ER 2017 tutorial - On Paradoxes, Autonomous Systems and dilemmas

On paradoxes, robots and

autonomous systems -

conceptual model or losing

control?

Speaker: Opher Etzion

Asimov coined the axioms for robotics. These are the assertions that every robot must obey

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The Autonomous Car Paradox

) based on article in Scientific American)

OUTLINE:

1. On Paradox, contradiction and logic

2. On Autonomous Systems

3. On dillemas

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1. On Paradoxes2. On Autonomous Systems3. On Dilemmas

OUTLINE:

OUTLINE:

1. On Paradox, contradiction and logic

2. On Autonomous Systems

3. On dillemas

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On Paradoxes

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Paradoxes: Let’s go to the basics…

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Russell’s paradox: The Barber version

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Bibliographies that quote themselves

Bibliographies that don’t quote themselves

Russell’s paradox: The Librarian version

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These are the assertions that every model must obey

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The Heap Paradox

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Zenon’s Paradox

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The man from Mars allegory

Nuel Belnap

What is the color of this desk?

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Is the desk RED ?

Sure...

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Not really. This

desk is YELLOW

Is the desk RED ?

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I don’t have a clue

Is the desk RED ?

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This desk is GREEN

This desk is RED

Is the desk RED ?

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Nuel Belnap

The man from Mars allegory

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Fuzzy Logic

On Autonomous Systems

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Autonomous systems – analogy to human thinking

Sensing

Making sense of what we sense

Real Time Decision Making

Acting

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IoT and robotics

Robots serve as intelligent actuators – and are becoming autonomous

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Healthcare robotics

Rehabilitation robots: enhancing patients with motoric and cognitive skills

Assistive robots: Robots for independent living of disabled persons

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Some future healthcare

robotics applications

Automated assistance of monitored patients

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Help in sit-to-stand and sit-down actions for people with motor disabilities

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Autonomous moving of drugs and medical equipment within the hospital

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Support of medical staff in various activities

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People movement and movement monitoring

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People assistance in panic and danger situations

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I(

The classical use of robots are for industrial purposes: production, machinery control, product design…

Industrial Robots

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I(

Autonomic management and coordination of production activities among multiple robots

Industrial Robots and IoT

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I(

Autonomous management of equipment and instruments


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I(

Immediate reaction to critical situations such as: high temperature, harmful chemicals in the air


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I(

Autonomic control of electrical and energy plants


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Robotics for defense

Robots are used for unmanned tools (ground and air) for transport and intelligence , threat detection and combat

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Robotics for defense and IoT

Autonomous and smart detection of harmful chemicals and biological weapons

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Autonomic control of land vehicles and aircrafts

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Identification and access prevention of suspicious people intruding to sensitive places

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Rescue trapped people

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Smart pacemaker

A pacemaker is a small device that's placed in the chest or abdomen to help control abnormal heart rhythms. This device uses electrical pulses to prompt the heart to beat at a normal rate.

Implants for cardiovascular diseases

source: https://www.cambridgeconsultants.com/media/press-releases/setting-pace

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Sensors and actuators –technology still under development

Goal:

to improve insulin replacement therapy until glycemic control is practically normal, and to ease the burden of therapy for the insulin-dependent.

Implants for diabetes patients

Source: https://www.slideshare.net/energexsystems/pancreas-presentation

Dilemmas

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Causality

In order to derive conclusions from facts and events there is a need to identify causalities.

Statistical methods can infer correlations.

Causality inference is more tricky….

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Causal inference

How the knowledge about causality is being acquired?

Expert knowledge

Statistical inference

Inference using semantic or association net

Necessity? and relevance?

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Dangers of using correlation as causality

indicator

Correlation between A and B:

1. A causes B

2. B causes A

3. There is C which causes both A and B

4. A combination of all three interpretations

The faster windmills are observed to rotate, the more wind is observed to be.

Therefore wind is caused by the rotation of windmills.

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indicator


1. A causes B

2. B causes A



Sleeping with one's shoes on is strongly correlated with waking up with a headache.

Therefore, sleeping with one's shoes on causes headache.

(correct answer: going to bad drunk causes both)

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indicator


1. A causes B

2. B causes A



As ice cream sales increase, the rate of drowning deaths increases sharply.

Therefore, ice cream consumption causes drowning. (real answer: they are both in the same context – summer).

False positives and negatives

False positive:The pattern is matched;The real-world situation does not occur

False negative:The pattern is not matched;The real-world situation occurs

Learning from experience

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Sensing can be noisy

What are we uncertain of?

Uncertain whether a reported event has occurred (e.g. accident)

Uncertain what really happened. What is the type and magnitude of the accident (vehicles involved, casualties)

Uncertain when an event occurred (will occur): timing of forecasted congestion

Uncertain where an event occurred (will occur): location of forecasted congestion

Uncertain about the level of causality between a car heading towards highway and a car getting into the highway

Uncertain about the accuracyof a sensor input: count of cars, velocity of cars…

The pattern: more than 100 cars approach an area within 5 minutes after an accident derives a congestion forecasting

Uncertain about the validityof a forecasting pattern

Uncertain about the quality of the decision about traffic lights setting

Sources of uncertainty

Uncertaininput data/

Events

SourceMalfunction

ThermometerHuman error

MaliciousSource

Fake tweet

Sensor disrupter

Projectionof temporalanomalies

Wrong hourly sales summary

SourceInaccuracy

Samplingor

approximation

Propagationof

uncertainty

Visual data

Rumor

Wrong trend

Inference based on uncertain value

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Defense Robots

Unmanned aerial vehicle – Robots that arebeing employed for logistics, intelligence,and combat

In reality –Asimov’s axioms were not adopted

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What would you

do?

BACK TO:

The Autonomous Car Paradox

) based on article in Scientific American)

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Deep Learning is takingover autonomous

systems

Autonomous systems are equipped withself-learning capabilities. This creates asituation where the actual algorithmbehind their activities is not transparent

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Murder by the Internet

“With so many devices being Internet connected, it makes murdering people remotely relatively simple, at least from a technical perspective. That’s horrifying,” said IID president and CTO Rod Rasmussen. “Killings can be carried out with a significantly lower chance of getting caught, much less convicted, and if human history shows us anything, if you can find a new way to kill, it will be eventually be used.”

EXAMPLES: Turn off pacemakers, Shutdown car systems while driving, stop IV drip from functioning

Safe vs. connected

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The Singularity Dillema

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Who will move to the next phase of evolution?

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Implications on socialequality

Will the majority of humanity stay behind?

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The Solaria Paradox

||autonomous systems|| >>||human beings||

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Progress vs. Employability

What will be the purpose in life? Howshould the time be spent?

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Maybe Asimov was rightand the galaxy should becontrolled by a smartrobot?

Science

ER 2017 tutorial - On Paradoxes, Autonomous Systems and dilemmas