Understanding the Dynamics of artificial intelligence in Intellectual Property.

whitePaper | October 20, 2022

The digital evolution of the financial services (FS) industry is heavily reliant on having quality information and analytics to deliver services to customers and manage operations in an efficient and risk-appropriate manner.

whitePaper | January 28, 2022

Since more and more decisions that used to be made by humans are nowadays made either with the help of Artificial Intelligence (AI) or by AI alone, it is essential that the AI algorithms are “fair.” In this whitepaper, we discuss issues surrounding the fairness of AI applications, with a special focus on how it can be assessed independently and subsequently certified. We explain why an AI application cannot be classified – and subsequently certified – as “fair” or “unfair” in a general sense and propose an approach that makes it possible to classify it as “fair” or “unfair” under the (application)-specific definition of fairness.

whitePaper | November 1, 2019

It's futile to deny it, but Artificial Intelligence (AI) is no longer the buzzword of tomorrow, it's a striking reality of today, and the enterprise landscape of AI has never looked more promising than it does today! Indian Enterprise Market for AI to be estimated to be $100 million, growing at 200-250% CAGR. Futuristic growth of this sort clearly underscores the potential in the big revolution that business leaders should prepare for!

whitePaper | December 23, 2022

The transformative potential of artificial intelligence (AI) is a kind of truism. Seeking to capture the benefits of the “Fourth Industrial Revolution” or “third wave of the digital revolution,” countries are prioritizing efforts to reorganize their public and private sectors, fund research and development (R&D), and establish structures and policies that unleash AI innovation.

whitePaper | June 13, 2022

As businesses move beyond rigid rules and strictly linear processes in IT service management, there’s a world of opportunity for artificial intelligence-powered automation in both proactive and reactive service delivery. We discuss what that smart tech-driven world can look like and how you can get there.

whitePaper | July 20, 2022

The growing diversity of actors and circumstances involved in AI/ML deployment makes establishing a set of ethical participatory practices especially difficult for this field. Even among practitioners working at the same organization, there can be substantial differences in both their knowledge about how AI/ML systems were created or will be used and their ability to incorporate inclusive practices. Additionally, the greater availability of AI development platforms, including “no-code” platforms, means that algorithmic models can be deployed without having deep expertise, expanding the number of circumstances automated systems are deployed in. This means many more instances where automated systems are being deployed without consideration of how the algorithms were developed, the provenance of the datasets and nature of the bias on which they were trained and tested, and the ethical implications of their development and deployment.