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Engineering Faculty

Civil engineering Department

Third Year Major Research Project

A CRITICAL EXAMINATION OF USING HUMANOID ROBOTS IN

CONSTRUCTION:

Exploring the Potential Risks through Artificially Intelligent Behaviour

Supervisor: John may

DECLARATION

The work described in this project report is all my/our own unaided effort, as are all the text,

tables, and diagrams except where clearly referenced to others.

Signed: Signed:

Peter Neville Baiju Vaidya

Date: 23/04/2008 Date: 23/04/2008

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Acknowledgements

Firstly we would like to thank John May for his supervision and assistance with our report.

Also, from the University of Bristol Psychology department, Dr Clive Frankish, who helped

with guiding us in a previously unfamiliar area. Thanks also goes to Dr Zeyang Xia of Tsingua

University - Robotics and Automation Department, Kayla Kim of Robotis Corporation and

Junichira Maeda of The Shimizu Corporation, for their support and information of current

humanoid technologies. Finally, a thank you to The Singularity Institute for Artificial

Intelligence for providing an insight into AI.

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Executive Summary

The main objectives of this report are to highlight the crucial discussion points for the future of

Artificial Intelligence, and show how these will determine the nature of risks through using

humanoid robots in construction. In this report, humanoid refers to a humanoid robot. This is

an autonomous robot, is the form of a human, which can be advantageously deployed to

perform tasks in a range of environments [i]. Construction is one of the largest industries in the

world, and one which humanoids could greatly benefit.

Introduction

The limited history of robotics and the rate of progression in technology has emphasised how

important it is to consider the risk of tomorrows artificial agents today. Looking at the potential

of humanoids at present has shown that they could be ideal for use on construction sites. The

main needs for humanoids in construction were found to be limited human capabilities, more

effective & efficient site operation, and safer working practices.

Artificially Intelligent Behaviour

By studying cognitive psychology and human internal processes, various limitations that

humanoids in construction may face transpired. These included inadequacies in sensation,

perception, recognition and attention. Researching modern theories of AI, two possible futures

of intelligence in artificial agents were concluded, one where there is a limit at basic

intelligence and one where this limit does not exist. Following this a functional analysis was

carried out for each AI future, which declared what functions a humanoid would need for

construction.

Risk

For basic intelligence, a risk assessment was carried out and showed that the majority of

consequences were detrimental to the construction industry in terms of human resources and

productivity. With highly intelligent humanoids, it was shown that the major risks lie in lack of

human control. Masked by the potential benefits of using humanoids, construction companies

could underestimate the complexity of control needed, and so be under the pretence that their

control is sufficient when it is not. If this is the case, the risks could be catastrophic.

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Contents

Introduction 4-14

A Brief History of Robots and Humanoid Robots 4-6

Case Study: Honda – The development of Asimo 6-8

Current Uses of Humanoid Robots 8-9

What are the needs for Humanoid Robots in Construction? 9-11

Automation in Construction now 12

Inhibitors to Progress and Recommendations 13-14

Where is Industry Heading? 14

Artificially Intelligent Behaviour 15-28

Introduction to AI Behaviour 15

Psychology of Artificial Intelligence: How a humanoid might behave 16-20

Agency and Artificial Intelligence – Intelligent Agents 20-25

Possible application and issues regarding humanoids for construction tasks 25-27

Investigation by Functional Analysis Method 27-28

Risk Assessment – Humanoid Robot: Weak AI (Basic Intelligence) 29-31

Risk Assessment table 30-31

Risk Assessment – Humanoid Robot: Strong AI (High Intelligence) 32-39

Intelligence Levels 34-36

Control 36-37

Ethics 37-39

Final Discussion 40-42

References 43-44

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Introduction

A Brief History of Robots and Humanoid Robots

The era of robots, in particular humanoid robots, is in its infancy. Much of the work that has

taken place in this field dates only to the last century, but this has laid vital foundations that can

be built upon. Our efforts in understanding a humanoid robot’s behaviour and estimating the

potential risks associated with its use, have to stem from previous results established by

inventors, scientists and theorists.

The operation of humanoid robots has yet to happen and the research currently ongoing is

progressive, but limited. In addition, it is probable that humanoids will emerge as specialists in

certain tasks (similar to automated robots used today), before ones with generic intelligence

materialise. A study of the development of robotics through time will provide an insight into

how technology has progressed, and hence better understand the direction that robotics is

heading in the future.

In the past, little research has been carried out on humanoids, but more on robots in general.

Only recently has the work on robots been advanced enough to create humanoids, so much of

the history lies in the broader field of robotics, rather than specifically on humanoids. In

reality, a humanoid is simply an autonomous robot but its overall form is based on that of a

human. Advances in humanoid robots will mainly be through their AI capabilities, as will be

shown in the following section. This means that the humanoid could one day have the ability to

interact with people using natural language, self-learn, and think in order to fulfil its goal.

The word robot originates from the Czech word robota, meaning slave-like labour [1]. Its clear

purpose from its original design was to be a simple aid to the human; to perform tasks the

human didn’t want to or shouldn’t have to perform. History on robotics is very vague, partly

due to false claims of robots having been built in the past, but mostly due to the definition of

the word robot. An actual mechanical agent, with the ability to decision-make, known as a

robot, has only truly been around for the past century. However the ideas and designs of an

‘inanimate creation’ that performs various tasks have been around for centuries. Various

‘machines’ have been constructed in the more distant past with the ability of performing one

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sole action but can these be defined as robots? It is more logical to say that the technological

age in the last century that has created detailed, reliable electronics and a vast increase in

computer technology, has ‘added brains to brawn’ so to speak. These machines now have the

ability to convey a sense that they have intent or agency of their own.

Agency is a philosophical concept of an agent being able to make choices and impose those

choices on the world [2]. Robotic engineers solely consider mental agency. This is judged not

on the appearance of the machine, but the way its actions are controlled. For example, a typical

remote controlled car is not considered to be a robot, however, self-controlled cars like the

1990’s driverless cars of Ernst Dickmanns, could be classified as a robot [3]. On the other

hand, for many laymen, a CNC (Computer Numerical Control) milling machine is not

considered to be a robot, but a factory automation arm or a humanoid is. Interestingly, the CNC

milling machine has a very similar control system to a robot arm, however the perception of

human features makes people feel that the machine is not simply a machine, but is aware of its

surroundings, and thus a robot. Due to this uncertainty, different countries set various

guidelines for what can be classified as a robot [4].

The first major design of a humanoid was by Leonardo da Vinci in around 1495, around 500

years before the first humanoid was ever constructed. The design is of a mechanical knight

able to sit up, wave its arms and move its head, and is said to be based on the Vitruvian Man.

Prior to the construction of robots, complex machines existed with the ability to perform

certain tasks. It was from these that robots came into being, and in turn from these that

humanoids were created. It is claimed that the first electronic, autonomous robot was created

by William Grey Walter in Bristol, in the early 1950s. Capable of sensing light and being able

to contact objects, meant it was able to easily navigate [4]. Following this, the first modern

robot was constructed in 1954 by George Devol named the Unimate [5]. Within the next six

years it was sold to a General Motors plant to lift hot pieces of metal from a die-casting

machine, and stack them.

In 1971 Miomir Vukobratovic and his team at Mihajlo Pupin Institute, Serbia, built the first

active anthropomorphic exoskeleton, meaning it had the unique human attributes but in a

nonhuman form. This led to construction of the first full-scale anthropomorphic humanoid

robot. Wabot-1, built in Waseda University, Tokyo, had the ability to communicate with a

person, measure distances and judge direction using external receptors, and could hold and

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transport objects using tactile sensors on its hands [6]. It consisted of limb-control, vision and

communications systems. This breakthrough in technology was the first glimpse that man

could appear to give life to an inanimate object. In quick succession, further similar humanoids

were produced, each trying to outdo the other. Like the space race, Japan and the USA had a

small technological race for humanoid creation. Laboratories and research centres were set up,

and a great deal money was given to fund R&D in this field.

Since Wabot-1, each new humanoid created had more similarities to not only the human form,

but also human behaviour. Primarily, the evolution of humanoids was in the way of increased

vision, increased speed and an increase in the degrees of freedom. It was then stepped-up to

designing a humanoid being able to walk on uneven surfaces, creating an artificial respiratory

system, and manufacturing a silicone skin.

Case Study: Honda - The development of Asimo

[7], [8], [9]

Before undertaking a study on humanoids, a general

understanding of a current humanoid’s components and

formation is necessary. Understandably, this delves into more of

the technological aspect of the humanoid and could be greatly

detailed. Furthermore, the variety of humanoid structures are

excessive, and so for the purpose of this introduction, a brief and

concise case study will be carried out on arguably the most

advanced humanoid today; Asimo, created by Honda.

Figure 1

In 1986, Honda set themselves the task of constructing a two-legged humanoid robot that had

some abilities similar to that of a human. Their goal was to ultimately create a partner for

people, a new kind of robot that functions in society.

Prior to Asimo, a series of development robots were constructed. In early experimental models

(E0 – E3), from 1986 to 1991, the focus point was to create legs that could simulate the

walking motion of a human. The second stage in the development of these models (E4 – E6),

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took place between 1991 and 1993, where the motion of legs was developed for stabilisation

and stair climbing. Honda’s first series of prototype humanoid robots (P1 – P3) were developed

between 1993 and 1997; a head, body and arms were added to the robot to improve stability

and add functionality. The evolution from P1 to P3 was through weight and height decrease,

and its aesthetics; on the whole making it more similar to a human. In 2005, the latest version

of Asimo was unveiled. Having surpassed all of its counterparts, Asimo has the ability to walk

and run (both feet off the ground between paces) on uneven surfaces, register and interact with

objects, recognise certain programmed faces, and comprehend and respond to voice

commands.

Weighing 52kg and with a height of 120cm, meant that Asimo was the smallest model

produced so far. Through anthropometric research, it was found that this combination of height

and weight made the humanoid more ergonomically optimal. Asimo has 34 degrees of freedom

meaning that its motion is more fluid and dynamic. A major development from the prototype

models is the ability of Asimo to change direction while running. This, along with Asimo’s

advanced communications technology and increased sensory perception, has assisted Asimo in

realistic movement and actions.

Recent developments have meant Honda can now enable humanoid-humanoid interaction. This

has been through developing information transfer systems between Asimos. Through this, a

range of Asimos can interact, and deduce the most time-efficient way to complete a task. In

addition, Asimo can now also detect a variety of surrounding movement and thus can identify

oncoming people. It can then choose the most appropriate path so that it does not block the

movement of others. Most recently, a new space-saving battery recharging station has been

created, and through the latest technology, Asimo will automatically recharge at the nearest

station when its battery falls below a critical point.

A concise technological understanding of what can be called a ‘model’ humanoid of today can

be used as a solid foundation in order to progress in the report. If an understanding of an

undeveloped future humanoid is to be gathered, this technical case study of Asimo is

necessary. All of the recent developments mentioned have made the idea of humanoid use on

construction sites more of a reality, and so from this trend, it is logical to suggest that not only

will humanoids be present on a construction site in the very near future, but they could have

numerous uses.

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At this stage in the development of Asimo, Honda’s main aim is to put R&D funds into

looking more at intelligence and AI capabilities, as this is the difference between a limited use

humanoid and a next generation humanoid. This aspect of AI is what will be investigated in the

following section Artificially Intelligent Behaviour.

Current Uses of Humanoid Robots

Before looking at the uses a humanoid robot has in our society today, it is essential to look at

why it has them. Only then can future uses be appropriately assessed. The main areas of R&D

in humanoids are in motion, perception based control, interaction, and upper limb control [10].

The major flaw in motion is the use of a humanoid’s legs. Not only is speed very limited, but

also the ability to adapt to height changes in the ground causes significant movement issues.

Another major flaw is the ability of a humanoid to interact with its environment and with other

humans. These two flaws alone have limited the potential uses of humanoids due to health and

safety reasons. Therefore, the main uses at present are such that the flaws are not exposed.

Humanoids in entertainment, is a concept we are all aware of. Even before humanoid use,

science fiction films such as Star Wars have entertained us with humanoids like C3PO. Now,

universal studios have released Ursula [10]. A humanoid solely for entertainment, she will

walk, talk and entertain crowds. However, her abilities are very limited which is due to the two

major flaws discussed above. Sony also released a set of dream robots; however due to the fact

it was to be made available for children, its size had to remain at 0.6m tall and its strength

capabilities minimal.

Humanoid robots are only now being developed to work in close proximity with humans. In

2005, Wakamaru created by Mitsubishi was released to provide companionship to elderly and

disabled people. Its cost is relatively low at $14,000 in comparison to other humanoids being

developed. However this is in concurrence with its limited abilities. Functions include

reminders to take medicine and calls for help if it suspects something is wrong.

At this point in time, humanoid robots are still undergoing research and development. With the

idea of humanoid use still being in the very early stages, all that have been made so far are, in

principle, prototypes that are being tested. The uses mentioned above however are not the main

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ones forecast for the humanoid’s future. More importantly are the potential impacts that a

humanoid can make in industry; particularly the construction industry.

What are the needs for Humanoid Robots in construction?

In order to discover the needs for humanoids on construction sites, it is necessary to understand

how a typical construction site operates. The main flaws in the construction industry will be

identified, and robots that are used in the industry today will be examined. Also, inhibitors to

the progress of robotics in construction and ways to improve development will be reviewed.

Only then can it be understood where a humanoid could fit in, what tasks it could carry out,

and who it would need to communicate with. It is believed that there are needs for humanoids

in construction, and by understanding what they are, it will be seen how the construction

industry of tomorrow could be a safer and more efficient place.

A crucial aspect is to identify where humanoids could fit into the industry. It is clear that when

humanoids are first implemented on construction sites, they will take on the role of a

construction worker, receiving orders. Any higher-ranking humanoid is probably a very

futuristic scenario, and might not be seen unless they are commanding other humanoids. To

begin with, humanoids will most likely be used to assist human construction workers in

carrying out simple tasks such as lifting objects. Most importantly, they will need to

communicate with other robots or human workers in some way. Perhaps certain workers on

site will receive special training to allow them to give orders successfully to a humanoid. How

this might occur will be examined later in the report.

By looking at flaws in the industry, and the challenges that face construction now and in the

future, drivers for the acceptance of humanoids can be deduced. If humanoids are a realistic

vision for the near future, these drivers for change must be established and understood. In

Britain alone, there are over two million people working in the construction industry, making it

the country’s largest employer. In the past 25 years, nearly 3000 people have died and many

more injured as a result of construction work [11]. Nowadays, fatalities and serious injuries are

much rarer; however, they will inevitably happen which many people regard as unacceptable in

this day and age.

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There are various reasons for accidents occurring, the main one being human error, which will

always be present. It is due to nature and cannot be helped that humans have idle tendencies,

become tired, will not always stay vigilant, or will oversee errors. As long as humans continue

to work on construction sites, accidents will occur. The point being implied here is that

humanoids might ease this problem, although it is not as simple as that. Humanoids may also

be equally unsafe, if not more than humans, especially in the early stages of use. To what

extent this may be the case is unknown; assessing the risks to try and clarify the situation

would appear to be the only responsible course of action.

The arguments are complex, and there is an important temporal element. An idea that should

be considered is that humanoid use in the future could result in far fewer accidents occurring in

the even farther future. However, risks concerning humanoids in their early stages may be

plentiful, but it can be hoped that these safety issues will be eliminated with time. Surely, the

prospect of a construction industry involving humanoids with no accidents associated with

them is a driver for change.

A flaw of the industry today, which may not be immediately obvious, is human labour, and the

shortages or unreliability of supply; the Swiss construction sector for example is suffering from

a declining number of workers [12]. The reason why it is not focussed upon a great deal is

because there is no current viable alternative to the problem. Absence from work or sick leave

costs the UK economy around £1.75bn a year with back pain being a major cause of time off,

so understandably, much loss occurs within the construction industry [13]. Other factors that

incur losses include paying for training and holidays. Understandably, if humanoids are used in

construction, then far fewer losses would occur. Capital costs for the humanoid units would be

high, especially to begin with, but the life-cycle costs might be lower.

In many places around the world, shortages of skilled labour are a big problem and humanoids

could be implemented to ease this shortage. Additionally, more and more young people are

opting for university educations rather than learning a trade, which is another explanation for

the increasing shortage in some areas. It may be argued that humanoids will be used where

there is still a good supply of labour, putting people out of work. But the dissemination of these

robots is likely to be very slow and their abilities are unlikely to match that of humans for some

time after their debut. Therefore, any unemployment due to this is not seen as a major

significance, as it will be a natural progression of society and industry.

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Labour is the resource that is most critical for progressing in any project and its efficient use

must be harnessed in order to achieve project effectiveness [14]. Building sites are subject to

much delay such as obtaining certain work materials, and when work is rescheduled due to

this, workers can be left with nothing to do whilst still being paid.

Although the limit of human capabilities is not seen as a cause for inefficiency, this is again

because there is no current alternative. As well as some of the problems facing construction

being potentially reduced by using humanoids, productivity on site could be bolstered.

Humanoids could be designed with various attributes for certain tasks; there will no doubt be

different ‘breeds’. They could potentially be faster, stronger and more precise than human

beings. With this arise issues of safety, for example if a humanoid has greater strength than a

human, this could be a huge risk factor and there may need to be a trade-off, which is focused

on later in the report. If ways can be developed of confidently mitigating these risks though,

then the prospects are highly desirable.

In some ways, the use of humanoids could improve sustainability. For instance, many workers

in the construction industry use cars, as work is always changing and often in remote parts. In

the days of humanoids, there could be one delivery to and from site.

Certain areas of construction are high risk, such as mining, tunnelling, or any type of deep

excavation, and humanoids could be employed to reduce risk of harm to human life. That is not

to say a humanoid robot will be dispensable, but the value of human life will always be greater

than that of a machine. Mining in South Africa is more dangerous than in any other country

with over 200 deaths in 2007, an increase from the previous year [15]. Instances like this

contribute to the drive for change of attitudes and more towards artificial intelligence.

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Automation in construction now

Various automated robots used today have been examined in order to understand the current

state of the technology and how we are heading towards a future where AI will be a significant

feature. Automated robots in construction must control their own performance in carrying out

sequences of operations. Due to the nature of a construction site, prone to variation much

unlike a well-ordered factory, they must be highly suited to their purpose. For this reason the

robots found in construction at present will only carry out very specific tasks.

The Shimizu Corporation in Japan have developed prototypes and working construction robots

including a concrete power-floating machine and a wall climbing painting robot [16]. The

concrete power-floating machine is a good example of how productivity of the human task it

performs can be raised. Used regularly in Japan, it provides a means of acquiring a good finish

to the concrete surface in a third of the time that a team of construction operatives would have

taken.

The ‘RoadRobot’ is a fully automatic road paver developed by the German company Joseph

Vogele AG [17]. It is a masterpiece of automation and was developed to pave roads

automatically, improve quality and reduce costs. Not surprisingly, the RoadRobot is the most

expensive among Vogele road pavers, but certainly the most impressive [18]. Regular pavers

certainly have automation of individual functions but this will not satisfy future needs. By

linking all of the operating functions to form an overall automatic system, the human operator

can direct their skills to fewer jobs such as monitoring output to ensure highest quality is being

maintained.

A Surface Preparation system nicknamed ‘BIBER’, developed by a partnership of companies,

is an ingenious way of automatically removing, preparing or restoring surfaces, including wall

facades, ships and tanks [19]. It was developed as a major labour saving device and a way of

improving quality and lowering costs. The system comprises a toolhead, telescoping lifting

unit and a vacuum cleaner. The innovative toolhead allows removal of rough or old coating

and scrubbing of large areas. The telescopic lifting arm can reach up to 60 metres, saving costs

of scaffolding, which would have been otherwise used, and the vacuum picks up the loosened

particles that are contained and the air is then filtered.

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Inhibitors to Progress and Recommendations

The development of robotics in construction is more difficult than in other industries for a

number of reasons. The industry is extremely diverse and one that has to cope with a unique set

of circumstances on each site. The seemingly unorganised nature of work, temporary works,

and weather issues are some of the main contributors to the barrier against robotics in

construction. There is also much investment needed [20]. That said, progress has been made

and if continued, civil engineering will see more autonomous machines replacing humans

where safety and efficiency are paramount. These issues are likely to become even greater

driving forces as time progresses.

In more general terms, one of the greatest inhibitors to progress is the lack of advancement in

AI. It is a huge challenge to develop a humanoid to see and hear, and all the other senses that it

needs to possess in order to work with humans. An important concept will be the issue of

checking how much information a humanoid is processing and what it will do. If it is unable to

process certain information, or data is handled incorrectly, the humanoid could cease the task

or carry out the wrong function; this may be a risk to itself and others on the construction site.

Giving the power of thought to a machine can be a very dangerous thing, so human control

must always be established.

In order to reach a future where humanoids work in construction, the problems facing

automation in general in the industry should be tackled. One of the greatest inhibitors to the

introduction of robotics is the lack of integration between design and production. By separating

these processes, designs will not take account of constructability issues, therefore not catering

for the needs of automation. A more logical approach to these processes is required if the

benefits of robotics are to be fully realised.

Construction companies can make a huge difference by developing strategies for embarking on

R&D programmes. They should form alliances with other relevant players in the construction

process. It could prove advantageous to focus on designers and engineering firms with the

ability to innovate. Clients and customers are also able to contribute by encouraging innovative

uses of technology.

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Much can be learnt from Shimizu’s SMART (Shimizu Manufacturing system by Advanced

Robotics Technology) program, which has looked at redefining the construction process [21].

Their aim is to recreate the ordered working environment of a factory as a construction site.

This is achieved by using CIC (Computer Integrated Construction), which automates a number

of processes including erection and welding of steel frames and placement of precast floors and

walls. With this system in place, construction processes can become more standardised and

project durations and man-hours greatly reduced.

As we have seen, robots used now can only function in very specific scenarios and if

construction processes do not change, this will cause set backs for robots of the future. Shimizu

is taking the SMART approach so that the application of robotics can be less problematic. In

turn, when humanoids are used, they will function much better in environments that are similar

and less prone to variation.

Where is Industry Heading?

In the coming years we can expect to see much more attention given to the navigation and

sensing (especially vision) of robots. There will be more investment for R&D and more

standardisation of components. There are likely to be changes in construction processes,

tending towards simplified assembly and fixing, and offsite prefabrication will increase.

Just as in the 1980s when technology was progressing rapidly and the possibilities for

automation in construction were realised, we are now reaching a stage where attitudes are

changing. The vision of humanoid robots working in construction is becoming more

widespread and companies are seeing them as a seriously viable option.

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Artificially Intelligent Behaviour

Introduction to AI Behaviour

Prior to analysing any form of risk that a humanoid robot of the future could cause on a

construction site, it is vital to have a fundamental understanding of cognitive psychology and

the mental processes that determine its behaviour. These mental processes are based on those

operating in the human brain, such as sensation, perception, problem solving, attention,

communication and memory. By analysing these, important design issues and limitations will

begin to surface. Focus will be given to the possible ways a humanoid could work on a

construction site, and a functional analysis will be carried out in order to help define what tasks

will be necessary. The specific concrete scenarios will help to further identify possible

limitations.

Due to the conceptuality of this report, it is near impossible to carry out a straightforward risk

assessment of humanoid robots, whose future is so ambiguous. As a result, one of the focal

aims of this section of the report will be to look at the essence of a humanoid, or any future

system for that matter - Artificial Intelligence (AI). This will help to estimate the extent to

which a humanoid will be able to act upon its own accord. By exploring some of the

compelling arguments concerned with AI, estimations will be made as to what level of

intelligence could actually develop in the future.

It should be noted that this section of the report will not focus on the technical details of

artificial intelligence and what can and cannot be currently achieved. This study looks at a time

in the future that cannot be designed for at present, and makes assumptions about what may be

possible. The aim is not to design a prototype humanoid, but rather, the work aims to make the

argument that it is essential to think critically about the future use of humanoids in

construction. A side effect may be that it is also useful to a designer of humanoids for

construction, helping to keep in mind certain design issues that will reduce the likelihood of

risks occurring - a critical but often overlooked part of defining requirements for a humanoid.

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Psychology of Artificial Intelligence: How a humanoid might behave

Cognitive Psychology

Cognitive Psychology is the scientific study of mental processes of behaviour. It is being

studied here to help to understand the limitations of a humanoid’s capabilities. This section will

highlight the relevant principles of mental processes, how they relate to humanoids, and what

potential limitations could arise as a result.

Before humanoids can be used in construction, we must ask ourselves: how is information

about the external world transmitted to the humanoid’s processor; and what design problems

must be solved by robotics engineers for sensory processing? It is difficult to investigate

relevant mental processes as there are few humanoids at this time and technology is limited.

Suitable assumptions and predictions will be made based on a number of key sources.

Information Processing [22]

Information processing is based on mental processes that acquire, interpret and transform

mental representations, from perception to memory. Input is registered through the appropriate

sensors and transferred to a short-term store where decisions occur and a response is the

outcome. As humans, we also transfer information from a short-term memory store to a long

term, or permanent memory store, shown in Figure 2. Humanoids will also need a memory in

order to recognise objects and perform tasks. The question that arises is, will a humanoid be

able to create its own memory by processing information in the same way as a human, or will it

merely manipulate

information? An attempt

at tackling this question,

along with the broader

issue, can be found in

subsection; Intelligent

Agents.

Figure 2

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Sensation and Perception [22], [23]

Sensation is the detection of simple properties such as brightness, colour, hardness or loudness.

Perception is the interpretation of these sensory signals that facilitates object recognition and

the identification of properties such as size and location. The distinction between sensory

signals may not be entirely clear; properties that can be directly sensed may be rather complex.

This could cause huge repercussions in the case of humanoids. The essential requirement for

their sensory system is a network mechanism for translating stimulus energy into electrical

signals and a means of differentiating between stimulus qualities.

The processes of perception are largely automatic for humans, but are very complex for

humanoids, where they may require a large amount of processing to perceive a single object.

The first stage of object recognition is to group elements of the visual array that correspond to

different objects. A humanoid will need to have sufficient means of defining between a figure

or object against the ground. Humans are able to use their vast knowledge and common sense

in order to perceive the world around us, but visual images could prove ambiguous for a

humanoid. For instance, how will it differentiate between size and distance; shape and

rotation/distortion; colour and illumination?

Perceptual information makes contact with meaning, for example, recognising objects and

faces, and reading and comprehending words. In order to identify the sensorial input, a

humanoid will need to match this up with its stored memory bank. For coherent cooperation

with human workers, designers should aim to match the efficiency and response time of around

200ms that humans are capable of. This is a difficult task due to the extreme variability that

exists in the sensory input.

Recognition [24]

In the film The Terminator [51], the humanoid robot is fitted with a camera like device, which

presents annotated output to an internal control post; this annotation relates to the concept of a

‘homunculus’, which is used to illustrate the functioning of a system, and can be viewed as an

entity or agent. An example of this is illustrated in Figure 3. If a similar approach is developed

for a humanoid for construction, then the question is raised: How will it recognise objects that

are annotated in the visual output?

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Figure 3

One possible solution to the question is the Template theory [Neisser, 1967]. It is achieved by

choosing the template stored in the memory that provides the best match to a sensorial input. It

is a simple idea and is already used by non-human recognition systems such as bar code

scanners. Problems arise due to the enormous amount of templates that the robot’s memory

would need, and also the similarities and dissimilarities that exist between stimuli and

templates that are not specified. Another theory that could form the basis of object recognition

for humanoids is Feature Matching. Patterns are recognised in terms of features, which are

fragments, or constituents of a larger unit. It works well in that a finite number of features

could potentially combine into an infinite number of objects; but feature matching only works

in fairly simple domains, such as printed letter recognition, and faces difficulty in the

recognition of real objects. Both these theories are possibilities for future humanoids but face

limitations.

Possibly the most realistic solution is recognition by components [Biederman, 1987], or geon

theory. Objects can be described in terms of small sets of geometrical parts named geons. The

24 established geons are simple 3D shapes like cubes, cones and wedges, each one having 15

sizes and builds. Representation of an object consists of an array of constituent geons, as well

as a description of the spatial relations among them. There are 81 possible ways to join them

and statistical analysis shows there are over 10 million possible objects that can be constructed

from two geons. Some geons are illustrated in Figure 4a with examples of objects they can

combine to make.

19

Figure 4a Figure 4b

Many everyday objects can be built out of a small number of geons into instantly familiar

shapes. The geon method of recognition could work very well for humanoids, as it would allow

them to confidently recognise the objects on a building site and also complex objects such as

animals and humans. Figure 4b shows how this can be achieved by breaking down the process

into several stages from simple to complex, until the desired level of confidence is reached.

Geon theory stands as a strong contender for recognition systems but still faces a key

limitation; distinguishing between different faces would be problematic due to the largely

generic geon construct of the face. Also, natural objects would cause difficulties, such as a tree

or puddle. Geon theory works well for artefacts, but due to the aforementioned limitations, it

would not be sufficient alone as a basis for recognition.

The human brain can interpret images of very unfamiliar objects. It may not be able to

recognise or name the object, but it can describe it in detail; shape, surface-texture, orientation,

size, position, and colour. Computer vision programs for humanoids in construction ought to

be able to do the same sort of thing if they are to be truly useful in the future.

Attention [25]

A humanoid will be able to sense a large amount of

information at any one time, but selectivity is required to keep

this information to a manageable size. It would therefore need

the attribute of attention in order to behave successfully on site,

which would filter out most irrelevant information.

Broadbent’s filter model [1958] in Figure 5 represents

sensorial information as identifiable balls, with attention symbolised by a Y-shaped tube. The

tube can only accept one ball at a time with a hinged flap acting as a filter.

Figure 5

20

f: P* A

Information is held in temporary store before it is reported and undergoes rapid decay. A

humanoid will need to be able to switch the filter from one channel to another, which could

take longer than it does for a human. This process is automatic for humans and highlights

another area of development that is required for success in humanoid AI. Name activation for

channel entry could be used to grab humanoid attention, but when tasks are becoming more

complex, and they have more responsibility, they should be working on their own accord

without constant prompting. A humanoid that exhibits a high level of intelligence will

understand natural language and various gestures, so will achieve a high level of attention.

Whether or not this level of intelligence can be reached, there will be a long time where robots

can only understand limited subsets of language. Communication processes are likely to be

slow and laborious, with possible consequences including misinterpretations of commands.

Agency and Artificial Intelligence – Intelligent Agents

Agency is the capacity of humans, animals, robots, or ‘agents’ to make choices and act upon

them; it will prove to be vital in understanding the behaviour of humanoid robots. So how do

Agency and AI link together? AI is the study of intelligent agents; ones that acknowledge their

surroundings and take certain actions in order to perform their tasks [26]. In terms of

intelligence, the simplest agent would be a single tasked computer programme, solving a basic

problem. On the other hand, the most complex agents are humans; the capability of the brain is,

as yet, unmatchable.

There is a format by which a humanoid, or any intelligent agent for that matter, relates to its

environment. The humanoid will perceive information from its environment. With its sensors

and actuators, it will respond the relative actions. Abstractly, an agent is a function from

percept histories (P*) to actions (A), illustrated in Figure 6 [27].

Figure 6

21

When analysing potential risks, what level of intelligence is being looked at, regarding the

operation of humanoid robots on a construction site? The main discussion within this section of

the report is what level of artificial intelligence can be physically achieved? Theoretically, it is

assumed that, as with any new technology, with time humanoid intelligence will continue to

increase. However with regards to the discussion of the philosophy of AI, compelling

arguments exist for and against ‘strong AI’ prevailing in the future. If strong AI does not

prevail, there will be an eventual standstill to the progression of AI; this is what is known as

‘weak AI’. In this report, when identifying risks further on, weak AI humanoids are those

possessing the basic attribute of intelligence, but intelligence levels have reached a threshold

from which they cannot increase. Strong AI however, is the case where this barrier is not

present, meaning that intelligence levels have the potential to increase to a level similar to a

human, or even beyond.

Strong AI [28]

In essence, for strong artificial intelligence to prevail, theory states that a digital computer,

which is ultimately what the heart of a humanoid is, can be programmed to be a mind. This

means that it should be able to exhibit cognitive states ascribed to human beings [29]. The

theory of strong AI sets certain specifications, which must be met in order for a machine to be

deemed intelligent. With regards to humanoids, if these properties can be exhibited, different

behavioral patterns will exist to those displayed by a humanoid solely capable of weak AI.

Specification – N.B. Specifications vary from source to source. However the most important

properties with regards to humanoid robots are shown below [29]:

• Ability to reason, and make judgments under uncertainty.*

• Ability to demonstrate common sense.*

• Ability to learn and adapt information.*

• Ability to plan a course of action.

• Ability to perceive external stimuli.

• Ability to communicate with humans (using Natural Language Processes, NLP).

• Ability to recognise, feel and display emotion.*

• Ability to manipulate its environment out of free will.

• Ability to demonstrate a state of consciousness.*

• Ability to be aware of its presence with respect to its environment.

22

It is clear there are some of these stipulations that have already been met; a humanoid has the

ability to perceive stimuli, communicate rudimentarily with humans, and in some respects

understand and manipulate its environment. Through these developments, it can almost be

declared certain that humanoids of the future will have enough technology to perform some

functions very well. However, the major points that would determine strong AI intelligence are

shown with an asterix above. If these are achievable, the humanoid will be a completely

different entity.

Weak AI

The concept of weak AI tells us that, in the case of humanoids, they have the ability to act

intelligently and simulate cognitive processes. However unlike strong AI, the weak AI system

is not itself a cognitive process [30]. As mentioned above, the weak AI system shares some

properties with strong AI, and these are clear in today’s humanoid research and development.

However, if strong AI is impossible, weak AI states that there will be a dead-end to AI

advancement. This would mean that the future of humanoids would be greatly restricted with

regards to intelligence.

Complexities of AI [31], [32], [33], [34], [35]

The debate lies in whether strong AI is possible. Many AI academics believe that Strong AI is

achievable, not perhaps in the very near future, but in the next 20-30 years. Some, on the other

hand, believe that it is physically unfeasible for strong AI to prevail, as for this to occur, the

computational system has to mimic the exact processes of the brain, which is considered

impossible.

On the other hand, the AAAS (American Association for the Advancement of Science) believe

that by 2029, machines and humans will eventually merge through devices implanted in the

body to boost intelligence and health [36]. IBM, together will a Swiss University team, are to

create the first ever computer simulation of the entire human brain [37]. This is being done in

order to allow scientists to discover more about exactly how the brain works; if projects like

this can be successfully completed, the possibility of mimicking a brain-like system on a robot,

is very feasible. However, all of this is simply speculation and two fundamental questions arise

creating flaws in this research; how can a brain be mimicked if we as humans don’t even fully

understand how it works? And, even if prototypes are constructed, is there actually any way of

developing them for use in real-life situations? Overall, the nature of the strong AI argument is

23

based on much theoretical suggestion, whereas the arguments against strong AI are more logic

and common-sensed based. With regards to the scientific argument, it is becoming more and

more possible to understand brain processes. If, hypothetically, the brain is fully understood,

there is no reason to believe that in a period of time a neuroanatomical map of the brain cannot

be reproduced onto a computer system [38].

However, there exist three fundamental differences between a brain and a computer, which

could potentially limit their similarities. Firstly, computers are digital systems and the brain is

largely an analogue device where activity varies continuously. Secondly, digital computer

systems are serial devices, in which one instruction is executed at a time, whereas the brain is a

parallel-processing device. Thirdly, software codes and brain cells differ in that codes can be

programmed to undertake a variety of tasks whereas many brain-cells are dedicated to one

purpose only. For example, cells in the visual cortex respond only to lines slanting in a

particular direction [32].

The rest of the strong AI argument is based on the ability to generate a mimic brain-like

structure. With technological advancements, it is considered possible by some that in about 20

years, it will be possible to imitate the brain’s circuitry using man made electronic components.

Counter-arguments state that even if this is possible, it is logically impossible for

computational systems to feel emotions, experience consciousness or understand the actions

that they perform. Without these, can a humanoid have the properties (those highlighted

previously) of strong AI?

The discussion above has surfaced some other important uncertainties. Can only an analogue,

parallel-processing, dedicated device be intelligent? Can AI developers ignore human

psychology and philosophy and get on with their job of building an artificial thinking machine

that may be very different from the brain? It is clear that this understanding of human

psychology and philosophy is needed. If AI is to progress, it needs a solid basis of reference

and what better basis of reference is there than the human brain; the most intelligent system

present. However, perhaps it should only be used as a reference and not completely duplicated.

If it seems that the route to recreating the human brain is impossible, maybe it is meant to be

this way, and other routes to creating intelligent systems should be considered.

24

The Turing Test & Chinese Room Experiments [28], [29], [39]

The Turing test was an experiment set up by Alan Turing in the mid 20th century. It is still

regarded as one of the strongest basis for a machine to demonstrate intelligence. The test

involves having a human judge engage in natural language with one human and one machine.

Both have the aim of trying to appear human; after a series of questions, if the judge cannot

decide which is which, the machine is considered to be intelligent. The strength of the test

arises from the fact that any question can be asked to either participant in the hope that one set

of answers will be distinguishable from the other, and as yet, no machine has been able to pass

the test. From this, it seems that if a humanoid in the future was able to successfully complete

the test, its role on the construction site would be benefited, and human-humanoid interaction

would be successful.

However, strong evidence also lies against the credibility of this test. One major flaw is that the

test is explicitly behaviourist, meaning it only tests how the subject acts. A machine may pass

the test by replicating human conversational behaviour, but this is only due to algorithms set to

perform string substitution and canned responses [40]. Moreover, with regard to humanoid use,

surely it is more necessary to have intelligence in cognitive processes such as reasoning and the

ability to learn, rather than simply being able to replicate a human conversationally.

In this way, Searle uses the Chinese room argument as a thought experiment to persuade

people of the uselessness of using AI-concepts in psychology. Searle rejects the notion that if

the Turing test were passed, a human-like robot would really understand and have real intent

similar to or exceeding that of a human (strong AI). Rather, he accepts that such robots are

merely manipulators of information (weak AI) and insists that the conceptual content of AI-

ideas cannot help to describe or explain mental processes as such, since minds possess

intentionality whereas computers do not. Searle declares that intentionality is a biological

phenomenon, just as dependent on the underlying biochemistry as photosynthesis is for

example [32].

25

The Future of AI

All of these theories and concepts are not useful in suggesting what our future will be like in

terms of artificial intelligence, due to the compelling opposing arguments. But it does help the

report in that it would be wrong to consider one definitive possible future. It has also shown

that the implications for strong AI prevailing, or weak AI being maintained, will be widely

divergent. This means that the future of AI will determine the behaviour, and so inevitably the

future, of humanoids. Therefore, when considering the risks involved with using humanoids in

construction, two futures will be explored; one where only weak AI is possible, and the other

where strong AI prevails.

Possible application and issues regarding humanoids for construction tasks [41], [42]

On outdoor construction sites, not every worker needs to be an expert in the job they are

carrying out. It is possible for many tasks to be carried out by one expert and one novice. It is

realistic for the applicable tasks to be carried out by a novice humanoid partner of an expert

human, perhaps even many humanoids for bigger tasks. This could be a viable option for

countries where labour forces are shrinking and societies are aging such as China and Japan,

where much of the associated research and testing is carried out.

Figure 7 shows the leg module of a humanoid being developed today in

Japan. Each hip has 3 degrees of freedom, the knees have 1, and the

ankles have 2, which equates to 6 DOF per leg. This is good progress

by today’s standards, but when more complex tasks are asked of a

humanoid, it will need many more DOF, for example, in order to

ascend a ladder, or crawl into an excavation.

Figure 7

Horizontal wobble occurs during walking due to mechanical factors, and presents problems in

stability. The torso should be kept relatively stable, as with human motion, in order to avoid

toppling. This can be achieved by:

- Allowing the swinging leg to make as large a range as possible, while also being able to

change the support stance rapidly in the event of loss of stability.

26

- Providing a smooth change in the centre of gravity during bipedal motion.

For level ground, flat-footed humanoids can gain maximum contact friction with the ground

surface. But for uneven ground, this would result in an uneven distribution of loading on

various contact points, leading to instability. To overcome this, flexible foot bases would be

required to match the ground surface. Also, each joint throughout the humanoid’s system

should not only be designed to simulate human movement, but also match the same range as

the respective human joint.

There are two possible methods of information transfer that we can expect to see in the future:

voice command and pressure sense operation. Voice command would be more intuitive, and

reduce the need for training. Pressure sense operation on the other hand, is slightly more

complex; it guides the robot through the pressure applied, then robot action is adjusted to

match the forces applied by the human worker. This type of process would be applicable to

carrying an object together such as a panel, or sections of formwork for example.

Basic systems of voice command have been developed today where a human worker wears a

portable controller, which mounts a voice recognition application with a microphone for input.

Voice data is converted into minimum task commands by the software, and transmitted to the

humanoid’s motion planner via radio LAN link. Numerical commands such as “one meter

forward” should be avoided in order to minimise voice recognition error in the system. Instead,

more abstract commands could be used like those demonstrated in Figure 8, which is adapted

from work undertaken by Kawada Industries [41].

Voice Command Motion Command (mm vectors)

Forward MOVE (50,0,0)

Backward MOVE (-50,0,0)

Right MOVE (0,50,0)

Left MOVE (0,-50,0)

More forward MOVE (200,0,0)

More backward MOVE (-200,0,0)

More right MOVE (0,200,0)

More left MOVE (0,-200,0)

Stop MOVE (0,0,0)

Quit QUIT

Figure 8

27

Further on in time, it is expected that the system will become more compact in size, perhaps

solely contained within the humanoid’s hardware. Also, we can expect to see a system that

integrates voice and pressure sensing.

Investigation by Functional Analysis Method [42], [43]

The performance and capability of a humanoid, which is required for construction work, has

been investigated. Figure 9 shows the primary functions that a humanoid must possess. The

secondary functions of individual performance must be realised for full satisfaction of the

primary function to occur. They also represent what must be complied with, in order for

humanoid use to be worthwhile. The functions displayed are vital for actual construction work

in an outdoor environment with human cooperation.

Primary Function Secondary Function

Ability to Move Travel over irregular terrain

Vary speed of movement

Change direction of movement

Generate movement course

Ability to Work Carry sufficient weight

Work at suitable speed (aim to match human)

Range of limb movement

Flexible hands

Accurate positioning (within millimetres)

Long operation hours

Ability to transfer Orders and Intention

Communicate with humans by means of voice recognition or pressure sensing

Ability to be Reliable Stable against falling over

Sufficient protection from impacts

Recognises danger of potential reckless move

Low frequency of failure

Ability to have Knowledge Interpret construction site data

Knowledge of materials

Capable of some memory

Sufficient knowledge of site regulations

Ability to Recognise Image recognition, perhaps by geon theory

Detection of states (solid, liquid, etc)

Ability to Judge Small degree of common sense

Figure 9

So, these functions represent what is required of a humanoid for construction work. It also

concerns that of a weak AI, one that is new or recently developed, or one that has reached a

limit or dead end in the possibilities of humanoid intelligence.

28

A second functional analysis has been performed which considers a time where tasks required

of humanoids are far more complex, their perception systems are more advanced, and they

have a real sense of intent; a time where strong AI exists, in which a new set of risks will

prevail. The functions stated here are additional to, or a more advanced form of those stated in

Figure 9.

Primary Function Secondary Function

Ability to Move Travel over a large variety of terrain, and ladders

Degree of expressive skills

Ability to Work Can operate a large number of tools/machinery

Ability to transfer Orders and Intention Capable of smooth conversation using natural languages processes (NLP)

Understands fully and learns, not merely manipulating data

Ability to be Reliable High strength protection can resist many forms of damage

Understands danger and acts to prevent it

Near 0 frequency failure

Capable of homeostasis (self regulating)

Advanced vestibular system (balance)

Ability to have Knowledge Self-aware and can display sapience (wisdom)

Capable of short and long term memory, learning from it, and recounting perfectly

Ability to Recognise Displays advanced level of perception:

Recognises multitude of objects and makes reliable guesses of unknown

Motion processing

Auditory feature extraction

Face and eye detection

Figure-ground segmentation

Recognises self and other beings

Gesture recognition

Matches own behaviour to observation

Ability to Judge High level of commonsense (similar to human)

Can reason, strategise and solve problems

Figure 10

By carrying out these functional analyses, areas where risks may develop are beginning to

emerge. This gives a good starting point for delving into and imagining the sorts of risks that

could arise on a construction site through using humanoid robots. From exploring the

psychology of mental processes and investigating the future of AI, it has been found that weak

AI will exhibit various limitations. The degree of object recognition and level of commonsense

will be low, with a failure to cope with unknown situations, therefore much human assistance

will be needed. On the other hand, even though the aforementioned limitations will not apply

to a humanoid with strong AI (provided that strong AI triumphs), new forms of risk will

transpire.

29

Risk Assessment – Humanoid Robot: Weak AI (Basic Intelligence)

Analysing the behaviour of humanoids and imagining their possible work applications has

helped to identify seven main categories where risks are most likely to arise. The risk

assessment table shows these broken down into several sub-categories and the next column

briefly describes an array of risks. The likelihood, risk rating and cost of controlling each risk

is estimated in terms of high, medium or low (H, M, L), and brief descriptions of

consequences and suggested control strategies are given.

Risk likelihoods have been estimated and should not be taken too definitively, as it is difficult

to predict the future. Risk is often defined as the multiple of the likelihood and consequence,

but here it is mainly a consideration of the risk to human life. Thus, high risk ratings are those

likely to harm humans and low ratings are those risks that just disrupt the flow of work.

Where no cost of control is stated, the risk is as a result of a design issue, with no easy way of

treatment on site other than warning human workers of the risks.

By not being able to scrutinise retrospective risks, this risk identification process requires an

imaginative and conceptual understanding of the circumstances. This is another reason why

this topic is so important and must be considered. In many cases it is easier to see the

problem areas where risks are likely to stem from, hence why many of the consequences

explain how a multitude of risks could arise. These ratings are high because the risk is in the

realms of the unknown. The most important risk is number 43, concerned with control. It

allows the human to always have the upper hand in terms of power, being able to shut down

the humanoid system if it becomes out of control.

Perhaps surprisingly, few risks actually pose threat to humans. In fact, most of the risks are

concerned with too much human involvement, lack of productivity and hence an increase in

costs. In reality, could this fact equate to a much bigger problem for construction companies

than risks to human health?

30

No Category Sub Category Risk Description Likelihood Consequence Risk Rating Control Strategy

Cost of Control

1 Movement walking on uneven terrain trips and falls H damage to self, others, or materials H

take flatter route or avoid walking if possible (other transport?) L (H)

2 experiences difficulty M inhibits progress to work L human assistance and/or above L

3 inadequate DOF/flexibility/speed

has trouble with performing all but the most simple tasks H

range of possible accidents, more hindrance than benefit M

ensure humanoid is not working out of its depth L

4 causes obstruction to human worker M disrupt work efficiency on site L allow designated work areas M

5 clumsy behaviour H multitude of accident could form H ensure humanoid is not working out of its depth L

6 high strength causes damage to materials and equipment M loss of goods M

only allow humanoid to handle what it is trained to L

7 harmful collision with human due to error in movement M injury to human H

ensure all workers are aware of humanoid risks M

8 trips over whilst carrying a heavy load H same as 1, but heavy load makes worse H

ensure heavy loads carried on stable ground L

9 vary movement falls due to instability from changing speed or direction L damage to self, others, or materials M

keep speed and movement minimum for task H

10 generating movement course

falls or takes incorrect path from failure to identify ground materials/terrain L same as 1 or delays work M

disallow humanoid on complicated terrain L

11 Communication via voice recognition lack of clarity in human input L range of misinterpretation errors H increase human-humanoid interaction training M

12 laborious continual prompting and impatience on human part M

can lead to human negligence and errors forming M

rotate shifts to work with humanoid L

13 via pressure sensing human applies too high a pressure and humanoid loses balance L

same as 1, also more likely to involve human H

increase human-humanoid interaction training (for human) M

14 laborious continual prompting and impatience on human part M

can lead to human negligence and errors forming M

rotate shifts to work with humanoid L

15 general excessive human involvement M losses in productivity/money M no solution, inevitable byproduct of humanoid use -

16 Sensing large variation of sensory input unable to distinguish between signals M

confused, takes incorrect action, range of risks emerge M

only present simple scenarios to humanoid L

17 becomes inundated with large amount of input L

unable to function at all, hindrance on site L

only present simple scenarios to humanoid L

18 complex sensory signals mistakes still murky water for ground surface L

becomes submerged and breaks down M ensure all water is cordoned off L

19 confusion exists and data incorrectly processed L

inhibits perception process and unable to function M

only present simple scenarios to humanoid L

20 humanoid sensors fails to detect unknown or unfamiliar sense L multitude of risks could occur H do not employ humanoid in unfamiliar scenarios L

21 fails to differentiate between stimulus qualities (i.e. colour vs. brightness) L

incorrect detection and takes wrong action M

clear and simple colour coding for humanoid tasks M

31

No Category Sub Category Risk Description Likelihood Consequence Risk Rating Control Strategy

Cost of Control

22 Perception recognition fails to recognise figure against ground (bad lighting) L collision and injury to human H always ensure good lighting M

23 mistakes human body part for material object L injury to human H ensure human wearing PPE L

24

mistakes an object from failure to distinguish between size/distance or shape/distortion M

delays task, possible material/object damage M

material/object clear presented to humanoid M

25 natural objects (trees, liquid etc) mistaken for other materials L

delays task, possible damage to humanoid M

clear site appropriately for humanoid use H

26 processing slow response time from difficulty in recognition process M delays task L no solution, design issue -

27 Memory stored knowledge unable to deal with unknown situations which it has no memory or knowledge of L halts task L

only present known scenarios, inevitable with weak AI L

28 fails to treat material with care due to limited materials knowledge L damage to material M

sensitive or unique materials prohibited from humanoid L

29 limited common sense excessive human involvement due to poor initiative and independence M reduction in human productivity M

no solution, inevitable byproduct of humanoid use -

30 acts harmfully or unethically towards human L injury or negative effect on human H

largely design issue, warn humans of risks L

31 memory stored from experience

failure to remember the task being carried out L

need prompting and causes delay to human & humanoid M

do not leave humanoid alone for long periods L

32 (if possible) breaks rules due to failure in recalling new site regulations or ethical codes M range of unsafe behaviour H

ensure any new rule programmed into humanoid system H

33 Attention channel selection excess of information and unable to select correct channel L incapable of functioning L

keep commands short and simple, one human commander L

34 humanoid out of control, unable to attract attention L multiple risks could arise H reboot humanoid system L

35 channels busy and information is lost from short term store L delays task M repeat instructions L

36 process excessive human involvement M decrease in productivity M no solution, inevitable byproduct of humanoid use -

37 Reliability preservation fall or other accident, result of limited protection L damage to humanoid M

ensure sufficient protection, mainly design issue M

38 fall/collision from regular bouts of instability M damage to humanoid, and/or others M no solution, design issue -

39 bad weather harms humanoid mechanisms L temporary/permanent damage to humanoid M

predominantly design issue, and avoid use in bad weather M

40 health & safety fails to recognise danger of reckless movement L multitude of risk could occur H

predominantly design issue, and avoid dangerous tasks M

41 machine fails/breaks down M site obstruction, decrease productivity M ensure regular maintenance H

42 maintenance battery runs out of power L as above M ensure battery charged every day M

43 Control humanoid out of control, hazardous action towards human L

multitude of scenarios involving injury to human life VH

one human command that will shut down humanoid system L

32

Risk Assessment – Humanoid Robot: Strong AI (High Intelligence)

Introduction

It has been proposed from the previous section of the report that the risks involved with

humanoid robots possessing strong AI, and those with weak AI will be very divergent. Due to

the uncertainties and complications that strong AI results in, a risk assessment cannot be

performed in the same way as with weak AI. In fact, it would be unfeasible and completely

ineffective to try and determine the specific risks on a construction site; at present, there is

simply not enough information or evidence of high intelligence AI. Due to this, different

scenarios from which risks could evolve will be discussed, and then linked with humanoid

use in construction. “By far the greatest danger of Artificial Intelligence is that people

conclude too early that they understand it [44].”

Replicating the Brain

From the previous section, a strong basis for the prevalence of higher intelligent systems was

that they would mimic the human brain. If this is the case, the idea arises that surely the

majority of characteristics of the human would be mimicked, including those that are

undesired, such as human error. Human error is the single largest cause of accidents on any

construction site, and having a humanoid exhibiting this property would negate much of its

original purpose. The likelihood though of designers not resolving this issue is very low and

it is almost certain that all strong AI humanoids designed for construction will eventually

have close to zero humanoid error. The question is how long will this issue take to resolve,

and what will be deemed too long?

The human developmental process works by individuals, as children, possessing little or no

stored cognition, but learning and adapting information in the early years of their life. In this

way, the future of higher intelligence humanoids could begin with them as an ‘empty canvas’,

with the ability to learn what is needed for their purpose. With regards to construction,

humanoids could be site specific. This means that for each site there would be different tasks,

and these tasks would be taught to them on site rather than in their design and manufacture

phase. If this were to be the case, on-site supervisors training the humanoids would

themselves need to be trained. These training schemes would no doubt be complicated, and

unless the supervisors are successfully educated, poor training from them to the humanoids

33

would result in wasted time and resources (both human and humanoid). In worst case

scenarios, poor training could lead to humanoids malfunctioning or carelessly performing

their tasks, and thus potentially causing major risk to human life. Perhaps the chances of this

are minimal as the training would be thorough, and in the design phase humanoids would be

designed so their ability to be taught is simple and user friendly. But as a result of numerous

trainers and potential tasks asked of humanoids, the probability of failure due to poor training

and task variation would be astronomical.

Humanoid Consciousness

Consciousness is a difficult concept to delineate, but generally speaking means awareness of

ones existence, with full activity of mind and senses. An expression, not fully understood

with regards to humans, is therefore extremely complex to associate with a man-made entity.

With the height of intelligence that is expected if strong AI prevails, when examining

potential risks of humanoids, their ability to emote and feel should be assessed.

Even though all evidence to suggest high intelligence systems may emote is theoretical and

based solely on opinion, if this is the case, should it be able to possess this characteristic? In

many ways, it can be argued that it is our ability to emote that provides us with the capability

to reason, make judgements and adapt information. And isn’t it these reasons that we wish to

create strong AI humanoids? Conversely, it could be emotion that will be detrimental to a

humanoid’s performance, as evidence from humans show that emotion affects work rate and

productivity.

Additionally, if this were the case, the applicability of humanoid rights would increase. With

humanoids being perceived as more of a life form rather than a machine, standards would be

set, similar to humans, regarding the treatment of humanoids. This could nullify the primary

grounds for instating humanoids on construction sites in the first place. One of the major

intentions for humanoids in construction is their prolonged use on site, and it is hoped that the

site can potentially operate 24 hours a day in the future. But with the establishment of

humanoid rights, laws and policies, we may almost reach the stage of equal treatment of

humans and humanoids, in which case their benefits would dramatically decrease.

Another major factor of high intelligence humanoids on a construction site is human–

humanoid relations. When dealing with weak AI, this does not apply as much; the limited

34

features of a weak AI humanoid mean that the relations between a human and a humanoid

will be more similar to that between a human and a computer. With higher intelligence, it is

clear with human psychology that some humans may affiliate well with humanoids whereas

others may find them threatening; with this, a new set of risks will emerge. The poor synergy

between humanoids and other workers may lead to lack of work rate, striking and an overall

negative impact on the construction industry. Perhaps human-humanoid relations will

develop over time once humanoids have been suitably introduced into our society. But the

question arises of how long this period of time will be when humans will accept humanoids

and work together harmoniously? However if we look at trends in discrimination today, this

prospect may never be reached. If some humans cannot even accept others, then how can our

society ever fully accept humanoids?

Intelligence Levels

Within this report, strong AI has been classified as the potential of machine intelligence to

have no limit. Assuming AI will advance like current technology has, a machine’s

intelligence could theoretically increase to an infinite level. The foundation of this statement

lies in Moore’s Law which states that the number of transistors that can be inexpensively

placed on an integrated circuit is increasing exponentially, doubling approximately every two

years [45]. With regards to intelligence, this means that a system’s capability to be intelligent

is increasing exponentially. To note, this does not negate the discussion of whether strong AI

will prevail in the behaviour section, as these two points are mutually exclusive. However,

various factors affect the credibility of Moore’s Law in the future, however these delve into

very detailed computational jargon [46], and so are not necessary to discuss within this

report. What should be regarded however, is that a major consequence for artificial

intelligence from Moore’s Law in the future is technological singularity. This is a stage in AI

development, where a machine has enough intelligence to recursively self-improve; it will be

able to rewrite its own cognitive functions, and thus gain intelligence without human

intervention [44]. The scope for intelligence is extensive, and whereas weak AI has a clear

limit, if technological singularity occurs, machine intelligence could reach a level far beyond

human comprehension.

35

What is being dealt with here is a very open-ended discussion, and at present, there is very

little to emulate ideas from, as there is no past frame of reference. With the idea of AI being

in its initial stages, it seems almost absurd to delve into AI at a very high level. However, if

technological singularity occurs, the rate of intelligence could exponentially increase itself.

And so this level of very high intelligence could be seen sooner than we think.

Human-Like Intelligence Level

A level of very high intelligence, almost similar to that of a human’s, could result in a

complete shift of operations on a construction site. It is usually considered that the role of a

humanoid will remain at the bottom of the chain. From the introduction, it was found that

robots in general were designed to undertake tasks the human didn’t want to or shouldn’t

have to do. However, with this height of intelligence, construction companies may find that it

would be better to modify their resource management. If deemed suitable, should humanoids

perform tasks with less or even no human supervision? This question can be rephrased to how

much testing and safety analyses have to be performed before allowing a humanoid to work

solely? Perhaps the amount of testing and safety analyses may alter depending on the

frequency of failure from lack of human supervision. But is allowing this failure to occur

acceptable?

Another scenario that could emerge due to this height of intelligence is role alteration.

Primarily it could be seen that humanoids have more of an input into their work rather than

simply carrying out their tasks. Construction companies may use them in higher positions of

responsibility, or even have certain humanoids operating a team of secondary humanoids on

site. It is optimistic to believe that there will be a positive synergy on site between humans

and humanoids of similar intelligence levels (as mentioned in human–humanoid relations),

and whereas companies may believe that this will lead to a successful allocation of resources,

a great deal of risk lies in this change of site hierarchy. The predominant question arises that

if humanoid intelligence is high enough, could there ever be a time when a humanoid will be

above a human in the chain of command?

Smarter-than-Human Intelligence

The most abstract of all ideas involves deliberating over an entity that has more intelligence

than a human. Like our model of physics fails when we reach a black hole, our model of life

will fail if entities smarter than humans are introduced [47]. The risks can be classified as

36

non-anthropogenic existential risks [48], meaning that they are no longer at a local level

(construction site), but now at a global level. No detailed outcomes can be deliberated, as the

scenario is beyond comprehension. Two opposing views exist regarding smarter-than-human

intelligence. One extreme suggests that it will be the end of human life as we know it,

whereas another renders the view that solutions will be provided to previously unsolvable

problems.

With regard to construction, it could be said that this super-intelligence could transform the

construction industry from strength to strength. However the major flaw in this argument is

best represented using the Giant Cheesecake Fallacy. This states that super-intelligence could

potentially construct colossal cheesecakes; but would it actually want to? This vision of

providing impressive results goes from machine capability to actuality, but does not consider

the issue of motive [44]. Additionally, if the construction industry evolves in magnificent

ways due to super-intelligence, will this eliminate the need for any human involvement? This

situation can be compared to playing chess with a superior opponent. It is unknown what

moves he will play; if it was then he would not be superior at the game. All that is clear is

that the game will not turn out as you wish, and it is almost certain that you will lose. In this

way, it is a catastrophic risk for humans to take, to create a smarter-than-human entity.

Control

Arguably the most important factor with regards to risk within this project of humanoid

robots on construction sites is control. Control is the ability to have a dominating influence

over something else; to regulate, manage and direct something. Control is vital on a variety of

levels. In order to direct a command to a humanoid, substantial control is needed to make

sure that this command is carried out. However, for more serious purposes, control is needed

to restrain the humanoid from acting in a way which it must not. Risks from this can cause

wasted time and resources, but on a more serious note, can lead to human injury which could

range from minor harm to loss of life.

With regard to weak AI, this concept of control is relatively straight-forward. The

humanoid’s low intelligence means that it is easier to design such that the potential risks are

kept to a minimum, especially after analysing cognitive behaviour and carrying out a risk

37

assessment. Due to the minimal intelligence, its actions can be generally pre-determined.

However, an increase in intelligence levels results in an increase of uncertainty with regard to

a humanoid’s actions, and this poses a much greater risk. Furthermore, an increase in

intelligence, results in a changing context of AI behaviour. The level of risk does not simply

increase linearly, as not only does the probability of risk increase, so does the catastrophe

level. When dealing with more intelligent humanoids, their actions are backed by intent and if

this is negative, it can be greatly detrimental for human safety.

As long as a great degree of control is maintained, a human’s intention can be safely induced

into an intelligent entity. When dealing with humanoids with similar intelligence to humans,

control must be enforced to permit intelligence levels from further increasing. If smarter-

than-human intelligence exists in a machine, control has been immediately lost and it would

be impossible to regain.

Ethics

Machine ethics is concerned with ensuring that the behaviour of machines towards human

users and perhaps other machines as well, is ethically acceptable. ERRN (European Robotics

Research Network) believe that robots will eventually be intelligent enough to be considered

its own species [49]. If truly intelligent systems are present, society will be faced with an array

of ethical problems.

Moor describes two types of ethical agents that could exist. The first is an implicit ethical

agent, one that is programmed to behave ethically and its behaviour is constrained by a

designer who is following ethical principles. The second is an explicit ethical agent, one that is

able to calculate the best action in ethical dilemmas using ethical principles. It can represent

ethics explicitly and then operate effectively on the basis of this knowledge [49]. Developing

an explicit ethical agent is the ultimate goal as it would cope far better with unknown

situations. Certainly, this is concerned with strong AI and implicit agents with weak AI. This

will be a challenge as ethics has not been completely codified; it is a field that is still evolving.

Machine ethics is important for a number of reasons. Intelligent humanoid entities will be

capable of causing harm to human beings unless this is prevented by adding an ethical

38

component to them. Additionally, human fear of intelligent machines stems from the concern

over whether they will behave ethically or not. Popular culture is full of images of machines

without any ethical code, such as The Matrix [50] and The Terminator [51]. Joy [2000] argues

that the only antidote to such fates and worse is to relinquish dangerous technologies [52].

Many people working in machine ethics research believe they can offer a more realistic

solution. Perhaps if humanoids were designed so that they felt fear towards humans, control

would be a far easier issue [53]. Finally, research in machine ethics could advance the study of

ethical theory and help discover problems with current ones. Dennet believes that AI ‘makes

philosophy honest’ [49].

One scenario that could emerge is that a humanoid will begin to behave ethically and then

change, deciding to behave unethically in order to secure advantages for itself. This is not such

a far fetched thought as it may first seem. After all, humans are far from ethical agents, and

even though we are taught ethical principles, we tend to favour ourselves. So if humanoids

have a human-like-brain, they may act for their own interest; after all we do, and most of us

probably consider ourselves to be ethical. Dietrich contests this view, and argues that machines

may actually have an advantage over human beings with respect to behaving ethically [54].

Humans may have evolved with a genetic predisposition towards unethical behaviour as a

survival mechanism. We could now have the chance to create entities that inspire us to behave

more ethically.

Humanoid Consciousness discussed whether a humanoid should be able to feel emotion. If we

reach an age where strong AI is possible and a humanoid has an artificial brain that works

similarly to a human brain, is it inevitable anyway? This question cannot be answered at

present, but we can continue to think about the prospect of humanoid emotion. It is a strange

and disturbing thought to imagine a human being that possesses no emotion. If we want to

create a humanoid to look like, and work with humans, then can it do this without emotion?

Yes, is the probable answer, but will it do this successfully? Maybe not, we just don’t know.

Furthermore, emotions can equate to extreme forms of risk. Strong emotions such as hate and

jealousy can cause humans to be over zealous; perhaps we should try to restrict this possibility

from the robot domain [55]. An emotional robot may also ignore the laws it is programmed to

follow, or its ethical principles.

39

At present, the only form of principles set to govern the future of robots exists in fictional

stories by Isaac Asimov. His Three Laws of Robotics are as follows: A robot may not injure a

human being or, through inaction, allow a human being to come to harm; A robot must obey

orders given to it by human beings, except where such orders would conflict with the First

Law; A robot must protect its own existence as long as such protection does not conflict with

the First or Second Law [56]. Although popular in science fiction, these laws have been

suggested as flawed for actual implementation. If we imagine trying to set down a set of rules

for a machine that is going to exist in a situation where it is operating in a world of concepts

that we don’t even know, then the problem becomes apparent.

The singularity institute have recognised this and have made suggestions as to what an

intelligent agent should be able to understand, in order to act ethically. The first is that AI

agents need to understand evolutionary processes in order to display morality and ethics.

Humans display true altruism due to this involuntary understanding; if humanoids were

programmed to solely benefit others then we could feel much safer about their existence. Also,

their source codes should be made available for humans to view; essentially a way to see

humanoids think. In this way, they will be easier to control and more trusted as an entity.

Additionally, they should be more economically and emotionally sentient. By understanding

the value that humans place on things, it can be assumed that humanoids will not act in a way

that is harmful to human society [57]. A great deal of responsibility lies with those that may

eventually create an ethical machine. There is one thing that society should fear more than

sharing an existence with intelligent machines, and that is sharing an existence with machines

that do not behave ethically.

40

Final Discussion

This report has involved an understanding of a number of fields that were not originally

anticipated, but were required in order to formulate a thorough risk assessment of humanoid

robots in construction. The investigation of humanoid behaviour and artificial intelligence

involved research into engineering, psychology, philosophy, sociology, ethics and IT.

Preparing a risk assessment for the unknown future, of an entity not yet developed, meant

that simply using an engineering approach was not enough.

By carrying out a risk assessment of humanoids which exhibit weak AI, one fundamental

issue became apparent. An initial belief that the majority of risks would implicate harm to

human life was disputed. It was uncovered that most of the risks were concerned with three

main areas:

• Time – Many of the risks were concluded to result in a delay of the task being

carried out. This was either through the humanoid not being able to perform the

task, the task being carried out slowly, or the task being completed poorly.

• Human Resources – Due to the limited capability of the humanoid, many of the

tasks require an excessive amount of human assistance.

• Material/Humanoid damage – Taking into account human commonsense and

limited humanoid capability, if a malfunction occurred it was estimated more likely

to cause damage to itself and/or materials it was working with.

The significance of these consequences are still high because they result in losses for the

construction industry with regard to productivity and cost. On the other hand, risks to humans

are nonetheless present, and without significant humanoid development by designers, the

introduction of weak AI humanoids to construction sites cannot be a realistic idea. If the

harmful abilities of a humanoid are restricted in order to greatly reduce the risks to humans,

then their benefits on site could reduce. In order to trade-off humanoid capabilities for human

safety, designers need to devise ways of enforcing sufficient control for this level of

intelligence, whilst keeping their appropriate abilities.

On the following page is a flow diagram illustrating the possible paths that artificial

intelligence could take and the effects of this on construction.

41

Weak AI

Is there a

limit? Dead-end to AI

development Strong AI – continue development of higher

intelligence

Stop AI

development

Sufficient human control?

Has

singularity been

reached?

Are all

control measures are in place?

Will these measures be

sufficient?

Momentous benefits for construction

industry, intelligence can be controlled to

desired level

Intelligence levels will increase beyond human comprehension (smarter-than-human), all control

is lost

yes no

yes

yes

no

yes

yes

no

no

no

Through further development, weak AI can be perfected and still provide

benefits for

construction

Present day AI

development

through time

NB: not to

scale

FLOW DIAGRAM

SHOWING FUTURE

OF AI

42

It should firstly be noted that the flow diagram is based on theoretical ideas. It should not be

taken as a definitive route, but it does bring to light many eventualities that must be

considered in the present day. In the future there may be other variables that affect the

outcome of AI which cannot be forecast.

From this diagram, three major outcomes have been exposed. The first is that AI

development has reached a dead end. Even though a range of risks have surfaced concerning

weak AI, it is expected that through meticulous refinement, these risk could be notably

reduced and humanoids would provide ample benefits for construction. There is a worry that

construction companies may implement humanoids too soon, masked by their potential

benefits. If this happens and hazards occur, this could give humanoids a very bad reputation,

as well as the industry, and damage the prospect of future development.

The greatest area of difficulty lies in determining what control measures will need to be in

place if singularity is reached, and whether these will be sufficient. As yet, these are not

concrete but the suggestions are that humanoids should be explicit ethical agents and they

should follow new rules, such as those described in the ethics section. Whatever control

measures are in place, if they are sufficient, there will be momentous benefits for

construction. With higher-than-human intelligence that can be controlled to human desire, the

construction industry will flourish beyond belief. However, if control measures are not

sufficient then humanoid intelligence could increase to an inconceivable level where all

control is lost.

Perhaps it would be more beneficial in the long run to pursue a path towards perfecting

weaker AI and prohibit super intelligence from developing. The largest risk posed by the

flow chart is for one to believe that control measures are sufficient when they are in fact not.

This is because there are so many conditions that have to be met in order to control super

intelligence, and the consequence of failure could be overwhelming. Not only could this

potentially mean the downfall of the construction industry, but possibly even to mankind. It

is ironic to think that we may one day be on the path to creating our successors.

43

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