Artificial Intelligence and the Ethical Implications

Artificial Intelligence and the
Ethical Implications of Automation on
Employment
Assignment 3a – Project Report
IT Professional and Society
Thursday 6pm Tutorial Group
Spring 2017
Tutor:
Kimberly Blackerby
Group members:
Mohammadesmaeil Azadpour
Jagadesh Mudunuri
Hangjit Rai
Paulette Riley
David Schanzer
William Thomson
Artificial Intelligence and the Ethical Implications of Automation on Employment
Section Group Contributor name
Introduction Yes By group
Topic Description Yes By group
Stakeholders and Analysis Method No Hangjit Rai
Ethical Issues No Paulette Riley
Legal Issues No William Thomson
Social Issues No Jagadesh Mudunuri
Cultural Issues No David Schanzer
Business or Organisational Issues No Mohammadesmaeil
Azadpour
Resolutions – Positive Solutions, Strategy for
Implementation
Yes By group
Conclusion Yes By group
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Artificial Intelligence and the Ethical Implications of Automation on Employment
Executive Summary
This report discusses various technologies that are commonly grouped under the term Artificial
Intelligence (AI). It examines how recent advances in various AI subfields such as machine learning
have enabled these AI systems to achieve a high level of ‘cognitive’ ability.
In addition, the ethical implications of this technology, and the threat that they pose to long term
employment is examined. AI affects an increasingly significant portion of jobs and careers previously
thought to be the exclusive domain of humans and so the ethical and economical implications of this
technology are likely to become more acute in the future.
While the report suggests some potential solutions for these dilemmas, it also points to the urgent need
for further consideration and investigation into the ethical implications of automation on employment,
in order to transition into a new technological age.
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Artificial Intelligence and the Ethical Implications of Automation on Employment
Table of contents
Introduction 4
Topic Description 5
Stakeholders and Analysis Method 6
Ethical Issues 11
Legal Issues 15
Social Issues 20
Cultural Issues 23
Business or Organisational Issues 28
Resolutions – Positive Solutions, Strategy for Implementation 31
Conclusion 33
Reference List 34
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Artificial Intelligence and the Ethical Implications of Automation on Employment
Introduction
Automation has helped humans transition into the current modern world. The industrial revolution
brought about a lot of changes in how humans worked in successive years, but these automated tasks
were mostly mechanical. Industrial automation uses control systems to control robots or machines
which perform around the clock. These tasks are repetitive and doesn’t require any sort of cognitive
abilities to perform except the routine repetition of the tasks. However, Artificial Intelligence (AI) is
giving cognitive power to machines.
In the recent years, AI has seen rapid development. A number of products backed by AI have been
developed and released. Speech recognition softwares like Cortana, Siri, and Google Assistant are
examples of these pervasive technologies as they are easily accessible via an internet backed device.
One of the most striking differences between these AI technologies and the industrial automation
devices is that the former has the ability to teach itself new things. This poses a threat to humans as
machines have abilities like faster processing speed, working tirelessly, infinite memory, and a
significantly lower error rate with which humans can’t compare. Hence, as these AI systems become a
part of our society in the future, they will displace a lot of people from their jobs. It’s not just menial
tasks that are at risk. Even jobs requiring extensive mental processing like doctors and lawyers can be
automated by smart AI robots.
In this report, the entities affected by the automation of jobs and its gradual overtaking of intellectual
jobs in various fields will be discussed. Also, the related ethical issues will be discussed along with
legal, social, cultural, business and organisational issues. Finally, the possible resolution around
curbing the impact of automation on the general public will be analysed and studied.
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Artificial Intelligence and the Ethical Implications of Automation on Employment
Topic Description
In this report, we will consider the ways in which recent advances in Artificial Intelligence (AI) have
the potential to alter the mix of available jobs for humans, due to the automation of jobs that these
advances allow.
What do we mean by “Artificial Intelligence” (AI)? The Oxford Dictionary gives the definition as
“the theory and development of computer systems able to perform tasks normally requiring human
intelligence, such as visual perception, speech recognition, decision-making, and translation between
languages” (Oxford Living Dictionaries 2017). However, we contend that this definition is
insufficient for the ensuing discussion of the effects of automation on employment, because it is
obsolete. No longer is the end-game of Artificial Intelligence the achievement of mere “human
intelligence”. Instead, advances in AI allow for the creation of “super-human intelligence”, in other
words, a level of intelligence that is beyond the capability of any individual human, or even all
humans. What gives this new level of AI its advantage is the sheer volume of data that it can process.
Humans are limited in the scope and scale of experiences that they can absorb and remember. A
“synthetic intellect” – to use Kaplan’s terms for AI-based automated decision-making (Kaplan 2015) –
has (through the ever-expanding array of “Internet of Things” (IoT) sensors in the physical world,
combined with all online resources) access to vast mountains of data, along with the ability to analyse
and look for patterns in this data at blinding speed and make hypotheses, test whether these
hypotheses are valid and learn from what can be proved, and then remember everything it learns,
forever. No human, nor even any group of humans, is capable of such a task.
For instance, imagine a doctor who could hold in their head the avalanche of ever-increasing research,
clinical trials and advances in medical science, who was an expert in every medical specialty, and
also has access to your complete life-long medical record. Now imagine that this doctor also has
access to your entire genome sequence, to narrow down the range of possible treatments for your
condition to one that your DNA shows is the one most likely to work for you personally. Such is the
promise of Artificial Intelligence as applied to medical science, and IBM’s Watson technology has
already been applied to this goal (Loughran 2011). Will doctors become unemployed? Not all of them.
Imagine your friendly GP with this Artificial Intelligence available to them as a decision support tool.
Will we need as many specialists as we do now? We contend that, in time, we will not.
Therefore, for the purposes of this report, we define AI as it relates to automation and its effects on
employment as “the application of information technologies to tasks that are able to be performed as
well as or better than humans are able to achieve, supplementing or replacing human effort”.
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Artificial Intelligence and the Ethical Implications of Automation on Employment
Stakeholders and Analysis Method
Automation is still limited to mostly big corporations but it won’t be long before they will become a
part of our everyday lives. It touches on a number of industries. Some of these stakeholders are
directly affected by automation whereas others are affected as a flow-on effect of automation. In the
analysis below, the goodwill of these stakeholders are analysed and the ethical issues are thus
analysed. A few industries have been taken into account and their stakeholders have been listed
below.
Stakeholders
Automotive Industry Auto makers – Audi, Tesla, Uber
Drivers
Motel owners/employees
Restaurant owners/employees
Gas station owners/employees
Robots
Government
Professionals’ Industries Lawyers
Accountants
Accounting clerks and bookkeepers
Keyboard Operators
Trades Industry Network administrators
Electrician
Mechanics
Plumbers
Bricklayers
Carpenters
Joiners
Panelbeaters
Manufacturing and Production Industry Painters
Inspectors
Testers
Sorters
Warehouse pickers
Packaging
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Artificial Intelligence and the Ethical Implications of Automation on Employment
Filing
Machine operators
Table 1: Stakeholders
The Four Step Stakeholder Analysis Approach
Step 1 – Analysing the facts
In recent years, due to technological advancements, machines are capable of doing not just physical
tasks but also mentally challenging jobs. A number of high-profile car makers and technology
companies like Google, Ford, Mercedes-Benz, Tesla, and Uber have claimed that by 2021, their fully
autonomous cars will be on the road (Hassler 2017). The roads in big cities like Singapore and Boston
are getting more congested. So, autonomous cars are appealing in that more cars can fit in the same
stretch of roads.
According to Borenstein, Herkert & Miller (2017), about 1.3 million people die in crashes on the road
each year and 20-50 million more are injured or disabled. Moshe Vardi, one of the computer scientists
claims that we can save millions of lives by the use of automated cars. There are several benefits to
these cars like decreased traffic congestion, increased fuel economy and thus environment friendly.
One of the most important utilities of autonomous vehicles are providing mobility to disabled people
who otherwise wouldn’t be able to drive or travel without any assistance. The US government has
seen the potential of self-driving cars and thus would request a $4 billion investment in research and
infrastructure improvements (Borenstein, Herkert & Miller 2017).
Looking at other industries, automation has had some noticeable impacts. Business process
automation has pushed up the productivity of HR, finance and accounting business units significantly.
The companies are reporting up to 5 to 10 times increase in productivity with 37% less input
(‘Information Services Group, Inc.; ISG: RPA Increasing Productivity, Not Job Losses’ 2017). Also,
there has been no significant job losses as predicted. The employees are working on important tasks
which can’t be automated. 68 percent of business leaders assert that IT will be the most affected
support unit within businesses. Although AI is still in its infancy, it won’t be long before it will be
able to do complex tasks on enterprise level.
Large corporations are using the latest automation technologies to achieve business offerings which
wouldn’t be possible without the aid of AI. A practical example of use of automated drones is by the
online retail giant Amazon. They provide a service called ‘Prime Air’ where the parcels are delivered
via unmanned drones. The delivery time is estimated to be within 30 minutes while increasing the
safety of the parcel and efficiency of the delivery system (Amazon.com 2017). The company is at the
forefront of advanced usage of automated technologies.
Automation has a lot of usage in the modern society and the technology giants are trying hard to
incorporate them into our everyday lives but there are consequences of deep integration of automation
and AI technologies in our society. Gownder (2017) has claimed that even though 14.9 million new
jobs will be created, 24.7 millions jobs will be lost by 2027 leaving the net job loss to 9.8 million
within the US alone. The new jobs will mostly be in software development arena whereas sales roles
will be hardest hit by the automation technology. Also, office and admin jobs will be taken by robots.
The most menial of tasks will be overtaken by AI and robots leaving most of the human resource to
focus on more important and mentally challenging tasks.
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On the same note, Dubie (2004) argues that the main purpose of automation is to reduce the number
of humans required to do the work. Low entry-level jobs will be no more. Although, it will be years
before fully autonomous systems are created, it’s just a matter of time when these systems will be
ubiquitous in offices and our daily lives alike.
Figure 1: Future employment projections by sector 2012-2022 (in millions) (West 2015)
When it comes to IT, some of the big tech companies are already setting examples. Markoff (2016)
said that Amazon, Facebook, Google, IBM and Microsoft came together to establish an organisation
to set ground rules for protecting the rights of humans and saving their jobs. Currently, there’s a lot of
debate raging about robots and other computing systems like automated cars and mechanical
industries. This organisation will play a crucial role in laying down the ethical rules for any
organisation that gets into the development and research of automation. This is a step in the right
direction to pin down the basic ethical standards at the enterprise level for the sake of the public and
human society as a whole.
It may come as a surprise that Rockwell Automation, Inc. (NYSE: ROK), the world’s largest company
dedicated to industrial automation and information that employs 22,500 people serving customers in
more than 80 countries, was named one of the “World’s Most Ethical Companies” for 7 years in a row.
They incorporate leading ethical standards and practices that ensure long-term value to customers,
suppliers, investors and employees alike. They have been awarded as an ethical company because of
their workplace practices and values. In the future, when they produce AI-related systems, millions of
people may be displaced which isn’t very ethical per se. So it is yet to be seen whether they will be
able to retain this title that they have held for so long.
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Artificial Intelligence and the Ethical Implications of Automation on Employment
Rich Picture of Stakeholders and their relationships
Figure 2: Rich Picture with Stakeholders in the Automotive Industry
If we take an example of self-driving cars, the winners will be the auto-makers. They will be able to
sell cars and making huge profits. Consumers will also be able to get a lot of benefits of having
autonomous systems helping them drive which are much less error-prone than human drivers. Also, a
lot of disabled people who otherwise wouldn’t be able to drive will be able to do so without any
assistance. This will give them a sense of independence which could increase their quality of life.
On the other hand, there will be job cuts. Many drivers won’t be able to work anymore. They will
have to switch to other means of earning money. Also, the industries supported by drivers like motels
and restaurants may go out of business as the automated vehicles will need neither food nor sleep. It’s
not as easy to switch to other roles if all you’ve done for your whole life is drive. The government will
be questioned by the general public why the automation is taking up their jobs and what measures
have been implemented to minimise the effects of transition to an AI-centric age.
Step 2 – Isolate ethical issues
As the automotive industry has several stakeholders, there are many ethical issues that affect them.
There are subtle ethical issues associated with self-driving cars which requires the attention of
engineering bodies and other communities (Borenstein, Herkert & Miller 2017). De George states that
the engineers must uphold the safety standards at any cost but he also suggests that if it means
challenging managerial decisions, then it’s best not to do that as that may jeopardise their career. This
is the job of the regulators and not line-worker individuals. At the same time, waiting for regulators to
enforce safer designs can result in significant harm to people.
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Artificial Intelligence and the Ethical Implications of Automation on Employment
Furthermore, there are ethical issues around employees being displaced from their current workplace.
Even if they were to be trained into newer roles, who’s to say they will all fit in? Also, if all the
entry-level jobs are taken by machines, how will new entrants find their way into the higher-level
jobs? Unless the attitude towards fresh graduates change and adequate training is provided, humans
will not be able to progress into better positions. Further ethical issues are discussed in the Ethical
Issues section in detail.
Step 3 – Decide on steps to resolve the current situation
Automation is going to happen. It’s not a question of if, but when. As discussed earlier, organisations
are already incorporating AI into their business processes to increase productivity and profits.
Automated cars are being brought into the market which has a lot of people wondering whether they
will be safe or not, and other implications. Above all, the ethics surrounding automation is a hot topic,
and there are many things that can be debated, the most important one being the displacement of
workers who cite driving as their primary means of income. Hence, there should be means in place to
minimise the impact of automation.
Employees spend a lot of time learning at their workplace and becoming experts in their field. If they
get displaced, then they will need to be retrained in other positions they will later assume. There must
be policies in place to ensure this happens. Musk proposes a radical solution of having a universal
income when the human labour becomes cheaper due to AI to ensure the wealth is distributed among
the population (Weller 2017). Another way to minimise the impact of automation is to only have
selected jobs and industries to be automated. The remaining employees will then have job security.
As discussed in the previous section, the proposed Ethics Committee created by the large IT
companies is another way to enforce ethics across large organisations. They will be able to standardise
ethical policies and disseminate that information, so other companies can abide by them and also
implement them to run their business.
We feel that the best course of action would be to make sure that there are policies in place that makes
sure that human employees fare well when AI is introduced in our society. The Ethics Committee will
be all-encompassing, so all industries will need to abide by it and make sure that human beings come
before machines and that there aren’t a lot of human casualties from automation.
Step 4 – Prepare policies and strategies to prevent recurrence
Even though there are a lot of ethical issues surrounding automation and AI, automation is inevitable.
We can only work to reduce the impact of AI’s impending havoc on the job market. As this is a
completely novel scenario, only a few measures can be put in place to decrease the impact of AI when
it becomes mainstream and pervasive.
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Artificial Intelligence and the Ethical Implications of Automation on Employment
Ethical Issues
The following is proposed to show the potential unethical implications that automation has within the
workforce. This list shows a small example of the complexity and moral issues that automation has on
general society and does not express the full magnitude that rapid application automation has on the
public.

  1. Utilitarianism views of automation
    The path of automation is no longer a sci-fi movie but is now an ingrained part of our society. As
    during the industrial revolution, technology has created new jobs, while many argue taking even more
    positions away; and as of 2017, the path of job creation is still moving at a slow speed, as job
    redundancies and newly created automated jobs increase. The attitudes of many organisations and
    individuals within the technology industry can compare to a utilitarian point of view, stating the
    creation of computerized functions will improve the economy and productivity of workers overall.
    The aim of companies in automation is to remove mundane processes that are done every day and
    allow workers extra time to focus on creative solutions and problem solving, resulting in the idea that
    automation is for the greater good of society. Whilst automation has increased the economy and
    produced some higher specialized jobs, it has come with a cost. Instead, AI has reduced many jobs
    overall from manufacturing jobs to very highly skilled jobs such as the scientist. The rapid pace of job
    automation has some saying its outcome has presented unethical consequences to individuals,
    ultimately compromising the health and well-being of the majority but benefitting a select few such as
    organisations and shareholders with cheap labor and higher profits.
    Some world leaders have already expressed concerns over the impact automation has on the social
    welfare of the people and effects it will have on the economy. Ex US President Barack Obama warned
    in his farewell speech “The next wave of economic dislocations won’t come from overseas. It will
    come from the relentless pace of automation that makes a lot of good middle-class jobs obsolete.”
    (Miller, 2017) This has been successful in starting conversations to produce ethical actions, such as
    adopting a few laws protecting workers and giving them benefits such as resources to enter another
    field or go back to university to pursue another degree. But the acknowledgment of a problem versus
    the actual application of laws protecting people has different outcomes, and as a world leader you
    have an obligation similar to the ethical theory of “Deontology”, to follows their obligations to
    another individual or society. By acknowledging that there is a problem, world leaders have a
    responsibility to fix the problem as they must serve the public over organisations.
    But in contrast, this has yet to be actioned, as Daron Acemoglu, an economist at MIT, discussed:
    “political leaders are unprepared to deal with how automation is changing employment” (Rotman,
    2017). The results are affecting workers’ inability to respond if their job is due to be made redundant
    or they are considering career changes. They are finding it difficult to get the skills necessary to enter
    these “specialised” jobs, resulting in them settling for lower-skilled and lower-paid jobs, or if their job
    has become redundant, forced to be unemployed. The response or lack of response of organisations to
    protect its workers has also ethically come into question. As businesses look at the processes that can
    be eligible for automation, they are aware this task might result in redundancies for those workers, and
    so the ethical principle of “Least Harm” then comes to the fore. The ethical theme of “Least Harm”
    deals with the reduction task that will result in the organisation not needing specific functions of the
    worker as much as before. This can result in a business paying more for less, which is not profitable
    from an organisation’s point of view, but in contrast automating a specific task can result in a lack of
    work by the employer; leading to the company not requiring the position anymore. The result of this
    will only lead to the deterioration of the skills and career development of the employee. Business has
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    yet to realize that, without supporting the development of their workers after process automation, in
    the long run, it will not benefit the company as there are some benefits that computers can’t replicate.
  2. Inequality of wealth and job allocation
    The increase in automation has also created another ethical dilemma, the distribution of available jobs
    to the general public and the resulting income inequality, bringing into question if the application of
    automation goes against the ethical principle of Beneficence.
    “McKinsey & Company study found that about 30% of tasks in 60% of occupations could be
    computerized and last year, the Bank of England’s chief economist said that 80m US and 15m UK
    jobs might be taken over by robots.” (Mahdawi & Chalabi, 2017). The increase in automation and
    some offshore job placements have been two actions by an organization to remove “low-paying
    mundane” jobs and gain higher profits, with a promise to have these positions replaced. But how are
    the reductions of these positions any good for society? For example, the gap between the GDP and the
    household income has only widened in the recent years; while the country has been producing more,
    household incomes have not reflected the increase. The graph below show the gap increasing.
    Figure 3: GDP and Median Family Income over Time (Merlini, 2014)
    The graph also confirms that while production has increased, some individuals will benefit financially
    from the use of automation such as top executives, business owners, while other individuals will stay
    the same financially, such as the average middle-class worker. “Economist Ed Wolff determined that
    between 1989 and 2009, 100 percent of the wealth increase went to the top 20 percent of households,
    while the bottom 80 percent saw a decline in their net wealth over the same period. Even within the
    top 20 percent inequality is significant. The top 5 percent received 80 percent, and the top 1 percent
    took in 40 percent of the wealth gained over those 30 years.” (Merlini, 2014). The graph below
    demonstrates that, while workers productivity has risen, the number of available jobs has decreased.
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    Artificial Intelligence and the Ethical Implications of Automation on Employment
    Figure 4: Job Growth by Decade (Merlini, 2014)
    Figure 5: Jobs at risk of automation (Rotman 2017)
    Some individuals and corporations explain that automation is to be expected, and that certain jobs
    always become obsolete. This happened in the industrial revolution, and this is now happening in the
    technology revolution. But the graph also exposes that organisations are not acting in the public’s best
    interests, and the trend is that it does not deign to keep its promise to do what is best for its employees
    and the organisation. Its goal is always to produce more while cutting or paying less. The lack of jobs
    and increase in production will also increase the cost of goods sold, and people will not be able to
    afford them. That can be hazardous for many individuals that now do not have the additional
    resources to cover the new cost. Take for example a single mother that lives paycheck to paycheck
    and does not receive any supplementary support;, if her job becomes redundant, she has the potential
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    to lose her home. To ask her to take on the additional cost to go back to school with a child, and to
    support both her and her child, is incredibly challenging and perhaps unrealistic. This can put an
    individual into further debt and make it even more difficult to get on top financially, as she will have
    to use her savings (if she has any) to live and provide childcare and pay for tuition books and supplies.
    Not only does the lack of jobs caused by automation result in a reduction in income and further debt
    for trying to another job, but having jobs automated will also reduce the number of hours in a working
    week. The available hours will then need to allocated among multiple people which can be difficult.
    The result will have household income further reduced, which can lead to further unemployment.
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    Legal Issues
    The automation of previously human-only activities is a distinct ethical challenge. It requires that
    industry and society consider how to ethically apply the ground-breaking technology of Artificial
    Intelligence in practice. While the automation of work can be considered within the context of ethical
    issues, it can also be considered within the context of legal issues. The rise of Artificial Intelligence,
    and the subsequent resulting automation of work, creates a number of legal issues that challenge the
    institutions that create and enforce the law.
    This section highlights a number of legal issues that arise as a result of Artificial Intelligence and
    automation. In the seemingly inevitable transition to a new age of technology, this section of the paper
    offers a consideration of the legal issues that will influence a sustainable and ethical transition to a
    future which continues to benefit Australians.
    The legal profession and industry:
    The pervasiveness of automation, a direct challenge to the legal profession and the concept of law.
    Technology increasingly dictates which human skills are employable for any given industry and role.
    In a major study that examined the skill content of 673 occupations between 2006 and 2014, it was
    found that advances in technology results in “a reduction in occupational content of skills that
    compete with machine, an increase in skills that complement machines, and no significant change in
    skills where technology has not made major inroads” (MacCrory et al. 2016, p.1). The key takeaway
    is that technology has a direct impact on the skills that are required to gain employment, and that as
    technology becomes more prevalent in any given field, the composition of skills required for
    employment substantially shifts. Additionally, with the rise of Artificial Intelligence, fewer and fewer
    industries are immune from the impact of technological advance.
    The legal profession is also subject to shifts in technology, with the impact upon the profession likely
    to accelerate in coming years. In fact, Artificial Intelligence is already being applied to some use cases
    within the industry. A number of vendors use natural language and machine learning for electronic
    discovery, Lex Machina uses predictive analytics to forecast the outcomes of litigation and a
    collection of companies have produced Artificial Intelligence backed technology to analyse contracts
    (Mills 2016, p.4-6). Additionally, the traditional legal work areas of discovery, legal search, document
    generation, brief generation and the prediction of case outcomes could also be dramatically changed
    by machine intelligence in the near future (McGinnis & Pearce 2013, p.3046). Cognitive skills are no
    longer immune from automation, and industries such as the legal profession, which were previously
    relatively unaffected by automation are now likely to see significant shifts in the skill content required
    for employment.
    In addition to this challenge to the industry and professional practice, the rise of Artificial Intelligence
    also poses a general and significant challenge to the concept and theory of law. For example, a theory
    of law attempts to understand culture, institutions and self, “to promote serious moral assessment of
    those institutions” (Green 1996 p.1687). It goes beyond understanding specific cases and considers
    questions such as “Is law a good idea? How and to whom do legal institutions distribute power?…Can
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    it help achieve justice?” (Green 1996 p.1717). A theory of law considers that law is a social
    construction that embodies justice, but which also distributes power within society. This is interesting
    because Artificial Intelligence and the automation of work draws focus back to these fundamental
    questions which define a theory of law. How is it that the law and existing legal institutions will
    remain relevant in a new age of Artificial Intelligence and technology? New technology such as
    Artificial Intelligence opens up completely unchartered territories and possibilities which never before
    existed. So not only do legal institutions face the difficulty of creating rules that address Artificial
    Intelligence, they also face the difficulty of fulfilling the purpose of justice and fairly distributing
    power within a society. In a time when technology is making the value of many human skills
    completely redundant, this may prove to be of fundamental importance.
    Clearly, the relevance and purpose of existing legal institutions is directly challenged by Artificial
    Intelligence and the new wave of automation that it brings, to the point that it is no longer certain that
    existing legal structures will be able to continue to effectively distribute power or achieve justice.
    Labour Law:
    What about redundancies? Can Australian law remain relevant?
    Not only does Artificial Intelligence create a substantial legal challenge to legal institutions generally,
    but it also confronts specific parts of the law, which has implications for both industries and
    individuals. Labour law is one example of this. The purpose of labour law can be articulated as having
    “the goal of correcting an imbalance in bargaining power between employer and employee in order to
    secure a more just working relationship for the worker” (Howe 2011, p.295). As such, labour law is
    the primary mechanism by which workers are treated ethically, and given protection, especially in
    situations where employers have significantly more power.
    In Australia, the most turbulent period in relation to labour law occurred in the 1990s; a period which
    involved increased protection for workers under the Keating government, the reversal of the level of
    protection under Howard’s ‘Work Choices’ and the subsequent restoration of overall levels of
    protection via the Fair Work Act (Mitchel et al 2010). Despite this period of turbulence however,
    Australia’s long-term level of protection under labour law has remained relatively stable since the
    1970s (Mitchel et al 2010, p. 24). Australian labour law can be described as a “middling ranked
    common law type demonstrating only moderate protections to labour and its institutions” (Mitchel et
    al 2010, p. 29), with higher protections that the US and UK but lower protections that France and
    Germany as civil law equivalents (Mitchel et al 2010, p. 29).
    While current labour law in Australia specifies legal minimum entitlement for workers (as specified in
    the National Employment Standards) and describes entitlements ranging from leave, employment
    types, contracts, awards, wages, pay slips and flexible working arrangements (REF), the most relevant
    topic in relation to Artificial Intelligence and automation is that of employment termination and
    redundancy. This is because that while during a shift in skill composition that will arguably benefit
    those with the skills that remain in demand, there is little to protect employees against the more
    dramatic possibility of total redundancy (rather than just the redundancy of certain skills).
    Furthermore, under Australian law, automation is one legitimate reason for the dismissal of an
    employee (Fairwork 2017). In addition to this, the number of jobs under threat by automation is
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    rapidly expanding, especially as Artificial Intelligence makes more and more historically human tasks
    automatable. Automation is no longer limited to physical and low skilled jobs, rather it can be applied
    to a range of roles that require cognitive functions. As a result, it’s also plausible that many industries
    will become more vulnerable, even those which previously had little need of the basic protections
    afforded to workers under labour law.
    While labour law has remained relatively stable in Australia, a key issue is whether the various laws
    that intend to protect workers will remain relevant in the future. Artificial intelligence has the
    potential to bring a new wave of automation, which in the context of Australian law could prove to be
    problematic. There are no restrictions on automation, and it’s completely legal to make an employee
    redundant on the basis that their job can be automated. If Artificial Intelligence has the effect of
    rapidly accelerating automation across all industries, including traditionally cognitive roles, it’s very
    possible that labour law in Australia could soon fail in its purpose to maintain a “just working
    relationship for the worker” (Howe 2011, p.295).
    Australian Road Rules and Driverless Vehicles:
    Changes to the law are required, but then what happens to the workers?
    Driverless vehicles combine a vast array of sensors and radar equipment with Artificial Intelligence
    techniques in order to reduce and remove the need for human drivers to be at the wheel. In the past
    “Skills associated with Awareness of one’s physical surroundings…may have been in a similar period
    of technological pause” but that “recent advances in autonomous vehicles and visual processing
    threaten to end the pause” (MacCrory et al. 2016, p.14). In fact Waymo (originally the Google
    self-driving car project) is currently running public trials of self-driving vehicles in Phoenix, Arizona
    (Waymo 2017).
    Yet current legal frameworks may not be sufficient for future ‘disruptive’ technologies, or may have
    insufficient legal definitions to support such new technology. For example, according to Clayton Utz,
    substantial changes to the Australian law are required in order to capture the benefits and manage the
    risks associated with the technology (Clayton Utz 2016, p.2). One substantial barrier to the technology
    is that “our laws presently assume that vehicles will be driven by a human” (Clayton Utz 2016, p.13),
    meaning that the legal concept of a driver now needs to be clarified. Specific examples include
    requirements for the driver to wear a seatbelt, giving the name and address to another party when
    involved in a crash, and a prohibition from using mobile phones while driving (Clayton Utz 2016,
    p.13). This is one specific legal concept, however additional concepts which may also need to be
    revised include the concept of proper control, responsibility, law enforcement (for example who will
    be fined for speeding), liability, negligence, contracts, consumer law, insurance and a raft of other
    considerations (Clayton Utz 2016, p.13-25). Evidently there are a number of issues that need to be
    addressed within Australian road rules in order to enable self-driving cars to be incorporated into the
    current legal system.
    Once these legal requirements are met it’s likely that consumers will soon be able to take fully
    autonomous self-driving cars to the road. Yet, there is another consideration that ought to be made,
    and that’s in regard to the workers whose previously human-only skills of spatial and physical
    awareness (that is, of driving) are now made redundant. Considering that a fair and legal reason for
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    Artificial Intelligence and the Ethical Implications of Automation on Employment
    the redundancy of a worker is when a business “introduces a new technology… the job can be done
    by a machine” (Fair Work 2017), what will happen to these workers?
    One purpose of labour law is in regard to regulating the just distribution of power between employer
    and employee. If, when taking advantage of the latest Artificial Intelligence enabled technology an
    employer is able to make an entire workforce redundant, has labour law succeeded in its purpose?
    Driverless vehicles are just one example of a new and novel automation technology that allows
    machines to perform previously human-only tasks. While there are inevitably a number of legal issues
    that focus on the implementation of driverless technology, this significant legal issue remains
    uncertain, which is concerned with whether current legal frameworks will be sufficient to protect
    workers in a time of accelerated change and technology.
    Intellectual Property:
    Machines generating IP – far more than just routine tasks
    A key skill of humans is the ability to generate intellectual property, which is often then monetized by
    corporations. Legal concepts such as copyright, patents, trademarks and registered designs exist to
    encourage innovation and creation. Yet the skills of cognition, language generation and in short, the
    ability to generate intellectual property may soon also be a possible function of Artificial Intelligence.
    In regard to Intellectual property, AI could displace not just the tasks involving routine tasks (such as
    has been done in the manufacturing industries in the past), but also the tasks that involve generating
    Intellectual Property. In this new age of intelligence, it’s no longer clear who the inventor of IP is,
    when robots and AI generate new ideas – the question must be asked – how does this fit in? And what
    are the current regulations around this?
    Privacy:
    In addition to the erosion an individual’s ability to create value, there is also the issue of privacy. If
    you purchase an Artificial Intelligence product, who will own the intellectual property and data that is
    created as a result of its use?
    For example, continuing with the example of self-driving cars, a vehicle which naturally has a host of
    sensors and other equipment, will it be able to record information about your movements for the
    benefit of other companies? Perhaps it could be used for targeted marketing, to allow companies to
    pay to change your driving route, to advertise nearby businesses and so on. According to the Privacy
    Act, in Australia personal information can be disclosed with individual consent, or if “the individual
    would reasonably expect” the disclosure, based on its relation to the purpose for which it was
    collected (Clayton Utz 2016, p. 29). As with many current technologies, privacy remains a real
    concern for the implementation of Artificial Intelligence.
    Legal Issues Conclusion
    The tension between the law, automation and employment raises wider ethical questions about the
    ability of law to appropriately regulate technology, and whether or not the legal system will be able to
    fulfil its purpose in the context of new Artificial-Intelligence-driven technologies. The major
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    Artificial Intelligence and the Ethical Implications of Automation on Employment
    challenges and legal issues naturally relate to two key concepts, the achievement of justice, and the
    distribution of power – both of which are fundamental concepts in relation to the nature and purpose
    of law.
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    Artificial Intelligence and the Ethical Implications of Automation on Employment
    Social Issues
    Artificial Intelligence is for intelligent machines utilising computer programmes where the research is
    based on the study and the designing of different smart agents. The study also includes the analysis
    which is based on the designing and then working over intelligent agents. The study is about the
    context which provides for the ability to follow human thoughts. The area of research is to perform
    tasks which only humans can do. The current technology has not been so advanced for the machines
    as it comes with the reality of rapid development. (Hutter 2017). The example includes the robots,
    robotic vehicles, and the other AI software. When it comes to making use of the robots, one of the
    best examples of the industrial firms to build up the proper system of humanoid robots who act as the
    domestic helpers for the elderly.
    Previous Knowledge or Experience
    As per previous knowledge, DARPA has been able to create and develop autonomous vehicles that
    can drive itself for 132 miles. There are combatting system programs which are developing with the
    armed robotic cars or bikes that helped the troops on the ground with the direct fire anti-tank weapons.
    AI is also used for stock trading which is then handled by AI-based software. It is not always for the
    creation of machines but also for the invention of tools and the programmes that help in the effortless
    performance of the tasks. A lot of inaccurate information is available through the information
    technology these days. (Lu et al. 2017) One problem was the access to private data, and the other is
    that of intellectual property, i.e., the information that one makes available, without having the
    authority to do so.
    Expectations
    Another ethical issue relates to robot ethics which include the treatment of privacy as well. The AI
    program works on speech recognition which is essential for processing power and then working on
    understanding operations. This application of AI is set to allow the government and the other entities
    for the suppressing of the dissent and the attacks that are done by the enemies. AI surveillance is
    mainly to monitor the activities of a human using cameras as is done for controlling traffic, with the
    creation of threats to individual privacy. As most people use computers, a lot of information is stored
    in these systems and often even shared with others. People upload essential information, information
    that is sensitive or private, or work that they may have done with a lot of hard work.
    Major Social Issues
    The other social issue is related to unemployment which could lead to stealing and the unethical
    activities to make money for the people to survive. There is a need to focus on the automation which
    could lead to the reduction of different human tasks. (Lu et al. 2017) AI software has also replaced
    some junior lawyers for the analysis of documents and searching of case law. A higher usage of
    technology could lead to environmental pollution as well. Unauthorized access, sharing, or reuse of
    this information is something that is a breach of an individual’s privacy and must be considered by the
    AI developers. For the protection of users of these methods, laws have been put in place to ensure that
    unfair advantage cannot be taken using these methods. The responsibility does not just lie in the
    interest of society and public users of information technology systems but also towards the
    organization that one works for. Towards one’s clients, the responsibility exists to keep their
    information safe from unwanted usage by anyone else. Prevention of leaks of the personal or
    professional details of clients must be addressed. As per the analysis, the social issues and
    implications related to the applications could be used to intensify the battles.
    Unemployment
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    Artificial Intelligence and the Ethical Implications of Automation on Employment
    The innovation in AI and robotics have forced the government to make use of technology and replace
    regular people with machines and software. The competitive advantage of the poorer in society, and
    the emerging economies based on the cheaper workforce, is going to erode as the robot production
    lines and the intelligent computer systems are going to undercut the cost of human endeavor. The
    study is also focusing on the legal implications of the rapid change in the technology. The report
    covers the difference with the future consequences and the legal consequences of the rapid
    technological changes which act as a global forum for the legal profession.
    Racism
    The robotic AI platforms are replacing the human decision makers who are racist and sexist. The
    programmes are designed with the pre-selection of the candidates to assess the eligibility for insurance
    covers or the bank loans to likely discriminate against the women. The women need to be encouraged
    into the IT industry to redress the automatic biasing. The researchers warn the problem does not lie
    with humans as Artificial Intelligence use machine learning algorithm. Machines adopting racist and
    sexist tendencies occurs when the learning is from humans and favor white men, and the machines
    then mimic the humans and the social actions.
    Peer Pressure
    The peer pressure of the destruction and taking away of the jobs by the robots has been a significant
    concern for the people. The human touch has always been hard to replicate with harder to reduce to
    the formula and the scale. It is essential to focus on the flexibility and the effectiveness of setting
    things right through the human labor as the jobs at all levels in the society are primarily undertaken by
    the automation control and reassigned to the robots or AI. The peering into the future is where one
    needs to decide which jobs need to be performed exclusively by humans like the caring for babies
    only.
    Homelessness
    With the increased form of mechanism autonomy, there is an increase of problems as defined by the
    legal responsibility for the accidents involving the new technology. The homelessness issues and the
    other liability issues have been the insurmountable obstacle to introducing the fully automated
    driving. The driverless forklifts used by people in the factories which has led to no labor work by the
    people. There are other limitations which are imposed by the different aspects of the machine
    autonomy as well.
    World Hunger
    With the use of AI automation, there is a possibility that the value of the crop industry and the other
    delicate production relies on declining number of available human-made products to harvest. The
    mechanized farmers are for monitoring, pruning and then thinning which could replace with the AI
    machines. It will lead to a better output but the decrease in the labor quality, altogether.
    Depression
    As per the analysis, the rise of the technological unemployment can lead to the advancement which
    can cause in AI. The government needs to focus on the high depression where the government set up a
    guaranteed basic income. The fictional future includes the machines replacements which are
    dangerous, menial and then degrading the work as well. It will directly lead to the deterioration and
    lead to depression as well.
    Divorce
    The robots are also taking the jobs of the lawyers, where the conflicts and the other issues are solved
    by filling the dispute online, and the robots are working on it. On the other hand, they are working
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    towards unemployment, and the divorce cases are increasing as there is no possibility to increase the
    human-made labor or the monthly income.
    Terrorism
    The social issues are also related to terrorism where the people will be facing the problems associated
    with robot automation machines. The robot rights have been for the moral obligations of the society
    which includes the human values as well.
    Bullying
    Its primary requirement is to be “a good citizen,” who follows the laws of the nation. Besides these,
    there are specific values that have prescribed. They include the keeping of the public interest on the
    top of the priority. Above all else, the private and business interests, the public interest must be kept
    and should be adhered too. It is a primacy of the public interest.
    Slavery
    Without the due permission of the owner of the information, it is used for personal gains. AI is also
    for ethical issues that based on the robot ethics, machine, and the other noble standards. The moral
    problems are related to the threats of privacy and the human dignity. The rights which set for life,
    liberty, freedom of thought and equality before the law. As per the evaluation, is seen that Japan and
    Korea can make use of the robots for the household activities.
    Examples
    The best example is the use of the AI which has used for the development of the armed robotic
    vehicles that could be for the war purpose mainly. The significant impact is the society where the
    technology could use for the war-related functions. The unpleasant activity includes the higher impact
    on the technological advancements which could be for war or other destruction activities. (Conitzer et
    al. 2017) There are other issues related to understanding the limits of the tools and the agents. The
    example is robots who are for household activities to learn and then work over the learning activity for
    the users who tend to cause the social implications as the users are general. The further assistance
    based on the Artificial Intelligence which raises the bar for the information literacy and the computer
    literacy as well. Here, the AI programmes work on the systems and the implementation of how the
    users trained with the new learning and exposure. It involves the system information where the users
    work on ethical, social and professional issues which relate to the Artificial Intelligence. The forms set
    with the positive and the negative consequence where the Artificial Intelligence include the robot
    rights, machine rights, threats to privacy which consists of the risks to the human dignity also.
    Conclusion
    The technology is vital for the change which set to advancement at the rapid pace. For this, the
    emerging technologies also need to focus on the improvement of the quality, cost and the availability
    of goods and services. It has been proved to be holding the possibility to make the changes in the
    society with the implication that it affects the jobs of the people in the community. The recent trend
    towards increased automation is forced to operate with fewer workers. The business has set with the
    continued robot with the operations set rather than for hiring additional workers. The technologies are
    found to make the job less secure in a way that it is out of the employment.
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    Artificial Intelligence and the Ethical Implications of Automation on Employment
    Cultural Issues
    Culture can be defined as “the collective programming of the mind that distinguishes the members of
    one group or category of people from others” (Hofstede 2011). We may not feel “programmed”, but
    the culture within which we live, and particularly the culture within which we were raised, plays a
    major part in how we perceive ourselves and our role and responsibilities in society.
    Culture is essentially a construct, one that is not directly accessible to observation but rather is
    inferable from behaviour. An understanding of culture can be useful in predicting behaviour, and
    specifically in this context, it provides some insight into the possible behaviour of individuals,
    organisations and societies in the face of future job losses due to automation.
    Of course, this is not a new issue. Jobs have been lost to automation throughout human history, from
    the replacement of human labour with animal labour on early farms, which was then in turn replaced
    by machinery such as tractors, and so on. Human cultures have adapted to these changes because they
    have occurred relatively slowly and locally, giving those affected by change enough time to adjust to
    “the new normal”.
    However, the application of “forged laborers” and “synthetic intellects” – to use Kaplan’s terms for
    AI-embodied systems and AI-based automated decision-making (Kaplan 2015) – has the potential to
    eventually have significant effects on the entire human race. Undoubtedly some of these effects are
    going to be positive, making us safer (think self-driving cars), saving us time (think domestic robots),
    and freeing us from tasks and decisions that we are happy to avoid. However, the risk of increased
    unemployment in the short-term and medium-term is high, and is likely to be a serious problem unless
    steps are taken to mitigate this risk.
    Why is this the case? It may not be simply that there are not enough jobs available for those displaced
    by automation. Kaplan (2015) suggests that, rather, it may be that the skills required to do these
    available jobs are likely to evolve more quickly than people can adapt to them.
    Our traditional sequential system of education and work, with its assumption of “first you go to school
    & university or learn a trade, then you get a job”, was designed for (and was highly effective in) an
    era in which you could reasonably expect to stay in your chosen “living”, practising and refining the
    skills in which you were once trained, for your entire working life. This model simply will not work in
    this new age of rapid change brought on by continually refined automation and our evermore
    technological world. There is a danger that the jobs available will shift more rapidly than a person of
    average ability and intelligence can effectively update their skills to stay “ahead of the curve”. The
    wave of change is moving more quickly this time around.
    Of course, some traditional subsistence cultures still survive in our modern world, growing or
    catching their own food largely in isolation from the rest of the world (for instance, the Arctic Inuit
    peoples surviving on hunted sea-life, and self-sufficient tribes in the highlands of New Guinea that
    survive on vegetables and a mixture of hunted and domesticated animals). For these cultures,
    AI-based automation in the rest of the world is unlikely to impact their simpler way of life in any
    significant way, since their daily life revolves mainly around what they will catch, kill and eat for that
    day and the days ahead.
    Nevertheless, we contend that for the remainder of the human race, the risk of looming unemployment
    as a result of AI-based automation remains, a human race made up of many different cultures. Two
    primary questions arise:
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    Artificial Intelligence and the Ethical Implications of Automation on Employment
  3. Will the types of problems to which automation is applied vary from one country and culture
    to another?
  4. How will different cultures adjust to the displacement of jobs, and with what cultural
    distinctives?
    We propose that these effects are likely to be experienced differently by different cultures across the
    world, as each adjusts to these changes through their own cultural filters.
    Cultural Effects on Automation
    Let us turn first to the first question, that of whether cultural differences might lead to differences in
    individual countries’ choices of where AI-based automation is best applied. It is well-recognised that,
    in many countries, there has been a significant loss of trust in institutions in general, and governments
    and political parties in particular, in recent decades. We can see this particularly in Australia, where an
    Essential Media report showed that “trust in institutions” ranges from above 50% for the High Court,
    the ABC and the Reserve Bank but down to 20% or lower for trade unions, business groups and
    political parties (cited in Menadue 2015). Compare this with Nordic countries which, according to a
    Eurobarometer survey of broad social trust, responding to a question about “tending to trust”, gives
    Finland a score of 59%, Denmark 53%, and Sweden 52%, compared to a European average of 32%,
    and only 25% in Russia (cited in a Special Report “Northern Lights” in The Economist 2012).
    We can conclude from this that Nordic cultures are innately more trusting, which includes trusting
    that their government will act in their interests, including maintaining the generous social welfare net
    for which they pay such high taxes. As The Economist (2012) puts it, in Nordic countries, “Citizens
    pay their taxes and play by the rules. Government decisions are widely accepted.”, and that Nordics
    “regard the state’s main job as promoting individual autonomy and social mobility”.
    In such cultures, given that democratic governments reflect the culture of the people who elected
    them, we can speculate that this higher level of mutual trust between citizens and their government to
    lead to choices being made by the government of AI-based automation that are more socially
    beneficial, for example legislating for safer cars, rather than replacing government employees with
    automation.
    In contrast, in a culture such as the United States where there is less trust in government, combined
    with a preference for “small government” and a greater belief in the free enterprise system and the
    market economy to deliver benefits to individuals, there may be less reluctance to reduce the total
    number of government employees by automating what can be more cheaply performed by a “synthetic
    intellect”, such as decisions on challenges to parking tickets.
    Automation Effects on Culture
    We now turn to the second question, that of how different cultures may react and adjust to the
    displacement of jobs, and with what cultural distinctives. This is also necessarily speculative, as there
    is no adequate historical precedent for AI-based automation from which we can extrapolate. We thus
    turn to research that reveals insights into cultural differences between countries, from which we can
    infer likely outcomes.
    Hofstede’s Cultural Dimensions Theory (Hofstede 2011) provides a useful way of comparing the
    culture of individual countries with one another, measuring them along six dimensions with a value
    between 0 and 100, summarised in Table 2 below:
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    Hofstede’s Cultural Dimensions
    Individualism vs
    Collectivism
    The extent to which people feel independent, as opposed to being
    interdependent as members of larger wholes
    Power Distance The extent to which the less powerful members of organizations
    and institutions (like the family) accept and expect that power is
    distributed unequally
    Masculinity vs
    Femininity
    The extent to which the use of force in endorsed socially
    Uncertainty
    Avoidance
    The extent to which a society tolerates uncertainty and ambiguity
    Long-Term vs
    Short-Term
    Orientation
    The extent to which a society considers that the world is always
    changing or is essentially as it was created
    Indulgence vs
    Restraint
    The extent to which a society values freedom and following your
    impulses over duty
    Table 2: Hofstede’s Cultural Dimensions (Hofstede 2011)
    In order to explore the cultural distinctives associated with AI-based automation and its effects on
    employment, we will consider just one of Hofstede’s dimensions, Individualism vs Collectivism , in
    the context of just one example of automation, that of autonomous vehicles .
    In Hofstede’s construct, an Individualist culture is one in which the ties between individuals are loose,
    and everyone is expected to look after themselves, and their immediate family. Examples of countries
    that score high on the Individualism dimension are US (score of 91), Australia (90), Britain (89),
    Netherlands (80), New Zealand (79) and Italy (76).
    In contrast, a Collectivist culture is one in which individuals, from birth onwards, are part of strong,
    cohesive in-groups, often extended families (uncles, aunts, grandparents) that continue to protect them
    in exchange for unquestioning loyalty, and oppose other in-groups. Examples of countries that score
    low on the Individualism dimension (and therefore high on Collectivism) are Guatemala (6), Ecuador
    (8), Panama (11), Venezuela (12), Columbia (14) and Pakistan (14).
    Hofstede (2011) includes a useful table of selected differences between societies which is reproduced
    in Table 3 below:
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    Artificial Intelligence and the Ethical Implications of Automation on Employment
    Individualism Collectivism
    Everyone is supposed to take care of him- or
    herself and his or her immediate family only
    People are born into extended families or
    clans which protect them in exchange for
    loyalty
    “I”–consciousness “We”–consciousness
    Right of privacy Stress on belonging
    Speaking one’s mind is healthy Harmony should always be maintained
    Others classified as individuals Others classified as in-group or out-group
    Personal opinion expected: one person one
    vote
    Opinions and votes predetermined by in-group
    Transgression of norms leads to guilt feelings Transgression of norms leads to shame
    feelings
    Languages in which the word “I” is
    indispensable
    Languages in which the word “I” is avoided
    Purpose of education is learning how to learn Purpose of education is learning how to do
    Task prevails over relationship Relationship prevails over task
    Table 3: Ten Differences Between Collectivist and Individualist Societies (Hofstede 2011)
    Turning now to the characteristics of autonomous vehicles, that is, self-driving cars, we contend that
    the widespread introduction of these vehicles is likely to have massive effects on society, with Kaplan
    (2015) predicting that over the next 20-25 years, 75% of vehicles on the road are forecast to be
    autonomous.
    Kaplan (2015) raises a huge number of likely flow-on effects that these societies would experience
    including:
    ● Only need 1 vehicle for every 3 currently in use (Spieser et al 2014)
    ● A 90% reduction in traffic accidents
    ● 4 million less injuries annually costing $871 billion in US in 2010 (Blincoe et al 2010)
    ● A greatly reduced motivation for personal car ownership, leading to reduced need for garages
    attached to houses, amongst other effects
    ● Reduced load in hospital ERs, reducing the number of doctors and nurses required in ER
    ● Reduced number of police required to attend the scene of road accidents, leading to more
    police being available to attend to other policing needs
    ● Reduced number of wrecked cars, leading to reduced employment in the tow-truck industry
    ● Reduced number of vehicle repairs, leading to reduced employment in the panelbeating
    industry
    ● Reduced number of traffic-related court cases, leading to reduced delays in other cases
    coming to court
    ● Return of land from parking lots (Templeton 2014)
    ● Reduced environmental pollution, leading to improved public health
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    ● Greatly reduced motivation to learn to drive, leading to reduced employment in the driving
    instructor industry
    ● Reduced number of traffic jams, leading to a reduction in lost worker time and increased
    productivity
    ● A possible removal of speed limits, or an increase in speed limits, leading to shorter commute
    times, which would then lead to an increase in the cost of housing further away from city
    centres as they come within an expanded “commuter belt”, but a corresponding reduction in
    the cost of housing nearer workplaces as the current premium paid for such proximity
    collapses due to reduced demand
    ● Increase in personal productivity due to there being no need to pay attention to the road
    ● No need to avoid alcohol before travelling in an autonomous vehicle
    ● “In short, this single application of AI technology changes everything. It alone will make us
    far richer, safer and healthier. It will destroy existing jobs (taxi drivers, to name just one) and
    create new ones (commuter shared club-car concierges, for instance).” (Kaplan 2015)
    So, while we might disagree on the need for commuter shared club-car concierges, we contend that
    the effects of autonomous vehicles, once fully deployed into a society, will be far-reaching, and will
    potentially cause unemployment in a wide range of industries.
    How might it be reasonable to speculate that these societal changes will be dealt with by countries
    whose cultures are high on the Hofstede’s Individualism scale? In these countries, such as the United
    States, Australia and Britain, with their emphasis on self-determination, there is the possibility of
    significant social and economic disruption, as autonomous vehicles displace workforces more quickly
    than the individuals in them can retrain in new skills. The benefits, such as reduced road fatalities and
    a cleaner environment, are likely to be welcomed by all, but there is also likely to be the expectation
    that individuals with now-redundant skills will spend their own money to learn new skills that are still
    in demand by employers. There may not be the political will for governments to fund mass retraining
    schemes, and displaced individuals are likely to only receive help from their immediate families.
    Some will be able to afford to fund their own reskilling, and others will not, leading to entrenched
    unemployment for some and a further widening of the existing gap between the employed “haves”
    and unemployed “have-nots” in these societies.
    On the other hand, how might we speculate that these societal changes will be absorbed by countries
    that are low on Hofstede’s Individualism scale? Countries that have a more collectivist culture, such
    as Guatemala, Ecuador and Panama, are likely to also welcome the benefits of autonomous vehicles
    (although their widespread use will take much longer in these poorer countries, due to lower wages
    making them less attractive), but strong family and cultural ties may well cushion the effects of job
    displacement. Despite having generally lower GDPs than countries with Individualist cultures, these
    countries’ economies tend to be more centrally-planned, and so government intervention to deal with
    job displacement may be more likely. Although these governments are likely to have less money
    available to spend on this issue, interventions such as large-scale infrastructure projects could absorb a
    large pool of the displaced, similar to the dams, bridges, hospitals, and schools that were initiated in
    the US as part of the National Industrial Recovery Act 1933 in response to the Great Depression.
    Although there is a low level of trust in the government in some of these countries, the strong and
    cohesive extended-family structure described above may mean that social and economic disruption
    can be expected to be less severe than in high-Individualism countries, as extended families “circle the
    wagons” to help each other without limits, even in their relative poverty.
    A complicating factor in this is that these Central and South American countries that are high on
    Hofstede’s Collectivist scale also have a strong “machismo” character, meaning that men generally
    want to be seen as self-reliant, and so may be less willing to accept government help or handouts. Will
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    Artificial Intelligence and the Ethical Implications of Automation on Employment
    this “pride” tend to disincline displaced men in these cultures from accepting assistance? For better or
    worse, given the inevitability of AI-based automation, we may be about to find out.
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    Artificial Intelligence and the Ethical Implications of Automation on Employment
    Business or Organisational Issues
    There is no doubt that machine learning and automation can improve company’s work processes. The
    amount of time and money that companies are investing on machine learning and Artificial
    Intelligence is enormous. It is predicted that collective company investment on machine learning and
    AI will increase to $100 billion by 2025. Machine learning is a solution for companies to increase
    their efficiency in many ways. It decreases the cost of production that lead to a cheaper product as
    well as increasing the quality of product that helps in customer satisfaction. All these benefits can
    easily convince companies to adopt machine learning, automation and AI. Some of these benefits are
    mentioned below:
    ● Personalizing customer service can help to provide high-quality customer care. By
    analyzing customers’ information, it is possible to design services based on each
    customer’s needs.
    ● Improve productivity by replacing workers with tireless machines.
    ● Providing risk and fraud management by analyzing demographics and payment
    history details of customers to identify credit risk.
    ● Increase sales and marketing by analyzing customer behaviour and predicting which
    product a customer would be likely to buy.
    All these benefits ultimately could lead to high performance, reliability, availability, productivity and
    reduction in cost for businesses. By improving all of these qualities, companies can remain
    competitive.
    As an example, the agriculture industry is now benefitting from job automation by using machine
    learning and AI.
    PicknPack is an automated agriculture packing system that consist of seven different modules. Each
    module has its own intelligent functions. It automatically checks the agriculture product, put it on the
    production line then it does the quality assurance check, packages the product and labels it based on
    the destination of the product. It also does the audit to make sure all the steps have done completely
    and correctly. The whole process is completely automated and no human interaction is needed.
    PicknPack is a game changer for agriculture and food industry as it works tirelessly without pause.
    These kinds of automation technology can undoubtedly benefit companies and their customers in any
    industry.
    However, these changes could be extremely challenging for companies. Some of these challenges are
    mentioned below.
    Companies need to remain competitive to survive.
    Staying competitive is one of the big challenges within any company. There are many different
    strategies to help companies remain competitive but always the company that chooses the best one
    would be more successful. It is extremely challenging to find the best ways of remaining competitive
    especially when it comes to technology.
    In today’s world, competition has become a race between companies. From 2001 to 2017 more than
    500 companies have lost half of their fortune and many of them are totally out of the market such as
    Kodak and Circuit City. They need to know about many different aspects of the business and industry
    such as understanding the nature of competition in the market, knowing the needs of the customers,
    providing the best customer care, decreasing the price and increasing the quality to grow their market
    share.
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    Artificial Intelligence and the Ethical Implications of Automation on Employment
    Machine learning, AI and automation can turn many obstacles into opportunities. It can help
    companies find reliable, actionable and predictable ways to grow. AI can help them to find, better than
    any sales person, the customers most ready to purchase as well as the ones that are at risk of buying
    from competitors.
    Adopting the new technologies is extremely challenging.
    There are many challenges involved in adopting AI. One of the biggest challenges for companies is
    finding the right people with deep knowledge of AI. It is very expensive and difficult for companies to
    find data scientists. They also need to train these people to know about their business and customize
    the technology based on their needs. Deep knowledge of AI needs many different skills such as
    mathematics, computer science such as deep understanding of computer programing and new
    technologies such as IoT as well as having business insight.
    Heavily investing in AI and machine learning involves many risks such as the risk of return on
    investments. Since it is linked to improvement in quality, productivity and efficiency of the business
    in the long run, many companies are worried about these investments. As an example, e-commerce
    websites are heavily investing on AI to improve the quality of their suggestions to their customers but
    the results of using AI are not immediately obvious.
    Developing AI and machine learning technologies is very expensive as the technology itself is very
    expensive. It needs many sophisticated technologies and knowledge. Cloud computing is one of the
    technologies that is needed to implement AI. Building and making the infrastructure of the cloud
    environment can be challenging and expensive.
    Big Data and information are another challenge involved with AI and machine learning. AI needs a
    huge amount of data to be accurate. Lack of data lead the companies to rely on the data that is
    insufficient for AI and machine learning and this can result inaccurate decisions. To tackle this
    problem, companies also need to invest in data gathering and data warehousing. This could be very
    challenging in some sectors in which it is difficult to collect data.
    As an example, finance companies are worried about adopting AI. Although there is a vast
    opportunity for finance companies to adopt AI, they claim that the technology is new, untested and
    risky. They also think that there is a high chance of failure since there should be some alternative
    plans in case anything does not work the way that want. They are also worried about the security risks
    involved because they need to rely on many third-party companies to develop and utilize the
    technology. It can put their valuable data in danger of compromise or data theft, so they need to make
    sure that the security of their data is the priority in order to trust the technology and use it.
    Transition from a traditional system to a high-tech system is challenging.
    Moving away from traditional systems to high-tech automation is another challenge that companies
    need to address. In many countries, the infrastructure of the country is not ready to accept such a big
    change. Governments know that the changes are on the way and it will affect the country and
    companies sooner or later, but because they are not ready for these changes, they do not want to
    accept them. When government cannot prepare for these changes and delay it, this can lead to a
    situation in which ordinary people cannot understand the effects of these changes and they are unable
    to prepare for them. Companies also cannot speed up these changes as they are dependent on
    government decisions so it would delay their transition. It can lead to a labour market that is not ready
    for high-tech jobs. All these delays can lead to a situation that triggers a community backlash due to
    the social pain that it can cause for people.
    Providing education to the society related to AI and machine learning is one of the important tasks
    that government and companies need to do to prepare the society for all these changes. It is very
    Page 30 of 39
    Artificial Intelligence and the Ethical Implications of Automation on Employment
    important that companies educate the workforce that their jobs are in danger of replacement with
    machines and automation.
    Companies and government need to plan all these changes in a thoughtful way in advance, otherwise
    it would be too late for government, companies and society to adjust themselves with all these
    changes. The worst thing that could happen is to wait and think retraining of the workforce can solve
    the challenges that job automation brings. Leadership and insight are the keys to managing all these
    inevitable changes.
    Leadership can lead the industries to commitment and planning so they would know the roadmap for
    the future and they can manage the risks accordingly. The role of the government also is crucial as it
    can help industries in many ways to prepare for these changes. Leadership of the government in this
    area could benefit both industries and society.
    Industries and government need to work hand-in-hand, together with a great insight to build durable
    strategies and policies that help the society to walk safely through this transition. It is important that
    companies ask the government to inform the society and help the society as well to get all this insight,
    so then people within the society can prepare themselves for these changes, to lessen the effects when
    the changes are happening.
    Adopting to all of these changes could be very challenging for government, industries and society but
    with the right decisions these challenges could be turned into great opportunities. Government can
    help industries and the society to meet each other’s needs by educating people about new technologies
    and adjusting policies that help companies to more easily adapt to automation.
    As an example, the Industrial Revolution led to a higher quality of life for ordinary workers but this
    change did not happen without its own challenges. Job automation, machine learning and AI can lead
    to much higher productivity for companies, and for a period of time can bring challenges for the
    workforce in different industries, but ultimately leads to better conditions in the workplace and a
    higher quality of life across society.
    It is important that companies and government learn from history and adjust to all of these changes, to
    reduce the negative impacts that it could have on the society.
    Page 31 of 39
    Artificial Intelligence and the Ethical Implications of Automation on Employment
    Resolutions – Positive Solutions, Strategy for
    Implementation
    The potential problems raised by the implementation of widespread AI-based automation are, as we
    have seen in the preceding sections, both credible and concerning. Some researchers have proposed
    various solutions that attempt to address these concerns.
    For instance, Loi (2015) suggests that there is no reason to naively assume that the jobs displaced or
    replaced by automation are the “worst” ones (ie. jobs that people are happy to give up because they
    are repetitive, unpleasant or dangerous), and that, on the contrary, the jobs that remain may be
    “worse” than the jobs that most humans have now. She also describes Moravec’s paradox (Moravec
    1988), which predicts polarisation of jobs leading to relatively fewer middle-class jobs than low-skill
    and high-skill jobs, and posits that this is already occurring, and that this may leave most people with
    worse jobs than the ones they currently have.
    As a result, she suggests a number of possible strategies to prevent the “deleterious effects of current
    innovation”, which she also calls “human disenhancement”:
  5. The establishment of “ethics committees” to protect the immediate and long-term interests of
    people whose jobs are under threat from automation. She acknowledges, however, that for
    this to be effective, it would need to be adopted globally (since unilateral adoption by any
    country would disadvantage it due to competitive handicap), and that therefore this is unlikely
    to succeed.
  6. The establishment of “non-conditional welfare systems”, that is, payment of a minimum wage
    or basic income to all citizens, since it would mean that people are less incentivised to take
    undesirable jobs, and that therefore organisations are more likely to use automation to replace
    these undesirable jobs rather than jobs that humans prefer.
  7. Direct investment by governments in automation technology that would replace humans in the
    least desirable jobs, leaving the more preferable jobs for humans to take.
  8. Advancements in education that significantly raise the skill-base of the median citizen, so that
    their skills are complementary to Artificial Intelligences rather than in competition with them.
    This will also lead to downward pressure on wages for these workers since they will be in
    greater supply, leading to a reduction in the motivation for employers to replace them with
    automation.
  9. More controversially, she suggests that “biomedical enhancement” (genetic, pharmacological
    or public health “upgrading” of the intelligence of the populace) may become a necessity in
    order to compete with job-displacing automation technologies on a more equal footing.
    On the other hand, Kaplan (2015) suggests that a key part of the solution is to replace our current
    sequential system of “education, then work”, with a new type of financial instrument, the “job
    mortgage”. This is an intriguing idea that we contend is a more practical approach than those
    suggested by Loi (2015). The central idea is that employers would issue nonbinding “letters of intent”
    to employ you if you acquire specific skills that the employer needs, with payroll tax breaks if they
    follow through on the deal. As Kaplan puts it, “These letters of intent will serve the same purpose for
    job mortgage lenders as an appraisal serves for a home mortgage lender” (Kaplan 2015, p14).
    Training providers, including schools and universities, are therefore incentivised to collaborate with
    employers to provide training for these skills, in order to attract students. A worker is free to accept a
    better offer if one is made before employment, as the letter of intent is not binding on them either, but
    knows that the skills being acquired are valued. Thus, the free market enforces the necessary
    discipline to bring together the needs of employers, the knowledge and skills training offered by
    Page 32 of 39
    Artificial Intelligence and the Ethical Implications of Automation on Employment
    training providers, and the workers who seek both. We propose that this approach is both easier to
    implement and more likely to succeed than those presented by Loi.
    How should Information Technology professionals respond to the ethical challenges posed by the
    effects of automation on employment? Would it be morally defensible to call for IT professionals to
    “voluntarily refrain from making progress in software creation” (Loi 2015), in order to avoid negative
    future social outcomes? We suggest that this is not reasonable, on the basis that:
  10. IT professionals are just one of many enablers of automation, and that ultimately it is an
    economic imperative driven by senior management;
  11. It would be unreasonable to ask or require IT professionals to forego the practice of their
    ethically-neutral professional skills and thereby potentially forego salaries and livelihood;
  12. The many and varied benefits of automation to society would also be foregone if IT
    professionals are not able to apply their skills in this way;
  13. Unemployment stemming from automation is a systemic problem, and therefore requires a
    systemic, not an individualistic, solution.
    Other ethical considerations for IT professionals to ponder, as they consider their role in AI-based
    automation that leads to job losses, have already been covered in the Ethical Issues section.
    While the best solution to the problem of automation-led unemployment is unclear, it is clear that, in
    order for humanity’s interests to prevail, careful risk management needs to be undertaken.
    Page 33 of 39
    Artificial Intelligence and the Ethical Implications of Automation on Employment
    Conclusion
    This report discussed Artificial Intelligence in the context of the automation of employment. A
    number of ethical issues are raised as a result of automating jobs via the use of Artificial Intelligence.
    While the automation of work is not a new concept (think of the industrial revolution), the concept of
    Artificial Intelligence, which automates human-like cognitive abilities (and in many cases exceeds
    human ability) is entirely new.
    Artificial Intelligence has reached into a wide range of industries, however one industry which we
    have considered in more detail was the auto industry, which is currently testing self-driving
    technology. It’s from this perspective that we have illustrated the disruption that Artificial Intelligence
    could cause this industry, which then made it possible to examine a variety of perspectives in relation
    to the ethical implications of automation on employment through the rest of the report.
    While a number of legal, social and other issues slow the development of the technology, the effect of
    automating a skill which is connected to human employment (such as careers involving driving) has
    very real consequences. Such automation poses the threat of inequality, influences the distribution of
    jobs, challenges the ability for labour law to protect workers, creates social consequences as a result of
    high unemployment, is responded to differently by different cultures, and forces companies to remain
    technologically relevant and competitive.
    This report has examined a variety of perspectives and ethical challenges for a future in which
    Artificial Intelligence is able to perform many new tasks that were previously performed exclusively
    by humans.
    A key issue, which the report has repeatedly highlighted, is the potential consequences and ethical
    risks that exist as a result of automating jobs with Artificial Intelligence. While we have provided
    some suggestions as to how to mitigate these risks, our discussion points to the urgent need for further
    investigation into the ethical implications of automation on employment, and especially, of the steps
    that need to be taken in order to ethically transition into a new age of Artificial-Intelligence-enabled
    technology.
    Page 34 of 39
    Artificial Intelligence and the Ethical Implications of Automation on Employment
    Reference List
    Altman, R.B., 2017. Artificial intelligence (AI) systems for interpreting complex medical
    datasets. Clinical Pharmacology & Therapeutics , 101 (5), pp.585-586.
    Amazon.com 2017, Amazon Prime Air , viewed 27 September, 2017 2017,
    < https://www.amazon.com/Amazon-Prime-Air/b?node=8037720011 >.
    Bianca, A. 2017, How Does a Company Stay Competitive? , viewed 8 October 2017,
    < http://smallbusiness.chron.com/company-stay-competitive-78219.html >.
    Blincoe, L.J., Miller, T.R., Zaloshnja, E. & Lawrence, B.A. 2010, The Economic and Societal Impact
    of Motor Vehicle Crashes , viewed 10 September 2017,
    < https://www.nhtsa.gov/sites/nhtsa.dot.gov/files/2015sae-blincoe-costs_of_crashes2010.pdf >.
    Borenstein, J., Herkert, J. & Miller, K. 2017, ‘Self-Driving Cars: Ethical Responsibilities of Design
    Engineers’, IEEE Technology & Society Magazine , vol. 36, no. 2, pp. 67-75.
    Cameron, P. 2017, Automated Operations: 5 Benefits of Automation , Help Systems, viewed 6 October
    2017,
    < https://www.helpsystems.com/resources/guides/automated-operations-5-benefits-your-organization >
    .
    Conitzer, V., Sinnott-Armstrong, W., Borg, J.S., Deng, Y. and Kramer, M., 2017. Moral Decision
    Making Frameworks for Artificial Intelligence. In AAAI (pp. 4831-4835).
    Davids, M. 2017, 3 Challenges Manufacturers Face When Implementing Robotics , viewed 8 October
    2017, < https://blog.robotiq.com/3-challenges-manufacturers-face-when-implementing-robotics >.
    Dubie, D. 2004, ‘Automation can create job loss: analysts’, ComputerWorld Canada , vol. 20, no. 12,
    p. 32.
    Engineering.com 2017, How Robotic Automation Will Benefit Agriculture 2017 , viewed 8 October
    2017,
    < http://www.engineering.com/AdvancedManufacturing/ArticleID/14816/How-Robotic–Will-Benefit- Food-and-Agriculture.aspx >.
    Fair Work Ombudsmen 2017, Redundancy – Fair Work Ombudsmen, viewed 3 September 2017,
    < https://www.fairwork.gov.au/ending-employment/redundancy >
    Gownder, J.P. 2017, ‘Why CIOs should care about robots stealing jobs’, CIO .
    Green, L. 1996, ‘The Concept of Law Revisited’, Michigan Law Review , vol. 94, no. 6, pp.
    1687–1717.
    Page 35 of 39
    Artificial Intelligence and the Ethical Implications of Automation on Employment
    Grosz, B.J. 2017, ‘Utterance and objective: Issues in natural language communication’, AI
    Magazine , 1 (1), p.11.
    Hassler, S. 2017, ‘Self-driving cars and trucks are on the move [Spectral Lines]’, IEEE Spectrum , vol.
    54, no. 1, pp. 6-.
    Hofstede, G. 2011, ‘Dimensionalizing Cultures: The Hofstede Model in Context’, Online Readings in
    Psychology and Culture , vol. 2(1).
    Howe, J. 2011, ‘The Broad Idea of Labour Law: Industrial Policy, Labour Market Regulation and
    Decent Work’ in Davidov, G. Langulle, B [ed], The Idea of Labour Law , Oxford University Press,
    New York, pp. 295-313.
    Husic, E. & Priddis, M. 2017, Australia unprepared for automation of its workforce , Australian
    Financial Review, 31 July 2017, viewed 8 October 2017,
    < http://www.afr.com/technology/australia-unprepared-for-automation-of-its-workforce-20170730-gxl wj5 >.
    Hutter, M. 2017, ‘Introduction to Artificial Intelligence’, Viewed 6 October 2017,
    < http://www.hutter1.net/ai/ >
    Information Services Group, Inc.; ISG: RPA 2017, ‘Increasing Productivity, Not Job Losses’, Journal
    of Engineering , 15 May 2017, p. 295.
    Kaplan, J. 2015, Humans need not apply : a guide to wealth and work in the age of Artificial
    Intelligence , Yale University Press, New Haven.
    Lavenda, D. 2017, How machine learning influences your productivity , VentureBeat,
    < https://venturebeat.com/2017/05/07/how-machine-learning-influences-your-productivity/ >.
    Loi, M. 2015, ‘Technological unemployment and human disenhancement’, Ethics and Information
    Technology , vol. 17, no. 3, pp. 201-10.
    Loughran, M. 2011, WellPoint and IBM announce agreement to put Watson to work in health care ,
    IBM Media Relations, 12 September 2011, viewed 30 September 2017,
    < http://www-03.ibm.com/press/us/en/pressrelease/35402.wss >
    Lu, H., Li, Y., Chen, M., Kim, H. & Serikawa, S. 2017, ‘Brain Intelligence: Go beyond Artificial
    Intelligence’, Mobile Networks and Applications .
    MacCrory, F. Westerman, G. Alhammadi, Y. and Brynjolfsson, E. 2014. ‘Racing with and against the
    machine: changes in occupational skill composition in an era of rapid technological advance’, Thirty
    Fifth International Conference on Information Systems, Auckland.
    Mahdawi & Chalabi 2017, What jobs will be around in 20 years? , The Guardian, viewed 6 October
    2017,< https://www.theguardian.com/us-news/2017/jun/26/jobs-future-automation-robots-skills-creati ve-health >
    Page 36 of 39
    Artificial Intelligence and the Ethical Implications of Automation on Employment
    Makadia, M. 2017, Why is it Difficult for Businesses to Adopt Artificial Intelligence? , viewed 8
    October 2017,
    < http://www.business2community.com/tech-gadgets/difficult-businesses-adopt-artificial-intelligence- 01787000 >.
    MarketingDonut.com 2017, Ten ways to keep ahead of the competition , viewed 8 October 2017,
    < http://www.marketingdonut.co.uk/marketing-strategy/ten-ways-to-keep-ahead-of-the-competition >.
    Markoff, J. 2016, ‘Protecting Humans and Jobs From Robots Is 5 Tech Giants’ Goal’, New York
    Times , 2016 Sep 29.
    Menadue, J. 2015, Why are the Nordics so successful? Part 2 , Pearls and Irritations, weblog, 18
    January 2015, viewed 23 September 2017,
    < https://johnmenadue.com/john-menadue-why-are-the-nordics-so-successful-part-2/ >.
    McGinnis, J.O. and Pearce, R.G., 2013. ‘The great disruption: How machine intelligence will transform
    the role of lawyers in the delivery of legal services’ Fordham Law Review , vol. 82, pp. 3041-3066.
    Miller, C 2017, The Relentless Pace of Automation , MIT Technology Review, 120, 2, pp. 92-95,
    Environment Complete, viewed 6 October 2017 ,
    < https://www.technologyreview.com/s/603465/the-relentless-pace-of-automation >
    Mitchell, R., Gahan, P., Stewart, A., Cooney, S. and Marshall, S., 2010, ‘The evolution of labour law in
    Australia: Measuring the change’ Australian Journal of Labour Law , vol. 23 no. 2, pp.61-93.
    Oxford Living Dictionaries 2017, Definition of Artificial Intelligence in English , Oxford Dictionaries,
    viewed 30 September 2017, < https://en.oxforddictionaries.com/definition/artificial_intelligence >.
    Peters, G. 2017, How Artificial Intelligence Helps B2B Companies Succeed in Competitive Markets ,
    viewed 8 October 2017,
    < http://resources.zilliant.com/blog/how-artificial-intelligence-helps-b2b-companies-succeed-in-compe titive-markets >.
    Rosu, D., Aleman, D.M., Beck, J.C., Chignell, M., Consens, M.P., Fox, M.S., Grüninger, M., Liu, C.,
    Ru, Y. and Sanner, S., 2017. Knowledge-Based Provision of Goods and Services for People with
    Social Needs: Towards a Virtual Marketplace.
    Rotman, D. 2017, The Relentless Pace of Automation , MIT Technology Review, 120, 2, pp. 92-95,
    Environment Complete, viewed 6 October 2017 ,
    < https://www.technologyreview.com/s/603465/the-relentless-pace-of-automation >
    Spector, M., Kituse J.I. 2017. Constructing social problems . Routledge.
    Spieser, K., Treleaven, K.B., Zhang, R., Frazzoli, E., Morton, D. & Pavone, M. 2014, Toward a
    Systematic Approach to the Design and Evaluation of Automated Mobility-on-Demand Systems: A
    Case Study in Singapore , Springer, viewed 10 September 2017,
    < http://dspace.mit.edu/handle/1721.1/82904 >.
    Page 37 of 39
    Artificial Intelligence and the Ethical Implications of Automation on Employment
    Templeton, B. 2017, The Numbers , Robocars, weblog, viewed 10 September 2017,
    < http://www.templetons.com/brad/robocars/numbers.html >.
    The Economist 2017, Northern lights , viewed 23 September 2017,
    < https://www.economist.com/news/special-report/21570840-nordic-countries-are-reinventing-their-m odel-capitalism-says-adrian >.
    Tripathi, S.K. 2017, How Machine Learning Algorithms Improve Business Efficiency , viewed 6
    October 2017,
    < https://www.kelltontech.com/kellton-tech-blog/how-increase-business-efficiency-machine-learning >
    Weller, C. 2017, ‘Elon Musk doubles down on universal basic income: ‘It’s going to be necessary’’,
    Business Insider .
    Vardi, M.Y. 2017, What the Industrial Revolution really tells us about the future of automation and
    work , TheConversation.com, viewed 8 October 2017,
    < http://theconversation.com/what-the-industrial-revolution-really-tells-us-about-the-future-of-automat ion-and-work-82051 >.
    Waymo 2017, Waymo early rider program, viewed 11 September 2017
    < https://storage.googleapis.com/sdc-prod/v1/press/Waymo_One-Pager_EarlyRider.pdf >
    Wellers, D., Elliott, T. & Noga, M. 2017, 8 Ways Machine Learning Is Improving Companies , Work
    Processes, HBR.org, viewed 6 October 2017,
    < https://hbr.org/2017/05/8-ways-machine-learning-is-improving-companies-work-processes >.
    West, D.M. 2015, ‘What happens if robots take the jobs? The impact of emerging technologies on
    employment and public policy’, Governance Studies , Washington, DC.
    Zhou, A. 2017, Banks Eager For Artificial Intelligence, But Slow To Adopt , Forbes.com, viewed 8 October
    2017,
    < https://www.forbes.com/sites/adelynzhou/2017/05/29/financial-services-industry-banks-artificial-intellige nce-slow-adoption/ >.
    Page 38 of 39

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