Dr. Cindy Mason
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"RADIO AI's AI and Environment series continues with Part 2 - Its not "all about the data"! When it comes to AI projects that work with environmental problems, there is a big deal about the people who use them! And, unlike the rest of AI that is still struggling with the people factor, when it comes to Environmental systems the AI systems have always been about the people. From explaining how a decision is made to keeping it simple during an emergency operation to realizing governments, institutions and academic bodies need to cooperate to solve these problems Dr. Cindy Mason, editor and author of the unique new book, Artificial Intelligence and the Environment, says its essential and not an option, to put people's needs front and center in AI tools. Hear about some of the latest environmental monitoring systems like Argo Float and find out the cool citizen tools available to see our planet, from planet dot that has 200 plus satellites orbiting the planet every 24 hours to underwater webcams filming coral reefs and Oculus Rift.This is the last episode of Season Three.Radio AI will resume in the fall of 2021.
13 min 36 sec
In Radio AI Episode 3.5, Dr. Cindy Mason shares why AI is a SUPER TOOL for working on the environment. In the episode you find out why. Dr. Mason proposed the first U.S. and first international AI gathering of AI and Environmental scientists while working at NASA Ames and she has just completed a book, "Artificial Intelligence and The Environment", on Amazon. While working on the book she discovered that although there are many different kinds of environmental projects and many different kinds of AI used in these projects, across all these projects, something is striking. AI is a SUPER TOOL. The things that make environmental projects hard are exactly the things that AI was cut out for. Find out more in this episode with Radio AI director, AI researcher and author, Dr. Cindy Mason. PS. Did you know, most AI and Environment systems use more than one kind of AI in their projects?
13 min 49 sec
In this Radio AI Episode 3.4, Dr. Emily Ury, an ecologist from Duke University, is haunted by ghost forests. Using big rubber waders, insect protection and AI, Dr. Ury and a team of ecologists investigate these ghost forests using AI to go back through time and space to find the patterns and extent of ghost forests. Dead trees with pale trunks, devoid of leaves and limbs are the tell tale sign of saltwater. Scientists call them "Ghost forests." Emily hits the coastal trail in her waders and insect protection in North Carolina's Alligator River National Wildlife Refuge, near the Outer banks where she slogs knee deep on a section of trail that is completely and permanently now underwater. She saw evidence of forest die off everywhere so she sent up a drone. But drone data wouldn't cut it, so they went to the sky. The ghost forests are so big they can be seen from space. Dr. Ury and her team used NASA and Google Earth's satellite data with AI to find out pattern of ghost forests extend all along the coast - from Main to Florida. Using AI to find patterns over time and space it was possible to see the spike in North Carolina happened when there was a triple whammy - drought, then fire, then a hurricane, along North Carolina's coast. Dr. Ury said their results could be a warning for coastal areas around the world. Join RADIO AI special guest Dr. Ury as she walks us through her very special use of AI and remote sensing data to hunt for ghost forests.
10 min 5 sec
RADIO AI Episode 3.3 discusses the problem of algorithmic justice with Henry Lieberman, an AI machine learning expert at MIT . Machine learning algorithms and models can be found across many many apps. They have become institutionalized, making life impacting decisions like hiring and firing or prision sentences. Staggering errors with this technology mostly affect women and minorities. Joy Buolamwini at MIT found this out the hard way when she tried to build a magical mirror for a class project. The face recognition in the mirror would only work if she wore a white face mask. Wow. Investing further, she discovered how widespread and devastating this problem was. So she created The Algorithmic Justice League. Based on the work of the Algorithmic Justice League, many cities have now revised or removed their face recognition technologies until the error rates improve. Algorithm justice means data used to train machine learning for predicting our words, recognizing our faces and voices, represents all of us, or that the algorithms themselves can take reality into account. What if, before an algorithm or technology is unleashed on the public it was vetted to be sure it does not create harm or that it actually makes our lives better, not more annoyed? Right now, companies have a predatory relation with people. When Henry says corporations benefit when they have cooperative relations with customers he hits the nail on the head.
9 min 28 sec
In this RADIO AI Episode, we travel to India to find out about AI and Common Sense. AI researcher, Pushkar Sawant, explains the AI problem of common sense. People find common sense easy, but its one of THE hardest unsolved problems in AI. Pushkar explains that we need common sense for life and that in India, grandmothers hold the treasure of common sense. When it comes to common sense, your grandmother may be smarter than Einstein.
5 min 31 sec
We depend more and more on AI programs in critical systems and in our lives - from military weaponry and healthcare to employment and mortgages. But what if those programs have "bugs" or errors? In this RADIO AI Episode 3.1, MIT AI research scientist, Henry Lieberman, talks about the process of building a computer program and getting it to run without bugs. He proposes the radical idea of using AI to debug our computer programming code because if we have errors in our code, it can be a safety issue. An AI system has no more bugs than a regular computer program, but the tasks we use AI for have become essential and our lives can be in the balance. Finding a bug in a computer program can be difficult. But AI is good for difficult problems….so why not use AI to debug AI?
6 min 46 sec
RADIO AI presents part II of the Artificial Compassion podcast series. Part II lecture is delivered by Cindy Mason, an AI researcher who invented Artificial Compassion after recognizing that scientific discoveries about compassion can rub off on us through our own digital devices. In this podcast we learn how to achieve artificial compassion using cognitive architectures. We look at 3 increasingly sophisticated cognitive architectures, starting with an insect robot. Insect robots are useful and some might say intelligent, but they have no memory, no ability to plan a route, or any type of AI that can do more than respond to sensory input. That's why its usefulness is limited - they can be helpful at times, but get stuck in places like the end of a hallway or a box canyon, and sometimes can't get out. This brings us to cognitive architecture number two. It has sophisticated AI components like machine learning, memory, common sense, and planning. This is the kind of cognitive architecture we can use to describe softbots like Siri and Alexa. Still, they have no ability for emotional or social intelligence, so there's no capacity for compassionate intelligence. For compassionate intelligence, we need more than architeture two provides. We need social and emotional intelligence and computations that have a stake in us. We also need programmers who have a stake in us. This brings us to architecture number three. By adding components that allow a representation of self and other, social and emotional intelligence, and data sets that include positive examples of pro-social and emotional intelligence, our machine intelligence becomes more than we could ever have dreamed. It becomes capable of artificial compassion.Join us for Episode 2.6 for an inspired podcast with the possibility to change life for the better, not just for the wealthy or the educated, not just for the young or old, not just for one race or one group. Artificial compassion belongs to all of us, and when we build this, it will be available to anyone with a browser, a cellphone or a device that supports artificial compassion. See you there.
13 min 9 sec
RADIO AI Episode 2.5 opens up a whole new world of AI to us with Compassionate Intelligence. In this episode we discover how our own biology depends on kindness and compassion to function and explore some of the human sciences discoveries that inspired inventor Cindy Mason to create it. Part I takes us on a journey of building a system with Artificial Compassion. What is Artificial Compassion? Why build it? How might it change us? We learn about a special tool for building AI systems called a cognitive architecture. We also get a quick tour on the different ways robots function and explore a basic tool for building insect robots called the Sense-Act cognitive architecture.
10 min 59 sec
RADIO AI Episode 2.4 is a continuation of Episode 2.3 on AI and Social IssuesDescription: Prof. Peter Sincak, head of Cybernetics and AI at Kosice University in Slovakia of Central Europe collaborates with roboticists in Japan, China and other places around the world. He continues sharing his world perspective on AI and raises many important issues about AI, from media hype to the singularity. He also covers some of the AI lingo like What is "strong AI" or "weak AI"? What about the singularity? How AI might empower humankind?
9 min 47 sec
RADIO AI Episode 2.3 features a special guest Prof. Peter Sincak, head of Cybernetics and AI at Kosice University in Slovakia of Central Europe, who shares important ideas on the social impacts and isssues of AI on the public. Prof Sincak collaborates with roboticists in Japan, China and other places around the world. He shares his world perspective on AI and raises many important issues about the AI media hype vs. reality of AI and society. He also covers some of the AI lingo like "strong AI" and "weak AI." He also discusses what the future of AI might look like, the singularity, and how AI might empower humankind?
6 min 48 sec
How does an AI system organize information? The say way the brain does! Machine Learning, Robotics, Natural Language Processing, and all branches of AI, organize the world as Concepts and Categories! In Part II (Ep. 2.2) we continue our exploration of AI's use of Concepts and Categories to organize and understand the objects in the world with RADIO AI Director Cindy Mason and answer the big question: How does an AI system do this? We use programming ideas based on nature, the brain and math, to make clusters, hierarchies, lists, sets, graphs, networks, etc. for millions and MILLIONS of concepts and categories. It really is an amazing subject because we have named all living things in this way.
13 min 58 sec
Season 2 kicks off with Episode 1 - Concepts and Categories Part I with RADIO AI, Director Cindy Mason who reveals AI's hidden key to 'making sense' of the world - Concepts and Categories. People name and organize everything in the world this way, and AI systems do, too. Some neuroscientists even think our physical brain is organized around Concepts and Categories. And its not just one kind of AI that does this, but ALL of AI is based on naming and labeling the world as concepts and categories. For Machine Learning, Robotics, Natural Language Processing or any other branch of AI, this is true. Examples of categories are Dogs, Cats, and Beachy-Things. How does an AI system know that a turtle is a Beachy-Thing, but a clown shoe is not? How does an AI system determine that a 3-legged Dalmatian named "Spot" is a Dog and not a Cat? Join Cindy as she explores the answers to these questions and more!
8 min 39 sec
Can AI systems solve problems the way Sherlock Holmes does? Yes, it’s elementary! with deductions. This kind of AI is called “cognitive AI” systems because it imitates some of the ways we think about the world using symbols. A cognitive AI system uses symbols not only to communicate with people but it represents a problem with symbols and solves it similar to the way that mathematicians and physicists do. If you think about how lawyers and doctors use deduction, it’s easy to imagine how powerful an AI system that “thinks” like this can be. For example, the first AI system that won the Jeopardy World Championship, Watson, used deduction. Without symbols, we are faced with a pile of 0’s and 1’s. Join Radio AI director Cindy Mason on a journey through the world of deductive cognitive AI systems with special guest, Richard Waldinger, an AI researcher who specializes in deductive AI systems. Richard is a senior scientist at Stanford Research Institute, Intl. and is the recipient of many AI prizes, including the Herbrand Award.
15 min 14 sec
How do you make an AI system mimic human curiosity? What an amazing idea! Join Professor Mary Lou Maher on Episode Five of RADIO AI to find out what it means to make an AI system “curious”! What might happen?! You’ll have to listen to the podcast to find out more! Be curious!Mary Lou Maher is the Chair of the Department of Software and Information Systems, College of Computing and Informatics, University of North Carolina, Charlotte. Mary Lou is a founder of nature-net.org, a community-driven environmental learning project and has won many awards!
5 min 9 sec
“C3P0” “BB8” When someone says, “Artificial Intelligence,” we usually think about ROBOTS! In episode four, RADIO AI Director Cindy Mason, invites us to learn more about the robots we find in our world - from the shopping mall to outer space missions. Robots have many kinds of sensors and some can even fly or go underwater! In this podcast we learn the answers to 3 big questions: 1) What is a robot? 2) How do we interact with it? And 3) Who’s controlling it? Dr. Mason was on the NASA robotics team that sent the first teleoperated undersea vehicle to Antarctica. She also created a novel kind of astronomy called “Pass the Star” with cooperative robotic telescopes. She once staged a “Robot Fashion Show” to demonstrate the need for Robot WYSIWYG (What You See Is What You Get) so people can trust robots from appearances. She also pioneered the idea of giving robots Artificial Compassion(TM).
11 min 35 sec
“Hey SIRI!”, “Alexa…” These and other "Software agents" or "bots" are everywhere now - on our phones, in our cars, in our homes and they are partnering with us to get things done. We owe it to ourselves to know more about them. Join us in Episode 3 with RADIO AI host, Cindy Mason, as we explore the inside world of an AI technology called "software agents". Dr. Mason has an in-depth background in building software agents and answers questions like: (1) What is a software agent? (2) What do software agents do? and (3) How do we Interact with it? She also talks about the exciting new area of cooperating agents. She will also tell us about a special software agent called SEA, designed to help scientists and U.N. treaty verification specialists sift through humongous mountains of data to ensure countries adhere to international treaties regulating nuclear tests. Dr. Mason has worked on software agents and cooperative software agents at Lawrence Livermore Lab, NASA Ames, and UC Berkeley. She created cooperating agent systems for global sensor networks, cooperative robotic telescopes, and designed an Emotion Oriented Programming language to build agents (and robots) with Artificial Compassion(TM).
10 min 2 sec
Join Henry Lieberman, an MIT machine learning expert, and Cindy Mason, Radio AI Director, as they talk about the A, B, C's of machine learning in six minutes. Find out about Supervised learning, Unsupervised learning, and the Machines that learn by discovery and interact with us! Season 1. Episode 2. For the full season of podcast episodes check out https://www.academia.edu/s/cfdfba6691?source=news For more about Radio AI, see www.radioai.net.
6 min 6 sec
Radio AI is a collection of podcasts for public literacy on AI and is for all ages.In this episode, AI researcher and Radio AI host, Dr. Cindy Mason, talks with Undersea Robotics specialist Hans Thomas live from research vessel off the coast of California.Hans and his crew along with 2 cranes and 3 robots are on a 3 week expedition at sea mapping and exploring the sea floor to find out if it will support a new kind of energy with windmills.Cindy and Hans were in the same robot research lab at NASA and are old friends.They talk about basic ideas of undersea robots like, how does it navigate? What happensif it gets lost? What's it like to live on a boat with robots?
17 min 35 sec