augmenting human intelligence

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Augmenting Human Intelligence AQUIBUR RAHMAN 12MEB160 A3MB-31

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Page 1: Augmenting human intelligence

Augmenting Human

Intelligence

AQUIBUR RAHMAN

12MEB160

A3MB-31

Page 2: Augmenting human intelligence

Contents

Introduction to IA

Potential of IA

Approaches and Methods of IA

Defining the problem

The “Upgrade Plan”

Future Prospects

References

Page 3: Augmenting human intelligence

Introduction to Intelligence Augmentation (IA)

human + machine = “super intelligence”

Intelligence Augmentation (IA) refers to the effective use of information technology in augmenting human intelligence. The theory was developed in the 1950s and 1960s by cybernetics and early computer pioneers. *

AKA “cognitive augmentation” and “machine augmented intelligence”

Page 4: Augmenting human intelligence

Potential of (Human + Machine)

Reduce absenteeism

by 50%

Eliminate classes

of injuries

Increase work consistency

ProductivityReduces task time

Utilization

Safety

Quality

Page 5: Augmenting human intelligence

Approaches to IA

Stubborn

naturalism

Raping

your brain

Chaotic props

New Age

Open-minded

enhancement

Page 6: Augmenting human intelligence

Methods of IA

Wetware-basedMnemonic techniques – inefficient

Nootropics – just emerging

Software-basedPatterns and strategies

ICT tools (and paper tools), such as mind maps

Hardware-basedDevices (neuro feedback, brainwaves, etc.) – too crude

Implants – not here yet

Page 7: Augmenting human intelligence

Examples of IA

• Exo-skeletal Arm Systems (zeroG):

ZeroG arm mitigates the weight of heavy tools

Arm supports the tool through a wide range of motion

Arm requires no power. Can reduce vibration transmission. Single arm stabilize tools to 40 lbs, dual arm

to 80 lbs.

.

• Lower Body Exoskeleton (HULC):

Load of up to 200 lbs is transferred to the ground 20 hour charge life at expected work rates. HULC at TRL 5. HULC being developed for multiple applications

Lockheed Martin Equipois Proprietary Information

Page 8: Augmenting human intelligence

Defining the problem

A: limitations of today

B: limitless future

How do we get from A to B?

Page 9: Augmenting human intelligence

A: Limitations of today

Brain is a system evolved for certain environment and tasks

It is not a universal Turing machine, it has weaknesses, limitations, biases and bugs

All “human errors” are caused by our limitations

But we don’t even understand the limitations.

Page 10: Augmenting human intelligence

B: Limitless future

Likely (almost certain) prospects:

Merging with the AI

Super-intelligence

Recursive self-improvement

Technological Singularity

Page 11: Augmenting human intelligence

How do we get from A to B?

Page 12: Augmenting human intelligence

Technological inventions that overcome

physical/perceptual limitations:

glasses

hearing aids

cars

bicycles

voice synthesizers

And many more…

Page 13: Augmenting human intelligence

Why do we need technology to overcome

cognitive limitations?

lousy memory (short term as well as long term)

only good at dealing with one thing at a time

probabilities, logic non-intuitive

slow to process large amounts of information

bad at self-knowledge, introspection

And much more...

Page 14: Augmenting human intelligence

The “UPGRADE PLAN”

•we’re monkeys•biological limitations, we don’t know them•to merge with computers need to think like them

best strategy: open-minded enhancementgeneral strategy:•use a framework•manage life•put data into a good system•stick to the process•use creativity techniques

•thinking•processing info•mapping your mind•getting things done•collaborating

future:•brain-computer interface•assisted thinking•mixed reality•all data captured and shared

Do it now!

Watch this

Accept

the solution

Understand

the problem

Page 15: Augmenting human intelligence

Future Prospects of IA:

Brain computer Interface (2015–2025) requires: understanding neurons, fast computers, micro devices

Assisted thinking (2000–2025) requires: data digitising and formalisation, digital lifeflow, weak AI

Mixed reality (2015–2025) requires: computer vision, world modelling, comfortable interfaces

All data captured and shared (2010–2020) requires: fast computers, cheap sensors, large storage

Page 16: Augmenting human intelligence

References:

http://evolvingtrends.wordpress.com/2006/06/26/wikipedia-30-the-end-of-google/

http://www.rtqe.net/ObliqueStrategies/

http://en.wikipedia.org/wiki/Intelligence-amplification/

William Ross Ashby: Intelligence Amplification

http://pespmc1.vub.ac.be/ASHBBOOK.html

http://www.cambridge.org/catalogue/catalogue.asp?isbn=0521834074&ss=exc

http://en.wikipedia.org/wiki/List_of_cognitive_biases

Page 17: Augmenting human intelligence