Machines and Ethics: Evaluating the Impact of AI and Robotics

This report provides an evaluation of several articles concerning the ethical and social impacts of artificial intelligence (AI) and robotics. It summarizes key findings from articles discussing the social impact of robot co-workers in industrial settings, ethics in robotics related to machine learning, the in...Read More

Running head: MACHINES AND ETHICS
MACHINES AND ETHICS
Name of the Student
Name of the University
Author note

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Introduction:
Technology has already changed the worlds face to a huge extent. It plays a major
role in the day to day life of the normal human beings. This advancements in the technology
have become of the most used thing for making the lives of the human beings a lot easier.
Artificial Intelligence and the use of the robots are the two examples of the same (Xu et al.
2015). The ability of the machines to learn new things without the help of the human beings
is known as the AI. The mixture of the AI and the robots have helped the people to do task
that were once near to impossible for the humans. The purpose of this report is to evaluate
few articles.
Summary of the Social Impact of a Robot Co-Worker in Industrial Settings:
This article focuses about the one of the major phenomenon of the recent generation
that is robots working alongside workers for making the products more precise (Shukla,
Khare and Deo 2015). This paper also focus on three different sites where the robots works
with the human foe producing the better results. While robots have long been anticipated as
global assistants that work in day-to-day human atmospheres, the prime use of robotic
technologies have been in manufacturing works and field settings for automating monotonous
work or performing tasks that are difficult to get to or dangerous for humans (Zhou et al.
2013). In order to better understand how the collaborative robots are effecting the work and
insights of manufacturing employees, the authors conducted an ethnographic study at three
industrial plants that had picked up a particular robotic platform which is a much important
tactic to understand the relationships
Summary of Ethics and Robotics:
This paper is basically about the ethics related to robotics and how the machine
learning performances are related to the ethical impact in the society. Advances in

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information technologies have given rise to many technical improvements that have paved
the way for the spread of robots in today's world. The authors brought to notice the history of
the machine learning pros and cons. This can be explained as of the area which is much
needed in the paper for highlighting the factors that were held in the past. The author brought
to light the issues of the present day machine learning objectives (Mohri, Rostamizadeh and
Talwalkar 2012).
Summary of Social Robots' Impact on Human Judgment:
The social are gaining influence day by day in many of the sectors of the industry due
to their high potential of the social good such as the healthcare and the engineering (Kanda
and Ishiguro 2016). But the problem in this are bearing the high responsibility and the
profound understanding the degree of the sociological responsibity. In compare to robots in
the environment of industry, social robots are specially designed to co-operate with humans,
transportation, healthcare, and retail, housework.
Summary of the Smart Machines Are Not a Threat to Humanity:
There are huge concerns for the factor that the smart machines are a huge threats to
the human beings. One of the major thing is that the machines are taking away the jobs of the
human beings (Mohri, Rostamizadeh and Talwalkar 2012). According to Stephen Hawking is
quoted in Cellan-Jones1 as saying: “The development of full artificial intelligence could spell
the end of the human race.” Also amazon Founder Jeff Bezos expressed something similar to
this. But such concerns are part if the long history as new researches explains that the AI will
make the life of normal human beings easier and comfortable.
Evaluation:

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Evaluation of Social Impact of a Robot Co-Worker in Industrial Settings:
In the table below, social impact of the robots, the industrial settings the resource is an
authenticated source for understanding the concept of the industrial analysis (Lee et al. 2012).
The article is not freely available and the users have to buy the same in order to get
information about the topic. The researchers are very famous in their respective field making
the more accurate. The robotic platform that the authors chose was the Baxter robot,
developed and manufactured by Rethink Robotics (Singh and Chandra 2014). In order to get
the best results the author conducted different method of analysing which included the study
of the working of the robots and that is fly on the wall observations and interviews of the
management staffs, workers and the maintenance staffs. The finding that came up were huge
(Kanda and Ishiguro, 2016).
Evaluation of Ethics and Robotics:
The table below provides with the information about the research, the analysis done in
this report is one of the best that can be done in the similar papers. The paper is a paid paper
and cannot be accessed by everyone. Making the value of the paper higher. The paper also
highlighted the applications and the advantages of the machine learning concepts, variety of
the fields and how they can be used for the betterment of the day to day work. One of the
major analysis that the author highlighted in the paper is the information and the system
security application (Xu et al. 2015).
Evaluation of the Smart Machines Are Not a Threat to Humanity:
This paper is one of the freely available paper in the Google scholar. People who are
willing to study the concept of the AI and the future of the AI can related to this paper. Some
of the serious claims that are made by the paper are true. AS claimed by the author AI

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systems are, of course, by no means unique in having bugs or limited expertise (Genc, Dag
and Ardiclioglu 2015). Any computer system deployed in a safety or security critical
situation potentially poses a threat to health, privacy, finance, and other realms. Some of the
threats are also mentioned in the paper making it one of the best paper available in the market
for getting proper information. Also there are enough evidences for the claims that are made
in the paper.
Evaluation table
Criteria Social Robots'
Impact on
Human
Judgment
Social Impact of a Robot Ethics and
Robotics
Smart
Machines Are
Not a Threat to
Humanity
Reliability Allison
Sauppe and
Bilge Mutlu
Daniel Ullrich LMU
Munich
[e-mail]
Andreas Butz LMU
Munich
[e-mail]
Sarah Diefenbach LMU
Munich
sarah.diefenbach@lmu.d
e
Sarah
Bouazzaouri*
Megan A.
Witherow
Kaitlynn M.
Castelle
Alan Bundy

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Relevance Yes ,
authenticated
Yes , authenticated Yes ,
authenticated
Yes ,
authenticated
Accuracy yes,
highly
accurate –
accurate
sources
-data and
references - no
error
yes,
highly accurate
- accurate sources
- no error
yes,
highly accurate
-accurate
- data and
references
- no error
yes,
highly
accurate -
accurate
sources
- data and
references
- no error
Lack of Bias Lack of bias Potential bias Highly biased Not biased
Completeness Completed Completed Completed Partial
Up to date Published -
2014
Published - 2018 Published -
2015
Published -
2012
Conclusion:
Thus concluding the topic it can be said that the articles are some of the best articles
that are available in the market and the users can relate to this articles. This reports not only

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gives proper information about the topics but also provides with enough evidences for the
claims that are made.

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References:
Genc, O., Dag, A., and Ardiclioglu, M., 2015. A novel study for the modeling of monthly
evaporation using k-nearest neighbor algorithms for a semi-arid continental climate. 2015
IEEE 14th International Conference on Machine Learning and Applications, 341-346.
doi:10.1109/ICMLA.2015.74.
Kanda, T. and Ishiguro, H., 2016. Human-robot interaction in social robotics. CRC Press.
Lee, M. K., Kiesler, S., Forlizzi, J., and Rybski, P. Ripple effects of an embedded social
agent: A field study of a social robot in the workplace. In Proc. CHI ’12 (2012), 695–704.
Mohri, M., Rostamizadeh, A., and Talwalkar, A. 2012. Foundations of Machine Learning.
Cambridge, MA: The MIT Press.
Shukla, R., Khare, D., and Deo, R., 2015. Statistical Downscaling of Climate Change
Scenarios of Rainfall and Temperature over Indira Sagar Canal Command area in Madhya
Pradesh, India. 2015 IEEE 14th International Conference on Machine Learning and
Applications, 313-317. doi:10.1109/ICMLA.2015.75
Singh, N., and Chandra, N., 2014. Integrating Machine Learning Techniques to Constitute a
Hybrid Security System. 2014 Fourth International Conference on Communication Systems
and Network Technologies, 1082-1087. doi:10.1109/CSNT.2014.221
Xu, K., Yue, H., Guo, L., Guo, Y., and Fang, Y. 2015. Privacy-preserving Machine Learning
Algorithms for Big Data Systems. 2015 IEEE 35th International Conference on Distributed
Computing Systems, 318-327. doi:10.1109/ICDCS.2015.40
Zhou, J., Huang, W., Xiong, W., Chen, W., and Venkatesh, K., 2013. Segmentation of
Hepatic Tumor from Abdominal CT Data Using an Improved Support Vector Machine

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Framework. 2013 35th Annual International Conference of the IEEE Engineering in
Medicine and Biology Society, 3347-3350. doi:10.1109/EMBC.2013.6610258