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\nGlobalized technology has the potential to create large-scale societal impact, and having a grounded research approach rooted in existing international human and civil rights standards is a critical component to assuring responsible and ethical AI development and deployment. The Impact Lab team, part of Google\u2019s Responsible AI Team<\/a>, employs a range of interdisciplinary methodologies to ensure critical and rich analysis of the potential implications of technology development. The team\u2019s mission is to examine socioeconomic and human rights impacts of AI, publish foundational research, and incubate novel mitigations enabling machine learning (ML) practitioners to advance global equity. We study and develop scalable, rigorous, and evidence-based solutions using data analysis, human rights, and participatory frameworks.\n<\/p>\n <\/p>\n \nThe uniqueness of the Impact Lab\u2019s goals is its multidisciplinary approach and the diversity of experience, including both applied and academic research. Our aim is to expand the epistemic lens of Responsible AI to center the voices of historically marginalized communities and to overcome the practice of ungrounded analysis of impacts by offering a research-based approach to understand how differing perspectives and experiences should impact the development of technology.\n<\/p>\n <\/p>\n \nIn response to the accelerating complexity of ML and the increased coupling between large-scale ML and people, our team critically examines traditional assumptions of how technology impacts society to deepen our understanding of this interplay. We collaborate with academic scholars in the areas of social science and philosophy of technology and publish foundational research focusing on how ML can be helpful and useful. We also offer research support to some of our organization\u2019s most challenging efforts, including the\u00a01,000 Languages Initiative<\/a> and ongoing work in the testing and evaluation of\u00a0language and generative models<\/a>. Our work gives weight to Google’s AI Principles<\/a>.\n<\/p>\n \nTo that end, we:\n<\/p>\n \nWe strive not only to reimagine existing frameworks for assessing the adverse impact of AI to answer ambitious research questions, but also to promote the importance of this work.\n<\/p>\n <\/p>\n \nOur motivation for providing rigorous analytical tools and approaches is to ensure that social-technical impact and fairness is well understood in relation to cultural and historical nuances. This is quite important, as it helps develop the incentive and ability to better understand communities who experience the greatest burden and demonstrates the value of rigorous and focused analysis. Our goals are to proactively partner with external thought leaders in this problem space, reframe our existing mental models when assessing potential harms and impacts, and avoid relying on unfounded assumptions and stereotypes in ML technologies. We collaborate with researchers at Stanford, University of California Berkeley, University of Edinburgh, Mozilla Foundation, University of Michigan, Naval Postgraduate School, Data & Society, EPFL, Australian National University, and McGill University.\n<\/p>\nWhat we do<\/h2>\n
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Current research efforts<\/h2>\n
Understanding social problems<\/h3>\n
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