Page 14 - Read Online

Page 9 de Silva. Intell Robot 2021;1(1):3-17 https://dx.doi.org/10.20517/ir.2021.01

developed by humans. It is true that due to learning, the particular robot intelligence (the decision-making
ability related to the learned knowledge) improves. Unlike humans, whose level of intelligence can
depreciate for many reasons (physiology, lack of practice, new knowledge, new and complex environments,
etc.), machine learning will always improve robotic intelligence. This means a chess-playing robot will
continuously improve its skills through learning (practice) and can thereby defeat a chess champion.
However, we have to realize that such intelligence is provided to robots by humans through control
programs. That program will never be able to acquire all the characteristics of a human brain. For instance,
we may question whether a chess-playing robot can also perform other tasks (e.g., caring for an elderly,
carrying out medical surgery) unless specifically developed and trained for such activities and has the
needed mechanical capabilities. Also, can a robot ever acquire such characteristics as common sense or
emotions that are possessed by a human, in the same manner as in a human brain?

Humans develop robots, and we program their controllers (brains). We can set limits, checks and balances,
regulations, and guidelines as we wish. We should collaborate with social scientists and develop proper
guidelines and regulations for the development and the safety and ethical use of robots. Since a proper
ethical evaluation and certification are essential for any technology that is used by humans, this should
properly adhere for robots as well. In medical surgery, for example, a robot will facilitate the surgical
procedures, but they should be performed under the supervision of a human surgeon, who must have the
capability to abort the robotic procedure immediately, if necessary.

In fact, those who fear AI simply fear a black box! In order to make a proper determination, we should
know what methodologies are used exactly in the AI black box and how those methodologies are
implemented and operated. So, we should explore the black box carefully and in detail (with the help of
experts who are knowledgeable in the subject) and only then indicate what methodologies in the AI black
box might be dangerous. Then other experts will be able to respond intelligently and in an informative
manner.

4.1. Characteristics of intelligence
Before exploring AI itself, let us examine intelligence. No precise definition exists for intelligence. They are
the external characteristics and capabilities (that we observe from actions) that enable us to claim whether
an entity (for example, a robot) is “intelligent”. Essentially, the outward characteristics define intelligence.

The characteristics of intelligence include sensory perception; pattern recognition; learning (i.e., knowledge
acquisition, which is extremely important for intelligence); inference (i.e., making decisions) from
incomplete information; inference from qualitative or approximate information (this is commonly used in
“qualitative reasoning” as in fuzzy logic or fuzzy reasoning); ability to deal with unfamiliar situations;
adaptability to new, yet related situations (through “expectational knowledge”. For example, a human is able
to expect the nature of an environment, like a classroom, even when encountering that environment for the
first time); inductive reasoning (people must have done this in high school mathematics when proving a
mathematical result “by induction”); common sense; display of emotions; inventiveness; and self-awareness
(i.e., knowing their own capabilities).

A simplified model for the dynamics of intelligence is shown in Figure 4. The intelligent preprocessors are,
in fact, learning modules. They enable one to gain knowledge by “learning” from information and also
achieve expertise by further learning through knowledge (including practice). The achieved knowledge and
expertise can depreciate for various reasons (including environmental and biological) and also can become
outdated. Even though intelligent preprocessing or learning is vital in this model, it is unlikely that machine