One of the key regulatory problems that are hindering the acceptance of AI in Bio-Pharma is the apocalyptic prediction about Human jobs being traded by machine intelligence and the other Key Problem is the siloed regulatory infrastructure. Although the technological advancements in the field of healthcare have grown heavily, the regulatory ecosystem has bungled to keep up.
One more aspect is that AI, particularly neural nets, is a Pandora box; while we can program it, we really don’t know how it rests with the existing technologies within the Organization. That creates the dilemma of explicability. More than the regulatory Reluctance Forebear AI, regulatory authorities are trying to keep pace.
Another core regulatory challenge is in administrating data accessibility in a way that is lean, balanced for benefits between the data-sources and data-users, and assures confidentiality and prevention of misuse.
How to Regulate AI in Bio-Pharma
- “Display of orthodox AI solutions with regulatory frameworks absorbs new standards to be developed that align with and Support existing regulatory structure while keeping pace with sprouting technologies.”
- Collaborating Machine intelligence & humans in the loop compliment strengths to achieve a common goal, solve problems, gain insights, and create value.
Leading organizations are taking a new tack, and are at a crossroads with respect to AI strategy despite the apocalyptic prediction about Human jobs being traded by machine intelligence,many life sciences companies are behind the maturity curve in the adoption of automation.
By understanding these considerations, Bio-Pharmaceutical Organizations can pursue Automation opportunities more assertively and potentially trounce the risks of falling behind competitors in technology adoption.