Concern 766 · Working draft · editorial review in progress

AI-in-development narratives

AI development projects can weaken local capacity when outside tools and priorities replace local expertise instead of helping it grow.

Understanding the concern

A project advertised as helping a community may depend on a foreign vendor for operation, repairs and decisions about data. If local staff cannot maintain it or adapt it, the service may become fragile when funding ends. A useful demonstration is not the same as a lasting ability to solve local problems.

UNCTAD emphasizes infrastructure, data and skills as foundations for inclusive AI development. Think of donating a machine without training mechanics or supplying parts. A stronger project starts with the community's own goals, pays attention to existing knowledge and plans for ongoing control and maintenance. Success can mean more local capability, even when that requires a simpler tool.

An example

An AI pilot ends when its grant expires because local staff have no access to maintain the system or move its data.

Illustrative unless identified as a documented case.

Words in plain English

AI
Software that learns patterns from examples or uses rules to perform tasks such as recognizing images or generating text. It can make mistakes and does not understand every situation as a person would.
Training
The process of using examples to shape how an AI model behaves. Learning patterns from material does not establish that the material is true or fair.

Evidence and its limits

This is an application of development principles, not a claim that every externally funded AI project displaces local expertise.

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Broader frameworks and background

These resources provide context. They do not establish every claim in this concern.

A question to discuss

What skills, ownership and practical choices will remain with the community after the project ends?

Keep track of different views, what needs checking, and any next step in your own discussion notes.

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Principles for the conversation

Before you finish · reflect together

Virtues and principles to consider

Virtues are qualities we practice in how we treat people and make choices. They are not scores for judging someone. Use these ideas to explore what a thoughtful response could look like.

Justice

Justice means fair treatment, fair procedures, and attention to who receives benefits and burdens. It asks whether people with less power can be heard and seek repair.

Look at outcomes across different groups and individual cases. Provide a usable way to challenge decisions and correct harm. Equal wording in a policy does not guarantee equal treatment in practice.

Ask together: Who benefits, who bears the cost, and who can challenge the decision?

Solidarity

Solidarity means standing with people whose lives are affected, especially when they have less power to protect their interests. It turns concern into a willingness to share responsibility.

Include affected people in decisions and support practical remedies when something goes wrong. Do not leave the cost of learning or repair entirely with those who were harmed.

Ask together: What would it mean to stand with the people carrying the greatest burden?

Service

Service means using abilities and resources to meet real needs. It asks whether the people meant to benefit actually receive help, rather than treating them as a means to another goal.

Speak with the people the project is meant to serve. Notice burdens it may add, such as extra checking or confusing forms. Judge success by their experience as well as the organization's targets.

Ask together: Who is this meant to serve, and do they experience it as helpful?

Editorial ratings

These are editorial judgments from the register, not measured probabilities or predictions about your situation.

Severity
Serious · 3/5
Likelihood
Widely observed · 4/5
Time horizon
Now
Register risk score
12
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