The territory of expertise: machine vs. human expert vs. group of amateurs

Nicolas Maisonneuve speech at Design School ENSAD 2012

The territory of expertise: machine vs. human expert vs. group of

amateurs

The raise of machines

CERN- the Large Hadron Collider

Computer Room (2008)

8,000 servers housing 40,000 processor Experiments produce about 15 petabytes of data per year (= 1.500.000 giga) – 5% of internet in 2001

First computer in CERN ?

Wim Klein first computer in action at CERN

(when machine was slower than human)

Wim Klein worked at CERN from 1958 to 1976

First computer in CERN (Wim Klein)When machine was slower than human

CERN -Farewell Party - 1973

http://www.youtube.com/watch?v=urFiv_PQ2FQ

Wait a minute.. 48 x 65 x 37 x 84 = ?

(yes.. I checked all the results of the video)

Wait a minute.. 48 x 65 x 37 x 84 = 9696960

In Science repeatability >> speed: • Human experts make sometime mistakes • Machine repeat a mistake forever => much

better

In 1973 the CERN started to use machines. Klein retired in 1976 (HP vs Klein) !Expertise in computation: Machine, winner since the 70s

(don’t trust experts)

Intelligence: Human expertise/capability vs. machine

• Yes but computation is a “stupid” activity, humans are more “intelligent” than machine.

• Fair enough, what about Chess?

Chess = Traditional challenge in Artificial Intelligence !Expertise in Chess: Machine, winner since 2003 !But is it a real victory for the A.I field?Kasparov vs. machine (Deep

blue)

Moravec Paradox & The nature of intelligence

“The main lesson of thirty-five years of AI research is that. the hard problems are easy and the easy problems are hard”

Linguist and cognitive scientist Steven Pinker 

Kasparov vs. machine (2003) Fake victory of AI (brut force computation)

“It is easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility” - 1988 Moravec

1969 by neuroscientist Paul Bach-y-Rita et al.

SIDE NOTE: Cognition and intelligence development

sensorimotor skills and instincts that we share with the animals require enormous computational resources compared to symbolic thinking

Turing Test

Modern example, the captcha

Recognizing words is too hard for machines, but easy for people.

= Testing the machine's ability to exhibit intelligence human expertise.

Traditional Turing Test: a conversion. !

If, during a conversation, machine can fool the interrogator into thinking that it is human, then it pass the test

!!

The raise of crowdsourcing and the decentralization of expertise

Crowdsourcing not a new practice: distributed computing in the old days

 a computer at work 1940.

(Human) Computer < 1950The First World War required large numbers of human computers.

The Mathematical Tables Project • 450 'human computers' mostly people

with low incomes • Worker  split up according to arithmetic

function (+, -,* , if skilled /)

Modern examples

[1]- Jim Giles, « Special Report Internet encyclopaedias go head to head » Nature 438, 900-901 (Dec 2005)

Encyclopaedia expertise: Amateurs winner since 2005 vs. professionals (Wikipedia vs Encyclopaedia Britannica - [1])

Image interpretation expertise: amateurs still winner vs. machine (e.g. Galaxy zoo’s project: 60M of images of galaxies classified in few months by 80.000 amateurs with high accuracy, too hard for the machines (and the amateurs teached the machine [2])

[2] The output data was used to improve the algorithm

Expert vs amateurs, another kind of Turing Test..

Croatia's Ruđer Bošković Institute website • Against spammer and beginners… • Extra-hard version of a regular CAPTCHA-type

micro-task economy

• Amazon Mechanical Turk (2005 – present)

>80.000 HITs (Human Intelligence Tasks)

(Science: low cost living lab for social/behavior research)

and what about school? Change in teaching expertise/skill)

Victor Papanek, Design pour un monde réel, 1971

Khan Academy

• http://www.youtube.com/watch?v=gM95HHI4gLk

"23

"24

Human Expert

Machine Crowd

How to make them collaborate and not

only compete?

Open General Question