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.

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OTHER WHITEPAPERS
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CIO vision 2025: Bridging the gap between BI and AI

whitePaper | September 23, 2022

It’s been several years since organizations began adopting artificial intelligence (AI) to improve their business; few have come close to mastering its existing capabilities. A small number of organizations in our research aim to become AI-driven—a status we define as AI and machine learning underpinning almost everything the enterprise does—by 2025. However, this elite group—who we term “AI leaders”1—as well as the many others looking simply to embed AI more firmly in the enterprise foundations face formidable challenges to achieving their objectives.

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Implementation Challenges to Three Pillars of America’s AI Strategy

whitePaper | December 23, 2022

The transformative potential of artificial intelligence (AI) is a kind of truism. Seeking to capture the benefits of the “Fourth Industrial Revolution” or “third wave of the digital revolution,” countries are prioritizing efforts to reorganize their public and private sectors, fund research and development (R&D), and establish structures and policies that unleash AI innovation.

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Why Automation and AI Will Define the Future World of Work

whitePaper | June 16, 2022

As companies continue their digital transformation journey, it’s clear that automation and artificial intelligence (AI) are now a competitive imperative. Companies can no longer ignore the gains intelligent automation solutions deliver. Such solutions free up employees from repetitive tasks, making them available for more valuable work. Automation and AI tools also enable companies to harness the value of their own data for competitive advantage while automating its processing.

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Leveraging a comprehensive reference architecturefor AI that significantly reduces time-to-insight

whitePaper | September 29, 2021

Penguin Computing’s Analytics Practice acts as a single point of reference for hardware, software, architectural design, and much more, enabling organizations to focus their energy on their AI projects. Access this white paper to learn more about this secure, end-to-end solution designed to alleviate AI infrastructure woes.

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Delivering Exceptional Customer Experience Through Your Contact Center

whitePaper | October 3, 2022

Contact center associates deal with complex incall tasks, across multiple systems. High staff turnover is common, and training up new staff can take weeks or even months. These challenges can quickly begin to affect engagement, performance and KPIs. With a cohesive digital strategy, your Digital Workforce has instant access to all customer information from one system, meeting the customer’s expectation of immediacy.

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HFS Enterprise AI Services Top 10

whitePaper | January 12, 2020

“The services market for artificial intelligence technologies is rapidly maturing on the back of several years of learning and a realization—delivering AI is unlike delivering any other technology thus far. Delivering on the promise of AI calls for far more collaboration between service providers, tech vendors, and enterprise clients.” The biggest differentiator in enterprise AI services, as described by most of the customer leaders, is the quality of people—not just the quantity available for a specific skill. Domain understanding and data engineering capabilities are top priorities. A culture of innovation, experimentation, collaboration, and co creation with customers is the key winning formula here.”

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