Breaking Barriers With Ai Empowering Latin America Through Machine Learning

Discover how artificial intelligence and machine learning are revolutionizing Latin America, breaking down barriers to economic growth, social progress, and technological innovation, and paving the way for a brighter, more equitable future.

Governments can use artificial intelligence (AI) to design better policies and make better and more targeted decisions, enhance communication and engagement with citizens, and improve the speed and quality of public services. The Latin America and the Caribbean (LAC) region is seeking to leverage the immense potential of AI to promote the digital transformation of the public sector.

Governments can use artificial intelligence (AI) to design better policies and make better and more targeted decisions, enhance communication and engagement with citizens, and improve the speed and quality of public services. The Latin America and the Caribbean (LAC) region is seeking to leverage the immense potential of AI to promote the digital transformation of the public sector. The OECD, in collaboration with CAF, Development Bank of Latin America, prepared this report to help national governments in the LAC region understand the current regional baseline of activities and capacities for AI in the public sector; to identify specific approaches and actions they can take to enhance their ability to use this emerging technology for efficient, effective and responsive governments; and to collaborate across borders in pursuit of a regional vision for AI in the public sector. This report incorporates a stocktaking of each country's strategies and commitments around AI in the public sector, including their alignment with the OECD AI Principles. It also includes an analysis of efforts to build key governance capacities and put in place critical enablers for AI in the public sector. It concludes with a series of recommendations for governments in the LAC region.

Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts. [Publisher summary, ed]

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

After a long time of neglect, Artificial Intelligence is once again at the center of most of our political, economic, and socio-cultural debates. Recent advances in the field of Artifical Neural Networks have led to a renaissance of dystopian and utopian speculations on an AI-rendered future. Algorithmic technologies are deployed for identifying potential terrorists through vast surveillance networks, for producing sentencing guidelines and recidivism risk profiles in criminal justice systems, for demographic and psychographic targeting of bodies for advertising or propaganda, and more generally for automating the analysis of language, text, and images. Against this background, the aim of this book is to discuss the heterogenous conditions, implications, and effects of modern AI and Internet technologies in terms of their political dimension: What does it mean to critically investigate efforts of net politics in the age of machine learning algorithms?