Hatch's AI Compass
Updated 30 October, 2026
For everyone at Hatch: this is how we think about AI, how we use it, and how we talk about it with learners, clients and partners. Read it before you teach, pitch or build with AI on Hatch’s behalf.
We train people for the future of work, and AI is now part of that future. We can’t afford to ignore it, and we can’t afford to be naive about it. This compass is our attempt to do both.
It is not a rulebook. It is a set of positions we hold today, written down so we can act on them, hold each other to them, and change them honestly when we learn more.
Part 1: Where we stand
AI is moving faster than anyone can fully see. The field changes every day, and much of how it is built is hidden from the public. None of us will ever have full oversight of it, and we shouldn’t pretend to.
Each of us decides for ourselves. We respect every person’s right to make choices about AI based on their own convictions and boundaries. Some of us use it every day. Some of us use it sparingly, or not at all. Both are welcome here, and nobody should feel pressured either way.
We can’t stop AI, but we can shape who benefits from it. AI will advance with or without us. As an academy, our responsibility is to engage with what is happening now and use our position to level the playing field for the people we train.
What gives us hope. AI can save us time and energy, and sometimes it makes our work better. Beyond our own desks, it is making scientific breakthroughs possible, removing barriers for some people, and supporting important research. Used well, it can bridge inequalities and amplify good work. That is why we are in this at all.
What troubles us. We see people relying on AI so heavily that their own abilities suffer, along with their time with each other. We see it eroding livelihoods and the entry-level work where people used to build skills, especially for creatives and fresh graduates, many of whom are the people we serve. We see harm from bad actors, and from ordinary people who don’t know better. We see data centres draining water and nature from communities, and workers underpaid to label the data that trains these models. And we see how unpredictable all of it still is.
Part 2: Our roles and responsibilities
As a training academy, we teach the whole picture. Our curriculum should not stop at how to use AI. Learners should leave with a critical, informed view of how it works, what it costs, and who it affects. That means we commit time and resources to our own learning, and put what we learn back into our curriculum and content.
As a social business, we use AI with intention. If and when we use it, we hold ourselves and each other to the following:
Use it for something that matters. Reach for AI when it serves a real purpose, not to ride a trend or pass the time. There are other ways to have fun (ask each other for suggestions!).
Keep a human hand on everything. Every AI-assisted output we share needs a person who has shaped it, checked it, and can explain it. If someone asks what you meant by a line, “AI wrote that” is not an answer.
Keep our footprint small. Where a smaller or local model can do the job, use it instead of defaulting to the biggest one.
Part 3: How we act publicly
As a team, we commit to:
Teaching responsible AI, not just useful AI. Knowing how to use AI is an essential skill in most workplaces now, and we will keep teaching it. Our learners should also understand what AI really costs, and leave with concrete ways to reduce the footprint of their own use. We aim to complete this shift across our training, to a standard we can stand behind.
Not making art with generative AI. We will not produce or promote artwork made with generative AI. Any communications asset drafted with AI must be wholly defensible: if you created it, you must be able to stand behind every word and every choice in it.
Bringing our conscience to the table. As AI trainers and part of the social impact ecosystem, people listen to what we say about AI. We will be honest about our excitement and our discomfort, and we won’t avoid difficult conversations with stakeholders, communities, or the public.
Learning continuously. However much or little each of us uses AI, we owe it to our learners and ourselves to understand the developments shaping our work and our world.
Advocating across our ecosystem. We sit between learners, employers, funders and fellow social purpose organisations, and what we learn about AI shouldn’t stay inside Hatch. We will share what we have learnt, including our mistakes, with the people and organisations around us. We will actively advocate for AI that is used responsibly and fairly. With funders in particular, we will make the case for critical AI literacy alongside practical skills, because what gets funded shapes what gets taught.
All of this might change as AI changes and as our understanding grows. When it does, we will update this compass and say why.
Hatch's AI Compass
Updated 30 October, 2026
For everyone at Hatch: this is how we think about AI, how we use it, and how we talk about it with learners, clients and partners. Read it before you teach, pitch or build with AI on Hatch’s behalf.
We train people for the future of work, and AI is now part of that future. We can’t afford to ignore it, and we can’t afford to be naive about it. This compass is our attempt to do both.
It is not a rulebook. It is a set of positions we hold today, written down so we can act on them, hold each other to them, and change them honestly when we learn more.
Part 1: Where we stand
AI is moving faster than anyone can fully see. The field changes every day, and much of how it is built is hidden from the public. None of us will ever have full oversight of it, and we shouldn’t pretend to.
Each of us decides for ourselves. We respect every person’s right to make choices about AI based on their own convictions and boundaries. Some of us use it every day. Some of us use it sparingly, or not at all. Both are welcome here, and nobody should feel pressured either way.
We can’t stop AI, but we can shape who benefits from it. AI will advance with or without us. As an academy, our responsibility is to engage with what is happening now and use our position to level the playing field for the people we train.
What gives us hope. AI can save us time and energy, and sometimes it makes our work better. Beyond our own desks, it is making scientific breakthroughs possible, removing barriers for some people, and supporting important research. Used well, it can bridge inequalities and amplify good work. That is why we are in this at all.
What troubles us. We see people relying on AI so heavily that their own abilities suffer, along with their time with each other. We see it eroding livelihoods and the entry-level work where people used to build skills, especially for creatives and fresh graduates, many of whom are the people we serve. We see harm from bad actors, and from ordinary people who don’t know better. We see data centres draining water and nature from communities, and workers underpaid to label the data that trains these models. And we see how unpredictable all of it still is.
Part 2: Our roles and responsibilities
As a training academy, we teach the whole picture. Our curriculum should not stop at how to use AI. Learners should leave with a critical, informed view of how it works, what it costs, and who it affects. That means we commit time and resources to our own learning, and put what we learn back into our curriculum and content.
As a social business, we use AI with intention. If and when we use it, we hold ourselves and each other to the following:
Use it for something that matters. Reach for AI when it serves a real purpose, not to ride a trend or pass the time. There are other ways to have fun (ask each other for suggestions!).
Keep a human hand on everything. Every AI-assisted output we share needs a person who has shaped it, checked it, and can explain it. If someone asks what you meant by a line, “AI wrote that” is not an answer.
Keep our footprint small. Where a smaller or local model can do the job, use it instead of defaulting to the biggest one.
Part 3: How we act publicly
As a team, we commit to:
Teaching responsible AI, not just useful AI. Knowing how to use AI is an essential skill in most workplaces now, and we will keep teaching it. Our learners should also understand what AI really costs, and leave with concrete ways to reduce the footprint of their own use. We aim to complete this shift across our training, to a standard we can stand behind.
Not making art with generative AI. We will not produce or promote artwork made with generative AI. Any communications asset drafted with AI must be wholly defensible: if you created it, you must be able to stand behind every word and every choice in it.
Bringing our conscience to the table. As AI trainers and part of the social impact ecosystem, people listen to what we say about AI. We will be honest about our excitement and our discomfort, and we won’t avoid difficult conversations with stakeholders, communities, or the public.
Learning continuously. However much or little each of us uses AI, we owe it to our learners and ourselves to understand the developments shaping our work and our world.
Advocating across our ecosystem. We sit between learners, employers, funders and fellow social purpose organisations, and what we learn about AI shouldn’t stay inside Hatch. We will share what we have learnt, including our mistakes, with the people and organisations around us. We will actively advocate for AI that is used responsibly and fairly. With funders in particular, we will make the case for critical AI literacy alongside practical skills, because what gets funded shapes what gets taught.
All of this might change as AI changes and as our understanding grows. When it does, we will update this compass and say why.