Using LLMs ethically

The bigger picture

A small digression, before we dig in.

Insofar as possible, this blog isn’t overly political, normally focusing on technical topics and implementations. But caught up in the zeitgeist of the times, the subject of LLM usage is inescapable.

Most people seem to care about how they can use them effectively, to maximise productivity, automate away labour, and other things. The angle of this blog is different: I want to talk about ethics.

But before we get there, we need to zoom out a little.

Can we live life virtuously?

Sure, if you can afford it.

I can choose vegetarianism on moral grounds because of extremely fortunate positions:

• I was born in a liberal democracy.
• I am not living in abject poverty.
• I have time and education to read about animal welfare and climate science.
• I have access to varied food options.

A child born into extreme poverty in South Sudan does not have the luxury of philosophising about the suffering of livestock. Survival comes first.

Ethics is often downstream of privilege. This raises a difficult question: should we hold everyone globally to the same ethical standards? If ethics requires surplus time, energy, money, and education, then it is unevenly distributed by default.

We should remember at all times that our moral judgments should be tempered with humility.

Which hills are we willing to die on?

We all make ethically dubious choices constantly.

• Saying we “care deeply” about climate change while booking another short-haul flight.
• Buying from Amazon while knowing about the treatment of workers and market control issues.
• Using social media platforms we know are harmful to teens.
• Scrolling past news of a humanitarian crisis because we feel overwhelmed.
• Eating food we know was produced in ways we wouldn’t want to witness.
• Not acknowledging a homeless person that just spoke to you.
• Using “I’m busy” as a shield against civic responsibility.
• Buying cheap clothes that were probably not produced under great labour conditions.
• Staying silent in a conversation when speaking up would be socially costly.

How can we live with ourselves?

Because we are deeply human and life is inherently tragic.

No one can optimise for every moral dimension simultaneously. Philosophers from Aristotle to Herbert Simon have argued that the reasonable standard is not perfection, but deliberate satisficing: making the best available choice given real constraints, and owning it.

What can we realistically strive for?

So what remains?

• Awareness.
• Deliberation.
• Intentional trade-offs.
• A willingness to accept responsibility.

We just do our best given the circumstances. Nobody is a saint.

This framing matters when we start talking about LLMs.

Creating an ethical usage framework for LLMs

• We need a way to reason about LLM usage that acknowledges trade-offs instead of pretending they don’t exist.
• While working within the tech team of an NGO, we have been deliberating this dilemma.
• Full details can be found here: https://github.com/hotosm/docs/pull/21

Getting crushed in the wheels of the hype train

There is enormous pressure right now.

If you don’t use LLMs, you’re:

• Inefficient.
• Old-fashioned.
• “Falling behind.”

This narrative is powerful, especially in tech.

And to be fair, there’s something to it. Defenders of aggressive LLM adoption have a reasonable case: these tools can meaningfully reduce time spent on low-value repetitive tasks, free up human attention for higher-order work, and (in resource-constrained organisations) stretch limited capacity further.

The ethical question isn’t whether benefits can be found. But these tools can be used (i) deliberately (ii) compulsively (iii) through acquiescence.

I am advocating for more thoughtful and reflective consideration of our actions (a tough sell, considering this isn’t the default state of humanity).

Energy usage: a red herring?

Energy consumption is frequently cited as the core ethical issue.

There is something to this, as data centres consume significant power. Companies like OpenAI, Google, and Microsoft operate vast compute infrastructure to train and serve models.

But we need proportionality.

If you:

• Fly multiple times per year,
• Own and regularly drive a car,
• Heat a large home,
• Consume meat frequently,
• Participate fully in consumer culture,

…then your LLM usage is probably not your largest environmental impact.

It doesn’t make this irrelevant, but there are deeper concerns (listed in the framework discussion linked above).

Genuine concerns

I won’t dive too deeply into this, as the linked framework doc covers in more detail.

The digital divide is perhaps the most structurally troubling issue. Access to these tools is strongly unequal. Wealthy individuals and organisations in high-income countries gain productivity advantages that compound over time, while communities without reliable internet, hardware, or the educational background to use these tools effectively fall further behind.

This isn’t a new dynamic, as it mirrors historical patterns of technological colonialism, but LLMs accelerate it. For those of us in privileged positions, benefiting from these tools without any consideration of that asymmetry is a form of indifference worth highlighting.

Other major concerns, explored in depth in the linked discussion, include:

• IP theft: both the legalities and ethical position, with neither having easy answers.
• Extractive contributions: fracturing open-source communities through disingenuous contribution, and real burn-out risk from maintainers.
• Exploitation: exposure of communities to labour exploitation through low-paid data labelling and content moderation work that underpins the entire industry.

The least bad option

• If you are using LLMs to further maximise productivity and shareholder returns and are ok with that, that’s your call to make. I’d only ask: have you made a conscious decision, or did it happen by default?
• If you are coerced to use LLMs by organisational pressure or market forces, then I’m truly sorry that the world is structured this way. Learn the facts: perhaps there is scope for reasoned push-back.
• If you are in the tricky position of working on software that are digital public goods, yet can see that LLM usage may be beneficial to the project as a whole, then make your own assessment. There is a chance that the work you do is impactful enough to offset the potential negatives engendered.

The key point here is that it’s all about choosing the least bad option you can justify, and being honest about why.

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Contribute to the discussion

• Open source communities around the world are hotly discussing this topic currently.
• If you genuinely care, and have a perspective to share, then your input is duly welcomed.
• There couldn’t be a more important time to weigh in on the topic.