Krugman on Bernie

From today’s NYT. He’s not overly impressed by Sanders, but…

I’m more concerned about (a) the electability of someone who says he’s a socialist even though he isn’t and (b) if he does win, whether he’ll squander political capital on unwinnable fights like abolishing private health insurance. But if he’s the nominee, it’s the job of Dems to make him electable if at all possible.

To be honest, a Sanders administration would probably leave center-left policy wonks like me out in the cold, at least initially. And if a President Sanders or his advisers say things I think are foolish, I won’t pretend otherwise in an attempt to ingratiate myself. (Sorry, I’m still not a convert to Modern Monetary Theory.) But this is no time for self-indulgence and ego trips. Freedom is on the line.

The real test of an AI machine? When it can admit to not knowing something

This morning’s Observer column on the EU’s plans for regulating AI and data:

Once you get beyond the mandatory euro-boosting rhetoric about how the EU’s “technological and industrial strengths”, “high-quality digital infrastructure” and “regulatory framework based on its fundamental values” will enable Europe to become “a global leader in innovation in the data economy and its applications”, the white paper seems quite sensible. But as for all documents dealing with how actually to deal with AI, it falls back on the conventional bromides about human agency and oversight, privacy and governance, diversity, non-discrimination and fairness, societal wellbeing, accountability and that old favourite “transparency”. The only discernible omissions are motherhood and apple pie.

But this is par for the course with AI at the moment: the discourse is invariably three parts generalities, two parts virtue-signalling leavened with a smattering of pious hopes. It’s got to the point where one longs for some plain speaking and common sense.

And, as luck would have it, along it comes in the shape of Sir David Spiegelhalter, an eminent Cambridge statistician and former president of the Royal Statistical Society. He has spent his life trying to teach people how to understand statistical reasoning, and last month published a really helpful article in the Harvard Data Science Review on the question “Should we trust algorithms?”

Read on