Chapter 12 Challenges and ethical considerations
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Rishabha Malviya
Abstract
In the healthcare industry, artificial intelligence (AI) is crucial because it helps with disease diagnosis, treatment planning, and operational efficiency. However, there are issues with biases, data breaches, and ethical consequences. The chapter aims to provide some knowledge on the challenges faced by the researchers of AI in healthcare along with some ethical considerations. Collaboration between AI clinicians can succeed if appropriate governance frameworks are in place. An overview of the challenges and ethical quandaries surrounding AI in healthcare is given in the chapter. Explainable AI techniques address issues with bias and transparency. Data privacy, algorithmic transparency, and ethical issues are among the difficulties. Up skilling medical staff, addressing biases, and obtaining patient consent are all necessary before implementing AI in healthcare. Furthermore, healthcare professionals need to believe in AI for it to be adopted. Research suggests that AI holds promise for enhancing patient outcomes and healthcare delivery. More research is necessary to fully grasp how AI will affect healthcare professionals’ roles and responsibilities.
Abstract
In the healthcare industry, artificial intelligence (AI) is crucial because it helps with disease diagnosis, treatment planning, and operational efficiency. However, there are issues with biases, data breaches, and ethical consequences. The chapter aims to provide some knowledge on the challenges faced by the researchers of AI in healthcare along with some ethical considerations. Collaboration between AI clinicians can succeed if appropriate governance frameworks are in place. An overview of the challenges and ethical quandaries surrounding AI in healthcare is given in the chapter. Explainable AI techniques address issues with bias and transparency. Data privacy, algorithmic transparency, and ethical issues are among the difficulties. Up skilling medical staff, addressing biases, and obtaining patient consent are all necessary before implementing AI in healthcare. Furthermore, healthcare professionals need to believe in AI for it to be adopted. Research suggests that AI holds promise for enhancing patient outcomes and healthcare delivery. More research is necessary to fully grasp how AI will affect healthcare professionals’ roles and responsibilities.
Chapters in this book
- Frontmatter I
- Preface V
- Foreword VII
- Contents IX
- Chapter 1 Introduction to smart pharma: foundation of AI and big data 1
- Chapter 2 Emerging technology in pharma and the role of AI and blockchain 19
- Chapter 3 Partnership and collaboration in the pharmaceutical industry 37
- Chapter 4 Education and training in smart pharma 55
- Chapter 5 Drug manufacturing and quality control with artificial intelligence 77
- Chapter 6 Drug development and clinical trial via artificial intelligence 97
- Chapter 7 AI-driven clinical decision support systems for pharma executives 121
- Chapter 8 AI-based pharmacovigilance and drug safety 143
- Chapter 9 Intellectual property and data privacy in the pharmaceutical sector 163
- Chapter 10 Regulatory affairs and compliance in the pharmaceutical sector 183
- Chapter 11 AI and big data in post-marketing surveillance 201
- Chapter 12 Challenges and ethical considerations 219
- Chapter 13 Future trends and innovations of AI in healthcare 237
- Index 253
Chapters in this book
- Frontmatter I
- Preface V
- Foreword VII
- Contents IX
- Chapter 1 Introduction to smart pharma: foundation of AI and big data 1
- Chapter 2 Emerging technology in pharma and the role of AI and blockchain 19
- Chapter 3 Partnership and collaboration in the pharmaceutical industry 37
- Chapter 4 Education and training in smart pharma 55
- Chapter 5 Drug manufacturing and quality control with artificial intelligence 77
- Chapter 6 Drug development and clinical trial via artificial intelligence 97
- Chapter 7 AI-driven clinical decision support systems for pharma executives 121
- Chapter 8 AI-based pharmacovigilance and drug safety 143
- Chapter 9 Intellectual property and data privacy in the pharmaceutical sector 163
- Chapter 10 Regulatory affairs and compliance in the pharmaceutical sector 183
- Chapter 11 AI and big data in post-marketing surveillance 201
- Chapter 12 Challenges and ethical considerations 219
- Chapter 13 Future trends and innovations of AI in healthcare 237
- Index 253
