Ethical and Privacy Challenges That May Occur with AI In Healthcare

AI In Healthcare

Take heed of a few ethical and privacy challenges encountered by AI in healthcare before deployment

AI in healthcare facilitates enormous convenience with its automatic potential and data-driven algorithms. By adorning the healthtech with enough provisions to ease patient care, artificial intelligence portrays certain alarming privacy challenges that seem in dissent to ethical concerns. AI disadvantages are as concerning as the benefits extended by them, causing challenges in healthtech to be taken seriously. Every existing boon has its own limitation so as AI in healthcare. However, to prevent such blunders, the healthcare industry will have to be highly attentive and alert.

AI makers extensively depend upon healthcare data to introduce innovations in the field of healthcare. Certainly, breaching patient data becomes a necessity for their future. By employing highly fruitful data in their research they try to cultivate a better healthcare system. Although this happens for the good, it is highly unethical to use sensitive data, be it for any cause. Additionally, some stringent laws concerning data privacy have been scrapped by the administration of various countries which expedited the data breach during the pandemic.

Predictive Genetic Testing Susceptibility

Health insurance companies tend to charge higher costs from the consumers when they find out the vulnerability of certain individuals to life-threatening diseases. Every country is not as fortunate as the USA where discriminatory actions against particular genes are punishable (under GINA), however, even the US does not assure freedom from this discrimination completely as this protection act does not include other insurance companies except for health. Therefore, the ability of AI in healthcare to make predictive genetic testing possible also arises the possibility of these privacy challenges causing challenges in healthtech equally.

Non-HIPAA Compliant Entities

Social media giants like Facebook employed a “suicide detection algorithm” to analyse and understand users’ mental states. This would make their services even more advanced when they start to use them in anticipated scenarios converging with the data. This data is collected without the permission or awareness of the user, which makes even this greater cause a reason to be assessed. Facebook or other social media application do not seek HIPAA compliance, neither does HIPAA concern these tech giants. Eventually leading to vulnerability of privacy. This is apparent from the suicide prevention campaigns that automatically appear on the screen to transport relief to the victim. Moreover, in an augmented scenario the social media giants can also, purchase patient data from healthcare providers to align them with the existing to persuade healthcare consumers with various healthcare services. Therefore, AI in healthcare is increasingly lacking trustworthiness.

Besides social media, few DNA Testing organizations are also spared from the regulations of HIPAA. They do not even clarify the clauses in their terms and conditions, which makes their attempts to share patient data more suspicious with contractors and alliances. This would further mean that AI disadvantages are not because of the flawed mechanism but because of the intentional algorithms embedded.

The Solution to AI Disadvantages

Although we cannot disagree with the benefits that AI in healthcare has facilitated, neither we can escape from the privacy challenges that it poses. To regulate ethical concerns, it has to be humans in the loop to ensure privacy concerns to be in place. This will further the ethical standard to greater heights and enable AI in healthcare to function according to the human morale of privacy. Besides a human in the loop can also mediate the algorithms to follow certain protocols that would comply with the behavior to inform users about how their data is collected and further implemented. This would gain more trust. Recently WHO issued ethical AI to be placed in healthtech, which is another rigorous solution.

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