artificial intelligence overview
TRANSCRIPT
TABLE OF CONTENTS
Introduction 1
Historical Development 1
Main Issues of AI 3
Goals of Artificial Intelligence 3
Thinking Machines 6
Regulation and Ethics 8
Stakeholders 9
Government 9
Businesses 10
Society 11
Biblical Approach 12
Bibliography 16
Appendix 20
End Notes24
1
Understanding Artificial Intelligence
Introduction
On November 5, 2014, To-Robo, an artificial intelligence
(AI) agent outperformed the average of high school students on a
standardized test. To-Robo surpassed most students on the English
section of the exam, scoring a 95 out of 200 points compared to
the average of 93.1 for Japanese students.1 Even though To-Robo
struggles in other subjects such as object recognition and
politics it might one day be able to outperform humans in most
areas.
What is intelligence? Are machines capable of intelligent
behavior? Should AI focus on human biology to create intelligent
agents, or is AI unrelated to human intelligence?2 These
questions are the basis for the field that is known as AI today.
The purpose of this research is to provide a holistic approach to
2
the understanding of the field of AI. The following terms defined
are important for the understanding of AI:
Artificial Intelligence: Is the field of science that aims to create machines that possess intelligent behavior.
Algorithm: An algorithm is a step by step procedure or instructions given to accomplish a task.3 In the case of AI an algorithm will most likely be an equation or set of equations coded into a machine to accomplish a certain goal.
AI Agent: Stands for any new technology or procedure that isgenerated by the AI field.
Strong AI (General AI): For some experts, strong AI is the ultimate goal of the field which aims to produce an AI agentpossessing the same capabilities and intelligence a human does.4
Weak AI: In contrast with Strong AI, weak AI is any technology developed that is capable of accomplishing intelligent tasks but lacks the overarching purpose of general intelligence.
Moore’s Law: Theory proposed by cofounder of Intel, Gordon E. Moore. The theory states, processing power and speed of acircuit will double every eighteen months.5 This trend noticed in 1958 has held true to this day.
Historical Development
Humanity has always been fascinated by the possibility of
creating intelligent beings. Before AI emerged as a field,
writers, philosophers, and scientists were already speculating on
the possibility of intelligent machines. Mary Shelly is famous
for her book Frankenstein; published in 1818.6 The books main
event about a scientist who was able to create artificial life.
3
Isaac Asimov, a professor of biochemistry and fiction writer, is
perhaps most famous for his book series called I Robot, published
in 1950. Asimov is recognized for conceptualizing the possibility
of general intelligence, and creating a basic framework of rules
to govern all artificial agents.7 (See Appendix A, Asimov’s three
Laws of Robotics).
The possibility of an artificial agent had been discussed
years prior to the rise of the field. Alan Turing was one of the
first to introduce the possibility of intelligent machines.
Turing published his study called Computing Machinery and Intelligence
in 1950. In this book Turing poses the question: Can machines
imitate intelligent thinking?8 Turing, also proposed the Turing
Test as a means of assessing the intelligence of future AI
agents. The test is famous for devising a method to help prove if
a machine could be considered intelligent or not. Turing proposed
that through advances in technology it might be possible to
produce a machine that is capable of providing response and
solutions that accurately imitate the answers a human being would
give.9 Thus, this ability would constitute the machine to be
4
intelligent in the sense that it is capable of producing coherent
answers indistinguishable from human responses.
However, it was not until 1956 during a conference in
Dartmouth College that John McCarthy, computer scientist and
researcher, proposed the term Artificial Intelligence for the
first time in history.10 In this conference the term AI was used
for the first time along with the presentation of one of the
first AI programs. Herbert Simon, and Allen Newell presented the
Logic Theorist (LT) in 1956. The LT was a program that searched
for answers based on trial and error. McCarthy, was also the
first person to create a programing language for AI in 1957
called LISP.11 LISP made it easier to find a common language to
make new programs and generated several advances in the field.
There have also been setbacks for AI including a period in
the 1980s known as the AI winter. This period is known for an
overly optimistic view of AI and its capabilities. The Defense
Advanced Research Projects Agency (DARPA) also began to cut
funding for projects due to lack of results.12 During the 1990s
there was a resurgence of AI. For the first time, in 1997, a
computerized chess program (Deep Blue) beat the reigning world
5
champion Garry Kasparov.13 In the early 2000s robotic pets first
became available to purchase by the general public. From its
humble beginnings, AI has made tremendous contributions and
technological advances in the world. Understanding its history
allows for analysis of the implications that AI will represent
for society in the future.
Main Issues of AI
The goal of AI is to create machines that possess
intelligent behavior. This section is divided into two main
parts. The goals of the AI field will be discussed along with
strategies implemented by different scientists. The different
ideologies of whether or not it is possible to create thinking
machines will be reviewed along with two main problems of
creating a truly intelligent AI agent.
Goals of Artificial Intelligence
To create a truly strong AI agent researchers identified the
main areas that need to be developed. A truly intelligent agent
should have the ability to reason like humans do. AI should also
have vast knowledge on extensive topics. An AI agent should be
able to plan, set goals, and have a way to accomplish these
6
goals. An intelligent being should have the ability to learn new
information through experience in the real world, and be able to
communicate solutions verbally. Researchers also discuss the fact
that an AI agent has to have mobility (robotics), and be able to
manipulate objects, and have visual abilities just like humans
do.14 To accomplish these goals AI research has taken several
different paths. The most prominent branches of AI are discussed
in the following sections.
Symbolic AI
The possibility of Strong AI stems from the idea of
functionalism. Functionalism interprets the human mind and
conscious thoughts as a series of steps and symbols.15 Scientists
believe machines could also be able to produce intelligent
behavior similar humans through the use of algorithms and
heuristics. A notable success for symbolic AI was the development
of the system ELIZA by AI researcher Joseph Weizenbaum in 1965.16
Designed to hold conversations using a text interface, ELIZA is
scripted using a symbolic framework that looks for patterns in
the users inputs (See Appendix B, Conversation with ELIZA).17 The
development of ELIZA enabled to creation of knowledge-based
7
systems such as Deep Blue, the chess playing machine discussed
earlier capable of beating grand master level players.
A Knowledge-Based (also known as an expert system) system is
a specialized symbolic AI that is constructed by information
provided by experts on a specific field like medicine or
accounting. Knowledge in the form of facts is stored in a
database, which can usually be accessed through questions
postured by a user of the system (See Appendix C, Structure of an
Expert System). One of the earliest examples of an expert system
was developed by researcher Ted Shortlife in 1974. This AI agent
was called MYCIN.18 MYCIN was composed to be and aid in giving
medical diagnosis and suggest medical treatments. MYCIN proved to
be an extremely efficient tool. For example, “In one formal test,
a judging panel rated MYCIN’s prescription as correct 65% of the
time compared to 42.5-62.5% for human specialists presented with
the same cases.” 19
Just like MYCIN there are also powerful expert systems being
developed today. Apple Inc.’s Siri is an example of an everyday
expert system used by people on their phones. IBM also developed
a system called Watson in 2011. Watson was able to win a Jeopardy
8
competition, not by understanding what was asked but with raw
computational power.20 Even though expert systems are powerful
they lack conscious behavior and have no real understanding of
the answers that are given. An expert system might give a correct
answer, but it does not mean it understands the consequences of
the solution. This type of program is known as weak AI.
Neural Networks
The second approach to AI is the development of neural
networks, first conceptualized by Warren McCulloch and Walter
Pitts in 1943.21 Researchers of Neural Networks try to recreate
the activities of the human brain by the function neurons perform
in transferring information. The first application of a neural
network is called the perceptron, created by scientist Frank
Rosenblatt in 1950.22 The perceptron is an algorithmic function
created to follow the basic design of a real neuron. Neural
Networks require computers with great amount of raw processing
power which is why they fell out of favor with researchers in the
early years. Applications with neural networks surfaced as
computers gained more computational power in the 1980s.23
9
Genetic Algorithms (GA), is a branch of the neural network
approach that stems from evolutionary ideas. Scientists attempt
to create algorithms that copy evolutionary processes by process
of crossover and elimination.24 With this process GAs are able to
arrive to a best-fit solution by elimination, and arrive to an
optimum solution.
Robotics
In contrast to symbolic and neural approaches, robotics has
the ability to create AI agents that allow mobility. This
mobility also allows scientists to study how an intelligent agent
(robot) behaves when faced with uncertainties or unanticipated
situations that occur in a natural environment.25 Some scientists
say that it is not efficient to build robots because of the high
cost; instead computer programs should be able to model the same
abilities that robots would have in a real life situation.
Thinking Machines
When creating AI the following questions is considered: Are
machines capable of intelligent behavior? There are two differing
arguments supported by researchers. First, those who believe
10
general AI is possible and inevitable; this is based on the
theory of functionalism and Moore’s law. Second, the position
saying that achieving general AI is ultimately impossible.
Proponents of the possibility of general AI base their ideas
on Moore’s law, and the belief of a possible technological
singularity. General AI proponents believe that in the near
future machines will become so powerful (Moore’s law) that they
will become a super intelligent agent that is capable of
conscious human-like thought. This event will lead to a
singularity where machines will be so intelligent that they will
be able to reinvent themselves. One of the main scientists in
favor of the possibility of the singularity is Ray Kurzweil,
current director of the department of Artificial Intelligence for
Google Inc.26 Kurzweil popularized the idea of general AI, and of
the possibility of the singularity. If this were to happen,
Kurzweil also argues that human beings would be able to merge
with existing technologies forming a sort of cyborg mixture
between human and machine. What Kurzweil is advocating is the
possibility of being able to live on forever with the aid of
advanced AI; this view is also known as transhumanism. With this
11
view, humans will transition minds to advanced intelligent
systems.
The possibility of AI is also fueled by the idea that the
human mind processes information and ideas in terms of symbols
and ordered step-by-step procedures (Functionalism). Early
developments of AI through symbolic AI followed this train of
thought and proposed that through heuristics a machine could
eventually become intelligent. With enough processing power
(Moore’s Law), future machines could be able to learn by
themselves and gain some sort of consciousness.
Opponents of general AI disagree with Kurzweil’s ideas that
have become popular in recent years. John Searle, professor of
philosophy at the UC Berkeley, states that general AI is utterly
impossible. Searle expresses that computer programs are basically
algorithms that by analyzing inputs can be programmed to carry
out specific functions. This means that, the AI system does not
need to understand the underlying conscious thought of an action,
but rather be programmed to carry out a certain expression.27
This argument is famously known as the Chinese room argument. The
argument also states that, one cannot simply program a computer
12
to express consciousness like a human does.28 Thus, a true
general intelligent AI is not possible in the sense that the AI
agent will not understand the reason why it is performing certain
tasks.
Hubert Dreyfus, professor of philosophy at the UC Berkley,
states that there are two main problems with traditional or
symbolic AI approaches. These two issues are that computer
programs lack the understanding of common sense and relevance. In
the early 60s, AI researches embarked on trying to create
conscious thought on programs with algorithms and symbols. What
researches found is that in spite of programs being able to solve
problems and use algorithms to find new solutions they lacked
common sense. A program cannot understand why the solution
provided is the right one, it arrives to the solution through
mindless calculation. The issue of relevance (Frame Problem) is also
present. AI systems cannot differentiate which data is relevant
in a specific situation. Relevance as used by human beings is
easy to understand because humans analyze their surroundings and
are able to apply relevant facts to a specific situation. The
same is not true for computer systems.29 A computer systems with
13
millions of data would have trouble selecting a relevant frame of
data to apply to a specific situation without being told to do so
by a programmer. From these problems it is evident that all of
the AI agents that are present today are considered to be weak AI
agents. There is no evidence that strong AI is currently a
possibility with existing technologies, but rather the belief of
general AI is mere speculation with no hard facts to prove it.
Regulation and Ethics
Currently there are no existing governmental entities that
provide oversight for the field of Artificial Intelligence.
However, products arising from AI research are generally subject
to regulation. Government takes on a reactive role to provide
regulation as new AI products arise. For example, Google Inc. is
currently producing autonomous self-driving vehicles. Several
states that have already passed regulation for Google’s self-
driving vehicle, as well as other future automated automobiles
(See Appendix D, California Bill 1298 regarding autonomous
vehicles).
AI is a concern for regulators when it comes to privacy
laws, since AI agents pose an increasing danger when it comes to
14
safeguarding information. The US government is currently
considering threats to private and public entity security when it
comes to privacy and information sharing. On July 10, 2014 the US
Congress proposed the Cybersecurity Information Sharing Act
(CISA). CISA required private and public entities to propose
plans for information security in dealing with threats, and
vulnerabilities to technology.
If general AI is indeed a possibility, creating an ethical
framework for an AI agent is equally important to passing
regulation. Elon Musk, owner of Tesla Motors, argues that AI
could be one of the biggest threats to human existence if not
regulated properly.30 The branch of AI called Machine Ethics was
created to consider the ethical implications of general AI.
Machine Ethics classifies two types of AI, explicit and implicit
agents. An implicit intelligent agent would act according to the
behaviors programmed in the machine by the creator, assuming the
creator follows correct ethical standards. Explicit agents would be
able to make ethical decisions based on an agreed upon code of
ethics by the AI field.31 The desirable outcome of machine ethics
is to create an explicit AI agent, because the laws that govern
15
each agent would not depend on individual scientist beliefs but
rather on an agreed upon code of ethics.
Stakeholders
AI is everywhere, all technology new an old can be traced
back and related to an advancement in a branch of AI. Even though
general AI is not possible today, new technologies can have
tremendous benefits for society if handled with care. As a whole,
AI affects civilization in a global scale; consequently, the
following important stakeholders have been identified.
The government has always had a special interest in the
advancements of AI. Since the 1960s the government has provided
monetary support and facilities to develop new technologies in
the form of the DARPA organization. A main concern for the
government is to provide advanced technology for national
defense, and AI agents for assistance during war time. Some of
the arguments against AI dedicated to national defense is the fact
that advanced AI could be used to generate mass destruction.32
The threat itself would not be towards the AI agent but, towards
the world powers that would use these technologies to coerce
society and generate chaos. Bill Joy, chief technologist for sun
16
microsystems, argues that humans will not be able to control
future technologies which will cause confusion an increase
violence. Joy, advocates for disarmament and prohibition of
technologies that would lead to general AI, and autonomous
weapons.33
Supporters for autonomous weapons acknowledge the fact that
dangers exist when handling AI. Supporters suggest that, “Instead
of prohibiting or heavily regulating artificial intelligence, the
United States should support civilian research into a kind of AI
that will not endanger humans—a so-called friendly AI.”34 As
discussed with machine ethics, the creation of friendly AI would
largely depend on successful implementation of an ethical
framework for all future AI agents. A successful friendly AI
would be beneficial for humankind, especially when it comes to
national defense. The lives of human soldiers will not be
endangered with developments of technologies such as autonomous
drones.
Businesses have been a great beneficiary of artificial
intelligence. The benefits AI has given businesses are increased
efficiency in the workplace, enhanced security with work
17
procedures, and improved decision making.35 Advances in computing
has increased the efficiency of businesses to analyze data and
assess the position of a company. Technology has enabled
employees to perform better at their jobs, and increasing
profits. For example, the availability of computers for an office
enables employees to handle heavier workloads than when these
were not widely available for use. AI has eased data analysis
needs for businesses. Data mining is an example of an AI
technology that aids analysts with pattern, and trend recognition
of company data. New machinery has improved working conditions
for manufacturing companies, and eased the work employees have to
perform.
The challenge businesses face are related to the failure of
autonomous systems, and protection of information.36 If a machine
or a computer system fails, a company needs to have security
measures in place to correct a potential crisis and reduce
collateral damage. Businesses today also need to consider
cybersecurity to protect sensitive information from unauthorized
access. The biggest challenge for businesses is to stay
18
competitive with new technologies and being able to protect their
information.
Perhaps the most important stakeholder for the field of AI
is society, and the effects new technologies can have on the
community. There are differing views related to the benefits, and
repercussions that the generation of AI can have on society.
Effects can be seen in the areas of employment opportunities, job
displacement, and changing communication between cultures.
Opponents say that AI can be good for some social classes and bad
for others. For example as low skilled paying jobs like item
assembly or packaging become increasingly automated the industry
would experience a decrease in job openings. New jobs available
would displace the low-skilled workers (creating unemployment) in
favor of an educated work-force to maintain these machines. Even
though these displaced workers could find work somewhere else, it
is not a guarantee that the new job would generate the same
satisfaction and provide for the needs of these individuals.37
Opponents also discuss the fact that new technologies can
displace educated high-skilled workers. Paul Krugman, Nobel Prize
winner and professor of economics, expanded his idea that in
19
previous times unemployment caused by new technologies was solved
with intensive education of lower skilled workers. This method of
intensive education will not solve newer technological challenges
posed by AI.38 This is evident today, in the accounting field. In
the past a bookkeeper job was considered to be a technical job,
requiring education and experience. Today, newer accounting
systems, have simplified this job to an extent that a person with
little expertise can perform what used to be a high-skilled
position.
Scholars and economists who approve the creation of AI
contend that, “workers may be expelled from a company or a
sector, but sooner or later they will be hired by other companies
or reabsorbed by a different economic sector.”39 New technologies
will create temporary unemployment, but this change is never
irreversible since employment rates have always fluctuated. If
new technological advances increased structural unemployment by
now all the population would be unemployed because there has been
increasing technologies for over two centuries.40 There is always
a concern for increased unemployment, but AI is not the main
reason for this change. AI will restructure jobs and might create
20
temporary unemployment, but in general technology benefits
society in much greater ways.
Creation of new technologies, such as the invention of the
tractor have eased the work of farmers. Airplanes, and electronic
mail have made communication between cultures easier than ever
before. An important consideration is that increased connectivity
also decreases privacy. The complaints that users of technology
have is that businesses, government, and third party users can
have too much access to private information. Privacy will always
be an issue, especially with the nature of society for increased
communication and information sharing.
Biblical Approach
AI aims to create machines that possess intelligent
behavior. Some scientists such as Ray Kurzweil advocate for the
possibility of general artificial intelligence. Others, such as
Dreyfus, say general AI is impossible, and that the technology
produced by AI is considered to be weak AI. Nevertheless, both
scientists and the general public are sometimes fascinated by the
possibility of creating autonomous artificial agents
(specifically the possibility of the singularity). These AI
21
agents according to Kurzweil, will have the ability to reason and
behave like humans. We have seen the different approaches taken
by AI in creating an intelligent being. These approaches are the
symbolic approach, and the biological approach (Neural Networks).
Still after more than sixty years scientists have not been able
to create a machine that has common sense, and that is able to
reason like humans do. It is evident from the field of Machine
Ethics, that creating friendly AI is a priority, since an ethical
framework is essential for any new developments towards general
AI.
As a Christian I want to concentrate on the possibility of
creating a strong AI agent. Strong AI claims that it is working
towards producing a machine that is truly intelligent, human-
like, having a consciousness and being able to make ethical
decisions just like humans do. Machines might be able to imitate
intelligent behavior (computation, problem solving), but I do not
believe that it is possible to create AI with the ability to
reason and discern knowledge just like humans do. Referring to
intelligence in AI, I want to stress the fact that human
intelligence is completely different from machine intelligence.
22
In his publication, Computing Machinery and Intelligence, Alan Turing
acknowledges that his intention for AI was to create a machine
that is able to play the “imitation game”.41 To be considered
intelligent I will suggest that a machine does not need to, and
cannot, have conscious thought. An intelligent machine can imitate
intelligence with the use of databases and algorithms.
I believe that conscious thought and intelligence in humans
comes from God. Genesis 1:26 says, “And God said, Let us make man in our
image, after our likeness: and let them have dominion… and over every creeping thing
that creepeth upon the earth.” God made us in his image with a special
purpose in this earth. Clearly, God created us to be superior to
all of his creation, as everything created in the earth is given
for us by God to administer. Genesis 2:7 also states that God
“breathed into his nostrils the breath of life; and man became a living soul.” In the
Bible, the creation of human beings is the only time were it says
that God breathed life into his creation. By this verse we can
understand that our consciousness and ability to reason is not a
mere physical product, but a spiritual one. Thus, consciousness
if not provided by God is an impossible feat to accomplish. Job
33:4 shows that life comes from the Lord, “The spirit of God hath made
23
me, and the breath of the Almighty hath given me life.” God gave us both a
physical body, and a spirit which allows us to have discernment
of good and evil. Ultimately we are created for God’s glory, and
our ability to have conscious thought should be purposed to serve
the Lord (Thou art worthy, O Lord, to receive glory and honour and power: for thou
hast created all things, and for thy pleasure they are and were created. Revelation
4:11). It is impossible to create a machine that has a
consciousness, because our consciousness (and therefore
intelligence) is given by God.
I do not believe that man is capable of creating a truly
intelligent being. Proverbs 2:6 says, “For the Lord giveth wisdom: out of
his mouth cometh knowledge and understanding.” God in his power is the
only one that is capable of giving wisdom and knowledge. I
believe as humans we cannot, and should not attempt to create an
intelligent being, for only God alone is able to do this.
Intelligence comes from the Lord, and the purpose of being able
to reason should be for the glory God (The fear of the Lord is the
beginning of knowledge: but fools despise wisdom and instruction- Proverbs 1:7).
I am not opposed to technological innovation, and encourage
further development of technology that will increase the quality
24
of life that we enjoy today. However, the concept of general AI
supported by scientists (Transhumanists) like Ray Kurzweil is
flawed and contradicts Christian belief. Why would man be so
interested in the possibility of a technological singularity?
Genesis 11:4 shows man’s intention in his heart, “…let us make us a
name.” The story of babel shows us that, in his pride, man
rebelled against the Lord’s will. In our sinful nature we seek
our own desires, and advancement of personal agendas. Psalm 10:3
says that the wicked “boasteth of his heart's desire, and blesseth the covetous,
whom the Lord abhorreth.” The singularity approach to general
intelligence, seeks to create a godless world, were we are our
own god’s and control our destiny.
If the singularity were possible, we would be able to
achieve immortality by transferring our consciousness and
physical bodies to technological entities.42 As sinners our
penalty is death both physical and spiritual. Our bodies are
going to pass away someday, and the only solution to eternal
spiritual death is salvation through Jesus Christ (For the wages of
sin is death; but the gift of God is eternal life through Jesus Christ our Lord- Romans
6:23). The main belief and goal of singularity supporters is
25
based on the need to find an answer to death, which is the
penalty for our sin.
The pursuit of enlightenment and knowledge is not being done
with the purpose of glorifying the Lord, but rather to glorify
ourselves as supreme beings. This is not only the wrong approach
to take, but in the end is also a fruitless endeavor. As Solomon
says in Ecclesiastes 2:11, “Then I looked on all the works that my hands had
wrought, and on the labour that I had laboured to do: and, behold, all was vanity and
vexation of spirit, and there was no profit under the sun.” For these reasons I
concur that strong AI is not possible; even if the idea of a
strong AI agent can be entertained, I have also concluded that
this pursuit is not done with the right intentions. In the years
to come, we will be able to see new developments in the AI field,
and the attempts of different researchers to achieve this general
intelligence. For future developments of AI, I believe that
research should be directed towards development of weak AI, and
the idea of strong AI should not be considered. There are great
achievements and technological advancements that can be made
without the need for a singularity approach.
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Appendix
Appendix A
Biographical Information
32
Alan Turing: One of the leading scientists for deciphering the German Enigma code in the early 1940s. The first scientist towrite a philosophical analysis of the possibility of AI in his 1950 paper Computing Machinery and Intelligence.43 Devised the Turing Test in 1950. Which is still used today in annual competitions to measure the ability of machines to communicate like a real human being.44
John McCarthy: Born in Boston in 1927. Attended the California Institute of Technology and obtained a bachelor and graduate of science.45 McCarthy obtained a PhD from Princeton in1950. In 1952 he joined the faculty of mathematics in Dartmouth College. It is here in Dartmouth that McCarthy held the first conference and started formal research in the AI field.46 In 1963McCarthy invented the LISP language for AI programming. This yearMcCarthy also began his lifelong research project, which is to create a computer that possesses common sense.47
Appendix B
Asimov’s three laws of robotics were proposed in his fictionbook, I Robot. These laws were proposed by Asimov as a rule for creating AI that is friendly towards the human race:
1. A robot may not injure a human being, or through inactionallow a human being to come to harm.
2. A robot must obey the order given it by human beings except where such order would conflict with the first law.
3. A robot must protect its own existence as long as such protection does not conflict with the first or second law.48
33
Appendix C
The following conversation held between the AI agent ELIZA, and a person shows the ability that symbolic symbols have to analyze key words and provide appropriate responses. Although ELIZA is an older system, it still proved that computers in a waymimic human intelligent behavior.
ELIZA: I am the psychotherapist. Please, describe your problems.Person: Hello, can you help me?ELIZA: How do you do? What brings you to see me?Person: My wife asked me to see you.ELIZA: Tell me something about your family.Person: She says I use the computer too much.ELIZA: You have your mind on computers, it seems.Person: Yes, and my hands, too.ELIZA: Why do you say yes and your hands too?Person: Because I use it all the time.ELIZA: Is it because you use it all the time that you cameto me?49
Appendix D
Basic structure of an expert system (Knowledge-Based systems):50
Working Memory
Inference Engine
Interface
Knowledge Base
34
The Knowledge Base is data input by specialized experts to the system. Working Memory is the information the system (such as MYCIN) would use for the specific case the user is inquiring about. The inference engine would be the algorithm that sorts thedata input from the working memory and tries to match the information with the stored knowledge base. The interface allows the user to interact with the expert system and allows a user to reevaluate the question and receive appropriate responses.51
Appendix E
Bill 1298, passed in California (2012), is one of the examples of legislation made by government on a technological product produced by the efforts of the AI field.52
Senate Bill No. 1298
CHAPTER 570
An act to add Division 16.6 (commencing with Section 38750) tothe Vehicle Code, relating to vehicles.
[Approved by Governor September 25, 2012. Filed with Secretary ofState September 25, 2012. ]
LEGISLATIVE COUNSEL'S DIGEST
User
35
SB 1298, Padilla. Vehicles: autonomous vehicles: safety andperformance requirements.
Existing law requires the Department of the California HighwayPatrol to adopt rules and regulations that are designed topromote the safe operation of specific vehicles, including, amongother things, schoolbuses and commercial motor vehicles. Existinglaw also requires the Department of Motor Vehicles to registervehicles that are being operated in this state and to issue alicense plate to an applicant for the operation andidentification of that person’s vehicle.
This bill would authorize the operation of an autonomous vehicle,as defined, on public roads for testing purposes, by a driver whopossesses the proper class of license for the type of vehiclebeing operated if specified requirements are met, including thatthe driver be seated in the driver’s seat, monitoring the safeoperation of the autonomous vehicle, and capable of taking overimmediate manual control of the autonomous vehicle in the eventof an autonomous technology failure or other emergency. The billwould prohibit, except as provided for testing purposes, theoperation of such a vehicle on public roads until themanufacturer submits an application to the department thatincludes various certifications, including a certification thatthe autonomous technology satisfies certain requirements, and theapplication is approved by the department pursuant to theregulations that the department would be required to adopt. Thebill would require one of the certifications to specify that theautonomous vehicle’s technology meets Federal Motor VehicleSafety Standards for the vehicle’s model year and all otherapplicable safety standards and performance requirements setforth in state and federal law and the regulations promulgatedpursuant to those laws.
The bill would require that the Department of Motor Vehiclesadopt regulations as soon as practicable, but no later thanJanuary 1, 2015, setting forth requirements for the submission ofevidence of insurance, surety bond, or self-insurance required bythe bill and requirements for the submission or approval of anapplication to operate an autonomous vehicle, including any
36
testing, equipment, or performance standards, as specified, andto hold public hearings on the adoption of any regulationapplicable to the operation of an autonomous vehicle without thepresence of a driver inside the vehicle. The bill would providethat federal regulations promulgated by the National HighwayTraffic Safety Administration supersede state law or regulationwhen found to be in conflict.
The bill would require the department to approve an applicationsubmitted by a manufacturer upon making specified findings andwould authorize the department to impose additional requirementsif the application seeks approval for autonomous vehicles wherethere is no person in the driver’s seat. The bill would alsorequire the department to notify the Legislature of the receiptof an application from a manufacturer seeking approval to operatean autonomous vehicle capable of operating without the presenceof a driver inside the vehicle and the approval of theapplication. The bill would provide that approval of theapplication is effective no sooner than 180 days after the datethe application is submitted.
The department would be authorized to charge a fee for theapplication in an amount necessary to recover all costsreasonably incurred by the department.
37
End Notes
1 Jun Hongo. “Artificial Intelligence Outperforms Average High School Senior.” Dow Jones & Company, Inc.
2 Louis A. Del Monte. The Artificial Intelligence Revolution: Will Artificial Intelligence Serve us or Replace us? (USA: Louis A. Del Monte, 2013), 33.
3 James P. Hogan. Mind Matters: Exploring the World of Artificial Intelligence. (New York, NY: The Ballantine Publishing Group, 1998) 70.
4 Mark Bishop. "Why Computers Can’t Feel Pain." Minds & Machines 19, no. 4 (November 2009): 507.
5 Louis A. Del Monte. The Artificial Intelligence Revolution: Will Artificial Intelligence Serve us or Replace us? (USA: Louis A. Del Monte, 2013), 25.
6 Pamela McCorduck. Machines Who Think. (Natick, MA: AK Peters, Ltd. 2004), 19.
7 Isaac Asimov. I, Robot (New York, NY: Doubleday & Company, 1950), 85.
8 Aitopics. “Brief History.” Association for the Advancement of Artificial Intelligence.
9 Alan Turing. “Computing Machinery and Intelligence.” Association for the Advancement of Artificial Intelligence.
10 Aitopics. “Brief History.” Association for the Advancement of Artificial Intelligence.
11 Ibid.12 Pamela McCorduck. Machines Who Think. (Natick, MA: AK Peters,
Ltd. 2004), 442.
13 Aitopics. “Brief History.” Association for the Advancement of Artificial Intelligence.
14 Louis A. Del Monte. The Artificial Intelligence Revolution: Will Artificial Intelligence Serve us or Replace us? (USA: Louis A. Del Monte, 2013), 43.
15 Kenaw, Setargew. "Hubert L. Dreyfus’s Critique of Classical AIand its Rationalist Assumptions." Minds & Machines 18, no. 2 (May2008): 228.
16 Aitopics. “Brief History.” Association for the Advancement of Artificial Intelligence.
17 Hall, J. Storrs. Beyond AI. (Amherst, NY: Prometheus Books, 2007), 65.
18 Aitopics. “Brief History.” Association for the Advancement of Artificial Intelligence.
19 James P. Hogan. Mind Matters: Exploring the World of Artificial Intelligence. (New York, NY: The Ballantine Publishing Group, 1998), 246.
20 Louis A. Del Monte. The Artificial Intelligence Revolution: Will Artificial Intelligence Serve us or Replace us? (USA: Louis A. Del Monte, 2013), 17.
21 Aitopics. “Brief History.” Association for the Advancement of Artificial Intelligence.
22 Yu Golubev. "Neural networks in mechatronics." Journal Of Mathematical Sciences 147, no. 2 (November 22, 2007): 6607.
23 Ibid, 6007.
24 Blay Whitby. Artificial Intelligence: A Beginner’s Guide. Oxford, England: One World Publications, 2003.
25 James P. Hogan. Mind Matters: Exploring the World of Artificial Intelligence. (New York, NY: The Ballantine Publishing Group, 1998), 183.
26 Carole Cadwalladr. “Are the robots about to rise? Google's newdirector of engineering thinks so.” The Guardian News.
27 Blay Whitby. Artificial Intelligence: A Beginner’s Guide. Oxford, England: One World Publications, 2003.
28 Ibid.29 Hubert Dreyfus. "A History of First Step Fallacies." Minds &
Machines 22, no. 2 (May 2012): 90-91.
30 Szoldra, Paul. “Elon Musk Thinks Sci-Fi Nightmare Scenarios About Artificial Intelligence Could Really Happen.” Business Insider.
31 Anderson, Michael, and Susan Leigh Anderson. "Machine Ethics: Creating an Ethical Intelligent Agent." AI Magazine 28, no. 4 (Winter2007 2007): 15.
32 John O. McGinnis. "Accelerating AI." Northwestern University Law Review 104, no. 3 (Summer2010 2010): 1260.
33 Ibid, 1259.
34 Ibid, 1254.
35 AI Magazine. “A (Very) Brief History of Artificial Intelligence.” Association for the Advancement of Artificial Intelligence.
36 Ibid.
37 Riccardo Campa. "Technological Growth and Unemployment: A Global Scenario Analysis." Journal Of Evolution & Technology 24, no. 1 (February 2014): 87-88.
38 Ibid, 88.
39 Ibid, 87.
40 Ibid, 88.
41 Alan Turing. “Computing Machinery and Intelligence.” Association for the Advancement of Artificial Intelligence. 13.
42 Ronald Cole-Turner. "The Singularity and the Rapture: Transhumanistand Popular Christian Views of the Future.” Zygon: Journal Of Religion & Science 47, no. 4 (December 2012): 790.
43 R. K. Shyamasundar. "The computing legacy of Alan M. Turing (1912-1954)." Current Science (00113891) 106, no. 12 (June 25, 2014): 1669.
44 Ibid, 1679.
45 Hayes, Patrick I., and Leora Morgens Tern. "On John McCarthy's80th Birthday, in Honor of His Contributions." AI Magazine 28, no. 4 (Winter2007 2007): 94.
46 Ibid, 95.
47 Ibid, 96.
48 Pamela McCorduck. Machines Who Think (Natick, MA: AK Peters, Ltd, 2004), 25.
49 Hall J. Storrs. Beyond AI (Amherst, NY: Prometheus Books, 2007), 65.
50 James P. Hogan. Mind Matters: Exploring the World of Artificial Intelligence (New York, NY: The Ballantine Publishing Group, 1998), 246.
51 Ibid, 247.
52 State of California. “Senate Bill No. 1298.” California Legislation. http://leginfo.legislature.ca.gov/faces/billNavClient.xhtml?bill_id=201120120SB1298.