To reduce the risks posed by the rise of artificial intelligence, we need to figure out how to make sure that powerful AI systems do what we want. Many potential solutions to this problem will require a lot of high-quality data from humans to train machine learning models. Building excellent pipelines so that this data can be collected more easily could be an important way to support technical research into AI alignment, as well as lay the foundation for actually building aligned AIs in the future. If not handled correctly, this work risks making things worse, so this path needs people who can and will change directions if needed.
Sometimes recommended — personal fit dependent
This career will be some people's highest-impact option if their personal fit is especially good.
Based on a shallow investigation
Why might becoming an expert in data collection for AI alignment be high impact?
We think it’s crucial that we work to positively shape the development of AI, including through technical research on how to ensure that any potentially transformative AI we develop does what we want it to do (known as the alignment problem). If we don’t find ways to align AI with our values and goals — or worse, don’t find ways to prevent AI from actively harming us or otherwise working against our values — the development of AI could pose an existential threat to humanity.
Collecting this data — ideally by setting up scalable systems to both contract people to carry out these sorts of tasks as well as collect and communicate the results — could be a valuable way to support alignment researchers who use it in their experiments.
But also, once we have good alignment techniques, we may need AI companies around the world to have the capacity to implement them. That means developing systems and pipelines for the collection of this data now could make it easier to implement alignment solutions that require this data in the future. And if it’s easier, it’s more likely to actually happen.
What does this path involve?
Human data collection mostly involves hiring contractors to answer relevant questions and then creating well-designed systems to collect high-quality data from them.
Figuring out who will be good at actually generating this data (i.e. doing the sorts of tasks that we listed earlier, like evaluating arguments), as well as how to find and hire these people
Designing training materials, processes, pay levels, and incentivisation structures for contractors
Ensuring good communication between researchers and contractors, for example by translating researcher needs into clear instructions for contractors (as well as being able to predict and prevent people misinterpreting these instructions)
Designing user interfaces to make it easy for contractors to complete their tasks as well as for alignment researchers to design and update tasks for contractors to carry out
Scheduling workloads among contractors, for example making sure that when data needs to be moved in sequence among contractors, the entire data collection can happen reasonably quickly
Assessing data quality, including developing ways of rapidly detecting problems with your data or using hierarchical schemes of more and less trusted contractors
Being able to do all these things well is a pretty unique and rare skill set (similar to entrepreneurship or operations), so if you’re a good fit for this type of work, it could be the most impactful thing you could do.
If you follow this path, it’s particularly important to make sure that you are able to exercise excellent judgement about when not to provide these services.
We think it’s extremely difficult to make accurate calls about when research into AI capabilities could be harmful.
For example, it sounds pretty likely to us that work that helps make current AI systems safe and useful will be fairly different from work that is useful for making transformative AI (when we’re able to build it) safe and useful. You’ll need to be able to make judgements about whether the work you are doing is good for this future task.
If you think you might be a good fit for this career path, but aren’t sure how to avoid doing harm, our advising team may be able to help you decide what to do.
How to predict your fit in advance
The best experts at human data collection will have:
Experience designing surveys and social science experiments
Ability to analyse the data collected from experiments
Some familiarity with the field of AI alignment
Enough knowledge about machine learning to understand what sorts of data are useful to collect and the machine learning research process
At least some front-end software engineering knowledge
Some aptitude for entrepreneurship or operations
Data collection is often considered somewhat less glamorous than research, making it especially hard to find good people. So if you have three or more of these skills, you’re likely a better candidate than most!
How to enter
If you already have experience in this area, there are two main ways you might get a job as a human data expert:
If you don’t have enough experience to work directly on this now, you can gain experience in a few ways:
Do academic research, for example in psychology, sociology, economics, or another social science.
Work in human-computer interaction or software crowdsourcing.
Work for machine learning companies in labelling teams — and because these roles are less popular, they can be a great way to rapidly gain experience and promotions in machine learning organisations.
The Effective Altruism Long-Term Future Fund and the Survival and Flourishing Fund may provide funding for promising individuals to learn skills relevant to helping future generations — including human data collection. As a way of learning the necessary skills (and directly helping at the same time), you could apply for a grant to build a dataset that you think could be useful for AI alignment. The Machine Intelligence Research Institute has put up a bounty for such a dataset.
Find a job in this path
If you think you might be a good fit for this path and you’re ready to start looking at job opportunities, you may find relevant roles on our job board: