🔖 Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell

Bookmarked Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell (curtisbrown.co.uk)

No recent scientific enterprise has been so alluring, so terrifying, and so filled with extravagant promise and frustrating setbacks as artificial intelligence. But how intelligent—really—are the best of today’s AI programs? How do these programs work? What can they actually do, and what kinds of things do they fail at? How human-like do we expect them to become, and how soon do we need to worry about them surpassing us in most, if not all, human endeavors? 

From Melanie Mitchell, a leading professor and computer scientist, comes an in-depth and careful study of modern day artificial intelligence. Exploring the cutting edge of current AI and the prospect of 'intelligent' mechanical creations - who many fear may become our successors - Artificial Intelligence looks closely at the allure, the roller-coaster history, and the recent surge of seeming successes, grand hopes, and emerging fears surrounding AI. Flavoured with personal stories and a twist of humour, this ultimately accessible account of modern AI gives a clear sense of what the field has actually accomplished so far and how much further it has to go.

🎧 Episode 077 Exploring Artificial Intelligence with Melanie Mitchell | Human Current

Listened to Episode 077 Exploring Artificial Intelligence with Melanie Mitchell by Haley Campbell-GrossHaley Campbell-Gross from HumanCurrent

What is artificial intelligence? Could unintended consequences arise from increased use of this technology? How will the role of humans change with AI? How will AI evolve in the next 10 years?

In this episode, Haley interviews leading Complex Systems Scientist, Professor of Computer Science at Portland State University, and external professor at the Santa Fe Institute, Melanie Mitchell. Professor Mitchell answers many profound questions about the field of artificial intelligence and gives specific examples of how this technology is being used today. She also provides some insights to help us navigate our relationship with AI as it becomes more popular in the coming years.

Melanie Mitchell on Human Current
Definitely worth a second listen.

👓 The Racial Dot Map | Weldon Cooper Center for Public Service

Read The Racial Dot Map: One Dot Per Person for the Entire United States (Weldon Cooper Center for Public Service)
This racial dot map is an American snapshot; it provides an accessible visualization of geographic distribution, population density, and racial diversity of the American people in every neighborhood in the entire country. The map displays 308,745,538 dots, one for each person residing in the United States at the location they were counted during the 2010 Census. Each dot is color-coded by the individual’s race and ethnicity. The map is presented in both black and white and full color versions. In the color version, each dot is color-coded by race.

👓 Useful and not-so-useful links | Selcan Mutgan

Read Useful and not-so-useful links by Selcan Mutgan (Selcan Mutgan)
Maps & spatial analysis: One-dot one-person map for the entire United States:  Introduction to geo-scripting in R & Python:  Awesome blog with cool maps and the codes behind them by James C…
I’ve been stockpiling episodes in my podcast queue for far too long, but Haley and Angie have been killing it on Human Current doing interviews with some of my favorite complexity systems thinkers. My listened to list is slowly growing. If you haven’t already, I highly recommend subscribing.

👓 Neil deGrasse Tyson and the Careers That Weren’t | The Atlantic

Read Neil deGrasse Tyson and the Careers That Weren’t (The Atlantic)
The women who have accused the famed science educator of sexual impropriety have made claims not just about traumatized minds, but also about traumatized careers.  

👓 Robert Rauschenberg, Erased de Kooning Drawing, 1953 | SFMOMA

Read Robert Rauschenberg, Erased de Kooning Drawing, 1953 (SFMOMA)
From 1951 to 1953, Robert Rauschenberg made a number of artworks that explore the limits and very definition of art. These works recall and effectively extend the notion of the artist as creator of ideas, a concept first broached by Marcel Duchamp (1887–1968) with his iconic readymades of the early twentieth century. With Erased de Kooning Drawing (1953), Rauschenberg set out to discover whether an artwork could be produced entirely through erasure—an act focused on the removal of marks rather than their accumulation.
I love the idea here of making art by removing things. It’s somewhat akin to removing stone in a block of marble to create a sculpture, but at the same time this is also different. I’m also reminded of the idea of a photo negative or the concept of publishing negative results in science to give us a fuller picture of an area. Translating this idea from art into broader life could be quite interesting.

Hat tip: graffiti story, body art

🎧 Episode 088 The Science & Philosophy of Complexity: An Interview With Carlos Gershenson | Human Current

Listened to Episode 088 The Science & Philosophy of Complexity: An Interview With Carlos Gershenson by Haley Campbell-GrossHaley Campbell-Gross from HumanCurrent

In this episode, Haley interviews research professor and leader of the Self-Organizing Systems Labat UNAMCarlos Gershenson. Gershenson discusses findings from his book, Complexity: 5 Questions, which is comprised of “interview style contributions by leading figures in the field of complexity”. He also shares his own perspectives on the past, present and future of complexity science, as well as how philosophy plays a role in the emergence of science.

Carlos Gershenson

🎧 Episode 101 A Journey of Computational Complexity with Stephen Wolfram | Human Current

Listened to Episode 101 A Journey of Computational Complexity with Stephen Wolfram by Hayley Campbell-GrossHayley Campbell-Gross from HumanCurrent

In this episode, Haley interviews Stephen Wolfram at the Ninth International Conference on Complex Systems. Wolfram is the creator of Mathematica, Wolfram|Alpha and the Wolfram Language; the author of A New Kind of Science; and the founder and CEO of Wolfram Research. Wolfram talks with Haley about his professional journey and reflects on almost four decades of history, from his first introduction to the field of complexity science to the 30 year anniversary of Mathematica. He shares his hopes for the evolution of complexity science as a foundational field of study. He also gives advice for complexity researchers, recommending they focus on asking simple, foundational questions.

Stephen Wolfram

🎧 Episode 116 An Educator’s Guide to Systems Thinking: An Interview With Linda Booth Sweeney | Human Current

Listened to Episode 116 An Educator's Guide to Systems Thinking: An Interview With Linda Booth Sweeney by Angie CrossAngie Cross from HumanCurrent

In this episode, Angie talks with systems educator and award-winning author, Linda Booth Sweeney. Booth Sweeney describes her work as a systems educator and explains why understanding systems is so important. She shares many wonderful examples and stories of patterns (and feedback loops) that show up in everyday life and explains how seeing a pattern is the very first step toward influencing change. Booth Sweeney also talks about her books and why storytelling is such an instrumental tool in her work.

Linda Booth Sweeney
Some awesome ideas hiding in here. Definitely worth a second listen as well as bookmarking some of Sweeney’s books to read in the future. I particularly like the idea of systems thinking for children via storytelling. Some of the ideas here have some overlap with ideas in Big History.

🎧 Episode 115 The Network Science of Success: An Interview With Albert-László Barabási | HumanCurrent

Listened to Episode 115 The Network Science of Success: An Interview With Albert-László Barabási by Haley Campbell-GrossHaley Campbell-Gross from HumanCurrent

In this episode, Haley talks with Albert-László Barabási. Barabasi is the Robert Gray Dodge Professor of Network Science and a Distinguished University Professor at Northeastern University, where he directs the Center for Complex Network Research. He is also a renowned author of several books including his newly released book, The Formula: The Universal Laws of Success, which he discusses in-depth during his interview. Barabási shares key takeaways and important lessons from his new book and research on the science of success. He also gives us insights from his journey of learning about and pioneering the young field of network science and shares his hopes for the future of this field.

Albert-László Barabási

🔖 The Formula: The Universal Laws of Success by Albert-László Barabási

Bookmarked The Formula: The Universal Laws of Success by Albert-László Barabási (Little, Brown and Company)

In the bestselling tradition of Malcom Gladwell, James Gleick, and Nate Silver, prominent professor László Barabási gives us a trailblazing book that promises to transform the very foundations of how our success-obsessed society approaches their professional careers, life pursuits and long-term goals.

Too often, accomplishment does not equal success. We did the work but didn't get the promotion; we played hard but weren't recognized; we had the idea but didn't get the credit. We convince ourselves that talent combined with a strong work ethic is the key to getting ahead, but also realize that combination often fails to yield results, without any deeper understanding as to why. Recognizing this striking disconnect, the author, along with a team of renowned researchers and some of the most advanced data-crunching systems on the planet, dedicated themselves to one goal: uncovering that ever-elusive link between performance and success.

Now, based on years of academic research, The Formula finally unveils the groundbreaking discoveries of their pioneering study, not only highlighting the scientific and mathematic principles that underpin success, but also revolutionizing our understanding of:
Why performance is necessary but not adequate
Why "Experts" are often wrong
How to assemble a creative team primed for success
How to most effectively engage our networks
And much more.

Caught an interesting reference to this in an episode of Human Current, but I’ve also recently finished his prior book Linked. I’ll likely read it, but I’ll probably wish I had read the relevant papers instead.

🔖 Computational Complexity Conference 2019: Call for Papers

Bookmarked Computational Complexity Conference 2019: Call for Papers (computationalcomplexity.org)
Submission Deadline: Tuesday, February 19, 2019, 5:00pm EST
The conference seeks original research papers in all areas of computational complexity theory, studying the absolute and relative power of computational models under resource constraints. We also encourage contributions from other areas of computer science and mathematics motivated by questions in complexity theory.