You Can Always Get What You Want, But Not What You Need (2016) [video] | Hacker News Reader

You Can Always Get What You Want, But Not What You Need (2016) [video]

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136 pointsAlanTuring18 comments

Great video. I think the book The Elephant in the Brain is required reading in this context: http://elephantinthebrain.com/

Yes!

The sentiment is something I (and I suspect many other engineers) feel, but not able to express it nearly so simply and elegantly.

Before you sit down and start writing that code or creating that new algorithm, stop and think about what you really want to achieve.

Fascinating. Instead of banning money or fixing prices (did they try that in Russia?) we retain free markets but now with a new layer of government intervention. Not intervention by social spending or regulation but by buying and selling according to the dictats of an AI. And the utility function of this AI is set according to what exactly?

My guess is it would have to be according to our values, not to specific goals:

https://www.youtube.com/watch?v=tZBViI8ZaU0

This is the goal alignment problem that MIRI, FHI, and some safety groups at Open AI are working on. It seems like a hard problem to get right (with bad consequences if not aligned super intelligence happens first).

> Not intervention by social spending or regulation but by buying and selling according to the dictats of an AI.

Which would still run up against The Economic Calculation Problem which has constrained all central planning proposals and (probably) always will.

Once they solve that then we can talk about an AI which can predict the outcomes of billions upon billions of individual decisions which are made by market actors to fulfill their wants and needs.

> but now with a new layer of government intervention

As far as I can tell, the government is the least active actor in this area, so curious choice of picking it here.

The Soviet Union always had money and banking. It was just less meaningful than it is in America.

Multicriteria value decision analysis theory and methods are able to provide the solution to model the need (utility). For instance, in reinforcement learning the payoff (goal) function is always a given without any depth consideration about its construction. It can be modeled by using the methods referred previously.

I thought that theory told us multicriteria optimization is intractable?

Multicriteria optimization is distinct from multicriteria value decision analysis. The former does not model the value/utility of the criteria, while the latter does. If you do not model value/utility (what you need) then you cannot solve the underlying multicriteria problem.

If that's the same as multivariate opt, there are billion-dollar industries that rely on it every day.

No, unless I've mistaken the phrase, they're not the same. I'm thinking of the problem when competing criteria can't be satisfactorily combined as inputs to a function with a scalar output. This comes up in ethical paradoxes, for example.

Making value trade-offs between competing criteria ultimately boils down to hard ethical choices (not exactly paradoxes)

Companies make things that they can sell in a marketplace it is necessarily not what that place needs. For example social media companies just want to sell their social networks in any country with internet irrespective of that country have drinking water problem or humanitarian crisis.

Peter Norvig’s book A modern approach to AI is pretty cool. I don’t know what they use now in 101 AI courses but I remember that book being very complete.

I still believe though that hard AI will only ever be possible if we ever make serious breakthroughs in the material sciences.

To differentiate between needs and (economic) wants, I found the "fundamental human needs" framework quite useful: https://en.wikipedia.org/wiki/Fundamental_human_needs (as developed by Chilean Economist Manfred Max-Neef).

Basically: Subsistence, Protection, Affection, Understanding, Participation, Leisure, Creation, Identity and Freedom.

The key point @ 3:15 ... https://youtu.be/QCw_D7dr7Rw?t=193

Url changed from https://www.youtube.com/watch?v=Zsbb1Ze4T_M&list=PLrAXtmErZg..., which is a clip from this.

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