30% commitment, 70% flexibility
(and Machine Learning for Healthcare course launch)
Hey everyone,
I hope you had a great week.
Thanks so much to everybody that replied to my last email - it really helped me to reflect on where best to focus my time. My main takeaway was that time spent trying to serve the ‘niche’ of machine learning for healthcare will be time well spent, and things alongside that can be seen as a bonus.
This week’s reflection (below) is on balancing core commitments with flexibility.
As always, feel free to hit ‘reply’,
Chris
Flexibility and Core Commitments
One of my biggest weaknesses, historically, has been to take on too much.
I used to get excited and enthusiastic about a lot of things, struggle to say no, and then end up with more projects than I could meaningful contribute to.
By ‘maxing out’ my capacity at any moment in time, I didn’t leave space for unexpected events, or for spontaneous exploration.
Over the years I’ve gotten better at prioritising projects, and saying no when required. It’s been a concerted effort, driven largely by necessity.
Now I aim for my commitments to be around 30-50% of my max capacity.
I’ve found this quite liberating. If I have a cool project idea with a friend that gets me excited it, I can crack on with it. I don’t have to slot it into my schedule, at a future point where some of the excitement may have dissipated. I feel better placed to capitalise on spontaneity and follow what most excites me at one moment in time.
🔒The benefits of low-capacity commitments
Two of my personal commitments for 2020 are to, every week, share one YouTube video and share one reflection on this weekly email. Most weeks, this commitment fits well within my capacity. In busy ones, it becomes tougher but still achievable.
Setting the bar at this level is one reason I’ve been able to keep the commitment thus far (and, in some weeks, exceed it).
Setting commitments can definitely bring benefits. But restricting them gives you something equally valuable; flexibility. Commitment ensures I keep moving forward, flexibility ensures I’m always exploring new things and personal inclinations.
This week I played around with that flexibility by sharing my first ever Tweetstorm and learning how to deploy code on Amazon’s AWS Lambda. Both un-planned at the start of the week, but both very fun and (in my opinion) valuable ways to have spent my time.
How much flexible time do you have? What do you (or would you) do with it?
This week’s links:
(1) On a vision for technology in healthcare (a podcast)
I really enjoyed hearing my friend Ivan Beckley share his vision for the future of healthcare. I’ve always loved Ivan’s passion and authenticity, and felt both shone through in this podcast.
(2) On being a good dad (a podcast)
Derek Sivers is a treasure-trove of wisdom, and for the first time shares his philosophy for raising children in this podcast. A fascinating perspective.
(3) On technological stagnation as the undercurrent for social change (a podcast)
This was the first public discussion between Peter Thiel and Eric Weinstein. Both have very interesting perspectives on many ‘bigger picture’ issues. The latter is currently employed by the former (as MD of Thiel Capital). They touch on a lot in this conversation, from our current misperceptions about innovation, to politics and to what they view as challenges for the future. Thought-provoking.
This week’s video:
This is the first video in my 9-part ‘Machine Learning for Healthcare’ course that I’ll be sharing on YouTube. I outline the course content, and share my top two reasons why medical professionals should learn about machine learning.
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About Me
Hi! I’m Chris Lovejoy, a Junior Doctor and Data Scientist based in London.
I’m on a mission to improve healthcare through technology (particularly AI / machine learning), but along the way I want to share learnings that are relevant no matter your career choice or background.
In this weekly newsletter, I share my top thoughts and learnings from each week, as well as links to the best things on the internet that I come across.