Enhancing Access To And Sharing Of Data Reconciling Risks And Benefits For Data Re Use Across Societies

This report examines the opportunities of enhancing access to and sharing of data (EASD) in the context of the growing importance of artificial intelligence and the Internet of Things. It discusses how EASD can maximise the social and economic value of data re-use and how the related risks and challenges can be addressed. It highlights the trade-offs, complementarities and possible unintended consequences of policy action – and inaction. It also provides examples of EASD approaches and policy initiatives in OECD countries and partner economies.

This report examines the opportunities of enhancing access to and sharing of data (EASD) in the context of the growing importance of artificial intelligence and the Internet of Things. It discusses how EASD can maximise the social and economic value of data re-use and how the related risks and challenges can be addressed. It highlights the trade-offs, complementarities and possible unintended consequences of policy action - and inaction. It also provides examples of EASD approaches and policy initiatives in OECD countries and partner economies.

This Digital Government Review of Slovenia explores how the Government of Slovenia could enhance and harness digital government to achieve broader strategic goals. It evaluates the efforts made so far by the Slovenian government in shifting towards a digital government approach by looking at institutional governance, institutional digital talent, public service delivery and the strategic use of data.

This report presents current policy practice to promote access to publicly funded data for science, technology and innovation, as well as policy challenges for the future. It examines national policies and international initiatives, and identifies seven issues that require policy attention.

COVID-19 has hit the Polish society and its economy hard, even if to a lesser extent than other European countries. Employment has declined and public debt has increased abruptly, which will make it more challenging to solve long-term issues, such as the low productivity of some workers, weak environmental outcomes and rising ageing costs.

This progressive book critically analyses the current state of data protection enforcement and proposes a new auditable framework of practical guidelines to contribute to a more sustainable data-driven future. In outlining the debates relating to current data protection structures, Paolo Balboni and Kate Elizabeth Francis argue that legislation alone cannot sufficiently protect individuals’ fundamental rights and freedoms, and instead consider the pressing need for a more ethical approach to data protection.

The OECD Digital Economy Outlook 2020 examines trends and analyses emerging opportunities and challenges in the digital economy. This third edition of the OECD Digital Economy Outlook provides a holistic overview of converging trends, policy developments and data on both the supply and demand sides of the digital economy. It illustrates how the digital transformation is affecting economies and societies. Finally, it provides a special focus on how the COVID-19 pandemic is amplifying opportunities and challenges from the digital transformation.

Federated Learning: Theory and Practice provides a holistic treatment to federated learning, starting with a broad overview on federated learning as a distributed learning system with various forms of decentralized data and features. A detailed exposition then follows of core challenges and practical modeling techniques and solutions, spanning a variety of aspects in communication efficiency, theoretical convergence and security, viewed from different perspectives. Part II features emerging challenges stemming from many socially driven concerns of federated learning as a future public machine learning service, and Part III and IV present a wide array of industrial applications of federated learning, including potential venues and visions for federated learning in the near future. This book provides a comprehensive and accessible introduction to federated learning which is suitable for researchers and students in academia and industrial practitioners who seek to leverage the latest advances in machine learning for their entrepreneurial endeavors Presents the fundamentals and a survey of key developments in the field of federated learning Provides emerging, state-of-the art topics that build on fundamentals Contains industry applications Gives an overview of visions of the future