Thank you so much for your perspective and thought-out contribution here!
It's great to hear the ground-level interview-like experiences you've had with researchers from earlier generations, to consider how academic research has evolved from a much "freer" environment to a generally more constrained and results-driven endeavour.
Thank you so much for your perspective and thought-out contribution here!
It's great to hear the ground-level interview-like experiences you've had with researchers from earlier generations, to consider how academic research has evolved from a much "freer" environment to a generally more constrained and results-driven endeavour.
You have many great points in here -- like the reliance on AI which comes at the cost of exacerbating biases, or, alternatively, "Draconian criteria" by policymakers. That's precisely one of the toughest trade-offs. At the core, I often feel that practically all solutions using data are tricky, because we're always using data from an imperfect world to model our ideal future.
You've given much food for thought here and topics we'll hopefully delve deeper into in future Litmaps newsletters. Thanks again! :)
Thank you so much for your perspective and thought-out contribution here!
It's great to hear the ground-level interview-like experiences you've had with researchers from earlier generations, to consider how academic research has evolved from a much "freer" environment to a generally more constrained and results-driven endeavour.
You have many great points in here -- like the reliance on AI which comes at the cost of exacerbating biases, or, alternatively, "Draconian criteria" by policymakers. That's precisely one of the toughest trade-offs. At the core, I often feel that practically all solutions using data are tricky, because we're always using data from an imperfect world to model our ideal future.
You've given much food for thought here and topics we'll hopefully delve deeper into in future Litmaps newsletters. Thanks again! :)