Are we good to hand over ourselves to a robotic doctor in next 30 years?

If not, then what is OK in artificial intelligence(AI) impacted healthcare by 2050? There is something going to be more crucial beyond AI and patients i.e the medical ecosystem. Below are three checkpoints which need more improvement for this ecosystem to survive

1.      Global IT infrastructure readiness

2.      Regulatory framework readiness

3.      Ethical management practice

Global IT Infrastructure Readiness

With more consumers looking for better health care services including quick diagnosis, shorter turnaround for medicines and treatment for lethal diseases, the need for faster approach can only be achieved with the right set of data and analysis. So is the required infrastructure ready to achieve this? Will the security and privacy concerns be managed diligently?

A fusion of big data with blockchain and tapping information from wearable are going to play significant roles. Data processing, data grouping based on age, gender, patient history and data localization based on geography, disease specific and interdependent diseases would need more focus.

As only in India with a population base of 1.39 billion we could imagine how much is the need of more computing power, inter clinic and inter hospital data sharing, volume hardware, network capacity, powerful algorithms, more servers, storage and network devices. Additionally, it calls for increased cyber-security focus which will need to be 50% more efficient than current capability with threat detection and removal of the same.

Hence, across the globe 1 trillion USD business opportunity is anticipated only for the infrastructure build.

Regulatory framework readiness?

As this is the rule book and most ignored part across geographies hence keeping this updated should be the prime responsibility of the regulators and government. So are the current international regulations sufficient enough to sustain the evolution? What is the change required? What factors are considered to decide the updates? What is short term and long term regulation we see?

Is the prediction based only on actual data, real time data or is it extrapolated? Who will be responsible for the treatment misconduct – the software, the clinician or the doctor? Should the treatment depend 100 % on the AI output? Hence, patrolling should be practiced at each phase in the ecosystem i.e. data protection, data sharing, tracking of data access and for the organizations working on the AI capability and development.

Ethical management practice

Am I made aware about how my personal medical data will be used by clinics, insurers and hospitals? Is the disclosure by them 100% or something is missed? As diagnoses, reading medical device images, medical research and development will be significantly impacted by AI hence these basic queries are expected in absence of legal safeguards in place.

The existing laws do not take care of the data protection regulations in the amalgamated healthcare and AI world. So an immoral scenario is where an insurance company can use purchased data from technology company for inclined selection, pricing and more.

Suggested solutions –

–         Users must be educated and informed on the data usage details

–         Proactive step by technology companies to safeguard information

–         Implementing regulatory framework

Transparency about the AI algorithm should be the elementary ask from the government, hospitals and patients.

Finally, we should be cognizant about the information coming from the AI tools/software and should only be used for human benefit.