Hi,

I recently took the Giving What We Can 10% pledge (to give 10% of my income to effective charities). Part of the appeal of the pledge is making effective giving a cultural norm.

I wonder about the effects of that in the global economy, and on the economy of rich countries, where I hope the pledge takes roots stronger and faster.

Has anyone looked into that?

Hi EAs, I’m Dee, first-time forum poster but long-time advocate for EA principles since first discovering the movement through Peter Singer’s work. I’ve always had a particular interest in global health and wellbeing, which initially inspired me to complete a medical degree. While I enjoyed my studies, I became somewhat disheartened with the scope of impact I could have as a single doctor in a system largely geared towards treatment rather than prevention of disease. After a career pivot to management consulting for a couple of years, I eventually completed my PhD in epidemiology. I’m now using my research experience and medical knowledge to tackle complex public health problems. 

The more I’ve solidified my own goals to do good, including through my career as well as through giving to effective causes, I’ve sought to further engage with EA content and the community. I look forward to connecting and sharing ideas with you all!

A lot of EAs wanted to slow down AGI development to have more time for alignment. Now Trump's tariffs have done that - accidentally and for the wrong reasons - but they did slow it down. Yet no EA seems happy about this. Given how unpopular his tariffs are maybe people don't want to endorse them for PR reasons? But if you think that AI is by far the most important issue that should easily lead you to say the unpopular truth. Scenarios where China reaches AGI before the US became more likely, but that was always an argument against AI slowdown and it didn't seem to convince many people in the past.

Thoughts?

Maybe this post should be placed in some AI safety thread, but I wasn't sure where exactly.

Hi everyone! I'm Antony, and I work at the intersection of Data Engineering, People Development, Organizational Development, and Research/Writing.

A little bit more about me...

Three things I care about:

• Helping people to build meaningful and impactful careers.
• Designing organizations that become drivers of social change.
• Voicing ideas to help people understand how the world works and how they can make a change.

Three things I'm good at:

• Identifying inefficiencies and designing solutions with a deep understanding of what makes people and organizations thrive.
• Creating frameworks to systematically approach complex problems.
• Researching deeply and communicating insights clearly, because I believe solutions start with understanding.

Three things I have experience with:

• Engineering Management. I scaled up a data engineering department from 12 to 70 engineers for an AI Fund company backed by Andrew Ng, managing a team of 14 direct reports and 70 indirect reports.
• Mentoring. I've mentored over 50+ engineers over my career, helping them to gain clarity on what they want and how to approach challenges they face.
• Writing. I've published more than 20+ technical articles on Medium (~500k views), and I'm now currently building The Utopian Engineering Society.

I’d love to connect with people and organizations working at these intersections. While I’ve been following the EA movement for a couple of years, my involvement has been passive. But I’m now actively looking to change that.

If you know anyone, please point me in the right direction or just say hi. You can also connect with me on LinkedIn.

Since AI X-risk is a main cause area for EA, shouldn't significant money be going into mechanistic interpretability? After reading the AI 2027 forecast, the opacity of AIs appears to be the main source of risk coming from them. Making significant progress in this field seems very important for alignment.

I took the Giving What We Can Pledge, I want to say there should be something like it but for mechanistic interpretability, but probably only very few people could be convinced to give 10% of their income to mechanistic interpretability.