Over at #gartnerpeercommunity, many of us are attempting to find ways to Strike a Balance with Responsible #AI Governance!
Here is a quick overview of a much larger conversation.
In the dynamic realm of generative AI tools, crafting a robust governance model is a strategic imperative.
Tailoring a governance framework that marries innovation while building in clarity with ethics is the cornerstone of success. A high-level, tiered structure empowers users while ensuring compliance and risk mitigation.
Cross-functional collaboration is non-negotiable. Legal, IT, data science, ethics – all voices matter in shaping a holistic perspective.
Embrace the evolving nature of AI landscapes, especially, tried and tested approaches like Intelligent Automation and even LLM models to drive new innovative angles. A continuous “growth” learning mindset paves the way for adapting to emerging challenges and opportunities.
Recognize the varying digital savviness of your team. Comprehensive training is key to informed decision-making and minimizing unintended consequences. Again it’s not “Fire” it’s Don’t “Hire”. – No one should hire just to hire, hire with intent and drive for candidates with passion, and bring the customer to the center of the conversation.
: Ethical review processes, transparency, and alignment/accountability are the cornerstones of a responsible AI journey, or in reality any professional journey. Upholding principles of fairness and bias mitigation is paramount. ⚖️ It’s important to call out that “all humans” are biased. Until we can create and adopt “Brave Spaces” with open communication and no more finger-pointing, yet drive as a team toward solutions. Then why would anyone be surprised that “AI is biased”.
Curious to dive deeper? Join the conversation on Gartner Peer Experiences where we’re unraveling the nuances of AI governance. Let’s champion an ecosystem where innovation thrives responsibly.
#AIgovernance #EthicalAI #ai #gartner
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