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Exploring the Moral and Ethical Perspective of a Dataset while Building an Explainable AI Solution
Developing AI code in the 2010s relied on knowledge and talent. Developing AI code in the 2020s implies the accountability of XAI for every aspect of an AI project. It includes moral, ethical, legal, and technical perspectives, all for building an explainable AI solution. [Related article:... Read more
Responsible Data Science & AI – Challenges and Steps Towards a Practical Implementation
After major incidents, such as the Cambridge Analytica scandal and the alleged racial bias in the COMPAS system that assessed potential recidivism risk in the US, the call for responsible data science & AI frameworks increased. Books as weapons of math destruction, the black box society,... Read more
Responsible AI: Hype vs. Reality and Designing Responsibly at Every Stage of AI
AI is increasingly being applied to business-critical use cases at companies across multiple industries, but the highest-performing algorithms are often black boxes, leading to a lack of transparency. This has led to a growing number of high-profile cases of allegedly biased AI algorithms in industries ranging... Read more
Responsible AI 2020: Expectations for the Year Ahead
In 2020, enabling responsible application of AI technologies is one of the field’s foremost challenges as it transitions from research to practice. More and more, we’re hearing of researchers and practitioners from disparate disciplines highlighting the ethical and legal challenges posed by the use of AI... Read more