We recently published our new monitor, where we asked 1682 Flemish people how they stand on data-driven technologies in the public space. This brAInfood summarises the main results.
In this brAInfood, we highlight various regulatory regimes which should be taken into account at different stages of the lifecycle of an AI system in a practical overview.
In this brAInfood, we explore the importance of employee engagement for successful AI technology adoption.
In this brAInfood, we elaborate on the tasks and organisation of Athumi under its founding decree. We discuss the provision of personal data vaults and SOLID.
In this brAInfood, you can read more about which AI technology determines what your Instagram Discover page looks like and how you can have a say in what it looks like.
Smart home technologies are largely present in our households. How exactly do these technologies work, how do they handle your data and what are the consequences for your privacy?
What are important points of attention in change processes when data-driven innovations or AI are implemented in an organisation? In this brAInfood, we explain why it is important to give employees a voice and a fundamental role and let them actively participate in such a change process, and how you can do this.
Data Governance Act, Digital Services Act and Digital Markets Act: overview of key concepts, potential impact and the obligations.
Which AI systems are used in education and what are the results? Who is (in)directly involved in the development and use of those systems, and with what data are they fed? Read more about it in this brAInfood, along with what you as a teacher can do with AI and what you should pay attention to.
In this brAInfood, we look at 'operator assistance technologies': what are they and how valuable are they?
In this brAInfood you will find out how you can ensure that your next of kin can access your digital data after your death, if you wish, of course.
Does the computer give you the job you deserve? AI systems that make important decisions for you can sometimes reaffirm existing biases. By applying fairness notions, developers can address this. We introduce some of these notions to you.
In this brAInfood, we provide a brief introduction to text-to-x generators and explain some legal considerations in terms of copyright
In this brAInfood, we highlight the different aspects and principles to verify whether an AI system is reliable.
In this brAInfood, we take a closer look at the competency model "What qualifications are needed to develop responsible systems?".
The brAInfood series is being translated into several languages thanks to CLAIRE. You can read more about it in this blog post.
In this brAInfood, you can check whether your AI system is forbidden according to the AI Act or not.
In this brAInfood you can read more about the setup of a Datawalk and take a look at some examples of data hubs that you can encounter in the city.
In this brAInfood, we take a closer look at the possible legal restrictions you may encounter when using data.
In this brAInfood, we explain more about Industry 4.0.
In this brAInfood, we will look at how you can take digital inclusion into account in the development of your new product or service.
In this brAInfood, we take a closer look at Mobility as a Service, a new mobility model based on data.
In this brAInfood, we take a closer look at fitness trackers. What do they do? What to pay attention to when using fitness trackers?
In this brAInfood, we briefly explain a number of types of transparency, and how best to tackle that balancing act between too little or too much transparency.
In this brAInfood you will learn more about deepfakes with some examples and tips on how to recognise them.
This brAInfood explains what the risks of algorithmic news selection are and how you and the news media can counter them.
In this brainfood, we provide some general tips and tricks you can take into account if you want to make your data more secure against all-comprehensive surveillance by companies or governments and/or all your data being made publicly available by a single data leak.
This brAInfood explains some points of attention regarding chatbots, and gives youngsters a number of tips to better protect their (personal) data.
This brAInfood exposes potential issues of data sharing using a sample case on ANPR (Automatic Number Plate Recognition).
This brAInfood is about algorithms for machine learning, illustrated by two popular services (Netflix and navigation apps) who make use of these algorithms.
This brAInfood gives you more information on explainability and AI.
This brAInfood presents a number of concerns related to the privacy and data protection of voice assistants.
This brAInfood presents a questionnaire for users of AI technology to determine for themselves whether an AI system is behaving ethically or not.
This brAInfood summarises complex legal challenges on liability for damage caused by self-driving cars.
What do you know about artificial intelligence? Are you an expert or a novice? Take this quiz and find out!
This brAInfood discusses the topic of 'legal sandboxing' for artificial intelligence (AI) in more detail, as mentioned by the High-Level Expert Group on Artificial Intelligence (AI HLEG) of the European Commission in the document 'Policy and Investment Recommendations for Trustworthy AI'.
A brAInfood that describes the 7 requirements of AI from the AI HLEG and formulates a number of questions that help you to think about the reliability of your AI system.
This brAInfood summarizes 8 concepts that often occur in conversations about artificial intelligence. Once you have read and mastered these 8 concepts, you will be able to have and/or follow a basic conversation about artificial intelligence.