Tag Archives: ethical ai

IIT Madras Fellowship in AI for Social Good

IIT Madras AI Fellowship for Social Good

Are you an AI researcher driven by the passion to make a positive impact on society? Do you seek to use your knowledge in machine learning and AI to contribute to real-world issues? Are you intrigued by the idea of joining a leading interdisciplinary research center for data science in India? Then here is the opportunity to discover a unique opportunity that aligns with your aspirations and expertise at the Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI), IIT Madras. Apply Now for fellowship program in AI for social good. About RBCDSAI RBCDSAI is one of India’s pre-eminent interdisciplinary research academic centers specializing in Data Science and AI. …

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Posted in AI, Career Planning, Data Science, Ethical AI, Machine Learning, Online Courses. Tagged with , , , .

Facebook Responsible AI: Lessons, Examples

meta facebook responsible ai examples lessons

As technology continues to advance, it’s important that we prioritize ethical considerations and ensure that the development and deployment of AI technologies are responsible and fair. Meta (formerly known as Facebook) recognizes the importance of responsible AI and has taken several steps to ensure that their AI systems are developed and deployed in an ethical and fair manner. In this blog post, we’ll be exploring the latest responsible AI updates from Meta, which every company should take into consideration when developing and implementing their own AI strategies and systems. I will keep the blog short and crisp. If you want greater details, visit this page. Use Varied Datasets & Robust …

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Posted in AI, Ethical AI, Responsible AI. Tagged with , .

Artificial Intelligence (AI) for Telemedicine: Use cases, Challenges

In this post, you will learn about different artificial intelligence (AI) use cases of Telemedicine / Telehealth including some of key implementation challenges pertaining to AI / machine learning. In case you are working in the field of data science / machine learning, you may want to go through some of the challenges, primarily AI related, which is thrown in Telemedicine domain due to upsurge in need of reliable Telemedicine services. What is Telemedicine? Telemedicine is the remote delivery of healthcare services, using digital communication technologies. It has the potential to improve access to healthcare, especially in remote or underserved communities. It can be used for a variety of purposes, including …

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Posted in AI, Data Science, Healthcare, Machine Learning, Telemedicine. Tagged with , , , , , .

Ethical AI Principles – IBM, Google, Intel, Microsoft

microsoft ethical ai principles

In this post, you will get a quick glimpse of ethical AI principles of companies such as IBM, Intel, Google, and Microsoft. The following represents the ethical AI principles of companies mentioned above: IBM Ethical AI Principles: The following represents six ethical AI principles of IBM: Accountability: AI designers and developers are responsible for considering AI design, development, decision processes, and outcomes. Value alignment: AI should be designed to align with the norms and values of your user group in mind. Explainability: AI should be designed for humans to easily perceive, detect, and understand its decision process, and the predictions/recommendations. This is also, at times, referred to as interpretability of AI. Simply …

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Machine Learning Models – Bias Mitigation Strategies

Machine learning models - Bias mitigation strategies

In this post, you will learn about some of the bias mitigation strategies which could be applied in ML Model Development lifecycle (MDLC) to achieve discrimination-aware machine learning models. The primary objective is to achieve a higher accuracy model while ensuring that the models are lesser discriminant in relation to sensitive/protected attributes. In simple words, the output of the classifier should not correlate with protected or sensitive attributes. Building such ML models becomes the multi-objective optimization problem. The quality of the classifier is measured by its accuracy and the discrimination it makes on the basis of sensitive attributes; the more accurate, the better, and the less discriminant (based on sensitive attributes), the better. The following are some of …

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Posted in AI, Data Science, Machine Learning. Tagged with , , .