Software Product Development Maturity Model

whitePaper | August 26, 2022

Started in 2013, Arya.ai is the first deep learning (DL) startup in India and has been one of the very early adopters to use DL in Financial Institutions. AryaXAI by Arya.ai, a full stack ML Observability platform, offers multiple components - AI explainability, ML monitoring, ML audit and Policy controls, which organisations require beyond simple ML monitoring tools.

whitePaper | February 23, 2023

In December 2022, Rackspace Technology® polled 1,420 IT professionals throughout the world and across multiple industry verticals. Survey respondents worked in financial services, manufacturing, retail, hospitality, government and healthcare in the Americas, Europe, Asia and the Middle East.

whitePaper | December 30, 2022

The technological development of artificial intelligence (AI) is proceeding rapidly, with investment in AI-based solutions dramatically increasing across the globe. Europe is no exception.

whitePaper | October 26, 2022

The Blueprint for an AI Bill of Rights: Making Automated Systems Work for the American People was published by the White House Office of Science and Technology Policy in October 2022. This framework was released one year after OSTP announced the launch of a process to develop “a bill of rights for an AI-powered world.” Its release follows a year of public engagement to inform this initiative. The framework is available online at: https://www.whitehouse.gov/ostp/ai-bill-of-rights

whitePaper | May 12, 2023

Onward’s mission is to develop bold and practical ideas to boost economic opportunity, build national resilience, and strengthen communities across all parts of the United Kingdom. Our vision is to address the needs of the whole country: young and old, urban and rural, for all communities across the UK – particularly places that have too often felt neglected or ignored by Westminster. We believe in an optimistic conservatism that is truly national – one that recognises the value of markets, supported by a streamlined state that is active not absent. We are unapologetic about standing up to vested interests, putting power closer to people, and supporting the hardworking and aspirational.

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.