Overview Index

Computer intelligence versus Human intelligence

Intelligent systems (both natural and artificial) have several key features. Some intelligence features are more developed in a human’s brain; other intelligence features are more developed in modern computers.

 

Name of intelligence feature

Who has the advantage

Comments about comparison

Experimental learning

Human

Currently computers are not able to general experimenting. Computers are able to make some specific (narrow) experimentation though.

Direct gathering information

Computer

Modern computers are very strong in gathering information. Search engines and particularly Google is the best example

Decision making ability to achieve goals

Human

Currently computers are not able to make good decisions in “general” environment

Hardware processing power

Computer

Processing power of modern computers is tremendous (several billion operations per second)

Hardware memory storage

Computer

HDD memory storage of modern computers is huge

Information retrieval speed

Computer

Data retrieval speed of modern computers is ~1000 times faster that human’s ability.

Examples of high-speed data retrieval systems: RDBMS, Google

Information retrieval depths

It’s not clear

Both humans and computers have limited ability in “deep” informational retrieval.

Information breadth

Computer

Practically every internet search engine beats human’s in the breadth of stored and available information

Information retrieval relevancy

Human

Usually human’s brain retrieves more relevant information than computer program. But advantage of humans disappears every year.

Ability to find and establish correlation between concepts

Human

Currently computers are not able to establish correlation between general concepts

Ability to derive concepts from other concepts

Human

Usually computers are not able to derive concepts from other concepts

Consistent system of super goals

Human

Humans have highly developed system of super goals (“avoid pain”, “avoid hunger”, sexuality, “desire to talk” …). Super goals implementation in modern computers is very limited.

Features of intelligence

Learning ability

Learning ability consists of two parts:

  1. Experimental learning (acquire knowledge through experimenting).
  2. Direct gathering of information (from books, web-sites, conversation).

Ability to achieve goals by decision making

Hardware power

  1. Processing power
  2. Memory storage

Information retrieval from the internal memory ability

Three characteristics are important for retrieval ability

  1. Retrieval speed. (That is how quick can system find necessary information and make this information available for further processing).
  2. Retrieval depth and broadness. (That is how deep information searching process is. How many related concepts system selects during retrieval.)
  3. Retrieval accuracy.
    Retrieval accuracy shows how accurate retrieval process is. What the “useful concepts/total concepts” retrieval ratio is.

 

Examples:

Let’s imagine that system tries to find answer to the question “How to talk to Mary?”

 

Deliberation ability

Deliberation ability is:

-         Ability to find and establish correlation between previously not related concepts.

-         Ability to derive concepts from other concepts.

Example of concept derivation:

Let Intelligent System knows concepts “mother”, “father”, “brother”, “sister”. After deliberation process Intelligent System unites these concepts under concept “family”.

Example of establishing correlation between different concepts:

Let Intelligent System knows that “have a job” is a cause to “salary”. Let Intelligent System also knows that “salary” causes “ability to pay for food”. As a result of deliberation process Intelligent System would conclude that “have a job” is a cause to “ability to pay for food”.

Consistent system of super goals

Intelligent System should have convenient/understandable/easy-to-use set of super goals that direct system self-development.