Artificial Intelligence Ethical Issues

The argument of the author consists of the limitations of the practical model of diagnosis, which have current systems based on the AI. Salvado underlines, even throughout the significant gap between the amount of information of which the computer may know, compared to the human brain, there is still a great difference between the accuracy of diagnosis provided by a real doctor and a program. The examples provided by the author brightly support his argument and show disadvantages and gaps in the current model of artificial intelligence technology application.

When reading “AI in Clinical Medicine and Dentistry” written by Milan Miladinović and several research scientists from Serbia has a very effective rhetorical approach. Artificial intelligence can be defined as the process of robots doing tasks that a human would require to do. This source of information is a highly scholarly source since it is writing by many scientists in the field of medicine. The article “Artificial Intelligence in Clinical Medicine and Dentistry” provides several points to show how Artificial Intelligence (AI) is beneficial to the medical community. The purpose of this essay is to be persuasive to tell people about the humane benefits that it would make easier to society. The audience of this source may include, but

New innovations are being created every year to help improve and protect patients from reckless and preventable errors. As healthcare providers, it is our duty to provide care ethically and to do no harm to our patients. On the contrary, “the culture of cover-up” still continues to exist today and although technology and informatics has progressively increased quality care, it has not completely eradicated errors. Integrity is the key component for every healthcare provider, along with other characteristics. Therefore, disclosing medical errors with our patients is imperative and our patients and their families deserve to know what occurred during their time of care. Technology is not able to prevent every mishap that causes patients harm (Gibson & Singh, 2003). On the other hand, communication and learning from the mistake can. As Gibson and Singh (2003) so eloquently stated, “…wise people learn form their mistakes, and those who don’t are bound to repeat

There are ethical issues everywhere one turns, so ethical issues in information systems should not be a new concept or surprise to anyone. There are emerging ethical issues and as information systems progress, new ways to access information becomes available. These issues can play a role in our personal and professional lives, as well as in government and social aspects. There are also ethical issues involved in the medical field. Two big ethical issues that are becoming more prevalent in discussions are tracking devices used for people with dementia and electronic medical records. There are benefits to both of these, but they also have disadvantages as privacy and patients’ rights come into question. These ethical issues are new and therefore

Dr. (Editor, Health Informatics Journal, Edinburgh, United Kingdom). Medical informatics has emerged as a diverse and important new field of study. The field deals broadly in the science of addressing how best to use information to improve health care. However, protecting public health requires the acquisition, use, and storage of extensive health-related information about individuals in a secured and reliable manner. Though the electronic accumulation and exchange of personal data has an important public health benefits, but have accompanies threatens individual privacy. The breach of privacy can lead to individual discrimination in employment, insurance, and government programs and as such, individuals concerned about privacy invasions may avoid clinical or public health tests, treatments, or research. The variation in state laws supports the need to build consensus on the appropriate use and disclosure of public health information among public health practitioners. Hence, a need for a consistent and congruential protection plan and security as the federal and state privacy protections do not adequately protect public health data, and are inconsistent and

Hospitals over the years have advanced their technology which has countlessly saved lives quicker and more effectively. But computer systems such as RIP should not make every decision made in the emergency room. Technology no doubt has advanced immensely, but ethical decisions that can only be made by a suitable human still need to be accounted for, which is outside of a computer’s

In the article The Legal and Ethical Concerns that Arise from Using Complex Predictive Analytics in Health Care, the authors, Glenn Cohen, Ruben Amarasingham, Anand Shah, Bin Xie, and Bernard, analyze the major challenges involved with implementing predictive analytics in a health care setting. More specifically, the article discusses the use of predictive models that evaluates the risk of a patient, then identifying what medical intervention that will most greatly benefit the population, not just the patient. As you can see this use of technology could raise policy, ethical, and legal challenges. This article breaks down the process of developing a predictive model into four life cycle phases and examines the challenges involve with each

“Might a computer be less likely to discriminate on the basis of these and other social characteristics? However, what is lost when the human dimension is subordinated to computer technology in medical decision making?”(pg 504) Those are just two of the many questions that concern sociologists. We must understand that technology continue to advance and that change is not always accepted at first, especially in the medical field. It will take time for the entire public to accept the new system and understand that it is truly beneficial to health care workers around the world.

At a time when patients’ health record could be accessed by almost everyone who cares for the patients, it brings to one’s attention the ideals proposed by Plato, Aristotle, Socrates, and the other philosophers and ethicists (McGonigle & Mastrian, 2015). One has to understand though, that in spite of the great headway that the Health Information Technology (HIT) has come to, there are certain worldviews on “basic values that remain unchanged, the standards for living out these values will take on new meanings as professionals confront new and different moral dilemmas brought on by the adoption of technological tools for information management” (McGonigle & Mastrian, 2015, p. 68).

Data mining health care information is so important, there are so many ways it can be used to the benefit of individuals in general. For example, if physicians are able to compare their patients’ information with thousands of other people information and compare their characteristics and similarities, this type of information to prove vital in caring for their patients (McFarland, 2014). It is also important to understand that computers have the ability to analyze genome and allow physicians the opportunity treat certain diseases by data mining health care information (McFarland, 2014). Data mining heath care information has been used in a lot of positive ways, for one, physicians are able to gather a large amount of patients’ information and then use it to predicts and improve patients’ health, and at the same time reduce the cost of health care (McFarland, 2014). Data mining not only helps healthcare facilities, but also the physicians, other healthcare personnel, insurance companies, and most importantly the patients.

Their practice will shift to a trend to consult cloud computers, like IBM's Watson, and ask complex questions and receive answers that improve diagnoses and reduce errors. AL-Hemsi (2014) points out the positive impact of AI in helping doctors learn, consult, and teach more effectively, also emphasising on the substantial role of AI in medical education to prepare young generations of future doctors to be ready in response to the emerging

Legal issues related to medical informatics was destined to be a problem. Before health records were only paper based and there was constantly incomplete or illegible information that was difficult to dicipher. Now that electronic health records are commonly used, health care providers have access to unlimited amounts of data that’s perfectly legible. The amount of data now avaialable to the providers could almost be overwhelming. “This virtual “mountain” of data can lead to information overload, a new liability that can lead providers to overlook key findings despite reliable access to documentation. For instance, clinicians who miss a critical detail that affects treatment decisions while reviewing the EHR could in fact be liable for negligence because “the fact in question was likely just a few clicks away.”’ (Sittig & Singh, 2011). The use of electronic health records,

fertilization, surrogate motherhood, and human cloning once were considered immoral, but since moral codes changed due to cultural settings, they became interweaved into the culture’s fabric and became acceptable. The key to understanding the moral and ethical issues raised by artificial intelligence are the four levels on which intelligent artifacts raise ethical and moral problems. The first level concerns the ethical uses of computers and how humans respond to a world that is constantly being transformed by artificial intelligence machines. With the rapid growth of the internet, it sets the values of people’s security and privacy to a higher standard. New inventions such as telepresence and telecommuting challenge how humans deal with

Artificial intelligence is changing many ways we do things within the healthcare industry. With it, comes improvement of the quality and availability of healthcare services[1]. Many companies and investors have sunk hundreds of millions of dollars into artificial intelligence[2]. With this comes mass amounts of information and data being collected daily. The amount of money and resources being invested into AI is tremendous. There is no surprise that AI is going to revolutionize the medical industry. Changing the way that people look at healthcare for the better.

We have been using machines to measure our pulse and blood pressure and it is as accurate as doctors use that measurements to determine our health. There is an innovation of a health scan with artificial intelligence which helps doctors to analyse the patient’s basic health conditions. (BBC, 2017) The reporter found it is not affordable and questioned about its security for users’ privacy. (BBC, 2017) However, the point to focus is not how helpful it is right now. Research and creation do not always result in what people are aiming to produce. The famous example is Pavlov’s dog. The Russian physiologist, Ivan Pavlov found a learning procedure called, the classical conditioning, while he was feeding dogs to research on the digestion mechanism (Rathus, 2012). Hence, the introduction of a better artificial intelligence to basic human health care to the doctor’s level is possible, or it might even bring better inventions in other