神学中的人工智能--我们的现状和未来前景如何?

Alexander Mundinger, Carolin Mundinger
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引用次数: 0

摘要

人工智能(AI)的定义是通过数字计算机或机器人系统模拟人类智能,已成为当下的热门话题。深度学习是人工智能的一个子类别,它基于复杂的人工神经网络,模仿人类突触可塑性和分层大脑架构的原理,并使用大规模数据处理。在乳腺筛查项目中,基于人工智能的图像分析显示出非凡的灵敏度,通过预选正常病例,最多可减少 70% 的工作量,与人工双读相比,召回率降低了 25%。自然语言程序(如 ChatGPT (OpenAI))与黄金标准(即人类判断)相比,在建议和决策方面达到了 80% 或更高的准确率。就患者安全而言,这还不能满足医疗产品的必要要求。人工智能的主要优势在于,它可以比人类更快、更少地完成常规但复杂的任务。医疗保健领域的主要问题是人工智能系统的稳定性、网络安全、责任和透明度。更广泛地使用人工智能可能会影响人类在医疗保健领域的工作,并增加技术依赖性。人工智能在老年学领域的应用才刚刚开始,它正朝着具有更好特性的更佳形式发展。有必要利用有意义的原始数据对人工智能系统进行负责任的培训,并开展科学研究来分析其在现实世界中的表现,以确保人工智能的正常运行。为了降低重大风险,有必要在积极推广和开发有质量保证的人工智能系统与谨慎监管之间取得平衡。人工智能监管最近才被纳入跨国法律框架,欧盟的《人工智能法》是 2023 年 12 月公布的第一个全面法律框架。不可接受的人工智能系统如果被认为对人们的基本权利构成明显威胁,将被禁止使用。利用人工智能并将其与人类的智慧、同理心和感情相结合,将是进一步发展未来智能学并取得丰硕成果的首选方法。
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Artificial Intelligence in Senology - Where Do We Stand and What Are the Future Horizons?
Artificial Intelligence (AI) is defined as the simulation of human intelligence by a digital computer or robotic system and has become a hype in current conversations. A subcategory of AI is deep learning, which is based on complex artificial neural networks that mimic the principles of human synaptic plasticity and layered brain architectures, and uses large-scale data processing. AI-based image analysis in breast screening programmes has shown non-inferior sensitivity, reduces workload by up to 70% by pre-selecting normal cases, and reduces recall by 25% compared to human double reading. Natural language programs such as ChatGPT (OpenAI) achieve 80% and higher accuracy in advising and decision making compared to the gold standard: human judgement. This does not yet meet the necessary requirements for medical products in terms of patient safety. The main advantage of AI is that it can perform routine but complex tasks much faster and with fewer errors than humans. The main concerns in healthcare are the stability of AI systems, cybersecurity, liability and transparency. More widespread use of AI could affect human jobs in healthcare and increase technological dependency. AI in senology is just beginning to evolve towards better forms with improved properties. Responsible training of AI systems with meaningful raw data and scientific studies to analyse their performance in the real world are necessary to keep AI on track. To mitigate significant risks, it will be necessary to balance active promotion and development of quality-assured AI systems with careful regulation. AI regulation has only recently included in transnational legal frameworks, as the European Union's AI Act was the first comprehensive legal framework to be published, in December 2023. Unacceptable AI systems will be banned if they are deemed to pose a clear threat to people's fundamental rights. Using AI and combining it with human wisdom, empathy and affection will be the method of choice for further, fruitful development of tomorrow's senology.
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