In the ever-evolving landscape of technology, emerging innovations are reshaping the way we collect, store, analyze and leverage data. From artificial intelligence (AI) and machine learning to blockchain and the Internet of Things (IoT), these technologies are revolutionizing the world of data. Data Science Central brought this interesting topic to us in their article, “The impact of emerging technologies on data excellence.”
As we navigate this rapidly evolving landscape, responsible and ethical use of these technologies will be key to harnessing their full potential for the benefit of society. The convergence of emerging technologies is reshaping the world of data, offering unprecedented opportunities for innovation across industries. While challenges exist, the responsible adoption of these technologies promises a future where data becomes a powerful tool for positive change.
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. |
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Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.
