𝗕𝗮𝗹𝗮𝗻𝗰𝗶𝗻𝗴 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻, 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 & 𝗥𝗲𝗴𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗶𝗻 𝗔𝗜/𝗠𝗟: 𝟯 𝗴𝗼𝘃𝗲𝗿𝗻𝗶𝗻𝗴 𝗽𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲𝘀

Effective tech governance isn’t just about rules—it’s about creating a symbiosis between human values and technological progress. Balancing Innovation, security and regulation will be key to achieve a delicate equilibrium in companies as AI/ML takes center stage in areas ranging from coding to hiring and selling to banking.

As we stand on the brink of unprecedented technological advancements, it’s crucial to ask ourselves: Are we truly governing these innovations in a way that benefits society?
Here are three governing principles that should guide corporations as they embrace the waves of emerging technologies:

(𝗮) 𝗛𝘂𝗺𝗮𝗻 𝗖𝗲𝗻𝘁𝗿𝗶𝗰 𝗙𝗼𝗰𝘂𝘀
Adopting human centric focus, leading with fairness, and with a clear purpose is paramount. The emerging technologies are supposed to work for human beings, augment human capabilities and create a better society.
The governance mechanism should not allow deep techs including AI to compromise on fairness, equality, non-discrimination or any such aspects that perpetuate biases.

(𝗯) 𝗕𝗮𝗹𝗮𝗻𝗰𝗶𝗻𝗴 𝗜𝗻𝗱𝗶𝘃𝗶𝗱𝘂𝗮𝗹 𝗮𝗻𝗱 𝗖𝗼𝗹𝗹𝗲𝗰𝘁𝗶𝘃𝗲 𝗥𝗶𝗴𝗵𝘁𝘀
Individual rights are as important as the rights of the larger communities. The governing mechanisms need to preserve and respect the human dignity by not unduly influencing human decision making or processes. Human autonomy and human dignity are crucial at any given situation. How advance the technology may be, it should not be allowed to manipulate its human masters. Preserving free will in an increasingly AI-influenced environment is crucial.

(𝗰) 𝗗𝗮𝘁𝗮 𝗧𝗿𝗮𝗻𝘀𝗽𝗮𝗿𝗲𝗻𝗰𝘆 𝗮𝗻𝗱 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝘁𝗵𝗮𝘁 𝗰𝗮𝗻 𝗯𝗲 𝗔𝘂𝗱𝗶𝘁𝗲𝗱
While, adopting advanced technology and data governance, any governing principles that will fail on data transparency and security may ring a death bell for the organization. Hence, putting in place a fool-proof mechanism is vital for both organisation and the larger stakeholder ecosystem.

When required, the organizations should be comfortable to answer transparently and with accountability. Organisation need to develop a competent risk assessment and management system and ensure there is an efficient data governance system in place.

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