podcast-

The discussion explores the transformative role of artificial intelligence (AI) in healthcare and the ethical dilemmas it raises. AI in healthcare operates by leveraging large amounts of healthcare data and using machine learning algorithms to interpret and identify patterns. This allows AI to assist in diagnosing diseases and creating personalized treatment plans. However, ethical challenges arise regarding data privacy, algorithmic bias, and accountability. The need for clear regulatory frameworks to address these issues is emphasized. The guest, a medical student, shares their perspective on responsibility, data consent, and algorithm bias. They highlight the importance of clear legal frameworks and the ethical considerations around using patient data. The conversation also touches on the role of empathy and compassion in healthcare, where AI can provide objective analysis but cannot replace the human touch. While AI has made strides in recognizing human emotions, it cannot truly ex Welcome, listeners, to a pivotal discussion at the intersection of innovation and ethics. Today, we dive into the transformative role of artificial intelligence in healthcare, a journey that started with Aliza in 1964. A simple conversational tool, marking our first step into harnessing AI to bridge human needs with technological prowess. But as we marvel at AI's capabilities, from diagnosing diseases with unprecedented accuracy to tailoring patient care like never before, we are compelled to confront the ethical dilemmas it brings to the fore. Data privacy, algorithmic bias, and mental health. How do we navigate these challenges to ensure AI serves the good of all? First, let's delve into how AI operates within the healthcare sector. AI technologies leverage vast amounts of healthcare data, from electronic health records to medical imaging and genomic sequences. These systems employ machine learning algorithms to interpret, learn from, and identify patterns within this data, forming what is essentially a neural network, an interconnecting web of information mimicking the neural network of the human brain. This process enables AI to assist in diagnosing beliefs, predicting patients' outcomes, and documenting personalized treatment plans. For instance, by analyzing the data from thousands of patients' records, AI can learn to recognize the early signs of conditions like cancer or heart disease, often with greater accuracy or speed than traditional methods. AI in healthcare navigates the complex interplay between innovation and ethical responsibility. The advancements offer immense benefits. However, they also introduce ethical dilemmas around data consent, the potential for bias, and patients' mental health, that could exacerbate existing healthcare disparities. Now, we are excited to speak to our special guest, a medical student who is currently studying in London. Thank you for joining us today. Thank you for inviting. It's an interesting topic to discuss. Firstly, the ethical challenges of AI in healthcare involve complex issues of ownership and accountability, especially when AI system errors in diagnosis. Determining who is responsible for such errors is complicated by the integration of AI into patient care, which differs from traditional settings where healthcare providers are clearly accountable. For example, a case highlighting these legal and accountability concerns involves the UnitedHealth Group, which faced a lawsuit for allegedly using an AI algorithm to deny extended care claims to elderly patients. This situation underlines the legal complexities and the need for clear regulatory and legal frameworks to navigate accountability in AI-driven healthcare decisions. So, what's your opinion on this? From my perspective, there needs to be a clear legal or regulatory framework to guide the use of AI in healthcare, especially concerning issues of responsibility and ownership. However, actually, as a medical student, I believe that all medical students would, by default, assume that if there is a problem in treating a patient, it should be the responsibility of the doctor, because the final treatment plan is often provided to the patient by the doctor. Thank you for your clarification. Moving to data privacy, as you know, creating AI algorithm requires large amount of private medical data sets from patient. It's only just about recently the laws and standards for collecting personal data have become increasingly strict. For example, the GDPR regulation in Europe requires explicit consent for the use of personal data, including medical data, and sets strict limitations on the purpose for which it can be used. So, what's your opinion as a medical student on ethical consideration when the data is obtained before or without consent? Actually, my opinion is, I believe that in certain areas or certain cases, it might be acceptable to use past medical data without directly obtaining patient consent, provided that the data is anonymized or de-identified, to ensure that it cannot be tracked back to an individual. The use of such data is usually limited to research purpose. So, it might be acceptable. However, I also agree that this is a very sensitive topic, because using patient data without their consent is highly unethical and could pose significant risk as well. Thank you, Clara. Moving to algorithm bias, recently, there was a team of MIT developed an algorithm on allocating organs to a list of donors, based on urgency where they assign different values to patients with different characteristics, to see who will receive different organ donations first or not. However, with the popular OpenAI's impressive new chatbots, which were asked to write a program if someone would be a good scientist, the chatbot returned with a racist and sexist Python function. Therefore, this is showing that AI has bias towards general rights. What's your take on these technologies? Do you think we should value human decisions since the AI is also not perfectly fair? Yes, actually, I believe that such bias could lead to unfair discriminatory outcomes, thereby exacerbating existing social inequalities, particularly in sensitive areas such as healthcare and employment. However, at the same time, issues like organ donations are also challenging for humans as well, potentially involving a lot of emotional reasoning. So the best approach might be to strive to improve the fairness and transparency of the AI system. This includes diverse and inclusive training data, regular audits for bias, and possibly transparent algorithms that can be understood by human experts. Many thanks. Lastly, I now want to pivot to a topic that's both cutting-edge and deeply contentious. It touches on the very core of our personal liberties, the sanctity of our mental well-being, and the frontier of technological innovation. We are about to delve into the realm of artificial intelligence and its role in mental health, a field where the potential for both breakthroughs and ethical dilemmas collides. Can you explain the role of empathy and compassion in healthcare, especially in the context of end-of-life care? It's a good but it's a difficult question, because I feel like there are some aspects of AI which is machine-like. They are programmed without any emotions, which can be actually beneficial to the healthcare industry. For example, when it comes to allocating organs, as you mentioned before, which is a tricky and emotional topic to not only the patients but families, sometimes even their doctors, because, as you know, when you take care of patients, you do develop a bond to the patient, and sometimes you do get very emotional about it. That could potentially cloud a doctor's judgment when it comes to important decisions like life-saving treatments, where only one can survive. So if we could allow AI to step into the game and make these really tricky decisions, they are more likely to give objective feedback than human doctors to navigate these difficult decisions. And also, however, I do recognize that the lack of empathy is something that cannot ever be substituted for AI or for AI to imitate. So, for example, if a doctor were to tell a patient about the end-of-life discussion with the family or with the patient, if the doctor is purely presenting the data as you have a condition A, heart disease, condition B, lung cancer, and your life expectancy is two to three months, it is not right for the doctor to restart your heart if your heart were to stop. So if the AI technology kicks in and just presents this data in a very machine-like manner, the patient would not take this information very well and would possibly file a complaint against the doctor. So that's where I feel empathy comes in and it's crucial in the healthcare setting. Oh, I see. You mean AI can provide objective analysis in healthcare but cannot replace empathy being essential in patient care. So there is an irreplaceable value in human touch. Thank you, Clara, for shedding light on the importance of empathy and compassion in healthcare. Moving forward from your expertise, where does AI stand today in understanding and simulating human emotions? AI has made significant strides in recognizing human emotion through various inputs like facial expression, voice modulation, and even text. For instance, there are AI systems designed to detect stress or depression levels in speech patterns, which can be particularly useful in therapeutic settings or monitoring patients' well-being. However, understanding emotion is not the same as feeling it. AI can identify sadness or happiness and respond in ways that are programmed to be appropriate, but it doesn't feel these emotions. So the empathy AI offers is based on algorithm and data analysis, not general emotional experience. Many thanks, Clara. Thank you again for sharing your insights and for reminding us ethical concerns of implementing AI in healthcare in the face of technological advancement. In today's chat, we navigated a tight and yet intricate world of AI in healthcare. We unpacked its potential to revolutionize healthcare and the ethical hurdles it brings, from data privacy to the challenge of ensuring fairness and keeping the human touch in medicine. Wrapping up, as AI transforms healthcare, prioritizing ethics, human oversight, and compassion is crucial for improving patients' outcomes. Thank you.