1 00:00:00,050 --> 00:00:00,800 Case study. 2 00:00:00,800 --> 00:00:05,150 Ethical governance and transparency in AI driven healthcare diagnostics. 3 00:00:05,180 --> 00:00:11,210 Deployment of AI driven diagnostic tools in health care has revolutionized patient care, but it has 4 00:00:11,210 --> 00:00:17,030 also highlighted the critical challenges of reducing unintended use and mitigating downstream harm. 5 00:00:17,720 --> 00:00:23,240 Doctor Emily Carter, a renowned specialist in medical AI, spearheaded the integration of an advanced 6 00:00:23,240 --> 00:00:26,540 diagnostic AI system at Saint Mary's Hospital. 7 00:00:26,930 --> 00:00:33,290 Despite the initial success in improving diagnostic accuracy and reducing patient wait times, the system 8 00:00:33,290 --> 00:00:36,770 soon faced ethical dilemmas and operational challenges. 9 00:00:37,580 --> 00:00:42,530 One of the first issues emerged when a patient, Jane Williams, was incorrectly diagnosed with a rare 10 00:00:42,560 --> 00:00:43,370 disease. 11 00:00:43,400 --> 00:00:50,030 This misdiagnosis stemmed from a data anomaly that the AI system had not previously encountered. 12 00:00:50,510 --> 00:00:56,630 This incident raised a crucial question how can AI systems be designed to handle rare and unexpected 13 00:00:56,630 --> 00:01:00,380 data anomalies without causing harm to patients? 14 00:01:00,380 --> 00:01:06,250 The hospital administration Guided by Doctor Carter, understood the importance of continuous monitoring. 15 00:01:06,250 --> 00:01:07,150 As a solution. 16 00:01:07,150 --> 00:01:12,790 They established a team dedicated to regularly assessing the AI system's performance, incorporating 17 00:01:12,790 --> 00:01:18,730 mechanisms for anomaly detection, and instituting feedback loops to quickly address detected issues. 18 00:01:20,560 --> 00:01:23,320 Another challenge involved data privacy. 19 00:01:23,500 --> 00:01:28,630 The AI system relied on extensive patient data for training and operational purposes. 20 00:01:28,870 --> 00:01:34,120 However, concerns about patient data security became evident when a breach occurred, compromising 21 00:01:34,120 --> 00:01:35,500 sensitive information. 22 00:01:36,130 --> 00:01:41,530 This situation necessitated a robust governance framework to address privacy concerns. 23 00:01:42,160 --> 00:01:47,740 To what extent should governance frameworks be customized to specific applications, such as healthcare, 24 00:01:47,740 --> 00:01:51,700 to ensure both ethical compliance and operational efficiency? 25 00:01:52,690 --> 00:01:55,330 Drawing from the ethical guidelines by Floridi et al. 26 00:01:55,360 --> 00:02:00,850 Doctor Carter and her team revised the hospital's AI governance framework to include stringent data 27 00:02:00,850 --> 00:02:05,550 privacy policies and adaptive Procedures tailored to the health care context. 28 00:02:06,810 --> 00:02:10,770 Transparency in AI operations emerged as another critical issue. 29 00:02:11,430 --> 00:02:17,100 Patients and health care providers struggled to understand how the AI system arrived at its diagnostic 30 00:02:17,100 --> 00:02:17,940 decisions. 31 00:02:18,450 --> 00:02:23,850 This lack of transparency led to mistrust among users and posed the question, what methods can make 32 00:02:23,880 --> 00:02:29,640 AI decision making processes more understandable for non-experts, thereby fostering trust and ensuring 33 00:02:29,640 --> 00:02:30,570 accountability? 34 00:02:31,350 --> 00:02:37,650 Doctor Carter introduced explainable AI techniques to make the systems decision making more interpretable 35 00:02:37,680 --> 00:02:41,610 by providing clear, understandable explanations for each diagnosis. 36 00:02:41,640 --> 00:02:45,000 The hospital aimed to build confidence among its stakeholders. 37 00:02:47,100 --> 00:02:52,320 The deployment of this AI system also brought to light significant ethical considerations. 38 00:02:52,710 --> 00:02:57,480 One major ethical dilemma involved balancing beneficence and non-maleficence. 39 00:02:57,510 --> 00:03:02,850 How can health care providers ensure that AI systems not only do no harm, but actively contribute to 40 00:03:02,880 --> 00:03:04,110 patient well-being? 41 00:03:04,550 --> 00:03:10,760 The hospital adopted the European Commission's Ethics Guidelines for trustworthy AI, which emphasized 42 00:03:10,760 --> 00:03:14,450 principles like beneficence, autonomy, and justice. 43 00:03:14,660 --> 00:03:20,990 These guidelines were integrated into the AI systems development and deployment phases to ensure alignment 44 00:03:20,990 --> 00:03:23,600 with societal values and ethical standards. 45 00:03:25,040 --> 00:03:30,710 Facial recognition technology used by law enforcement agencies has often been scrutinized for ethical 46 00:03:30,710 --> 00:03:32,360 and privacy concerns. 47 00:03:32,570 --> 00:03:38,420 At Saint Mary's Hospital, a similar technology was considered for patient identification to streamline 48 00:03:38,420 --> 00:03:40,100 administrative processes. 49 00:03:40,460 --> 00:03:47,180 However, instances of misidentification and biases in facial recognition technology raised significant 50 00:03:47,180 --> 00:03:48,320 ethical questions. 51 00:03:48,320 --> 00:03:54,290 How can healthcare institutions ensure that AI technologies do not perpetuate biases or infringe on 52 00:03:54,290 --> 00:03:55,430 privacy rights? 53 00:03:55,820 --> 00:04:01,670 Referencing Buolamwini and Gebru work on biased outcomes in facial recognition, Doctor Carter decided 54 00:04:01,670 --> 00:04:07,450 against implementing this technology without first ensuring robust governance frameworks and continuous 55 00:04:07,450 --> 00:04:11,470 monitoring to mitigate biases and protect patient privacy. 56 00:04:13,120 --> 00:04:17,080 Statistical insights further emphasized the necessity of these measures. 57 00:04:17,470 --> 00:04:24,310 A Pew Research Center survey highlighted a significant trust deficit in AI systems, with only 33% of 58 00:04:24,310 --> 00:04:28,930 Americans expressing confidence in AI's ability to make unbiased decisions. 59 00:04:28,930 --> 00:04:35,170 This statistic prompted the hospital to prioritize transparency and ethical practices to foster public 60 00:04:35,170 --> 00:04:36,010 confidence. 61 00:04:36,490 --> 00:04:42,100 How can healthcare institutions balance the benefits of AI integration with the need to build and maintain 62 00:04:42,100 --> 00:04:48,220 public trust by implementing transparent AI operations and adhering to ethical guidelines? 63 00:04:48,250 --> 00:04:54,130 Saint Mary's Hospital aimed to bridge this trust gap and enhance the reliability of their AI systems. 64 00:04:55,990 --> 00:05:01,750 In practice, these strategies proved essential in mitigating unintended consequences and ensuring the 65 00:05:01,750 --> 00:05:03,430 ethical deployment of AI. 66 00:05:04,210 --> 00:05:10,230 For example, the AI systems continuous monitoring revealed a tendency to recommend certain high cost 67 00:05:10,260 --> 00:05:16,710 treatments more frequently, raising concerns about potential biases favoring specific drug manufacturers. 68 00:05:17,370 --> 00:05:23,280 This discovery prompted the hospital to question what mechanisms can be put in place to detect and correct 69 00:05:23,280 --> 00:05:26,400 bias in AI driven treatment recommendations. 70 00:05:26,880 --> 00:05:33,240 Leveraging insights from the AI Now Institute study on biased AI systems in various sectors, the hospital 71 00:05:33,240 --> 00:05:40,080 implemented regular audits and bias detection protocols to ensure fair and unbiased treatment recommendations. 72 00:05:41,310 --> 00:05:47,790 Ultimately, the integration of AI systems into health care necessitates a proactive approach to governance, 73 00:05:47,790 --> 00:05:50,940 monitoring, transparency, and ethics. 74 00:05:51,210 --> 00:05:56,520 Doctor Carter's journey at Saint Mary's Hospital illustrates the importance of these principles in practice. 75 00:05:56,760 --> 00:06:02,520 Establishing comprehensive governance frameworks tailored to specific applications such as health care 76 00:06:02,520 --> 00:06:03,510 is crucial. 77 00:06:04,020 --> 00:06:10,400 Continuous monitoring enables the detection and rectification of performance issues and biases, ensuring 78 00:06:10,400 --> 00:06:12,890 the system adapts to changing environments. 79 00:06:13,490 --> 00:06:19,580 Emphasizing transparency through explainable AI fosters trust and accountability among stakeholders. 80 00:06:20,060 --> 00:06:25,220 Adhering to ethical guidelines based on principles like beneficence and justice ensures that. 81 00:06:25,250 --> 00:06:28,010 AI systems contribute positively to society. 82 00:06:29,300 --> 00:06:35,480 In conclusion, the deployment of AI in health care, as seen through Doctor Carter's experience, underscores 83 00:06:35,480 --> 00:06:42,770 the need for a multifaceted approach to managing AI systems by addressing data anomalies, privacy concerns, 84 00:06:42,770 --> 00:06:47,660 and ethical dilemmas through robust governance, continuous monitoring and transparency. 85 00:06:47,690 --> 00:06:52,010 Healthcare institutions can reduce unintended use and downstream harm. 86 00:06:52,010 --> 00:06:57,110 These strategies not only protect patients, but also enhance the trustworthiness and effectiveness 87 00:06:57,110 --> 00:06:58,370 of AI systems. 88 00:06:58,760 --> 00:07:05,090 As AI continues to evolve, healthcare providers must remain committed to ethical practices and responsible 89 00:07:05,090 --> 00:07:09,020 governance to ensure that AI serves as a force for good in society.