Breakthroughs, discoveries, and DIY tips sent every weekday. While it's not helping fly the Millennium Falcon, marine biologists have discovered a new type of deep-sea coral in the western Pacific Ocean that bears a striking similarity to a certain beloved character. A new scientific analysis of the species initially documented almost two decades ago indicates that is its own species, with long, hairlike branches that live up to its namesake Wookie. Ten years later, another example was documented close to the Mariana Trench . But it would take a few more years before University of Hawai'i ecologist Les Watling noticed the strange, ethereal sight while reviewing research from some of his colleagues.

Passive acoustic monitoring (PAM) studies generate thousands of hours of audio, which may be used to monitor specific animal populations, conduct broad biodiversity surveys, detect threats such as poachers, and more. Machine learning classifiers for species identification are increasingly being used to process the vast amount of audio generated by bioacoustic surveys, expediting analysis and increasing the utility of PAM as a management tool. In common practice, a threshold is applied to classifier output scores, and scores above the threshold are aggregated into a detection count. The choice of threshold produces biased counts of vocalizations, which are subject to false positive/negative rates that may vary across subsets of the dataset. In this work, we advocate for directly estimating call density: The proportion of detection windows containing the target vocalization, regardless of classifier score. Our approach targets a desirable ecological estimator and provides a more rigorous grounding for identifying the core problems caused by distribution shifts -- when the defining characteristics of the data distribution change -- and designing strategies to mitigate them. We propose a validation scheme for estimating call density in a body of data and obtain, through Bayesian reasoning, probability distributions of confidence scores for both the positive and negative classes. We use these distributions to predict site-level densities, which may be subject to distribution shifts. We test our proposed methods on a real-world study of Hawaiian birds and provide simulation results leveraging existing fully annotated datasets, demonstrating robustness to variations in call density and classifier model quality.

In the late winter and spring of 2019, a group of Indigenous scholars met in Hawai'i to think through concepts around artificial intelligence (AI) and how they related to the Indigenous experience. Co-organized by Jason Edward Lewis, professor in the Department Design and Computation Arts, the multidisciplinary group included participants from Canada, the United States, Australia, New Zealand and the United Kingdom. Concordia graduate students Scott Benesiinaabandan (MFA Studio Arts) and Suzanne Kite (PhD INDI) as well as Concordia research associate Skawennati also participated. The first session in March largely consisted of brainstorm workshops about how and where Indigeneity intersects with AI. The second, in May, focused more on writing and laying the foundations of what would become the now-completed Indigenous Protocol and Artificial Intelligence Position Paper.

Researchers at University of Hawai'i at Mānoa, University of Illinois at Chicago, and Virginia Tech were awarded a $5 million National Science Foundation grant to synergize two complementary technologies -- large-scale data visualization and artificial intelligence -- to create the Smart Amplified Group Environment (SAGE3) open-source software. SAGE, soon to be on its third iteration as SAGE3, is the most widely used big-data visualization and collaboration software in the world. SAGE and SAGE2 are software to enable data-rich collaboration on high-resolution display walls. SAGE2 moved SAGE into cloud computing and SAGE3 ushers in the inclusion of artificial intelligence. Principal investigator Jason Leigh is a computer and information science professor at University of Hawai'i at Mānoa and the inventor of SAGE.

This is an episode from Josh Reppun's "What School Could Be in Hawai'i," a podcast on the people, technology and methodologies pushing the mantle of education in the 50th state. Susannah Johnson is the founder of Individualized Realized, an education consultancy aimed at meeting educators where they are – as she did in the classroom with students for thirteen years – on the path to student-centered, authentic, globally minded, and liberated learning. In the move towards student-centered learning technology is essential for individualized learning. Over ten years developing a fully individualized program, the use of technology not only opens up learning to be multidimensional, but also for the asynchronous management of dozens of curricula. When students own their own learning, technology moves beyond learning tool to become a partner for that learning.

As AI algorithms play a bigger role in decision making, how do qualities like ethics, compassion, and inclusion get programmed into the code? On this edition of Bytemarks Café, a talk about the gathering of thought leaders in Hawai'i to discuss how to move the technology agenda. The event is called TechForce 2019, and its aim is to bring together leaders from key sectors to accelerate tech readiness in our islands. On this edition of Bytemarks Café, a discussion about a novel new project that projects a 3D hologram from Hawaii to American Samoa. The project is called Holo Campus, and is the delivery of University of Hawai'i lectures over the trans-Pacific fiber optic broadband network to the Pacific Islands.