Despite efforts to mitigate the inherent risks and biases of artificial intelligence (AI) algorithms, these algorithms can disproportionately impact culturally marginalized groups. A range of approaches has been proposed to address or reduce these risks, including the development of ethical guidelines and principles for responsible AI, as well as technical solutions that promote algorithmic fairness. Drawing on design justice, expansive learning theory, and recent empirical work on participatory AI, we argue that mitigating these harms requires a fundamental re-architecture of the AI production pipeline. This re-design should center co-production, diversity, equity, inclusion (DEI), and multidisciplinary collaboration. We introduce an augmented AI lifecycle consisting of five interconnected phases: co-framing, co-design, co-implementation, co-deployment, and co-maintenance. The lifecycle is informed by four multidisciplinary workshops and grounded in themes of distributed authority and iterative knowledge exchange. Finally, we relate the proposed lifecycle to several leading ethical frameworks and outline key research questions that remain for scaling participatory governance.

Recently, the AI/ML research community has indicated an urgent need to establish Responsible AI (RAI) values and practices as part of the AI/ML lifecycle. Several organizations and communities are responding to this call by sharing RAI guidelines. However, there are gaps in awareness, deliberation, and execution of such practices for multi-disciplinary ML practitioners. This work contributes to the discussion by unpacking co-production challenges faced by practitioners as they align their RAI values. We interviewed 23 individuals, across 10 organizations, tasked to ship AI/ML based products while upholding RAI norms and found that both top-down and bottom-up institutional structures create burden for different roles preventing them from upholding RAI values, a challenge that is further exacerbated when executing conflicted values. We share multiple value levers used as strategies by the practitioners to resolve their challenges. We end our paper with recommendations for inclusive and equitable RAI value-practices, creating supportive organizational structures and opportunities to further aid practitioners.

The text has been redacted and altered by the BMBF in addition to DW's normal editorial guidelines. As such, the text does not entirely reflect the audio of the interview as recorded on December 5, 2019. DW: We're in Berlin at an "Artificial Intelligence Camp" organized by the Gesellschaft für Informatik and the German Federal Ministry of Education and Research, where you head the department for "Research for Digitalization and Innovation." Artificial intelligence is in your remit. And all the people here are experts in the field.

It's been a great season for horror, with Blumhouse's "Happy Death Day" becoming the latest horror film to top the domestic box office in its opening weekend. The $5-million film, a bloody riff on the classic "Groundhog Day" concept, brought in an estimated $26.5 million in the U.S. and Canada, according to figures from measurement firm ComScore, above the $15 million to $20 million analysts projected. "We are absolutely thrilled with the opening," said Universal's Executive Vice President of Domestic Distribution Jim Orr. "Happy Death Day" marks Blumhouse's ninth film to open at No. 1 and its third to debut at No. 1 this year alone, following "Split" and "Get Out." The latest from producer Jason Blum and Universal Pictures, the film, about a woman who relives the day of her murder until she learns her killer's identity, earned a B rating on CinemaScore and a 64% "fresh" rating on Rotten Tomatoes.