Introduction to AI Part 1

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  • Broad and specific AI
  • Approaches to AI
  • Historical Overview
  • Challenges and benefits of AI


Artificial intelligence (AI) is a subset of computer science, it aims to make computers capable of performing narrow tasks.

There are two types of AI, broad AI and specific AI. Broad AI is ca

AI can be divided into symbolic learning and machine learning. Machine learning uses large amounts of data to develop a model, from this model the algorithim can classify or make predictions. Symbolic learning is about giving a machine rules and behaviours which it can then use to develop plans within the framework.

Historically, Symbolic learning was the leading paradigm in AI research from mid-1950s until the late 1980s. Until it was eventually realized that giving a computer rules about the real world would eventually lead to contradictions. Neural networks and machine learning are now the leading paradigms in AI. By making use of big Data, these algorithms can find patterns in multidimensional data, we humans can’t visualise this hence finding these patterns are a lot harder.

We will be looking at and developing chatter bots in week 3 and 4. Alan Turing, considered the father of AI, described the Turing Test which is essentially a way of determining whether a computer is artificially intelligent. The idea was if a conversation with a computer was indistinguishable from a conversation with a human, then the computer is artificially intelligent. This test is limited to testing chatter bots only, however, the paper was monumental in the AI revolution.

Potential Benefits

  • Better medical care and treatment as ai is able to detect patterns, make predictions and draw conclusion from a larger data pool then any doctor has ever been able to.
  • Most designs can be made to be more efficient, resulting in reduced emissions and more sustainable production.
  • Better prediction’s, you will get better shows recommended on Netflix and better shopping product recommendations.

Potential Risks

  • If a model is so good at predicting future trends, e.g a model of the stock market. The trader with the algorithm then gains an unfair advantage over the market analogous to the advantage from insider trading. Should this be illegal?
  • Replacement of white collar jobs as ai can be made to do it faster, better and more cost effectively.

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Question 1. [4 marks]

Contrast broad and specific AI, using examples for each.

Question 2. [2 marks]

Outline two significant contributions of Alan Turing to the field of AI

Question 3. [8 marks]

Evaluate the challenges and benefits associated with AI to determine whether we should continue to research AI?

Question 4. [3 marks]

Explain how symbolic learning differs from machine learning.

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