Ethics in Data Science and AI is a crucial component of delivering an AI Strategy. It also impacts diversity and inclusion in various parts of running a business, from hiring through to designing products, marketing and retaining customers. It also affects issues such as bias. In this session, we will examine the complexities involved in ethics, with a focus on bias, and look at ways in which Microsoft technology can be deployed to tackle bias in AI and Data Science.


How are artificial intelligence and data visualization connected? It’s the data. Data is everything to AI, and AI does not happen without the data. For the business to make use of AI, Data visualization is essential because it communicates insights from the data. For Artificial Intelligence, data visualization is particularly important since the concepts and data are complex, and data visualization is crucial to lead the business to articulate and understand difficult concepts. This is particularly crucial when we think about ethics and explainability; people have to understand AI first, and then they can consider the impact and ethics.


There are many great new technologies in Microsoft which offer opportunities for businesses to use AI, but we need to close the loop so that the insights are not lost. In this session, we will look at Microsoft Power BI, and open source technologies such as R and Python in Azure for AI and data visualization, along with best practices for visualizing data for artificial intelligence.

 

You will learn AI concepts in Power BI, and how Power BI can be used to help with explainability in AI.

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