Jaime Sevilla's Quick takes

A pattern I've recently encountered twice in different contexts is that I would recommend a more junior (but with relevant expertise) staff for a talk and I've been asked if I could not recommend a more "senior" profile instead.

I thought it was with the best of intentions, but it still rubbed me the wrong way. First, this diminishes the expertise of my staff, who have demonstrated mastery over their subject matter. Second, this systematically denies young people of valuable experience and exposure. You cannot become a "senior" profile without access to these speaking opportunities!

Please give speaking opportunities to less experienced professionals too!

Quick guide on the agree/disagree voting system:
 

• When you upvote a post/comment, you are recommending that more people ought to read and engage with it.
• When you agree vote a post/comment, you are communicating that you endorse its conclusions/recommendations.
• Symmetrically, if you downvote a post/comment you are recommending against engaging with it.
• And similarly, if you disagree vote a post/comment you are communicating that you don't endorse it's conclusions/recommendations.

Upvotes determine the order of posts of comments and determine which comments are automatically hidden, so have a measurable effect on how many people read them.

Agree votes AFAIK do not affect content recommendations, but are helpful to understand whether there is community support for a conclusion, and if so in which direction.

On getting research collaborators

(adapted from a private conversation)

The 80/20 advice I would give is: be proactive in reaching out to other people and suggesting to them to work for an evening on a small project, like writing a post. Afterwards you both can decide if you are excited enough to work together on something bigger, like a paper.

For more in depth advice, here are some ways I've started collaborations in the past:

• Deconfusion sessions. 
  I often invite other researchers for short sessions of 1-2 hours to focus on a topic, with the goal of coding together a barebones prototype or a sketch of a paper.
  
  For example, I engaged in conversation with Pablo Moreno about Quantum Computing and AI Aligment. We found we disagreed, so I invited him to spend one hour discussing the topic more in depth. During the conversation we wrote down the key points of disagrement, and we resolved to expand them into an article.
   
• Advertise through intermediate outputs. 
  I found it useful for many reasons to split big research projects into post-size bits. One of those reasons is to let other people know what I am working on, and that I am interested in collaborating.
  
  For example, for the project on studying macroscopic trends in Machine Learning, we resolved to first write a short article about parameter counts. I then advertised the post asking for potential collaborators to reach out.
   
• Interview people on their interests. 
  Asking people what motivates them and what they want to work on can segue into an opportunity to say "actually, I am also interested in X, do you want to work together on it?". I think this requires some finesse, but it is a skill that can be practiced.
  
  For example, I had an in depth conversation with Laura González about her interests and what kinds of things she wanted to work on. It came up that she was interested in game design, so I prodded her on whether she would be interested in helping me refine a board game prototype I had previously shown her. This started our collaboration.
   
• Join communities of practice.
  I found it quite useful to participate in small communities of people working towards similar goals. 
  
  For example, my supervisor helped me join a Slack group for people working on AI Explainability. I reached out to the people for one-on-one conversations, and suggested working together to a few. Miruna Clinciu accepted - and now we are buiding a small research project.