no code implementations • 15 Dec 2023 • Muneera Bano, Didar Zowghi, Pip Shea, Georgina Ibarra
Scientific research organizations that are developing and deploying Artificial Intelligence (AI) systems are at the intersection of technological progress and ethical considerations.
no code implementations • 11 Dec 2023 • Muneera Bano, Didar Zowghi, Vincenzo Gervasi
The growing presence of Artificial Intelligence (AI) in various sectors necessitates systems that accurately reflect societal diversity.
no code implementations • 7 Nov 2023 • Muneera Bano, Didar Zowghi, Vincenzo Gervasi, Rifat Shams
As Artificial Intelligence (AI) permeates many aspects of society, it brings numerous advantages while at the same time raising ethical concerns and potential risks, such as perpetuating inequalities through biased or discriminatory decision-making.
no code implementations • 27 Oct 2023 • Daniela Elia, Fang Chen, Didar Zowghi, Marian-Andrei Rizoiu
The fast adoption of new technologies forces companies to continuously adapt their operations making it harder to predict workforce requirements.
no code implementations • 20 Jul 2023 • Rifat Ara Shams, Didar Zowghi, Muneera Bano
Artificial Intelligence (AI)'s pervasive presence and variety necessitate diversity and inclusivity (D&I) principles in its design for fairness, trust, and transparency.
no code implementations • 23 Jun 2023 • Muneera Bano, Didar Zowghi, Jon Whittle
We compared the results with human classification and reasoning.
no code implementations • 22 May 2023 • Didar Zowghi, Francesca da Rimini
To date, there has been little concrete practical advice about how to ensure that diversity and inclusion considerations should be embedded within both specific Artificial Intelligence (AI) systems and the larger global AI ecosystem.
no code implementations • 12 Sep 2022 • Qinghua Lu, Liming Zhu, Xiwei Xu, Jon Whittle, Didar Zowghi, Aurelie Jacquet
Rather than staying at the principle or algorithm level, we focus on patterns that AI system stakeholders can undertake in practice to ensure that the developed AI systems are responsible throughout the entire governance and engineering lifecycle.
no code implementations • 10 Jul 2018 • Zahra Shakeri Hossein Abad, Munib Rahman, Abdullah Cheema, Vincenzo Gervasi, Didar Zowghi, Ken Barker
Requirements elicitation can be very challenging in projects that require deep domain knowledge about the system at hand.