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Mia Dand's Fight For Inclusion To Save Humanity From The Dark Side Of AI

#artificialintelligence

Mia Dand is an instigator. She has created an important platform in AI Ethics that has proven crucial in the times we currently live. Her most recent event, Women in AI Ethics Annual Conference brought together important voices in the current state of diversity in ethics and AI. Founded in 2018, 100 Brilliant Women in AI Ethics (WAIE) list has cultivated an engaged community and has created an emergence of women in research, technology, culture, business – spanning across the globe. What has emanated are the stories and lessons from their important works that have spilled into the mainstream.


Artificial Intelligence Is the Next Top Gun

#artificialintelligence

A few months ago I was at Johns Hopkins University's Applied Physics Lab in suburban Maryland, where I serve as a senior fellow. A group of us -- mostly retired four-star military officers -- were there to witness a computer-simulated dogfight of a unique character: man against machine. I was seated next to retired Admiral John Richardson, who until last fall had been chief of naval operations, the highest-ranking officer in the fleet. We were both skeptical that the artificial intelligence program that would be piloting one of the virtual aircraft would be able to outfight the human pilot, call sign "Banger," from the Air Force's equivalent of the Navy's legendary TOPGUN fighter-tactics instruction program. It was a remarkable blend of software development, AI, modelling and simulation, combat-aircraft dynamics and controls, and advanced video production -- it felt like watching an ESPN sports event.


Algorithms Help Spot Possible Suicidal Intent Among Veterans' Social Posts

#artificialintelligence

A social media platform designed for America's military community is now equipped with a custom machine learning model that insiders say can rapidly review public posts and pinpoint those that show signs and risks of potential self-harm. With support from the Veterans Affairs Department and Harvard University's Nock Lab, Amazon Web Services linked up with the existing RallyPoint military social media platform to target the production of a technological solution that can speedily surface sensitive public posts and boost online suicide intervention. "Historically, the heavy lifting of mental health support on RallyPoint has been shouldered by RallyPoint members stepping up to help each other when they come across people sharing their challenges on our site," RallyPoint CEO Dave Gowel recently told Nextgov. "Now, through our work with the VA, AWS and mental health experts from Harvard, we are more proactive in reinforcing our members' good work by offering helpful resources when we are alerted about public posts showing signs of risk." Launched in 2012, RallyPoint enables nearly 2 million service members, veterans, and their families to connect, share stories and information, ask questions and ultimately chat on topics that accompany military and veteran life.


Drone video captures dolphins sharing fish and getting frisky in Mexico

Daily Mail - Science & tech

It turns out humans are not the only creatures that use food as foreplay. Researchers in southwestern Mexico have recorded a group of rough-toothed dolphins sharing a meal and getting frisky. A drone camera caught two dolphins passing a piece of fish back and forth in what may be the first video of the conduct. The repast seemed to inspire some amorous behavior, as well, with two males initiating sexual encounters with another member of the pod. Rough-toothed dolphins spend up to 80 percent of their time in the ocean depths, making them extremely difficult to study.


Causal Feature Learning for Utility-Maximizing Agents

arXiv.org Artificial Intelligence

Discovering high-level causal relations from low-level data is an important and challenging problem that comes up frequently in the natural and social sciences. In a series of papers, Chalupka et al. (2015, 2016a, 2016b, 2017) develop a procedure for causal feature learning (CFL) in an effort to automate this task. We argue that CFL does not recommend coarsening in cases where pragmatic considerations rule in favor of it, and recommends coarsening in cases where pragmatic considerations rule against it. We propose a new technique, pragmatic causal feature learning (PCFL), which extends the original CFL algorithm in useful and intuitive ways. We show that PCFL has the same attractive measure-theoretic properties as the original CFL algorithm. We compare the performance of both methods through theoretical analysis and experiments.


Modeling Cell Populations Measured By Flow Cytometry With Covariates Using Sparse Mixture of Regressions

arXiv.org Machine Learning

The ocean is filled with microscopic microalgae called phytoplankton, which together are responsible for as much photosynthesis as all plants on land combined. Our ability to predict their response to the warming ocean relies on understanding how the dynamics of phytoplankton populations is influenced by changes in environmental conditions. One powerful technique to study the dynamics of phytoplankton is flow cytometry, which measures the optical properties of thousands of individual cells per second. Today, oceanographers are able to collect flow cytometry data in real-time onboard a moving ship, providing them with fine-scale resolution of the distribution of phytoplankton across thousands of kilometers. One of the current challenges is to understand how these small and large scale variations relate to environmental conditions, such as nutrient availability, temperature, light and ocean currents. In this paper, we propose a novel sparse mixture of multivariate regressions model to estimate the time-varying phytoplankton subpopulations while simultaneously identifying the specific environmental covariates that are predictive of the observed changes to these subpopulations. We demonstrate the usefulness and interpretability of the approach using both synthetic data and real observations collected on an oceanographic cruise conducted in the north-east Pacific in the spring of 2017.


Listen to AI Tries to Save the Whales

#artificialintelligence

"We head to the Pacific northwest to understand the obstacles that confront these endangered orcas and how researchers are using artificial intelligence to help orcas and humans to coexist. WHAT HAPPENED TO J thirty five or Tala wasn't an anomaly the southern resident cavs have been struggling to survive for some time they've been listed as endangered in both the US and Canada since the mid arts. But their numbers continue to fall in two, thousand five there were eight. Now there are just seventy two in the wild one lives in captivity. Their home waters in the sailor, see an elaborate network of channels that span the coasts of Seattle Vancouver from Olympia Washington in the south to the middle of Vancouver Island British Columbia in the north. The see encompasses puget sound the Strait of Georgia and the Strait of Juan De. Much of it is rich in natural beauty and teeming with wildlife with rural shorelines backlit by tall evergreens and craggy.


Urban Bike Lane Planning with Bike Trajectories: Models, Algorithms, and a Real-World Case Study

arXiv.org Artificial Intelligence

We study an urban bike lane planning problem based on the fine-grained bike trajectory data, which is made available by smart city infrastructure such as bike-sharing systems. The key decision is where to build bike lanes in the existing road network. As bike-sharing systems become widespread in the metropolitan areas over the world, bike lanes are being planned and constructed by many municipal governments to promote cycling and protect cyclists. Traditional bike lane planning approaches often rely on surveys and heuristics. We develop a general and novel optimization framework to guide the bike lane planning from bike trajectories. We formalize the bike lane planning problem in view of the cyclists' utility functions and derive an integer optimization model to maximize the utility. To capture cyclists' route choices, we develop a bilevel program based on the Multinomial Logit model. We derive structural properties about the base model and prove that the Lagrangian dual of the bike lane planning model is polynomial-time solvable. Furthermore, we reformulate the route choice based planning model as a mixed integer linear program using a linear approximation scheme. We develop tractable formulations and efficient algorithms to solve the large-scale optimization problem. Via a real-world case study with a city government, we demonstrate the efficiency of the proposed algorithms and quantify the trade-off between the coverage of bike trips and continuity of bike lanes. We show how the network topology evolves according to the utility functions and highlight the importance of understanding cyclists' route choices. The proposed framework drives the data-driven urban planning scheme in smart city operations management.


Navy seeks to combine operations of thousands of ships and drones

FOX News

Fox Business Flash top headlines are here. Check out what's clicking on FoxBusiness.com. The U.S. Navy could possibly operate thousands of combat ships in the coming years as the service seeks to combine surface, air and undersea drones into its fleet. It is part of a formal Integrated Force Structure Assessment in which analysis teams led by the chief of naval operations and Marine Corps commandant explored questions of fleet size in relation to fast-emerging man-unmanned teaming integration. "[W]e came up with a discreet number of ships which was more than 355 and then command and control drone networking separately unmanned," Admiral Michael Gilday, chief of naval operations, said earlier this year at the Navy's 2020 West Conference in San Diego, California. The assessment, Gilday explained, was not so much "coordinated" as "integrated," taking up a blend between a specific number of planned manned ships and a still "conceptual" number of drones.


Tech Workers Are Living the American Dream--in Canada

WIRED

Nitin Alabur is an iOS developer from India who lived in the US and dreamed of creating a tech startup. "I had a zillion ideas," he tells me. But he'd been hired by a US firm under an H-1B visa, which ties you to your employer. A green card that would make self-employment possible was years away. "It felt like shackles," he says.