Meaningful human control: actionable properties for AI system development

no code implementations • 25 Nov 2021 • Luciano Cavalcante Siebert, Maria Luce Lupetti, Evgeni Aizenberg, Niek Beckers, Arkady Zgonnikov, Herman Veluwenkamp, David Abbink, Elisa Giaccardi, Geert-Jan Houben, Catholijn M. Jonker, Jeroen van den Hoven, Deborah Forster, Reginald L. Lagendijk

The concept of meaningful human control has been proposed to address responsibility gaps and mitigate them by establishing conditions that enable a proper attribution of responsibility for humans; however, clear requirements for researchers, designers, and engineers are yet inexistent, making the development of AI-based systems that remain under meaningful human control challenging.

Deep Active Object Recognition by Joint Label and Action Prediction

no code implementations • 17 Dec 2015 • Mohsen Malmir, Karan Sikka, Deborah Forster, Ian Fasel, Javier R. Movellan, Garrison W. Cottrell

The results of experiments suggest that the proposed model equipped with Dirichlet state encoding is superior in performance, and selects images that lead to better training and higher accuracy of label prediction at test time.

Object Object Recognition +1