As artificial intelligence (AI) continues to revolutionize industries with its transformative capabilities, the importance of effective data governance has become more evident than ever. Lexology brought this interesting topic to our attention in their article, “What is AI Governance?“
The symbiotic relationship between AI and data governance, emphasizing the critical role of the latter in ensuring ethical, transparent, and responsible use of data in the age of advanced analytics.
In the AI-driven era, data governance emerges as the bedrock of responsible and ethical AI practices. Organizations that prioritize data governance alongside AI development pave the way for innovative, transparent, and socially responsible AI applications.
The seamless integration of data governance with AI is paramount to navigating the complex landscape of advanced analytics. As organizations continue to harness the power of AI, adopting robust data governance practices becomes not only a necessity for compliance but a strategic imperative for building trust and ensuring the responsible use of data in shaping our AI-driven future.
The biggest challenge is that most organizations have little knowledge on how AI systems make decisions and how to interpret AI and machine learning results. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms. Explainable AI is used to describe an AI model, its expected impact, and it potential biases. Why is this important? Because explainability becomes critical when the results can have an impact on data security or safety.
Melody K. Smith
| Data Harmony is an award-winning semantic suite that leverages explainable AI. |
|
Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.
