Artificial Intelligence
Building intelligent machines that complement human reasoning and extend what people can do.
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Automating Image-Based Biodiversity Surveys
Microsoft’s AI for Earth program develops tools at the intersection of machine learning and environmental science, through both external grants and first-party development. This demo will showcase our work on using computer vision to break…
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Workforce of the Future
The workforce of the future will have to be creative and innovative, rather than merely good at performing specific tasks. However, many individuals lack these skills, particularly if they suffer from cognitive disabilities or difficulties.…
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Augmented and Virtual Productivity Experiences
Important questions about how the productivity of VR/AR applications is measured remain. This panel discusses ways of conceptualizing and measuring productivity. Ideally, objective measures of the experience can be developed that evaluate the realism of…
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Task Intelligence: Doing More with Less
Tasks—defined pieces of work ranging in scope from the specific, such as sending an email, to the broad, such as shipping a feature—are central to all aspects of personal and team productivity. Task intelligence spans…
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AI-Driven Image Captioning For Inclusive Productivity
Advances in hybrid intelligence, deep learning, and related artificial intelligence techniques have provided us with a remarkable opportunity to ensure the future of work will be even more inclusive to more people than ever before.…
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The Future of Communication
Communication is the foundation on which our efforts toward accomplishing goals and tasks are built. We articulate needs and results and tell and react to stories about what we do and how we do it.…
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Recommendation and Learning to Improve Personal Productivity
Artificial intelligence has the potential to improve productivity throughout the workplace by leveraging how people communicate to proactively connect a person to the right people and information. Providing this benefit requires key system capabilities, including…
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Techniques for ML Model Transparency and Debugging
Without good models and the right tools to interpret them, data scientists risk making decisions based on hidden biases, spurious correlations, and false generalizations. This has led to a rallying cry for model interpretability. Yet…
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Envisioning Fluid Cross-Device Experiences
The future of work is beyond the desktop, existing in a more natural environment where individuals can grab a pen to annotate a document on any device and share it effortlessly with others, including themselves. The future of work is identifying relevant information on the web or in email on a phone while commuting and…
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Understanding Workplace Well-Being and Productivity through Sensor Tracking
The future of work will involve gaining a deep understanding of people’s workplace experience and use that understanding to develop solutions that improve health, mood, and productivity. Using wearable sensors, computer logging, and experience sampling…
