In the clinical laboratory, artificial intelligence (AI) is used to evaluate test results, analyze risk profiles, diagnose, and perform financial analysis, among other things. AI could help reduce costs, improve access, and improve the quality of care. Its implementation requires education about the technology and research to generate clinical evidence. The more we learn and the better we adapt, the more we will take advantage of its potential and add value to our profession. Also, we must learn about its limits and uncertainties.

The widespread use of AI has started to raise concerns. There are global discussions around security protocols that should be created that focus on making systems more accurate, interpretable, transparent, robust, reliable, and loyal. In addition, there is a strong desire to work with legislators to accelerate the enactment of laws that allow AI regulation. Specifically, in the field of health, legislation will be important to ensure that bioethical principles are complied with, which take on a new perspective in the face of the advent of AI.

Legislation is an important mechanism that is meant to reinforce ethical conduct in all aspects of laboratory medicine. The regulatory framework for AI must be designed to guarantee the safety and effectiveness of the product throughout its entire life cycle.To address civil liability for harm caused by AI, legislative and non-legislative instruments are required. The law must safeguard and protect data privacy. The use of AI must be declared. The logic involved and the consequences of processing health information should also be reported. In order for a patient's health information to be used to grow databases and improve algorithms, it must be adequately de-identified.Legislation must recognize the issue of AI vulnerability to cyber threats as well as other inherent dangers. Finally, to work appropriately, AI needs data, however, the data is coming from our patients. Transforming AI and big data into effective products, services and processes is an expensive and risky undertaking that needs a legal structure that guarantees and provides security for the investment. Intellectual property right and copyright arises which implies that the software and algorithms involved can be patented. Commercial secrecy is opposed to the transparency required of the systems. The law must try to achieve the balance between stakeholders.

Learning objectives

1. To understand how AI could be implemented in laboratory medicine.
2. To be aware of the necessity to respect bioethical principles when implementing AI in laboratory medicine.
3. To have a general knowledge of the different aspects to take into consideration in the development of laws that govern AI.

References

1. Paranjape K, Schinkel M, Hammer RD, Schouten B, Nannan Panday RS, Elbers PWG, Kramer MHH, Nanayakkara P. The Value of Artificial Intelligence in Laboratory Medicine. Am J Clin Pathol. 2021;155(6):823-831.
2. Haymond S, McCudden C. Rise of the Machines: Artificial Intelligence and the Clinical Laboratory. J Appl Lab Med. 2021;6(6):1640-1654.
3. Pennestrì F, Banfi G. Artificial intelligence in laboratory medicine: fundamental ethical issues and normative key-points. Clin Chem Lab Med. 2022;60(12):1867-1874.
4. Minssen T, Gerke S, Aboy M, Price N, Cohen G. Regulatory responses to medical machine learning. J Law Biosci. 2020;7(1):lsaa002.