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Showing 1 to 3 of 3 for “"AI Trustworthiness"”.

  1. Human-AI Handshaking: Supporting Extreme Sensemaking through Trustworthy Shared Perception

    … operations. These contexts are marked by uncertainty, fragmented information, and time-critical decisions that stretch human cognitive and physical limits. Artificial intelligence (AI) offers potential assistance, but distributed AI systems that rely on object detection, such as drone swarms, …

    vt Repository record for Human-AI Handshaking: Supporting Extreme Sensemaking through Trustworthy Shared Perception (opens in a new tab)

  2. Generating Trustworthy Synthetic Data

    … limiting: it may be privacy-sensitive, unfair, unbalanced, unrepresentative, or it may simply not exist for the setting of interest. These limitations continuously constrain how the machine learning (ML) community operates---from training to testing, from model development to deployment. …

    cambridge Repository record for Generating Trustworthy Synthetic Data (opens in a new tab)

  3. Methodologies for Systematic Evaluation and Targeted Mitigation of Deficiencies in Critical Machine Learning Models

    … learning in healthcare, critical challenges remain unaddressed, models often fail to respond appropriately to life-threatening conditions, exhibit poor generalizability in real-world clinical settings, and show unequal performance across patient subgroups. These limitations compromise the …

    vt Repository record for Methodologies for Systematic Evaluation and Targeted Mitigation of Deficiencies in Critical Machine Learning Models (opens in a new tab)