Five critical questions to explain Explainable AI. Getting started on your Responsible AI journey
In a recent conference on Responsible AI for Social Empowerment (RAISE), held in India, the topic of discussion was on explainable AI. Explainable AI is a critical element of the broader discipline of responsible AI. Responsible AI encompasses ethics, regulations, and governance across a range of risks and issues related to AI including bias, transparency, explicability, interpretability, robustness, safety, security, and privacy.
Interpretability and explainability are closely related topics. Interpretability is at the model level with an objective of understanding the decisions or predictions of the overall model. Explainability is at an individual instance of the model with the objective of understanding why the specific decision or prediction was made by the model. When it comes to explainable AI we need to consider five key questions — Whom to explain? Why explain? When to explain? How to explain? What is the explanation?
Keeping up in the new silicon-based survival of the fittest
There are many intersections and overlaps between AI and data science. AI has numerous subsets, like Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP). With many career opportunities in both fields, there are lots of conflicting perspectives on educational paths for starting a career in one of these fields.
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
XAI Is helping to create a shared understanding between AI and the people who rely on it. Artificial Intelligence (AI) has become an integral part of everything we do. Right from suggesting what to buy on Amazon to recommending the songs on Spotify. Chatbots have made our customer service operations way too simpler. In the recent pandemic, we have even seen governments using AI to detect face mask violations.
Pretty much all AI/ML customer and transactional models have been on pause for the last few months. As we speak, history is being written…