1. Can we morally justify the replacement
of humans by artificial intelligence in
cancer treatment?
Keywords: ​Artificial Intelligence, Machine learning, Future of Humanity, Transhumanists,
Bioconservatives, IBM Watson Oncology, Oncology
Info:​ Kai Bennink (4520491)
Study: ​MSc. Management of Technology student at TU Delft

2. 1. Introduction
In our current world, technology is growing with an intense pace. The internet connects not only
your computer but also the rest of your electronic devices. Gartner has predicted that there will
be over 20 billion electronic devices connected to the internet within four years. These devices
will all be generating and sharing data with insane rates. The accessibility of these enormous
amounts of data really drives the need to develop computational power that can detect new and
insightful patterns of behavior. These insights are fueled by a concept called: ‘Machine learning’
which is a quickly developing area of expertise in the field of artificial intelligence. With artificial
intelligence (AI) we mean a ​developing system that enables computers to display behavior that
at least resembles the cognitive abilities of humans. ​According to Shalev-Shwartz & Ben-David
(2014) the term ‘machine learning’ refers to the automated detection of meaningful patterns in
data. According to them we are surrounded by machine learning technologies. For example,
search engines learn how to bring us the best results (while placing profitable ads), anti-spam
software learns to filter our email messages, and credit card transactions are secured by a
software that learns how to detect frauds. Digital cameras learn to detect faces and intelligent
personal assistance applications on smart-phones learn to recognize voice commands. Cars
are equipped with accident prevention systems that are built using machine learning algorithms.
Currently there are a few ‘blue-chip’ companies that invest significant effort in the
development of artificial intelligence systems that enable them to use machine learning
algorithms to improve people’s welfare and wellbeing. To name a few companies that are
operating in the front line: Facebook, Amazon, Google, Apple, Tesla, Microsoft, IBM, Boeing,
etc. However, most of these companies apply artificial intelligence and machine learning in a
relatively simple context. This means in an environment where they need relatively low level
cognitive capabilities to perform their tasks. Nevertheless, AI and machine learning are also
being used in the more high-level thinking layers of our society. For example, in scientific
applications such as bioinformatics, medicine, and astronomy (Shalev-Shwartz & Ben-David,
2014). Artificial intelligence is becoming increasingly advanced and soon will not only replace us
in factories, with simple and repetitive manufacturing processes, but also in more advanced
scenarios that requires high-level thinking in areas such as science, law and medics. It does not
matter what you think; when or where artificial intelligence will transcend humans in their
performance, the quick and advancing capabilities of AI are empowering optimism and
investment opportunities in AI research (Jordan & Mitchell, 2015).
In this paper we want to analyse to what moral extent humans can be replaced by AI in a
medical assessment process like cancer treatment. We will perform our research by describing
and assessing the real-life case of IBM Watson Oncology. To give a quick idea of how rapidly
this platform is adapted: ​According to IBM Watson's former business chief Manoj Saxena, 90%
of nurses in the field who use Watson now follow its guidance (Upbin, 2013). ​IBM Watson
Oncology is a new platform that enables doctors with a set of AI and machine learning tools to
optimize their current treatment processes. To scope our research we will approach the IBM
case by assessing it from different philosophical viewpoints to create a clear image of the
current moral landscape and identify potential moral implications. The research question we will

3. try to answer in this paper is formulated as following: ​“Can we morally justify the replacement of
humans by artificial intelligence in cancer treatment?”
2. Theory
2.1 Definition of Artificial Intelligence
Different scientific and philosophical areas such as neuroscience, psychology and the
philosophy of mind, all are unsuccessful in defining what “intelligence” and “thinking” really is.
Their definitions are vague and generally applied to machines. A common definition of AI ​is the
subfield of Computer Science devoted to developing programs that enable computers to display
behavior that can (broadly) be characterized as intelligent ​(Russell & Norvig, 2010).
However, there is a definition that can be measured and tested, according to Dobrov
(2005): ​“Artificial Intelligence will be such a program, which in arbitrary world will cope not worse
than a human”. In this paper we will see the definition of AI as a derivation of Turing’s test and
use the term AI and ‘Artificial Intelligence’ based on Turing’s theory.
When we go deeper into the underlying features and functionalities of AI we see that,
according to O’brien (1999), there are three distinct areas of expertise: cognitive science,
robotics and natural interface applications (see figure 1). Since the objective of this paper is to
assess the possibility to replace humans in the process of cancer treatment, we will be
discussing the applications of cognitive science and robotics. These AI functionalities are the
salient drivers of today’s oncology decision-making processes and activities.
Figure 1

4. 2.2 Bioconservatives versus Transhumanists
To develop and visualize a moral landscape regarding the relationship between technology and
humanity, we will describe two extreme philosophical viewpoints that provide a spectrum or
point of reference for our case analysis. In this spectrum we highlight the transhumanists and
the bioethical bioconservatives.
First of all, what are transhumanists exactly? According to Nick Bostrom (2005), an
Oxford professor and director of the Future of Humanity Institute, transhumanists argue that
human enhancement technologies should be made widely available to all individuals. In his view
he stipulates that people should have a broad discretion over which of these technologies will
apply to them and that parents have the right to influence the way their future offsprings will
become.
On the other side we have the stream of bioconservatives (BC) that are opposing the
viewpoint of transhumanists. Biopolitical Conservatives distrust biotechnologies and wish to
implement strong restrictions to their use and even to their development. Sometimes, but not
always, this attitude is tied to a stance of defiance towards technology in general (Goffi, 2013).
Know writers of the bioconservative stream are: Leon Kass, Francis Fukuyama, George Annas,
Wesley Smith, Michael Sandel, and Bill McKibben. According to Bostrom (2005) they are
generally opposed to the use of technology to modify human nature. A central idea in
bioconservativism is that human enhancement technologies will undermine our human dignity.
However these two extremes may be described too briefly and may be missing
significant nuances, the distinct characterization is salient and will be used as a point of
reverence for our analysis. The two streams resemble an underlying problem that generates an
interesting question, namely, how should we look at the future of technology and humanity, and
how can we guide this disruptive technological movement in way that morally justifies its
presence?
3. Case description
3.1 Current oncology diagnosis and treatment
We chose to analyze the case of cancer treatment because this is a very large field of expertise
that is highly diverse and increasingly investigated by public institutions to test high-tech
solutions. Treatment of cancer highly depends on the physician’s expert opinion and the
diagnosed tumour or metastasis. According to the American Society for Clinical Oncology
(2016) there are currently over 70 different tumour types. This also means that there is not one
size fits all treatment to cure cancer. The alternatives include surgery, radiation therapy,
chemotherapy, hormone therapy, immunotherapy, targeted treatments and more highly
specialized therapies (Cancer.net, 2016). Sometimes it even requires a combination of
therapies to increase its effectiveness. Nowadays it’s becoming increasingly common to invite a
team of experts that provide the best combination of therapies to optimize the chance of
success. Each therapie has both effects that have advantages and disadvantages and highly
depends on the patient's current age and physical strength. When a diagnosis is set it is very

5. common, and maybe even recommended, to ask other physicians for a second opinion. From a
technology point of view this last sentence generates a very interesting question, namely, to
what extent can we use intelligent technologies to improve the accuracy and reliability of a
physician's diagnosis?
3.2 Description of IBM Watson oncology
Since 2009 IBM, a high-tech cloud computing company, is putting a lot of financial effort in their
new AI platform called: IBM Watson. This platform offers developers and scientist to make use
of the latest AI and machine learning tools. IBM has opened this platform up for developers to
work on creating and improving their software. For example, some tools that IBM Watson is
currently offering are: Natural language processors that process conversations, dialogs,
translations, natural language classifiers, personality insights and conversation tones. Speech to
text and text to speech processors. Visual recognition processors and other unstructured data
analytics (ibm.com/watson, 2016).
With all these high-tech tools, IBM now expands its horizon and seeks for new areas to
apply their Watson’s power. As a result they have recently launched IBM Watson Oncology,
which is a specific cognitive computing decision support system that includes the ability to
analyze patient data against thousands of historical cases and insights gleaned from working
thousands of hours with Memorial Sloan Kettering Cancer Center physicians and other analysts.
Secondly, it can provide treatment options to help oncology clinicians make informed
decisions. These treatment options are supported by literature curated by Memorial Sloan
Kettering, and over 300 medical journals and 200 textbooks, resulting in almost 15 million pages
of text (IBM, 2015). According to Dr. James Miser, Bumrungrad’s Chief Medical Information
Officer, it will be like having a capable and knowledgeable ‘colleague’ who can review the
current information that relates to my patient. It is fast, thorough, and has the uncanny ability to
understand how the available evidence applies to the unique individual I am treating
(ibm.com/watson, 2016).
4. Case analysis
4.1 Human responsibilities in applying Artificial Intelligence and Machine Learning
The results of IBM Watson are clear and impose a drastic improvement when it comes to
diagnosing cancer types. In almost 98% of the cases Watson diagnosed the same cancer type
as the oncologist and it delivers an almost 30% increase of proposing alternative treatment
methods when compared to an average oncologist expert (Lohr, 2016). However, these results
may appear solely as a gift, offering ill people with better and informed treatment, we want to
analyze and describe a range of implications in this chapter.
Just a month ago Zeynep Tufekci, a computer programmer, made a very interesting note
about machine learning and its implications in a TED talk. She thereby used IBM Watson as an
interesting example. According to Tufekci (2016) we are now using computation to make all sort

6. of decisions, but also new kinds of decisions. We are asking questions to computation that have
no single right answers, that are subjective and open-ended and value-laden.
Tufekci (2016) talks about a friend who developed a computational system that predicts
the likelihood of clinical or postpartum depression from social media data. It can predict the a
depression months before the onset of any symptoms. This means the prediction is based on
variables that are not known to us, which is a very interesting and maybe even scary idea.
Tufekci (2016) describes the system as a black box that does not provide information on what
variables the machine intelligence is learning, because this is not based on traditional coding,
where variables are fixed and created by the programmer. The machine intelligence has a
predictive power, but we don’t understand it (Tufekci, 2016). The question we have to ask
ourselves is: to what extent can we rely on machines, that we don’t understand, to take over our
(moral) decision-making?
According to Chiweon Kim (2016) IBM Watson’s improvements are astonishing since its
launched. It turned out that IBM Watson was not only capable of handling clinical situations
based on pre existing research results and guidelines, but also recommend treatment plans for
complex cases published in papers and textbooks. This means that it was able to acquire, learn
and reproduce tacit knowledge through experience with the best experts. Therefore it will
ultimately reach a stage where it can generate medical evidence and guidelines on its own
(Chiweon Kim, 2016). The tricky part of machines like IBM Watson is that we cannot define or
determine on what variables Watson will learn. Meaning, Watson may reach a point in the
future, where it is completely autonomous oncology standard in generating medical evidence
and setting up guidelines for future treatment policies, without us knowing exactly where its
standard is based on. However. How can we reassure that these future policies are in line with
what we really want?
As Tufekci (2016) mentioned in her TED Talk, these systems can be wrong in ways that
don’t resemble human systems. Take for example IBM’s machine-intelligence system that wiped
the floor with human contestants in the quiz show Jeopardy. It was a great player, but then for
Final Jeopardy, Watson was asked the following question: “Its largest airport is named for a
World War II hero, its second-largest for a World War II battle”. The answer was: Chicago. The
two humans got it right. Watson, on the other hand, answered “Toronto” -- for a US city
category! The impressive system made an error that a human would never make, even better, a
second-grader wouldn’t make (Tufekci, 2016). The important part of this anecdote is that our
super intelligent systems can fail in ways we haven’t expected and that do not resemble human
error patterns. IBM Watson, however, claimed to be the world wide health care support system
within the next five years. How can we prepare for errors we have never encountered and don’t
understand, on an worldwide healthcare level?
The problem is if we can’t determine on what variables Watson is learning on, we have
to set up principles that act as guidelines for Watson. These principles will incorporate our
human values to control this super intelligent force. We cannot escape these difficult questions
and outsource our responsibilities to machines (Tufekci, 2016). According to Leon Krass, which
is a known bioconservative, we cannot hide our heads in the sand because we enjoy the
blessings that medicine keeps supplying, or keep rationalizing our inaction by declaring that
human engineering is inevitable and we can do nothing about it (Krass, 2001). However Krass

7. is talking about human modification in his statement, he does make a similar point. We must not
see technology as an inevitable force that cleans up our garbage.
Before we can set up a set of principles that provide guidance to a machine learning
intelligence we must first come to consensus about what we value as humans. In the next part
we will analyze the case through the eyes of both the transhumanist and bioconservative view
to broaden our view on what we should or should not value as humans when it comes to
adapting AI solutions in healthcare.
4.1. Through the eyes of Transhumanists and Bioconservatives
Creating a clear vision of what we value as humans is an endless discussion. Therefore we will
look at this case through the goggles of two extremes in the human-technology spectrum:
transhumanism and a bioconservativism.
Transhumanists view human nature as a work-in-progress, a half-baked beginning that
we can learn to remold in desirable ways. Current humanity need not be the endpoint of
evolution. Transhumanists hope that by responsible use of science, technology, and other
rational means we shall eventually manage to become posthuman, beings with vastly greater
capacities than present human beings have (Bostrom, 1998). A technological solution as IBM
Watson offers many possibilities to enhance human's well being and to eventually aim for a
world without any form of diseases. Rometty, CEO of IBM stated that: ​“Our goal is augmenting
intelligence”. “It is man and machine. This is all about extending your expertise. A teacher. A
doctor. A lawyer. It doesn’t matter what you do. We will extend it”. The statements of IBM’s CEO
clearly describes an augmented form of Watson’s system that is similar to the features of a
cyborg, which is a pro trans humanistic concept. A cyborg deliberately incorporates exogenous
components extending the self-regulatory control function of the organism in order to adapt it to
new environments (Clynes and Kline, 1960). Undoubtedly, the CEO of IBM would not want to
state that Watson is turning humans into cyborgs, thereby giving up their self-regulatory control,
but surely these statements do have a lot of overlap with the transhumanist view; technology to
extend the capabilities of humans, which is in line with the core concepts of the ‘human
enhancement’ view.
Bioconservatives often express a general fear that new technologies will "rob" us of our
humanity. A clear definition of what makes us ‘human’ is often a key point of discussion.
According to Krass (2003) most of the given bestowals of nature have their given
species-specified natures: they are each and all of a given ​sort. Cockroaches and humans are
equally bestowed but differently natured. To turn a man into a cockroach—as we don’t need
Kafka to show us—would be dehumanizing. To try to turn a man into more than a man might be
so as well. We need more than generalized appreciation for nature’s gifts. We need a particular
regard and respect for the special gift that is our own given nature (Krass, 2003). Again Krass is
talking about human enhancement rather than curing humans from diseases in his quote,
however there is a striking resembles in the nature of his statement, regarding the use of
technology in our lives. The question that arises: Is IBM Watson dehumanizing our current
world? In the literal sense, yes, because it’s literally replacing human tasks in the oncology
process. However, according to ​Dr. Ian Hennessey (2016), clinical director of Innovation at

8. Alder Hey Children’s Hospital ​IBM ​Watson can provide a natural language interface for the
delivery of general and patient specific information. This has proven very interesting as children
seem to be more forthcoming in their interaction with Watson than with a doctor or nurse. This
interesting remark of children communicating better with a form of AI can be interpreted in two
ways. Either, a human (child) could be more at ease when communicating to an intelligent
machine (IBM Watson) than too another human (doctor). Or, our current designed intelligent
machines (IBM Watson) have developed themselves in such way that it can optimally
communicate with early stage humans (children). Although both cases could be true, they speak
in favor of the transhumanist view. Humans and technology are increasingly adapted to each
other.
The following question arises: is this a bad thing? Bioconservatives would argue that is
is. According to the bioconservative viewpoint we cannot allow ourselves to be altered or
enhanced by technology in such way that we become dependent of it. Therefore it would be
irresponsible to put our (child's) life completely in the hands of an intelligent system that bases
its actions on a set of black boxed algorithms.
However, when we approach this scenario from the transhumanist viewpoint we see
something completely opposite. It improves the quality of communication between patient (child)
and doctor (IBM Watson), what results in a better diagnosis and eventually a more effective
treatment process overall.​ For transhumanists the essence of our humanity, if there could be
such a thing, is simply our capacity to explore together what it means to be human (Carrico,
2004). Exploring together what it means to be human can loosely be interpreted as searching
for new ways to extend our survival as a species. The transhumanists counter that nature’s gifts
are sometimes poisoned and should not always be accepted. Cancer, malaria, dementia, aging,
starvation, unnecessary suffering, cognitive shortcomings are all among the presents that we
wisely refuse (Bostrom, 2005).
5. Conclusion
This paper analyzed the moral justification of replacing humans by artificial intelligence in the
process of treating cancer. Despite of all the possibilities that intelligent solutions like IBM
Watson offer, there are many concerns. A global anxiety is that super intelligent systems will get
so sophisticated that it will beat humans in performance of high level cognitive tasks and create
an environment in where we no longer can interfere with its control mechanism to determine
what is good and bad. Therefore, we need to think about the use of artificial intelligence in
healthcare and its implications on humanity appropriately.
Currently, artificial intelligence is only used in healthcare to support and optimize day to
day operations. IBM Watson is used as a computational tool that can provide oncology experts
with a set of tools to set a diagnosis and advice on what treatment fits best. It bases its analysis
on a carefully selected set of structured and unstructured data provided by ​Memorial Sloan
Kettering Cancer Center. According to IBM its only task is to support current oncology experts in
the field and provide them with up to date oncological research results. However, according to
Steadman (2013) the project (IBM Watson Oncology) also takes an early step into cognitive
systems by enabling Watson to co-evolve with treatment guidelines, policies and medical best

9. practices. This means that the system has the ability to improve iteratively as payers and
providers use it. In other words, Watson will get better the more it's used, both in working out
how to cure people and how to cure them more cheaply.
The scary thing is that if these intelligent healthcare systems reach a point in where they
become so sophisticated they may create their own medical knowledge and practices, because
they learn much faster than our current oncology experts. This can be dangerous because we
cannot control the variables these systems use to base their knowledge on. A machine values
not the same as humans do, which can cause outputs that do not resemble human values at all.
Secondly, we train our oncology experts to increasingly rely on these all-knowing intelligent
systems, which means that critical judgement by oncology experts regarding IBM Watson’s
diagnosis or treatment proposal is slowly degrading over time. Thirdly, we cannot disregard the
effects of social pressure that is put on oncology expert’s choices, to deny the proposal of an
all-knowing intelligent system like IBM Watson.
As a result we must think of a worldwide standard of rules and principles to govern the
indirect power of artificial intelligence in healthcare. The AI systems of today, like IBM Watson ,
have not reached the earlier described level of cognitive sophistication yet, but healthcare
institutions are currently using it to treat real humans. If we want to control an intelligent power
of the future, we must build its cage today, before it is too late. By creating ethical standards that
are based on our human values, we can control its advancement and provide AI with a moral
compass to safely and responsibly replace humans in the treatment of cancer.
6. Discussion
To further assess what values should be incorporated into the brain of future AI we must
perform research to identify our basic human values and discuss to what extent we allow
intelligent machines to grow their cognitive capabilities. Opposing philosophical views like
transhumanists and bioconvervatives provide guidance in what is morally correct when it comes
to the relationship between technology and humanity. An interesting research question that
complements, and at the same time turns the perspective of this paper, would be: To what
extent can we morally justify to ​disregard the use of artificial intelligence in our healthcare
activities?

10. 7.Sources
Bostrom, N. (1998). ​Transhumanist Values. Retrieved on 2-11-2016 from:
http://eclass.uoa.gr/modules/document/file.php/PPP566/Bostrom%20-%20Transhumanist%20V
alues.pdf
Bostrom, N. (2005). ​In defense of posthuman dignity. Retrieved on 31-10-2016 from:
https://ethicslab.georgetown.edu/phil145/wordpress/wp-content/uploads/2015/06/Bostrom_Post
human-dignity.pdf
Dobrev, D. 2004. ​A definition of artificial intelligence. Institute of Mathematics and Informatics.
Dobrov, D. (2005). ​Formal definition of AI. International Journal "Information Theories &
Applications", vol.12, Number 3, 2005, pp.277-285
Carrico, D. (2004). ​The trouble with “Transhumanism”: part two. Retrieved on 4-11-2016 from:
http://ieet.org/index.php/IEET/more/carrico20041222/
Chiweon, K. (2016). ​How much has IBM’s Watson improved in 2015. Health plus Digital Blog.
Retrieved at 5-11-2016.
http://healthplusdigital.chiweon.com/how-much-has-ibms-watson-improved-abstracts-at-2015-as
co/
Goffi. (2013). ​Transhumanism & Bioconservatives. Transhumanism & Bioconservatives.
Retrieved on 2-11-2016 from:
http://philosophie.ens.fr/IMG/GOFFI%20JEUD%20HPS%20ENS%20ULM%20S2%202012%20
2013.pdf
Harris, S. (2010). ​"The Moral Landscape: How Science Can Determine Human Values". (Free
Press)
IBM Corporate website. Retrieved at 2-11-2016: http://www.ibm.com/watson/health/oncology/
IBM Watson Oncology report Retrieved at 4-11-2016 from:
https://www.ibm.com/watson/developercloud/services-catalog.html
IBM United States Software Announcement 215-224, dated June 23, 2015. Retrieved at
4-11-2016 from:
http://www-01.ibm.com/common/ssi/rep_ca/4/897/ENUS215-224/ENUS215-224.PDF
Krass, L. (2001). ​Preventing A Brave New World. Published in TNR Online. The New Republic
Online. Ethics and Emerging Technologies​. pp 76-89

11. Krass, L. (2003). ​Ageless Bodies, Happy Souls: Biotechnology and the Pursuit of Perfection.
The New Atlantis 2003; 1.
Lohr, S. (2016). IBM is counting on its bet on Watson, and paying big money for it. Retrieved
from 4-11-2016:
http://www.nytimes.com/2016/10/17/technology/ibm-is-counting-on-its-bet-on-watson-and-payin
g-big-money-for-it.html?_r=2
O’brien, J.A. (1999).​ Introduction to information systems. McGraw-Hill, Inc. New York, NY, USA
1999. ISBN:0072297492.
Ping, W. et. al. (1999). ​A Screening Technique for Prostate Cancer by Hair Chemical Analysis
and Artificial Intelligence. Artificial intelligence in Medicine. Volume 1620 of the series Lecture
Notes in Computer Science pp 372-376.
Russell, S., Norvig, P. 2010, ​Artificial Intelligence: A Modern Approach, Englewood Cliffs, New
Jersey: Prentice Hall, 3 ed., ISBN-10 0136042597.
Shalev-Shwartz, S., Ben-David, S. (2014). ​Understanding Machine Learning: From theory to
Algoritms. Cambridge University Press New York, NY, USA. ISBN:1107057132
9781107057135.
Upbin, B. (2013). ​IBM's Watson Gets Its First Piece Of Business In Healthcare. Forbes
Magazine Blog. Retrieved on 4-11-2016 from:
http://www.forbes.com/sites/bruceupbin/2013/02/08/ibms-watson-gets-its-first-piece-of-business
-in-healthcare/#6a47e7a744b1
Zeynep Tufekci. 2016. ​Machine intelligence makes human morals more important. ​TED Talk.
Retrieved on 5-11-2016 from:
https://www.ted.com/talks/zeynep_tufekci_we_can_t_control_what_our_intelligent_machines_ar
e_learning/transcript