Artificial Intelligence (AI) in health, and six guidelines to design and implement it


Adoption of AI for health has presented governments providers, communities, and patients with both opportunities and challenges

Artificial Intelligence (AI) holds huge potential for improving the provision of medicine and healthcare across the world however only when human rights and ethics are at the center of its design, implementation and use as per the latest WHO guidelines released today.

This report Governance and ethics of AI in healthcare is the result of two years of discussions that were conducted by a committee of experts from around the world selected by WHO .

"Like all new technology, artificial intelligence holds enormous potential for improving the health of millions of people around the world, but like all technology it can also be misused and cause harm," said Dr. Tedros Adhanom Ghebreyesus. WHO Director-General. "This important new report provides a valuable guide for countries on how to maximize the benefits of AI, while minimizing its risks and avoiding its pitfalls."

Artificial intelligence is a possibility applied to a variety of countries , is being used to enhance the speed and precision of screening and diagnosis for illnesses; to aid with the clinical process; enhance the research in health and development of drugs and to support a variety of interventions in public health like monitoring of outbreaks, disease surveillance and health system management.

AI can also enable patients to take more control over their own healthcare and to better be aware of their needs as they change. It can also assist those in rural and resource-poor areas where patients are often denied limited access to health care workers and medical specialists, to fill in the gap in access to health care services.

However, the WHO's report warns against overestimating the value of AI in terms of health, especially when this happens in the absence of the core investment and strategies to ensure universal health coverage.

It further reveals the fact that there are opportunities linked to risks and challenges which include unethical use and collection of health information; algorithms that encode biases, and the risks of AI for patient safety security, cybersecurity, as well as the environment.

For instance, although both public and private sector investments in the development and application of AI is vital, inadvertent usage of AI Training Datasets can make it easier for the rights and interests of people and communities to the massive technological interests of companies , or to the interests of the government in the field of surveillance and social control. The report also explains that systems based using data gathered from people in countries with high incomes may not be able to meet the needs of people who live in middle and low-income situations.

AI systems must therefore be developed with care in order to take into account the variety of healthcare and socioeconomic settings. They should be supported with training in digital competencies such as community engagement, awareness-raising and community engagement specifically for thousands of healthcare workers who require digital literacy or retraining when their functions and roles are automated and have to contend with machines that might affect the autonomy and decision-making of both patients and providers.

Six guidelines to ensure that AI serves the public good in every country

To minimize the risks and maximize the benefits inherent with the application of AI in the health sector, WHO provides the following guidelines of AI regulations and management:

1. The protection of autonomy for humans in the context of healthcare, this means that human beings should remain in charge of health systems and medical decisions. Privacy and confidentiality should be safeguarded and patients should provide valid, informed consent by using the appropriate legal frameworks to ensure security of data.

2. Safety and well-being of humans and the public good. The creators of AI Technology must satisfy regulations regarding security, accuracy, and effectiveness in well-defined usage scenarios or indications. Quality control measures in practice and improvements in quality with respect to the use of AI are required.

3. Transparency, explanation and understanding. Transparency demands that adequate information is published or recorded prior to the creation or implementation of AI technology. The information needed must be easily accessible and allow for an informed public discussion and consultation about how the technology is developed and how it can or shouldn't be utilized.

4. Instilling accountability and responsibility. While AI technologies can be used to perform specific tasks but it is the responsibility of the stakeholders to ensure they are employed under the appropriate conditions and by properly skilled individuals. Effective mechanisms should be made available for questions and recourse for groups and individuals who are negatively affected by decisions based upon algorithms.

5. Insuring equity and inclusion. Inclusion requires that AI for health be developed to facilitate the most accessible and equitable use, regardless of age, sexual orientation gender or income, race or sexual orientation, ethnicity or any other characteristic that are protected by human rights laws.

6. Promotion of AI that is sustainable and responsive. Developers, designers and users must constantly and openly evaluate AI applications when they are in use to determine if AI is responsive and in a way that conforms to requirements and expectations. AI systems should be developed to minimize their negative environmental impact and improve energy efficiency. Businesses and government agencies should consider possible disruptions to work and health care, such as training health employees to adjust to the usage of AI systems, as well as possible job losses resulting from the the use of automated systems.

These guidelines will be the basis for the future WHO initiatives to help for ensuring the potential AI in the public and healthcare sectors can be utilized to the benefit of everyone.


Conclusion

At Global Technology Solutions, we create training data to provide the needed support for medical dataset as well as provide secure data services to be able to match the needs that you have for machine learning algorithms.. GTS offers a wide variety of services that comprise annotation, tuberculosis x ray dataset, data collection, and protected transcription in order to provide support for your healthcare datasets for machine learning.


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