Annotated Bibliography – 3 Additional Sources

Greenfield, D., & Wilson, S. (2019, June 19). Artificial Intelligence in Medicine: Applications, implications, and limitations. Retrieved November 21, 2019, from

This source talks about the current possible applications, as well as the limitations, of artificial intelligence in healthcare and the medical field. It also discusses the implications for the future, which are vast in scope due to the exponential way that technology is advancing each and every day (and advancements build upon themselves). The authors are students at Harvard University, and although they’re students, it’s safe to assume that they are still credible as a source of information since they are studying biology. I chose this source because it talks about current applications of artificial intelligence in healthcare and how artificial intelligence can be used to help surgeons and doctors. The source is relevant as it was written in 2019, which means it reflects new data and research. I found this source by doing a Google Scholar search using the term “artificial intelligence”. This is hosted on the Harvard University blog.

Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., … Wang, Y. (2017). Artificial intelligence in healthcare: past, present and future. Stroke and Vascular Neurology2(4). doi: 10.1136/svn-2017-000101

This source talks about how the use of artificial intelligence in healthcare and medical practices has evolved throughout history. The authors are researchers in several top Chinese universities, so it is safe to assume that they are knowledgeable about the topic. This, therefore, makes the source reliable. I chose this source because there are discussions within the text of the future of artificial intelligence in healthcare, which is a topic that I am particularly interested in delving deep into for my paper. The source is relevant as it was written in 2017, which makes the information rather recent. Additionally, it discusses the past, present, and projected future of artificial intelligence, so the information is not outdated but instead a prediction based on past and present trends. I found this source by doing a Google Scholar search using the term “artificial intelligence”. This is hosted in a journal called Stroke and Vascular Neurology.

Strait, W. J. E. (2019, January 8). Artificial intelligence and the future of medicine. Retrieved November 21, 2019, from

This source talks about how advancements in artificial intelligence and the technology associated with it could lead to many changes to the future of the medical field. The author is a writer at the Washington University in St. Louis, and even though they are a freelance writer first and foremost, their writing mainly revolves around biology and medicine, so I believe that they are still a credible source. I chose this source because it talks about the future artificial intelligence in the medical field and how the scope of medicine can be changed entirely by developments in technology. The source is relevant as it was written in 2018, so it’s recent and most, if not all, of the material shouldn’t be outdated. This is hosted on the Washington University blog.

TradeMark Reflection

I had originally thought that trademark laws were very rigid and that it was illegal to use or download anything without the permission of the original author or without giving them credit/money. However, TradeMark’s presentation challenged my thinking by teaching me that while copyright rules do exist and are quite strict, copyleft rules also exist that allow users the freedom to use and distribute works as they want under the condition that those works, once distributed, offer the same freedoms to other users. This advice helps me in that I now know that while citing sources remains important, using content freely is not always an issue, and that works protected by copyleft laws allow me to use, modify, and distribute them freely as well. Specifically, I am more aware of the legal issues surrounding the use and distribution of online content and media, which I will often need to use as a student. Therefore, I can rest at ease knowing that copyleft laws exist that will allow me to use media for my own academic works both now and in the future.

Example Argument

One of my arguments was that algorithms could make the implementation of medicine and healthcare much easier, but they are still unable to replace actual practitioners. The source Artificial Intelligence in Medicine: Applications, implications, and limitations, written by Greenfield in 2019, supports this argument. The link to this source can be found at

A counter-argument to this could be that with the amount that technology is exponentially advancing, it is hard to predict whether it could improve to the point where it could replace health practitioners. However, it is important to note that it is not this simple, for there are many regulations that also must be addressed, and many ethics issues are things that cannot be programmed but must instead be decided by an expert or professional. For example, ethics issues such as whether to save the mother or the baby during childbirth poses a huge issue and is often up to the discretion of the practitioner based on morals and chances of survival.

Annotated Bibliography – Source 4

Erickson, B. E. (2015, June 29). Editing Of Human Embryo Genes Raises Ethics Questions. Retrieved November 13, 2019, from

This source discusses more about the ethics issues involved with genetic engineering and genome editing, and raises some specific questions surrounding the issues. The author is a member of the American Chemical Society, so they are therefore credible on the topic since I assume they have experience with the chemistry of what goes on in the body, as well as the chemistry behind genome editing. I chose this source because the specific questions it raises against genetic engineering can be used for my counterargument in my paper. The source is relevant as many of the legal concerns are still applicable today. I found this source by doing a Google Scholar search limiting the keywords to words such as “genetic” and “artificial”. This is hosted on Chemical & Engineering News.

Annotated Bibliography – Source 3

Johnson, W. G. (2017, October 26). Where Genome Editing and Artificial Intelligence Collide. Retrieved November 13, 2019, from

The source discusses the ethical and legal issues that come with the development of the artificial intelligence and genetic engineering fields. The author is credible since he has a masters in Science and Technology Policy and is currently pursuing a career in law. This means that they are a knowledgeable source on both the fields of artificial intelligence as well as the ethics issues regarding it. I chose this source because it offers counterarguments to the use of genetic engineering, if uncontrolled. This source is relevant because it was written in recent years and argues about future implications of genetic engineering. I found this source by doing a keyword search using the terms “genetic” and “artificial” in Google Scholar and it is hosted by As We Now Think.

Annotated Bibliography – Source 2

Yeager, A. (2019, May 1). Could AI Make Gene Editing More Accurate? Retrieved November 13, 2019, from

The source states that patterns in sequence repair allow scientists to accurately predict guide RNAs that will reproduce exact human mutations and could lead to the ability to cure or prevent genetic diseases. The author has cited several scholarly sources in their work. I chose this source because it strengthens my argument in that genetic engineering has benefits in pathology that should not be overlooked. This source was written quite recently, and reflects new and updated information in the field. I found this resource through Google Scholar and by inputting keywords such as “genetic” and “artificial” into my search. It is hosted by The Scientist, an online publication.

Annotated Bibliography – Source 1

Dickson, E. M. (1984). Comparing Artificial Intelligence and Genetic Engineering: Commercialization Lessons. AI Magazine5(4), 44–47. Retrieved from

The source states that the movement of artificial intelligence into the mainstream industry instead of just for research purposes is similar to that of the commercialization of genetic engineering. The author is a biological researcher, meaning that he is well-versed in the topics of genetic engineering as well as artificial intelligence. I chose this source because it shows the similarities and differences between the commercialization of genetic engineering and artificial intelligence. This source covers the period of time in which artificial first began to bloom, but still holds relevant today since the comparisons remain generally true. I found this source through Google Scholar by limiting my search query to include keywords such as “genetic” and “artificial, as well as narrowing the date down to the more recent decades to reflect the development of the industry as a whole. This source is hosted by AI Magazine.

Expert Interview Answers

  1. Artificial intelligence is able to perform many jobs in the place of humans now, with even more accuracy than many humans do. This applies especially to low level jobs such as service workers, and even though skilled labor is affected, skilled workers are not impacted as much.
  2. Genetic engineering is being researched right now in labs, and it is projected that soon genetically engineered babies will be able to be made. This is just one step up from Genetically Modified Organisms (GMOs), which already exist. However, this brings up many ethical concerns, which will be discussed later.
  3. As mentioned before, jobs that require a low skill level will be much more heavily impacted by artificial intelligence than jobs that require some sort of skill. This could increase unemployment, but it must also be taken into consideration that there must be people who operate these machines. Therefore, there is no saying what impact artificial intelligence will have on the working population in the long run. It could make things easier, or much harder.
  4. As mentioned before, genetic engineering technically already exists. Genetically modified organisms exist. However, it is much more of an ethical dilemma to genetically engineer a baby as opposed to, say, a plant (that we will end up consuming anyway). Genetic engineering of plants also helps the plant to be better and healthier as it grows, so it provides more nutrition to the consumer. Additionally, sometimes genetic engineering can modify a plant species so that it is less likely to be consumed by predators (for example, insect-resistant potato crops). When it comes to genetically modifying a baby, though, it is hard to determine whether it is really beneficial to the health of the baby. Obviously, if it’s to get rid of a disease, it’s probably a good thing. However, genetic modification could just as easily be used to create babies with different colored eyes or hair, which has little to no correlation with survival, and could be seen as unethical.


Artificial intelligence developed by programmers and medical researchers collectively has largely benefitted the medical field, allowing for medical procedures to be done more efficiently and with less risk.