Jamillah Knowles & Reset.Tech Australia / https://betterimagesofai.org / https://creativecommons.org/licenses/by/4.0/ The team from DBC diadikasia, an ALFIE partner, has designed the ETD-Hub privacy and cookie policy.  ALFIE needs to ensure that a consent mechanism is implemented when the End Users access the ETD-Hub, allowing them to provide their valid and informed consent regarding the use of cookies. Specifically, a tick box will be added, and a relevant banner or pop-up will appear, enabling users to accept, reject, or customize their cookie preferences. When the end user lands on the ETD-Hub webpage a message will appear saying: “We use cookies to ensure a great browsing experience for

On April 2nd ALFIE held the second internal workshop with project partners. Led by BOSCH, the workshop aimed to organise and categorise the “designer user” requirements gathered during the initial stages of the project. In the ALFIE project a designer user refers to the user who wants to use the AutoML platform to create an ethical tool or model for a specific purpose. The designer user may be a designer, developer, or experienced user seeking to build a tool or model for their specific needs or for a specific purpose. Using the interactive platform Miro, BOSCH prepared a template with the three Use Cases, where

Yasmin Dwiputri & Data Hazards Project / https://betterimagesofai.org / https://creativecommons.org/licenses/by/4.0/   We are delighted to announce that ALFIE has partnered with the Data Science and Artificial Intelligence Summer School to lead a workshop on AI solutions for good. The Data Science and Artificial Intelligence (DSAI) Challenge for Social Welfare is an intensive, five-day programme designed for Una Europa doctoral and early-career researchers across all disciplines passionate about creating ethical and socially responsible AI solutions for social welfare. Participants will work on real-world challenges and design AI tools that address important social issues, guided by the principles of AI for Good—with a strong focus on ethics, bias, and

ALFIE Workshop on User Requirements for AutoML Platform On January 17th, ALFIE held an internal workshop with project partners. Led by the Universitat Autònoma de Barcelona (UAB), the workshop aimed to organise and categorise the user requirements gathered during the initial stages of the project. Using the interactive platform Miro, partners sorted the user requirement gathered by UAB into functional and non-functional requirements. Here are some of the results from the workshop:  Defining Key Terms: Functional Requirements: These define the specific capabilities and behaviours expected from the AutoML platform. Essentially, they outline what the system must do. Examples from the workshop include: Ensure unbiased recognition

ALFIE’s Kick-Off Meeting held in Nicosia From the 21st to the 22nd of November 2024, ALFIE  (https://alfie-project.eu) held its kick-off meeting in Nicosia, Cyprus. This was the first time partners met in person to discuss and plan our activities for the coming months of the project.  ALFIE with the grant number 101177912 stands for Assessment of Learning technologies and Frameworks for Intelligent and Ethical AI. The ALFIE project will create an ecosystem that combines advanced AI technology with ethical standards, ensuring that the resulting AI systems are not only high-performing but also fair, transparent, and free from bias. The project focuses on building two key

AI and Gender-Based Violence: A call for action and responsibility. 25th November 2024: International Day for the Elimination of Violence Against Women. Ying-Chieh Lee & Kingston School of Art / Better Images of AI / Who’s Creating the Kawaii Girl? / CC-BY 4.0 As society continues to confront the challenges of gender-based violence (GBV), emerging technologies like artificial intelligence (AI) are proving to be both an opportunity and a risk. While AI offers innovative ways to support prevention, response, and advocacy, it also poses critical threats that require immediate and thoughtful attention. Here are three key risks associated with AI in the context of GBV: