ML4Good Europe March 2025

How will the days be spent?

* Peer-coding sessions following a technical curriculum with mentors

* Presentations by experts in the field.

* Review and discussion of AI Safety literature.

* Personal career advice and mentorship.

* Evening activities - and time to rest!

We update our program between each camp, to stay up to date with the rapid development of the field of AI.

The program of the last camp was composed of talks, workshops and group discussions on:

• model evaluations
• AI trends
• forecasting and timelines
• risk models, risk scenarios and classifications
• landscape of solutions
• corporate governance
• international governance

Alongside technical content including:

• Implement SGD and other local optimisation algorithms, run remote hyper-parameter searches on a simple architecture
• Implement GPT-2 from scratch
• Implement and run RLHF
• Look at various interpretability techniques on GPT models and the ResNet
• Implement DQN and A2C, two important reinforcement learning algorithms
• Implement adversarial attacks and defenses
• Implement an LLM agent

There is also the opportunity to dive more into the topic of your choice during the literature review afternoon and the 2.5-day project at the end of the camp.

Timetable of the last camp:

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You are between the ages of 18 and 30 residing in France, Spain, Ireland, Sweden, the Netherlands and Germany. While you do not need to be a native of these countries, current residency is a prerequisite for eligibility. Those who do not meet these specific residency requirements are encouraged to sign up for updates on our homepage to hear about upcoming bootcamps in different countries. This bootcamp operates under sponsorship from the Erasmus+ program, which imposes certain unique constraints on eligibility not present for our other programmes.

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You are motivated to work on addressing the societal risks posed by advanced AI systems - ideally, motivated enough to consider making significant career decisions such as transitioning to AI safety, setting up a university AI safety group, or founding a project.

You have a programming background and comfortable with at least one year of applied mathematics at university levelYou have a high level of proficiency in EnglishYou can commit to completing our prerequisite material before the bootcamp (we will send this to you upon acceptance)* We expect this material to take 10 hours* This will include AI Safety conceptual readings and may include programming or mathematics preparation depending on your strengths

Will there be any spare time? There will be periods of leisure and rest during the camp. However, the course is intensive and full-time - don’t plan to do anything else during the camp.
What language will the camp be in? All courses, instruction, and resources will be in English.
What do you mean by AI Safety? By “AI Safety” we mean ensuring that AI doesn’t lead to negative outcomes for sentient beings or the premature disempowerment of humanity. In a recent open letter signed by many deep learning pioneers, it is stated that “mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.” Avoiding these bad outcomes is a challenge that has to be tackled on a societal level. In this camp, we will focus on technical approaches to building safer AI systems, for example by making their internal processes more interpretable.
I am not sure my level of technical knowledge is sufficient. Please see the prerequisite section above to see what level of technical knowledge we are looking for. If you have particularly strong mathematics skills then we would accept less programming experience and vice-versa. If you are still unsure, feel free to contact us. Additionally, before the camp begins we will provide some preparation work.
How much do I need to know about AI Safety to apply? We expect participants to have a solid grasp of why and how an AI could become existentially unsafe for sentient beings and a general overview of proposed solutions. When it comes to theoretical AI Safety topics, we don’t expect an advanced level of knowledge. You will get more value out of the event if you have more familiarity with AI Safety beforehand. We will provide some reading before the camp for those less familiar.
What might an ideal candidate look like? We have particular interest in those who we can support in planning concrete actions towards working on the reduction of AI risks. Examples of promising candidates include:
* You are an undergraduate in a technical subject with an active github account and you would consider setting up an AI Safety Reading Group at your university.
* You are early in your career or are a masters student in a technical field and you are interested in exploring a future career in alignment to reduce risk from advanced AI.
* You are a professional in the field of software engineering or data science and are looking for a way to alter the trajectory of your career towards work on AI Safety. You would be happy contributing engineering talent to open source tooling or helping found a new project.
* You already have prior machine learning experience and are keen to apply your skills to reduce risk from AI and plan to act on this by e.g. changing jobs, or planning your career, or would be willing to join early stage projects.

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