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ARTIFICIAL INTELLIGENCE AND AUTONOMOUS SYSTEMSLEGAL UPDATE (2Q19)

July 23, 2019

The second quarter of 2019 saw a surge in debate about the role of governance in the AI ecosystem and the gap between technological change and regulatory response. This trend was manifested in particular by calls for regulation of certain “controversial” AI technologies or use cases, in turn increasingly empowering lawmakers to take fledgling steps to control the scope of AI and automated systems in the public and private sectors. While it remains too soon to herald the arrival of a comprehensive federal regulatory strategy in the U.S., there have been a number of recent high-profile draft bills addressing the role of AI and how it should be governed at the federal level, while state and local governments are already pressing forward with concrete legislative proposals regulating the use of AI.

Spotlight

Forward Networks, Inc

Forward Networks delivers an innovative platform that provides network visibility, policy verification, and change modeling. Designed to help network teams eliminate costly network outages, the Forward Networks platform enables engineers and operators to easily visualize and search complex networks, quickly debug problems, verify network-wide policy correctness, and predict network behavior prior to making changes to production equipment — for legacy, SDN, or hybrid environments.

OTHER WHITEPAPERS

A New Technology Stack

whitePaper | November 23, 2022

Over the last four decades, the information technology industry has grown from about $50 billion globally in 1980 to more than $4 trillion. During this time, the IT industry has experienced the transition from mainframe computing to minicomputers, to personal computing, to internet computing, and to handheld computing.

THE NEED FOR EFFECTIVE INCIDENT RESPONSE

whitePaper | June 23, 2020

Modern organizations face unprecedented threats to their critical information assets and data. In previous years, the mindset of many cybersecurity professionals and business leaders was focused on avoiding attacks and building a strong perimeter to deflect them. However, more recently this approach has shifted, and these leaders now understand that attacks are inevitable. With this fundamental shift in thinking, cybersecurity professionals must build strong incident response programs that are capable of detecting threats in a timely manner and responding effectively when they occur.

Tame the Boom-and-Bust Cycle of Lending with Low-Code

whitePaper | October 18, 2022

If you have worked in lending for even just the past year, you have already experienced its cyclical nature. Take mortgage lending, for example. Less than a year ago, the main problem facing mortgage originators was how to process high volumes of applications while still observing regulatory compliance and conformance to underwriting policies.

Dell PowerScale: Key Performance Prediction using Artificial Intelligence for IT Operations (AIOps)

whitePaper | September 28, 2022

Architecting IT infrastructure has never been more challenging than it is today. Many enduser workloads, such as semiconductor design, autonomous driving development, and life sciences and healthcare are growing more complex every day. With that complexity comes growing demand on IT.

Into the era of secure remote work

whitePaper | April 14, 2021

While the new era of remote work has provided some businesses with surprising productivity boosts as high as 13%, many are still struggling to secure their suddenly expanded network of remote endpoints and IT resources against a growing onslaught of cyberthreats.

Trusted Artificial Intelligence Towards Certification of Machine Learning Applications

whitePaper | March 30, 2022

Artificial Intelligence is one of the fastest growing technologies of the 21st century and accompanies us in our daily lives when interacting with technical applications. However, reliance on such technical systems is crucial for their widespread applicability and acceptance. The societal tools to express reliance are usually formalized by lawful regulations, i.e., standards, norms, accreditations, and certificates. Therefore, the TÜV AUSTRIA Group in cooperation with the Institute for Machine Learning at the Johannes Kepler University Linz, proposes a certification process and an audit catalog for Machine Learning applications.

ARTIFICIAL INTELLIGENCE AND AUTONOMOUS SYSTEMSLEGAL UPDATE (2Q19)