Enterprise Use of Artificial Intelligence and Machine Learning

whitePaper | December 15, 2019

The debate between experts over how automation will affect the future of work has been one of the most active cottage industries in labor economics in recent years. Numerous scholars forecast major disruptions of human work; others minimize those impacts. And yet, the field has nevertheless managed to generate a number of shared insights, with none more consistent than the finding that least welloff will suffer automation’s greatest shocks on the labor market.

whitePaper | November 3, 2022

At Land O’Lakes, a member-owned cooperative agribusiness, farmers are using data and artificial intelligence to make smarter decisions. Over the past 30 years, corn farmers have used advances in bioengineering, chemicals, and analytics to boost their average yields by 50%, from 120 to 180 bushels per acre. T

whitePaper | July 20, 2022

In recent years, the use of AI in organisations has drastically increased. As a result, lawmakers around the world have been paying close attention to the developments in the field of AI too. While there is no comprehensive legal body in Switzerland and the EU that regulates the use of AI today, there are clear signs that Swiss and European organisations should prepare for stricter regulation.

whitePaper | June 9, 2022

Artificial Intelligence (AI) powered Analytics is taking data management to the next level for almost all industry sectors without having to rely on technical staff or data scientists. Technology is helping create blue ocean opportunities amidst red ocean realities.

whitePaper | January 11, 2023

Improving the trustworthiness of artificial intelligence (AI) systems is a shared priority for the private and public sectors, as indicated by prolific research and guidelines in recent years.

whitePaper | January 28, 2022

Since more and more decisions that used to be made by humans are nowadays made either with the help of Artificial Intelligence (AI) or by AI alone, it is essential that the AI algorithms are “fair.” In this whitepaper, we discuss issues surrounding the fairness of AI applications, with a special focus on how it can be assessed independently and subsequently certified. We explain why an AI application cannot be classified – and subsequently certified – as “fair” or “unfair” in a general sense and propose an approach that makes it possible to classify it as “fair” or “unfair” under the (application)-specific definition of fairness.