The introduction of artificial intelligence (AI) at a company can lead to increased complexity as well as the greater potential

In my blog post, I will be exploring the topic of explainable AI in more detail and demonstrating why this technology will be critical for the acceptance of machine and deep learning applications and to the future as well.

After taking a bird’s eye view of the holistic framework of trustworthy AI in the first blog post of this series, I would now like to delve deeper into the topic. In this blog post, I will take a look at the core requirement in the trustworthy AI field, namely ‘trust’. I will also elaborate on aspects regarding the division of labour between humans and machines.

Artificial intelligence is set to transform our lives. The task of UX design is to strengthen trust in AI-driven software and, above all else, increase our quality of life in the future. The following blog post explores key questions and describes the best methods to find solutions to them.

The trustworthy characteristics of an artificial intelligence (AI) are addressed in the context of Trustworthy AI. The spectrum of requirements for Trustworthy AI ranges from the AI’s design to its functions, all the way to its operation. At this point, you’re justifiably asking yourself: where should we start, and where’s the end? A holistic framework is used to create an overview, which, in turn, can be broken down into small parts. In my blog post, I’ll briefly present such a framework and highlight individual aspects of it.

The field of artificial intelligence (AI) is arguably the biggest technological driver of the future, but projects often fail due to the complexity of their implementation or a lack of experts. In the first part of this series, we tried to answer the question of how low-code platforms can facilitate AI adoption. In this part, we will now take look at intelligent process automation – a combination of different technologies: artificial Intelligence, low code and robotic process automation (RPA). What are the advantages of using this combination? Using a well-known use case with SAP, we will introduce you to the advantages of intelligent process automation to optimise workflows.

To ensure that AI initiatives don’t fall short of their objectives, insurance providers need to take a holistic approach that also includes people – both customers and employees. As I’ve mentioned in a few of my previous blog posts, there are quite a number of challenges involved in deploying AI-based systems. This blog post deals with the specifics of the approach and how it differs from traditional projects. I will not go into regulatory aspects in this post.

The field of artificial intelligence is arguably the biggest technological driver of the future, but projects often fail due to the complexity of their implementation or a lack of experts. In the first part of this blog series, we take a look at how low-code platforms as a disruptive innovation in software development can make adopting AI easier and show you two use cases to demonstrate how this technology is contributing to the ‘democratisation of AI’.