Let's Talk AI

Interdisciplinarity Is a Must


Let's Talk AI
Let's Talk AI
CC BY

Book Details

Authors Barbara Steffen, Edward A. Lee, Bernhard Steffen
Publisher Springer
Published 2025
Edition 1st
Paperback 317 pages
Language English
ISBN-13 9783032090072, 9783032090089
ISBN-10 3032090075, 3032090083
License Creative Commons Attribution

Book Description

This unique open access volume represents an interdisciplinary dialog with top-class researchers and practitioners on the Artificial Intelligence revolution. The contributions derive from structured interviews with community leaders who examine recent developments in AI and offer predictions about its impact on science, technology, business, and society. The interviewees, leading thinkers and practitioners from fields such as Computer Science, Software Engineering, Philosophy, Psychology, and Law, gathered at the multidisciplinary event AISoLA, where they discussed developments in AI technologies, tools, and research, and these exchanges were shaped into this coherent survey.

In the debates surrounding the rapid advancement of AI it's clear that while there is much sharing of ideas, in fact true cooperation and alignment is rare, most fields still operate in silos. Given the pervasive nature of AI, it's critical that we move forward carefully to ensure that our decisions and progress are well-considered. This book serves as a call to action, reminding us of our collective responsibility to shape the future. The authors offer points of agreement and contrast, the reader will better understand how we may still maintain control over technological progress in AI and its societal impact.


This book is available under a Creative Commons Attribution license (CC BY), which means that you are free to copy, distribute, and modify it, as long as you give appropriate credit to the original author.

If you enjoyed the book and would like to support the author, you can purchase a printed copy (hardcover or paperback) from official retailers.

Download and Read Links

Share this Book

[localhost]# find . -name "*Similar_Books*"


The AI Ladder

AI may be the greatest opportunity of our time, with the potential to add nearly $16 trillion to the global economy over the next decade. But so far adoption has been much slower than anticipated. With this practical report, business leaders will discover where they are in their AI journey and learn the steps they still need to take to implement an

The SysAdmin Handbook

Server

Over the past two years, Simple-Talk has published articles on a variety of SysAdmin topics, from Exchange to Virtualization, and including everything from Powershell to Unified Messaging. We have brought the best of these articles together to form The SysAdmin Handbook. With over fifty articles packed into this book, it will be an essential refere

AI for Mass-Scale Code Refactoring and Analysis

Analysis

As the software development landscape evolves, the challenge of managing and refactoring extensive code bases becomes increasingly complex. AI methods of code refactoring, while effective for smaller scales, can falter under the weight of mass-scale operations. The need for efficiency, accuracy, and consistency is more critical than ever. This key

Applied AI for Enterprise Java Development

Java

As a Java enterprise developer or architect, you know that embracing AI isn't just optional - it's critical to keeping your competitive edge. The question is, how can you skillfully incorporate these groundbreaking AI technologies into your applications without getting mired in complexity? Enter this clear-cut, no-nonsense guide to integrating gene

Achieving Real Business Outcomes from Artificial Intelligence

Artificial intelligence is already changing industry landscapes, with early adopters reporting benefits in high-value business cases such as fraud detection, preventative maintenance, and recommendation engines. Yet working on an AI initiative is demanding for many enterprises, whether you're in the middle of the process or just getting started. Th

Accelerating AI with Synthetic Data

Recently, data scientists have found effective methods to generate high-quality synthetic data. That's good news for companies seeking large amounts of data to train and build artificial intelligence and machine learning models. This report provides an overview of synthetic data generation that not only focuses on business value and use cases but a