This document discusses intelligence augmentation (IA), which refers to using information technology to enhance human intelligence. IA has the potential to significantly increase productivity, quality, and safety while reducing injuries and task times. Approaches to IA include software and hardware-based methods, such as mind mapping tools, neurofeedback devices, and future implants. However, the human brain has limitations that need to be overcome to reach the future possibility of superintelligence through merging with AI. The document proposes a "upgrade plan" involving techniques like assisted thinking, mixed reality, and capturing all data to help transition from the current limitations of the human brain to a future of enhanced capabilities.

1. Augmenting Human
Intelligence
AQUIBUR RAHMAN
12MEB160
A3MB-31

2. Contents
 Introduction to IA
 Potential of IA
 Approaches and Methods of IA
 Defining the problem
 The “Upgrade Plan”
 Future Prospects
 References

3. 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”

4. Potential of (Human + Machine)
Reduce absenteeism
by 50%
Eliminate classes
of injuries
Increase work consistency
Productivity
Reduces task time
Utilization
Safety
Quality

5. Approaches to IA
Stubborn
naturalism
Raping
your brain
Chaotic props
New Age
Open-minded
enhancement

6. Methods of IA
 Wetware-based
 Mnemonic techniques – inefficient
 Nootropics – just emerging
 Software-based
 Patterns and strategies
 ICT tools (and paper tools), such as mind maps
 Hardware-based
 Devices (neuro feedback, brainwaves, etc.) – too crude
 Implants – not here yet

7. 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 atTRL 5.
 HULC being developed for multiple applications
Lockheed Martin Equipois Proprietary Information

8. Defining the problem
 A: limitations of today
 B: limitless future
 How do we get from A to B?

9. A: Limitations of today
 Brain is a system evolved for certain environment
and tasks
 It is not a universalTuring machine, it has
weaknesses, limitations, biases and bugs
 All “human errors” are caused by our limitations
 But we don’t even understand the limitations.

10. B: Limitless future
 Likely (almost certain) prospects:
 Merging with the AI
 Super-intelligence
 Recursive self-improvement
 Technological Singularity

11. How do we get from A to B?

12. Technological inventions that overcome
physical/perceptual limitations:
 glasses
 hearing aids
 cars
 bicycles
 voice
synthesizers
 And many
more…

13. 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...

14. 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
Do it now!
Watch this
Accept
the solution
Understand
the problem

15. 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

16. 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