Should there be a code of conduct for artificial intelligence in healthcare?

The rise of generative artificial intelligence has prompted an AI ethicist to propose a framework to reduce the risks of using this evolving technology in the medical field. At the same time, the CEO of ChatGPT’s OpenAI also urged U.S. lawmakers to start regulating artificial intelligence to ensure human safety.

Above: The rise of generative artificial intelligence has prompted calls for the introduction of a framework to regulate its use in healthcare.

Science fiction writer Isaac Asimov proposed his Three Laws of Robotics in the 1942 short story "Runaround." He died in 1992, long before witnessing the rise of generative artificial intelligence in recent years.

Generative artificial intelligence includes algorithms such as ChatGPT or DALL-E, which can use trained data to create new content, including text, images, audio, video, and computer code. Large language models (LLMs) are a key component of generative artificial intelligence, neural networks trained on large amounts of unlabeled text using self-supervised or semi-supervised learning.

Currently, the capabilities of generative artificial intelligence are growing exponentially. In healthcare, it has been used to predict patient outcomes by learning from large patient data sets, diagnose rare diseases with incredible accuracy, and pass the U.S. Medical Licensing Examination without prior learning. Achieved a score of 60%.

The potential for AI to enter healthcare and replace doctors, nurses and other health professionals has prompted AI ethicist Stefan Harrer to propose a framework for using generative AI in medicine.

Haller is the Chief Innovation Officer of the Digital Health Collaborative Research Center (DHCRC) and a member of the Consortium for Health Artificial Intelligence (CHAI). The problem with using generative AI, he said, is its ability to generate content that is convincingly false, inappropriate or dangerous.

Stephen Haller said: “The essence of efficient knowledge retrieval is asking the right questions, and the art of critical thinking depends on one’s ability to explore answers by evaluating the validity of models of the world. LLMs are unable Complete these tasks."

Haller believes that generative artificial intelligence has the potential to transform health care, but it hasn’t happened yet. To this end, he recommended the introduction of an ethics-based regulatory framework containing 10 principles that he said could mitigate the risks posed by generative AI in healthcare:

1. Design artificial intelligence as an auxiliary tool that augments human decision-makers but does not replace them.
2. Design AI to produce metrics on performance, usage and impact, explain when and how to use AI to aid decision-making, and scan for potential bias.
3. Design artificial intelligence that is based on and adheres to the value system of the target user group.
4. Announce the purpose and use of AI from the beginning of concept or development work.
5. Expose all data sources used to train artificial intelligence.
6. Design AI to clearly and transparently label AI-generated content.
7. Regularly audit AI against data privacy, security and performance standards.
8. Record and share audit results, educate users about AI capabilities, limitations, and risks, and improve AI performance by retraining and updating algorithms.
9. Ensure Fair Work and Safe Work standards are applied when employing people development staff.
10. Establish a legal precedent that clearly defines when data can be used for AI training and establishes a copyright, responsibility and accountability framework to govern training data, AI-generated content, and human decisions made using that data Impact.

Interestingly, Stephen Haller’s framework coincides with calls from ChatGPT’s Open AI CEO Sam Altman, who has called on U.S. lawmakers to introduce government regulation to prevent artificial intelligence Potential risks that intelligence poses to humans. Sam Altman, who co-founded OpenAI in 2015 with the support of Elon Musk, has suggested that governments introduce licensing and testing requirements before releasing more powerful AI models.

In Europe, the Artificial Intelligence Bill will be voted on in the European Parliament next month. If passed, the legislation could ban biometric surveillance, emotion recognition and some artificial intelligence systems used in policing.

Stephen Haller’s rather general framework can be applied to many workplaces where there is a risk of AI replacing humans. It appears to come at a time when people (even those responsible for creating the technology) are calling for a pause in the world of artificial intelligence.

Is the medical industry facing greater risks than other employment industries? Is such a framework beneficial? More importantly, given the speed at which AI is developing, will it actually reduce risk? Perhaps, only time will give us the answers to these questions.

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