Robotics, artificial intelligence and expert systems


Robotics in the 21st Century
useful links can be found on this site

Introduction

The increasing capability of IT systems has allowed developers to implement systems that attempt to understand and imitate human behaviour. These systems have already had profound effects on society, although their effectiveness is largely determined by the accuracy of the algorithms that underpin them. The increasing use of robotics, artificial intelligence (AI) and expert systems raises a range of ethical issues. For example, at which point should humans hand over key decision-making to a computer? Should robots have the same rights as humans? What social impacts might arise with the replacement of human workers or the creation of smart weapons?

Possible scenario

A hospital administrator is considering using a computer-controlled robotic device to assist with knee surgery. The robotic system models the patient’s knee area prior to surgery. During the procedure the robot is controlled by the surgeon using a joystick. The system eliminates the effects of tremors in the surgeon’s hands and limits the range of movement of the cutter to areas of the knee that have been predetermined by the model. Although there are claims that the surgery is less invasive and patients have a shorter recovery time, questions may be raised about the reliability and the cost of the system.

IT concepts to address in this topic:
Robotics
    • Input devices: for example, camera, sensors, microphones
    • Output devices: for example, claws, wheels, motors, relays, speakers
    • Robot, android, cyborg
    • Sensors: for example, heat, proximity, magnetism, light, humidity, pH
    • It will be useful for you to see how you should discuss and summarise an issue by looking at the IB rubric



      Exam Question:
      Discuss 3 possible social and/or ethical issues raised by the use of Robots in the 21st Century. Weigh up the importance of your arguments. [12 marks]
      Notes: Each issue should be from a different 'area of impact' (Health, Military, Industry, Space etc)

      How to discuss and weigh up an issue
Artificial Intelligence
    • Artificial intelligence versus computational intelligence
    • Man or machine: Turing test, CAPCHA (completely automated public Turing test to tell computers and humans apart)
    • Capabilities and limitations: for example, learning to identify human emotions, evaluation of living things and machines (intuition, prior knowledge, jugement)
    • AI techniquies: searching, pattern recognition, heuristics, machine learning
    • Fuzzy logic, set theory
    • Machine learning:can machines become independent?
    • Natural language communication and translators
    • Neural networks: similarity to biological systems

http://www.sciencedaily.com/news/computers_math/artificial_intelligence/
Useful website for general information on robots

Fuzzy Logic



Further information and exercises on Fuzzy Logic

Heuristics
This refers to experience-based techniques for solving a problem, discovery and learning for oneself. These methods are used to speed up the process of finding a good enough solution. An example would be an intuitive guess or common sense.

Machine learning; can machines become independent?


Natural language communication and translators

Have a chat with Captain Kirk from the Enterprise
Or chat with A.L.I.C.E.


Neural networks: similarity to biological systems


Traditionally used to refer to a network of biological neurons, The term neural network is used to refer to artificial neural networks.

Processing is structured in terms of an interconnected group of artificial neurons.
  • Biological neural networks consist of real biological neurons that are connected to the central nervous system.
  • Artificial neural networks consist of interconnecting artificial neurons (they mimic the properties of biological neurons). These networks may be used to study biological neural networks, or used for solving AI problems without creating a model of a real biological system.

Pattern recognition: OCR(optical character recognition), image analysis, speech recognition, speech recognition, speech synthesizers

OCR - The machine recognition of printed characters. The electronic translation of images of handwritten, typewritten or printed text (usually captured by a scanner) into machine-editable text. Teaching robots to read.
Image analysis - extracting meaningful information from images, such as facial recognition



facial_scan.gif
Face recognition used at airports
Speech recognition-the ability of a machine or program to identify words and phrases in spoken language and convert them to a machine-readable format. Rudimentary speech recognition software has a limited vocabulary of words and phrases and may only identify these if they are spoken very clearly. More sophisticated software has the ability to accept natural speech. Speech recognition applications include call routing, speech-to-text, voice dialing and voice search (allowing users to create searches via spoken voice rather than by typing). The user can also instruct the machine to do certain tasks by speaking his/her commands.
Source http://searchcrm.techtarget.com/definition/speech-recognition
Speech synthesizers - the computer-generated simulation of human speech. Try this text to voice demo
Processing and storage requirements -

Processing power of robots (past, present and future)

Expert Systems

An expert system is a computer system that emulates the decision-making ability of a human expert. At the foundation of every expert system is a knowledge base representing ideas from a specific field of expertise. Because it’s a collection of specialized knowledge, an expert system’s knowledge base must be constructed by a user, an expert, or a knowledge engineer—a specialist who interviews and observes experts and painstakingly converts their words and actions into a knowledge base.
The first expert systems were created in the 1970s and then proliferated in the 1980s. Expert systems were among the first truly successful forms of artificial intelligence software.

Expert systems are often used to advise non-experts in situations where a human expert is not available e.g medical diagnosis, fault diagnosis (mechanics), financial management advice etc.

The 3 key elements of an expert system; a user-interface, a knowledge base, and an inference engine.

expert system.png
Example of online expert systems.

Symptom checker

Make notes on expert systems and ensure that you read a few related news articles


More info
http://www.igcseict.info/theory/7_2/expert/index.html
http://education-portal.com/academy/lesson/using-artificial-intelligence-ai-and-expert-systems-to-solve-complex-problems.html#lesson




Useful news articles on AI

IBM's supercomputer Watson to help solve Africa's problems
Best content in ITGSopedia | Diigo - Groups
http://www.horizonsbusiness.com/episode/robotics/

Sample Exam Questions on AI

In a real exam situation, you would have 30 minutes to answer the questions below:




Drones


Drones in the news

http://www.bbc.com/news/technology-32308104
http://www.bbc.com/news/technology-32334186
https://www.youtube.com/watch?v=Le46ERPMlWU
http://www.nytimes.com/2015/04/23/us/drones-smuggle-contraband-over-prison-walls.html?_r=0
http://edition.cnn.com/2015/04/22/asia/japan-prime-minister-rooftop-drone/

What technology is built into drones?



Overview

https://sketchfab.com/models/6e7dccf233db40b7921f1c6fc5a6e36d
http://www.cnet.com/products/parrot-bebop-drone/

After learning more, what modifications would you add (if any)?