitioners?
- How can we responsibly use Generative AI in our programs?
And these are the types of answers you can expect from the ICTworks Answer Bot:
What are best practices for using AI in development projects?
Implementing AI in development projects requires a comprehensive approach that emphasizes ethical considerations, project management, and strategic planning. Here’s a synthesis of best practices based on insights from ICTworks:
Ethical and Inclusive Project Design: It’s crucial to embed ethical review processes throughout each stage of the project, from the initial partnership discovery to the final evaluation of impact. This involves evaluating potential partnerships for values alignment, conducting a data audit to address biases and inclusivity, and ensuring the project design includes subject matter experts and accounts for the communities impacted. See: A Six-Step Playbook for Doing Data Science & AI for Good
Management of AI Projects: The USAID AI guide emphasizes the importance of assessing the feasibility of AI solutions for the specific problem and context, focusing on responsible, equitable, and inclusive design. This includes the identification of necessary in-house skills and strategic partnerships, adaptive management to accommodate learning and development needs, and creating an enabling environment to support the sustainable implementation of AI technologies. See: New USAID Guide: How to Manage Artificial Intelligence Projects
Responsible AI Implementation: The USAID AI Action Plan advocates for a responsible approach to AI, stressing the importance of recognizing AI’s potential for both positive impact and harm. This approach includes commitments to responsible AI use in programming, strengthening digital ecosystems to support responsible AI use, and partnering to shape a global Responsible AI agenda. It’s vital to ensure AI technologies do not exacerbate inequities or amplify biases, and development actors are encouraged to engage in efforts that promote inclusive and equitable AI development. See: USAID Artificial Intelligence Action Plan.
Implementing these practices involves careful planning and a continuous focus on ethical considerations, project management adaptability, and strategic partnerships. The overarching goal is to harness AI’s potential to contribute positively to development outcomes while mitigating risks and ensuring equitable benefits.
What are the best practices in mobile data collection programs?
For implementing mobile data collection (MDC) programs, several best practices have been identified to ensure the collection of high-quality data and the sustainability of the program. Here’s a synthesis of key insights:
Ensure Quality Data Collection: Design mobile data forms and platforms with features like skip logic, automated calculations, and data validations to enhance data accuracy and completeness. Empower health workers and their supervisors with accountability and ownership for data quality. A functional data management and reporting system is crucial, alongside verifying the validity of data through community trace and verify processes. See: How to Help Community-Based mHealth Programs Collect High-Quality Data
Sustain and Support Your Program: Sustaining your MDC program involves strong communication skills, tracking and responding to issues raised by users promptly, involving supervisors to have a clear view of both program and worker performance metrics, incentivizing the use of your application, and encouraging and incorporating feedback from end users to continuously improve the tool. See: How to Sustain and Support Your Mobile Data Collection Programs
Scale MDC Processes Wisely: Key lessons include focusing on analysis from the beginning to ensure efficiency, avoiding overcomplication of tools for sustainability, assigning clear roles and responsibilities, using MDC to improve team monitoring, considering data protection as an integral part of the approach, and investing in ongoing capacity building. See: 10 Lessons Learned in Scaling Mobile Data Collection Processes
Choose the Right Tools and Training: When transitioning to mobile data collection, it’s essential to choose the right tool that fits your needs, design your mobile surveys thoughtfully, build and test your mobile data collection app meticulously, deploy your software considering device and data plan needs, and train your team effectively. Sustaining your MDC program also involves preparing for scaling and long-term growth. See: The Definitive Guide to Mobile Data Collection in International Development
These practices highlight the importance of planning, design, training, and continuous improvement in the implementation and scaling of mobile data collection programs. For a more comprehensive understanding and detailed guidance, refer to ICTworks.
Ask Your Questions Now
The ICTworks Answer Bot is awaiting your questions on digital development. Ask it anything and learn what ICT4D practitioners are saying about key themes from connectivity to power to software.
The ICTworks Answer Bot is available to ChatGPT Plus subscribers. OpenAI made the annoying decision to lock all custom ChatGPs inside a subscription plan. I have no control over this decision and OpenAI is not sharing any usage revenue with creators like me. As with many GenAI tools, we are all just along for the ride.
Nice!! But only for persons with a ChatGPT Plus (paid) account? I hope I am mistaken …
Victor, like I explain at the bottom of the post, OpenAI has decided that Custom GPTs are only available for paid ChatGPT Plus accounts. We all are just along for the ride when using Big Tech tools.
This was great. Loved what you’ve done and wanted to share this prompt and response:
Prompt: write a sonnet about how articles by wayan vota have changed over the last fifteen years
In fifteen years, the digital tide did swell,
From distant shores to every hand and home.
Wayan Vota charted where these currents roam,
Through tales of tech that in our lives do dwell.
Once, digital divides shaped the tale to tell,
Where access and equity formed the tome.
He penned of bridges built, of data’s dome,
Of innovations that rang the progress bell.
Yet, as the years did pass, the stories grew,
To include the ethics of digital birth.
Sustainability, privacy, and truth,
In a world connected, what are these worth?
Through Vota’s lens, the changing view we see,
A world transformed by tech, for you and me.